Evaluation of the "e-rater"® Scoring Engine for the "GRE"® Issue and Argument Prompts. Research Report. ETS RR-12-02

ERIC Educational Resources Information Center

Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.; Davey, Tim; Bridgeman, Brent

2012-01-01

Automated scoring models for the "e-rater"® scoring engine were built and evaluated for the "GRE"® argument and issue-writing tasks. Prompt-specific, generic, and generic with prompt-specific intercept scoring models were built and evaluation statistics such as weighted kappas, Pearson correlations, standardized difference in…

Measurement Error and Bias in Value-Added Models. Research Report. ETS RR-17-25

ERIC Educational Resources Information Center

Kane, Michael T.

2017-01-01

By aggregating residual gain scores (the differences between each student's current score and a predicted score based on prior performance) for a school or a teacher, value-added models (VAMs) can be used to generate estimates of school or teacher effects. It is known that random errors in the prior scores will introduce bias into predictions of…

Exercise in prevention and treatment of anxiety and depression among children and young people.

PubMed

Larun, L; Nordheim, L V; Ekeland, E; Hagen, K B; Heian, F

2006-07-19

Depression and anxiety are common psychological disorders for children and adolescents. Psychological (e.g. psychotherapy), psychosocial (e.g. cognitive behavioral therapy) and biological (e.g. SSRIs or tricyclic drugs) treatments are the most common treatments being offered. The large variety of therapeutic interventions give rise to questions of clinical effectiveness and side effects. Physical exercise is inexpensive with few, if any, side effects. To assess the effects of exercise interventions in reducing or preventing anxiety or depression in children and young people up to 20 years of age. We searched the Cochrane Controlled Trials Register (latest issue available), MEDLINE, EMBASE, CINAHL, PsycINFO, ERIC and Sportdiscus up to August 2005. Randomised trials of vigorous exercise interventions for children and young people up to the age of 20, with outcome measures for depression and anxiety. Two authors independently selected trials for inclusion, assessed methodological quality and extracted data. The trials were combined using meta-analysis methods. A narrative synthesis was performed when the reported data did not allow statistical pooling. Sixteen studies with a total of 1191 participants between 11 and 19 years of age were included.Eleven trials compared vigourous exercise versus no intervention in a general population of children. Six studies reporting anxiety scores showed a non-significant trend in favour of the exercise group (standard mean difference (SMD) (random effects model) -0.48, 95% confidence interval (CI) -0.97 to 0.01). Five studies reporting depression scores showed a statistically significant difference in favour of the exercise group (SMD (random effects model) -0.66, 95% CI -1.25 to -0.08). However, all trials were generally of low methodological quality and they were highly heterogeneous with regard to the population, intervention and measurement instruments used. One small trial investigated children in treatment showed no statistically significant difference in depression scores in favour of the control group (SMD (fixed effects model) 0.78, 95% CI -0.47 to 2.04). No studies reported anxiety scores for children in treatment. Five trials comparing vigorous exercise to low intensity exercise show no statistically significant difference in depression and anxiety scores in the general population of children. Three trials reported anxiety scores (SMD (fixed effects model) -0.14, 95% CI -0.41 to 0.13). Two trials reported depression scores (SMD (fixed effects model) -0.15, 95% CI -0.44 to 0.14). Two small trials found no difference in depression scores for children in treatment (SMD (fixed effects model) -0.31, 95% CI -0.78 to 0.16). No studies reported anxiety scores for children in treatment. Four trials comparing exercise with psychosocial interventions showed no statistically significant difference in depression and anxiety scores in the general population of children. Two trials reported anxiety scores (SMD (fixed effects model) -0.13, 95% CI -0.43 to 0.17). Two trials reported depression scores (SMD (fixed effects model) 0.10, 95% CI-0.21 to 0.41). One trial found no difference in depression scores for children in treatment (SMD (fixed effects model) -0.31, 95% CI -0.97 to 0.35). No studies reported anxiety scores for children in treatment. Whilst there appears to be a small effect in favour of exercise in reducing depression and anxiety scores in the general population of children and adolescents, the small number of studies included and the clinical diversity of participants, interventions and methods of measurement limit the ability to draw conclusions. It makes little difference whether the exercise is of high or low intensity. The effect of exercise for children in treatment for anxiety and depression is unknown as the evidence base is scarce.

Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations

NASA Astrophysics Data System (ADS)

Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah

2012-02-01

This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate students in response to two different evolution instruments (the EGALT-F and EGALT-P) that contained prompts that differed in various surface features (such as species and traits). We tested human-SIDE scoring correspondence under a series of different training and testing conditions, using Kappa inter-rater agreement values of greater than 0.80 as a performance benchmark. In addition, we examined the effects of response length on scoring success; that is, whether SIDE scoring models functioned with comparable success on short and long responses. We found that SIDE performance was most effective when scoring models were built and tested at the individual item level and that performance degraded when suites of items or entire instruments were used to build and test scoring models. Overall, SIDE was found to be a powerful and cost-effective tool for assessing student knowledge and performance in a complex science domain.

Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies

NASA Astrophysics Data System (ADS)

Burns, Dana

Over the last two decades, online education has become a popular concept in universities as well as K-12 education. This generation of students has grown up using technology and has shown interest in incorporating technology into their learning. The idea of using technology in the classroom to enhance student learning and create higher achievement has become necessary for administrators, teachers, and policymakers. Although online education is a popular topic, there has been minimal research on the effectiveness of online and blended learning strategies compared to the student learning in a traditional K-12 classroom setting. The purpose of this study was to investigate differences in standardized test scores from the Biology End of Course exam when at-risk students completed the course using three different educational models: online format, blended learning, and traditional face-to-face learning. Data was collected from over 1,000 students over a five year time period. Correlation analyzed data from standardized tests scores of eighth grade students was used to define students as "at-risk" for failing high school courses. The results indicated a high correlation between eighth grade standardized test scores and Biology End of Course exam scores. These students were deemed "at-risk" for failing high school courses. Standardized test scores were measured for the at-risk students when those students completed Biology in the different models of learning. Results indicated significant differences existed among the learning models. Students had the highest test scores when completing Biology in the traditional face-to-face model. Further evaluation of subgroup populations indicated statistical differences in learning models for African-American populations, female students, and for male students.

Bifactor Structure for the Categorical Chinese Rosenberg Self-Esteem Scale.

PubMed

Xu, Menglin; Leung, Shing-On

2016-10-11

Recently, the bifactor model was suggested for the latent structure of the Rosenberg Self-Esteem Scale (RSES). The present paper investigates (i) the differences among bifactor, bifactor negative and other models; (ii) the effects of treating data as both categorical vs continuous; (iii) whether a problematic item in the Chinese RSES should be removed; and (iv) whether the final scoring would be affected. With a sample of 1.734 grade 4-6 school pupils in Hong Kong, we used BIC differences in addition to the usual model fit indices, and found that there was strong evidence for using the bifactor model (RMSEA = .052, 90% CI [.043, .062], CFI = .992, TLI = .984 for 9-item RSES categorical). Little difference is found between treating data as categorical or continuous for fit indices, but the factor loading patterns are better in categorical case. Keeping a problematic item has little effect on fit indices, but would lead to unexpected negative loading. The ranking of loadings within positive and negative items across different conditions are the same, which has important effects on scoring. Loadings in the method effects in the bifactor models are all positive (p < .001), which is different from previous research. All models show similar results on scoring, and support the usual simple sum score in most practice.

Analysis of the influences on plumage condition in laying hens: How suitable is a whole body plumage score as an outcome?

PubMed

Campe, A; Hoes, C; Koesters, S; Froemke, C; Bougeard, S; Staack, M; Bessei, W; Manton, A; Scholz, B; Schrader, L; Thobe, P; Knierim, U

2018-02-01

An important indicator of the health and behavior of laying hens is their plumage condition. Various scoring systems are used, and various risk factors for feather damage have been described. Often, a summarized score of different body parts is used to describe the overall condition of the plumage of a bird. However, it has not yet been assessed whether such a whole body plumage score is a suitable outcome variable when analyzing the risk factors for plumage deterioration. Data collected within a German project on farms keeping laying hens in aviaries were analyzed to investigate whether and the extent to which information is lost when summarizing the scores of the separate body parts. Two models were fitted using multiblock redundancy analysis, in which the first model included the whole body score as one outcome variable, while the second model included the scores of the individual body parts as multiple outcome variables. Although basically similar influences could be discovered with both models, the investigation of the individual body parts allowed for consideration of the influences on each body part separately and for the identification of additional influences. Furthermore, ambivalent influences (a factor differently associated with 2 different outcomes) could be detected with this approach, and possible dilutive effects were avoided. We conclude that influences might be underestimated or even missed when modeling their explanatory power for an overall score only. Therefore, multivariate methods that allow for the consideration of individual body parts are an interesting option when investigating influences on plumage condition. © 2017 Poultry Science Association Inc.

Modelling the Progression of Competitive Performance of an Academy's Soccer Teams.

PubMed

Malcata, Rita M; Hopkins, Will G; Richardson, Scott

2012-01-01

Progression of a team's performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents' scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model has marginal utility for estimating progression of soccer scores, owing to the uncertainty arising from low game scores. The estimates are likely to be more precise and useful in sports with higher game scores. Key pointsA generalized linear mixed model is the approach for tracking game scores, key performance indicators or other measures of performance based on counts in sports where changes within and/or between games/seasons have to be considered.Game scores in soccer could be useful to track performance progression of teams, but hundreds of games are needed.Fewer games will be needed for tracking performance represented by counts with high scores, such as game scores in rugby or key performance indicators based on frequent events or player actions in any team sport.

Modelling the Progression of Competitive Performance of an Academy’s Soccer Teams

PubMed Central

Malcata, Rita M.; Hopkins, Will G; Richardson, Scott

2012-01-01

Progression of a team’s performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents’ scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model has marginal utility for estimating progression of soccer scores, owing to the uncertainty arising from low game scores. The estimates are likely to be more precise and useful in sports with higher game scores. Key pointsA generalized linear mixed model is the approach for tracking game scores, key performance indicators or other measures of performance based on counts in sports where changes within and/or between games/seasons have to be considered.Game scores in soccer could be useful to track performance progression of teams, but hundreds of games are needed.Fewer games will be needed for tracking performance represented by counts with high scores, such as game scores in rugby or key performance indicators based on frequent events or player actions in any team sport. PMID:24149364

Scoring sensor observations to facilitate the exchange of space surveillance data

NASA Astrophysics Data System (ADS)

Weigel, M.; Fiedler, H.; Schildknecht, T.

2017-08-01

In this paper, a scoring metric for space surveillance sensor observations is introduced. A scoring metric allows for direct comparison of data quantity and data quality, and makes transparent the effort made by different sensor operators. The concept might be applied to various sensor types like tracking and surveillance radar, active optical laser tracking, or passive optical telescopes as well as combinations of different measurement types. For each measurement type, a polynomial least squares fit is performed on the measurement values contained in the track. The track score is the average sum over the polynomial coefficients uncertainties and scaled by reference measurement accuracy. Based on the newly developed scoring metric, an accounting model and a rating model are introduced. Both models facilitate the exchange of observation data within a network of space surveillance sensors operators. In this paper, optical observations are taken as an example for analysis purposes, but both models can also be utilized for any other type of observations. The rating model has the capability to distinguish between network participants with major and minor data contribution to the network. The level of sanction on data reception is defined by the participants themselves enabling a high flexibility. The more elaborated accounting model translates the track score to credit points earned for data provision and spend for data reception. In this model, data reception is automatically limited for participants with low contribution to the network. The introduced method for observation scoring is first applied for transparent data exchange within the Small Aperture Robotic Telescope Network (SMARTnet). Therefore a detailed mathematical description is presented for line of sight measurements from optical telescopes, as well as numerical simulations for different network setups.

An Alternative Approach for Supportive Supervision and Skill Measurements of Health Workers for Integrated Management of Neonatal and Childhood Illnesses Program in 10 Districts of Haryana.

PubMed

Aggarwal, Arun K; Gupta, Rakesh; Das, Dhritiman; Dhakar, Anar S; Sharma, Gourav; Anand, Himani; Kaur, Kamalpreet; Sheoran, Kiran; Dalpath, Suresh; Khatri, Jaidev; Gupta, Madhu

2018-01-01

"Integrated Management of Neonatal and Childhood Illnesses" (IMNCI) needs regular supportive supervision (SS). The aim of this study was to find suitable SS model for implementing IMNCI. This was a prospective interventional study in 10 high-focus districts of Haryana. Two methods of SS were used: (a) visit to subcenters and home visits (model 1) and (b) organization of IMNCI clinics/camps at primary health center (PHC) and community health center (CHC) (model 2). Skill scores were measured at different time points. Routine IMNCI data from study block and randomly selected control block of each district were retrieved for 4 months before and after the training and supervision. Change in percentage mean skill score difference and percentage difference in median number of children were assessed in two areas. Mean skill scores increased significantly from 2.1 (pretest) to 7.0 (posttest 1). Supportive supervisory visits sustained and improved skill scores. While model 2 of SS could positively involve health system officials, model 1 was not well received. Outcome indicator in terms of number of children assessed showed a significant improvement in intervention areas. SS in IMNCI clinics/camps at PHC/CHC level and innovative skill scoring method is a promising approach.

The Usefulness of the Bock Model for Scoring with Information from Incorrect Responses.

ERIC Educational Resources Information Center

Huynh, Huynh; Casteel, Jim

1987-01-01

In the context of pass/fail decisions, using the Bock multi-nominal latent trait model for moderate-length tests does not produce decisions that differ substantially from those based on the raw scores. The Bock decisions appear to relate less strongly to outside criteria than those based on the raw scores. (Author/JAZ)

Improving Factor Score Estimation Through the Use of Observed Background Characteristics

PubMed Central

Curran, Patrick J.; Cole, Veronica; Bauer, Daniel J.; Hussong, Andrea M.; Gottfredson, Nisha

2016-01-01

A challenge facing nearly all studies in the psychological sciences is how to best combine multiple items into a valid and reliable score to be used in subsequent modelling. The most ubiquitous method is to compute a mean of items, but more contemporary approaches use various forms of latent score estimation. Regardless of approach, outside of large-scale testing applications, scoring models rarely include background characteristics to improve score quality. The current paper used a Monte Carlo simulation design to study score quality for different psychometric models that did and did not include covariates across levels of sample size, number of items, and degree of measurement invariance. The inclusion of covariates improved score quality for nearly all design factors, and in no case did the covariates degrade score quality relative to not considering the influences at all. Results suggest that the inclusion of observed covariates can improve factor score estimation. PMID:28757790

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

PubMed Central

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test–post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences. PMID:29881032

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses.

PubMed

Cho, Sun-Joo; Preacher, Kristopher J; Bottge, Brian A

2015-11-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test-post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences.

Do Sex Differences in a Faceted Model of Fluid and Crystallized Intelligence Depend on the Method Applied?

ERIC Educational Resources Information Center

Steinmayr, Ricarda; Beauducel, Andre; Spinath, Birgit

2010-01-01

Recently, different methodological approaches have been discussed as an explanation for inconsistencies in studies investigating sex differences in different intelligences. The present study investigates sex differences in manifest sum scores, factor score estimates, and latent verbal, numerical, figural intelligence, as well as fluid and…

The Impact of Different Scoring Rubrics for Grading Virtual Patient-Based Exams

ERIC Educational Resources Information Center

Fors, Uno G. H.; Gunning, William T.

2014-01-01

Virtual patient cases (VPs) are used for healthcare education and assessment. Most VP systems track user interactions to be used for assessment. Few studies have investigated how virtual exam cases should be scored and graded. We have applied eight different scoring models on a data set from 154 students. Issues studied included the impact of…

Stratification of complexity in congenital heart surgery: comparative study of the Risk Adjustment for Congenital Heart Surgery (RACHS-1) method, Aristotle basic score and Society of Thoracic Surgeons-European Association for Cardio- Thoracic Surgery (STS-EACTS) mortality score.

PubMed

Cavalcanti, Paulo Ernando Ferraz; Sá, Michel Pompeu Barros de Oliveira; Santos, Cecília Andrade dos; Esmeraldo, Isaac Melo; Chaves, Mariana Leal; Lins, Ricardo Felipe de Albuquerque; Lima, Ricardo de Carvalho

2015-01-01

To determine whether stratification of complexity models in congenital heart surgery (RACHS-1, Aristotle basic score and STS-EACTS mortality score) fit to our center and determine the best method of discriminating hospital mortality. Surgical procedures in congenital heart diseases in patients under 18 years of age were allocated to the categories proposed by the stratification of complexity methods currently available. The outcome hospital mortality was calculated for each category from the three models. Statistical analysis was performed to verify whether the categories presented different mortalities. The discriminatory ability of the models was determined by calculating the area under the ROC curve and a comparison between the curves of the three models was performed. 360 patients were allocated according to the three methods. There was a statistically significant difference between the mortality categories: RACHS-1 (1) - 1.3%, (2) - 11.4%, (3)-27.3%, (4) - 50 %, (P<0.001); Aristotle basic score (1) - 1.1%, (2) - 12.2%, (3) - 34%, (4) - 64.7%, (P<0.001); and STS-EACTS mortality score (1) - 5.5 %, (2) - 13.6%, (3) - 18.7%, (4) - 35.8%, (P<0.001). The three models had similar accuracy by calculating the area under the ROC curve: RACHS-1- 0.738; STS-EACTS-0.739; Aristotle- 0.766. The three models of stratification of complexity currently available in the literature are useful with different mortalities between the proposed categories with similar discriminatory capacity for hospital mortality.

Utility of different cardiovascular disease prediction models in rheumatoid arthritis.

PubMed

Purcarea, A; Sovaila, S; Udrea, G; Rezus, E; Gheorghe, A; Tiu, C; Stoica, V

2014-01-01

Rheumatoid arthritis comes with a 30% higher probability for cardiovascular disease than the general population. Current guidelines advocate for early and aggressive primary prevention and treatment of risk factors in high-risk populations but this excess risk is under-addressed in RA in real life. This is mainly due to difficulties met in the correct risk evaluation. This study aims to underline the differences in results of the main cardiovascular risk screening models in the real life rheumatoid arthritis population. In a cross-sectional study, patients addressed to a tertiary care center in Romania for an biannual follow-up of rheumatoid arthritis and the ones who were considered free of any cardiovascular disease were assessed for subclinical atherosclerosis. Clinical, biological and carotidal ultrasound evaluations were performed. A number of cardiovascular disease prediction scores were performed and differences between tests were noted in regard to subclinical atherosclerosis as defined by the existence of carotid intima media thickness over 0,9 mm or carotid plaque. In a population of 29 Romanian rheumatoid arthritis patients free of cardiovascular disease, the performance of Framingham Risk Score, HeartSCORE, ARIC cardiovascular disease prediction score, Reynolds Risk Score, PROCAM risk score and Qrisk2 score were compared. All the scores under-diagnosed subclinical atherosclerosis. With an AUROC of 0,792, the SCORE model was the only one that could partially stratify patients in low, intermediate and high-risk categories. The use of the EULAR recommended modifier did not help to reclassify patients. The only score that showed a statistically significant prediction capacity for subclinical atherosclerosis in a Romanian rheumatoid arthritis population was SCORE. The additional calibration or the use of imaging techniques in CVD risk prediction for the intermediate risk category might be warranted.

Utility of different cardiovascular disease prediction models in rheumatoid arthritis

PubMed Central

Purcarea, A; Sovaila, S; Udrea, G; Rezus, E; Gheorghe, A; Tiu, C; Stoica, V

2014-01-01

Background. Rheumatoid arthritis comes with a 30% higher probability for cardiovascular disease than the general population. Current guidelines advocate for early and aggressive primary prevention and treatment of risk factors in high-risk populations but this excess risk is under-addressed in RA in real life. This is mainly due to difficulties met in the correct risk evaluation. This study aims to underline the differences in results of the main cardiovascular risk screening models in the real life rheumatoid arthritis population. Methods. In a cross-sectional study, patients addressed to a tertiary care center in Romania for an biannual follow-up of rheumatoid arthritis and the ones who were considered free of any cardiovascular disease were assessed for subclinical atherosclerosis. Clinical, biological and carotidal ultrasound evaluations were performed. A number of cardiovascular disease prediction scores were performed and differences between tests were noted in regard to subclinical atherosclerosis as defined by the existence of carotid intima media thickness over 0,9 mm or carotid plaque. Results. In a population of 29 Romanian rheumatoid arthritis patients free of cardiovascular disease, the performance of Framingham Risk Score, HeartSCORE, ARIC cardiovascular disease prediction score, Reynolds Risk Score, PROCAM risk score and Qrisk2 score were compared. All the scores under-diagnosed subclinical atherosclerosis. With an AUROC of 0,792, the SCORE model was the only one that could partially stratify patients in low, intermediate and high-risk categories. The use of the EULAR recommended modifier did not help to reclassify patients. Conclusion. The only score that showed a statistically significant prediction capacity for subclinical atherosclerosis in a Romanian rheumatoid arthritis population was SCORE. The additional calibration or the use of imaging techniques in CVD risk prediction for the intermediate risk category might be warranted. PMID:25713628

Assessment of Sex Differences in Body Composition Among Adolescents With Anorexia Nervosa.

PubMed

Nagata, Jason M; Golden, Neville H; Peebles, Rebecka; Long, Jin; Murray, Stuart B; Leonard, Mary B; Carlson, Jennifer L

2017-04-01

To compare deficits in fat mass (FM) and lean body mass (LM) among male and female adolescents with anorexia nervosa (AN) and to identify other covariates associated with body composition. We retrospectively reviewed electronic medical records of all subjects aged 9-20 years with a Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition diagnosis of AN and dual-energy x-ray absorptiometry scans after initial evaluation at Stanford between March 1997 and February 2011. From the dual-energy x-ray absorptiometry scans, LM and FM results were converted to age-, height-, sex-, and race-specific Z-scores for age using the National Health and Nutrition Examination Survey reference data. A total of 16 boys and 119 girls with AN met eligibility criteria. The FM Z-score in girls with AN (-3.24 ± 1.50) was significantly lower than that in boys with AN (-2.41 ± .96) in unadjusted models (p = .007). LM was reduced in both girls and boys with AN, but there was no significant sex difference in LM Z-scores. In multivariate models, lower percentage median body mass index was significantly associated with lower FM Z-scores (β = .08, p < .0001) and lower LM Z-score (β = .03, p = .0002), whereas lower whole body bone mineral content Z-score was significantly associated with lower LM Z-score (β = .21, p = .0006). FM deficits in girls were significantly greater than those in boys with AN in unadjusted models; however, the degree of malnutrition appeared to be the primary factor accounting for this difference. There were no significant sex differences in FM or LM in adjusted models. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Comparison of "E-Rater"[R] Automated Essay Scoring Model Calibration Methods Based on Distributional Targets

ERIC Educational Resources Information Center

Zhang, Mo; Williamson, David M.; Breyer, F. Jay; Trapani, Catherine

2012-01-01

This article describes two separate, related studies that provide insight into the effectiveness of "e-rater" score calibration methods based on different distributional targets. In the first study, we developed and evaluated a new type of "e-rater" scoring model that was cost-effective and applicable under conditions of absent human rating and…

Evaluation of "e-rater"® for the "Praxis I"®Writing Test. Research Report. ETS RR-15-03

ERIC Educational Resources Information Center

Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.

2015-01-01

Automated scoring models were trained and evaluated for the essay task in the "Praxis I"® writing test. Prompt-specific and generic "e-rater"® scoring models were built, and evaluation statistics, such as quadratic weighted kappa, Pearson correlation, and standardized differences in mean scores, were examined to evaluate the…

The potential of composite cognitive scores for tracking progression in Huntington's disease.

PubMed

Jones, Rebecca; Stout, Julie C; Labuschagne, Izelle; Say, Miranda; Justo, Damian; Coleman, Allison; Dumas, Eve M; Hart, Ellen; Owen, Gail; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund; O'Regan, Alison; Langbehn, Doug; Tabrizi, Sarah J; Frost, Chris

2014-01-01

Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.

Scoring the correlation of genes by their shared properties using OScal, an improved overlap quantification model.

PubMed

Liu, Hui; Liu, Wei; Lin, Ying; Liu, Teng; Ma, Zhaowu; Li, Mo; Zhang, Hong-Mei; Kenneth Wang, Qing; Guo, An-Yuan

2015-05-27

Scoring the correlation between two genes by their shared properties is a common and basic work in biological study. A prospective way to score this correlation is to quantify the overlap between the two sets of homogeneous properties of the two genes. However the proper model has not been decided, here we focused on studying the quantification of overlap and proposed a more effective model after theoretically compared 7 existing models. We defined three characteristic parameters (d, R, r) of an overlap, which highlight essential differences among the 7 models and grouped them into two classes. Then the pros and cons of the two groups of model were fully examined by their solution space in the (d, R, r) coordinate system. Finally we proposed a new model called OScal (Overlap Score calculator), which was modified on Poisson distribution (one of 7 models) to avoid its disadvantages. Tested in assessing gene relation using different data, OScal performs better than existing models. In addition, OScal is a basic mathematic model, with very low computation cost and few restrictive conditions, so it can be used in a wide-range of research areas to measure the overlap or similarity of two entities.

Using Patient Health Questionnaire-9 item parameters of a common metric resulted in similar depression scores compared to independent item response theory model reestimation.

PubMed

Liegl, Gregor; Wahl, Inka; Berghöfer, Anne; Nolte, Sandra; Pieh, Christoph; Rose, Matthias; Fischer, Felix

2016-03-01

To investigate the validity of a common depression metric in independent samples. We applied a common metrics approach based on item-response theory for measuring depression to four German-speaking samples that completed the Patient Health Questionnaire (PHQ-9). We compared the PHQ item parameters reported for this common metric to reestimated item parameters that derived from fitting a generalized partial credit model solely to the PHQ-9 items. We calibrated the new model on the same scale as the common metric using two approaches (estimation with shifted prior and Stocking-Lord linking). By fitting a mixed-effects model and using Bland-Altman plots, we investigated the agreement between latent depression scores resulting from the different estimation models. We found different item parameters across samples and estimation methods. Although differences in latent depression scores between different estimation methods were statistically significant, these were clinically irrelevant. Our findings provide evidence that it is possible to estimate latent depression scores by using the item parameters from a common metric instead of reestimating and linking a model. The use of common metric parameters is simple, for example, using a Web application (http://www.common-metrics.org) and offers a long-term perspective to improve the comparability of patient-reported outcome measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Cross-Cultural Evaluation of Antonovsky's Orientation to Life Questionnaire: Comparison Between Australian, Finnish, and Turkish Young Adults.

PubMed

Lajunen, Timo

2018-01-01

Antonovsky's concept "sense of coherence" (SOC) and the related measurement instrument "The Orientation to Life Questionnaire" (OLQ) has been widely applied in studies on health and well-being. The purpose of the present study is to investigate the cultural differences in factor structures and psychometric properties as well as mean scores of the 13-item form of Antonovsky's OLQ among Australian (n = 201), Finnish (n = 203), and Turkish (n = 152) students. Three models of factor structure were studied by using confirmatory factor analysis: single-factor model, first-order correlated-three-factor model, and the second-order three-factor model. Results obtained in all three countries suggest that the first- and second-order three-factor models fitted the data better that the single-factor model. Hence, the OLQ scoring based on comprehensibility, manageability, and meaningfulness scales was supported. Scale reliabilities and inter-correlations were in line with those reported in earlier studies. Two-way analyses of variance (gender × nationality) with age as a covariate showed no cultural differences in SOC scale scores. Women got higher scores on the meaningfulness scale than men, and age was positively related to all SOC scale scores indicating that SOC increases in early adulthood. The results support the three-factor model of OLQ which thus should be used in Australia, Finland, and Turkey instead of a single-factor model. Need for cross-cultural studies taking into account cultural correlates of SOC and its relation to health and well-being indicators as well as studies on gender differences in the OLQ are emphasized.

Analysis of the Sheltered Instruction Observation Protocol Model on Academic Performance of English Language Learners

NASA Astrophysics Data System (ADS)

Ingram, Sandra W.

This quantitative comparative descriptive study involved analyzing archival data from end-of-course (EOC) test scores in biology of English language learners (ELLs) taught or not taught using the sheltered instruction observation protocol (SIOP) model. The study includes descriptions and explanations of the benefits of the SIOP model to ELLs, especially in content area subjects such as biology. Researchers have shown that ELLs in high school lag behind their peers in academic achievement in content area subjects. Much of the research on the SIOP model took place in elementary and middle school, and more research was necessary at the high school level. This study involved analyzing student records from archival data to describe and explain if the SIOP model had an effect on the EOC test scores of ELLs taught or not taught using it. The sample consisted of 527 Hispanic students (283 females and 244 males) from Grades 9-12. An independent sample t-test determined if a significant difference existed in the mean EOC test scores of ELLs taught using the SIOP model as opposed to ELLs not taught using the SIOP model. The results indicated that a significant difference existed between EOC test scores of ELLs taught using the SIOP model and ELLs not taught using the SIOP model (p = .02). A regression analysis indicated a significant difference existed in the academic performance of ELLs taught using the SIOP model in high school science, controlling for free and reduced-price lunch (p = .001) in predicting passing scores on the EOC test in biology at the school level. The data analyzed for free and reduced-price lunch together with SIOP data indicated that both together were not significant (p = .175) for predicting passing scores on the EOC test in high school biology. Future researchers should repeat the study with student-level data as opposed to school-level data, and data should span at least three years.

www.common-metrics.org: a web application to estimate scores from different patient-reported outcome measures on a common scale.

PubMed

Fischer, H Felix; Rose, Matthias

2016-10-19

Recently, a growing number of Item-Response Theory (IRT) models has been published, which allow estimation of a common latent variable from data derived by different Patient Reported Outcomes (PROs). When using data from different PROs, direct estimation of the latent variable has some advantages over the use of sum score conversion tables. It requires substantial proficiency in the field of psychometrics to fit such models using contemporary IRT software. We developed a web application ( http://www.common-metrics.org ), which allows estimation of latent variable scores more easily using IRT models calibrating different measures on instrument independent scales. Currently, the application allows estimation using six different IRT models for Depression, Anxiety, and Physical Function. Based on published item parameters, users of the application can directly estimate latent trait estimates using expected a posteriori (EAP) for sum scores as well as for specific response patterns, Bayes modal (MAP), Weighted likelihood estimation (WLE) and Maximum likelihood (ML) methods and under three different prior distributions. The obtained estimates can be downloaded and analyzed using standard statistical software. This application enhances the usability of IRT modeling for researchers by allowing comparison of the latent trait estimates over different PROs, such as the Patient Health Questionnaire Depression (PHQ-9) and Anxiety (GAD-7) scales, the Center of Epidemiologic Studies Depression Scale (CES-D), the Beck Depression Inventory (BDI), PROMIS Anxiety and Depression Short Forms and others. Advantages of this approach include comparability of data derived with different measures and tolerance against missing values. The validity of the underlying models needs to be investigated in the future.

Propensity-score matching in economic analyses: comparison with regression models, instrumental variables, residual inclusion, differences-in-differences, and decomposition methods.

PubMed

Crown, William H

2014-02-01

This paper examines the use of propensity score matching in economic analyses of observational data. Several excellent papers have previously reviewed practical aspects of propensity score estimation and other aspects of the propensity score literature. The purpose of this paper is to compare the conceptual foundation of propensity score models with alternative estimators of treatment effects. References are provided to empirical comparisons among methods that have appeared in the literature. These comparisons are available for a subset of the methods considered in this paper. However, in some cases, no pairwise comparisons of particular methods are yet available, and there are no examples of comparisons across all of the methods surveyed here. Irrespective of the availability of empirical comparisons, the goal of this paper is to provide some intuition about the relative merits of alternative estimators in health economic evaluations where nonlinearity, sample size, availability of pre/post data, heterogeneity, and missing variables can have important implications for choice of methodology. Also considered is the potential combination of propensity score matching with alternative methods such as differences-in-differences and decomposition methods that have not yet appeared in the empirical literature.

Performance of Automated Speech Scoring on Different Low- to Medium-Entropy Item Types for Low-Proficiency English Learners. Research Report. ETS RR-17-12

ERIC Educational Resources Information Center

Loukina, Anastassia; Zechner, Klaus; Yoon, Su-Youn; Zhang, Mo; Tao, Jidong; Wang, Xinhao; Lee, Chong Min; Mulholland, Matthew

2017-01-01

This report presents an overview of the "SpeechRater"? automated scoring engine model building and evaluation process for several item types with a focus on a low-English-proficiency test-taker population. We discuss each stage of speech scoring, including automatic speech recognition, filtering models for nonscorable responses, and…

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Speech-discrimination scores modeled as a binomial variable.

PubMed

Thornton, A R; Raffin, M J

1978-09-01

Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.

Analysis of the American Society of Anesthesiologists Physical Status Classification System and Caprini Risk Assessment Model in Predicting Venous Thromboembolic Outcomes in Plastic Surgery Patients.

PubMed

Shaikh, Mohammad-Ali; Jeong, Haneol S; Mastro, Andrew; Davis, Kathryn; Lysikowski, Jerzy; Kenkel, Jeffrey M

2016-04-01

Venous thromboembolism (VTE) can be a fatal outcome of plastic surgery. Risk assessment models attempt to determine a patient's risk, yet few studies have compared different models in plastic surgery patients. The authors investigated preoperative ASA physical status and 2005 Caprini scores to determine which model was more predictive of VTE. A retrospective chart review examined 1801 patients undergoing contouring and reconstructive procedures from January 2008 to January 2012. Patients were grouped into risk tiers for ASA scores (1-2 = low, 3+ = high) with 2 cutoffs for Caprini scores (1-4 = low, 5+ high; 1-5 = low, 6+ = high), then re-stratified into 3 tiers using Caprini score cutoffs (1-4 = low, 5-8 = high, 9+ = highest; 1-5 = low, 6-8 = high, 9+ = highest). Median scores of VTE patients were compared to those without VTE. Odds ratio and chi-squared analyses were performed. Of the 1598 patients included in the study, 1.50% developed VTE. Median ASA scores differed significantly between comparison groups but Caprini scores did not vary regardless of cutoff. When examining the 2-tiered Caprini scores, using low risk = 1-5 showed a significant relationship between risk tier and DVT development (P = 0.0266). The ASA system yielded the highest odds ratio of VTE development between low and high-risk patients. The Caprini model captured more patients with VTE in its high-risk category. Combining the two models for a more heuristic approach to preoperative care may identify patients at higher risk. 4 Risk. © 2015 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

The power to detect linkage in complex disease by means of simple LOD-score analyses.

PubMed Central

Greenberg, D A; Abreu, P; Hodge, S E

1998-01-01

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage. PMID:9718328

The power to detect linkage in complex disease by means of simple LOD-score analyses.

PubMed

Greenberg, D A; Abreu, P; Hodge, S E

1998-09-01

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage.

Scoring of Decomposition: A Proposed Amendment to the Method When Using a Pig Model for Human Studies.

PubMed

Keough, Natalie; Myburgh, Jolandie; Steyn, Maryna

2017-07-01

Decomposition studies often use pigs as proxies for human cadavers. However, differences in decomposition sequences/rates relative to humans have not been scientifically examined. Descriptions of five main decomposition stages (humans) were developed and refined by Galloway and later by Megyesi. However, whether these changes/processes are alike in pigs is unclear. Any differences can have significant effects when pig models are used for human PMI estimation. This study compared human decomposition models to the changes observed in pigs. Twenty pigs (50-90 kg) were decomposed over five months and decompositional features recorded. Total body scores (TBS) were calculated. Significant differences were observed during early decomposition between pigs and humans. An amended scoring system to be used in future studies was developed. Standards for PMI estimation derived from porcine models may not directly apply to humans and may need adjustment. Porcine models, however, remain valuable to study variables influencing decomposition. © 2016 American Academy of Forensic Sciences.

Stratification of complexity in congenital heart surgery: comparative study of the Risk Adjustment for Congenital Heart Surgery (RACHS-1) method, Aristotle basic score and Society of Thoracic Surgeons-European Association for Cardio- Thoracic Surgery (STS-EACTS) mortality score

PubMed Central

Cavalcanti, Paulo Ernando Ferraz; Sá, Michel Pompeu Barros de Oliveira; dos Santos, Cecília Andrade; Esmeraldo, Isaac Melo; Chaves, Mariana Leal; Lins, Ricardo Felipe de Albuquerque; Lima, Ricardo de Carvalho

2015-01-01

Objective To determine whether stratification of complexity models in congenital heart surgery (RACHS-1, Aristotle basic score and STS-EACTS mortality score) fit to our center and determine the best method of discriminating hospital mortality. Methods Surgical procedures in congenital heart diseases in patients under 18 years of age were allocated to the categories proposed by the stratification of complexity methods currently available. The outcome hospital mortality was calculated for each category from the three models. Statistical analysis was performed to verify whether the categories presented different mortalities. The discriminatory ability of the models was determined by calculating the area under the ROC curve and a comparison between the curves of the three models was performed. Results 360 patients were allocated according to the three methods. There was a statistically significant difference between the mortality categories: RACHS-1 (1) - 1.3%, (2) - 11.4%, (3)-27.3%, (4) - 50 %, (P<0.001); Aristotle basic score (1) - 1.1%, (2) - 12.2%, (3) - 34%, (4) - 64.7%, (P<0.001); and STS-EACTS mortality score (1) - 5.5 %, (2) - 13.6%, (3) - 18.7%, (4) - 35.8%, (P<0.001). The three models had similar accuracy by calculating the area under the ROC curve: RACHS-1- 0.738; STS-EACTS-0.739; Aristotle- 0.766. Conclusion The three models of stratification of complexity currently available in the literature are useful with different mortalities between the proposed categories with similar discriminatory capacity for hospital mortality. PMID:26107445

Predicting in-hospital mortality of traffic victims: A comparison between AIS-and ICD-9-CM-related injury severity scales when only ICD-9-CM is reported.

PubMed

Van Belleghem, Griet; Devos, Stefanie; De Wit, Liesbet; Hubloue, Ives; Lauwaert, Door; Pien, Karen; Putman, Koen

2016-01-01

Injury severity scores are important in the context of developing European and national goals on traffic safety, health-care benchmarking and improving patient communication. Various severity scores are available and are mostly based on Abbreviated Injury Scale (AIS) or International Classification of Diseases (ICD). The aim of this paper is to compare the predictive value for in-hospital mortality between the various severity scores if only International Classification of Diseases, 9th revision, Clinical Modification ICD-9-CM is reported. To estimate severity scores based on the AIS lexicon, ICD-9-CM codes were converted with ICD Programmes for Injury Categorization (ICDPIC) and four AIS-based severity scores were derived: Maximum AIS (MaxAIS), Injury Severity Score (ISS), New Injury Severity Score (NISS) and Exponential Injury Severity Score (EISS). Based on ICD-9-CM, six severity scores were calculated. Determined by the number of injuries taken into account and the means by which survival risk ratios (SRRs) were calculated, four different approaches were used to calculate the ICD-9-based Injury Severity Scores (ICISS). The Trauma Mortality Prediction Model (TMPM) was calculated with the ICD-9-CM-based model averaged regression coefficients (MARC) for both the single worst injury and multiple injuries. Severity scores were compared via model discrimination and calibration. Model comparisons were performed separately for the severity scores based on the single worst injury and multiple injuries. For ICD-9-based scales, estimation of area under the receiver operating characteristic curve (AUROC) ranges between 0.94 and 0.96, while AIS-based scales range between 0.72 and 0.76, respectively. The intercept in the calibration plots is not significantly different from 0 for MaxAIS, ICISS and TMPM. When only ICD-9-CM codes are reported, ICD-9-CM-based severity scores perform better than severity scores based on the conversion to AIS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using propensity scores in difference-in-differences models to estimate the effects of a policy change

PubMed Central

Stuart, Elizabeth A.; Huskamp, Haiden A.; Duckworth, Kenneth; Simmons, Jeffrey; Song, Zirui; Chernew, Michael; Barry, Colleen L.

2014-01-01

Difference-in-difference (DD) methods are a common strategy for evaluating the effects of policies or programs that are instituted at a particular point in time, such as the implementation of a new law. The DD method compares changes over time in a group unaffected by the policy intervention to the changes over time in a group affected by the policy intervention, and attributes the “difference-in-differences” to the effect of the policy. DD methods provide unbiased effect estimates if the trend over time would have been the same between the intervention and comparison groups in the absence of the intervention. However, a concern with DD models is that the program and intervention groups may differ in ways that would affect their trends over time, or their compositions may change over time. Propensity score methods are commonly used to handle this type of confounding in other non-experimental studies, but the particular considerations when using them in the context of a DD model have not been well investigated. In this paper, we describe the use of propensity scores in conjunction with DD models, in particular investigating a propensity score weighting strategy that weights the four groups (defined by time and intervention status) to be balanced on a set of characteristics. We discuss the conceptual issues associated with this approach, including the need for caution when selecting variables to include in the propensity score model, particularly given the multiple time point nature of the analysis. We illustrate the ideas and method with an application estimating the effects of a new payment and delivery system innovation (an accountable care organization model called the “Alternative Quality Contract” (AQC) implemented by Blue Cross Blue Shield of Massachusetts) on health plan enrollee out-of-pocket mental health service expenditures. We find no evidence that the AQC affected out-of-pocket mental health service expenditures of enrollees. PMID:25530705

Automatic Promotion and Student Dropout: Evidence from Uganda, Using Propensity Score in Difference in Differences Model

ERIC Educational Resources Information Center

Okurut, Jeje Moses

2018-01-01

The impact of automatic promotion practice on students dropping out of Uganda's primary education was assessed using propensity score in difference in differences analysis technique. The analysis strategy was instrumental in addressing the selection bias problem, as well as biases arising from common trends over time, and permanent latent…

The Perceived Implications of an Outsourcing Model on Governance within British Columbia Provincial Parks in Canada: A Quantitative Study

NASA Astrophysics Data System (ADS)

Eagles, Paul; Havitz, Mark; McCutcheon, Bonnie; Buteau-Duitschaever, Windekind; Glover, Troy

2010-06-01

Good governance is of paramount importance to the success of parks and protected areas. This research utilized a questionnaire for 10 principles of governance to evaluate the outsourcing model used by British Columbia Provincial Parks, where profit-making corporations provide all front country visitor services. A total of 246 respondents representing five stakeholder groups evaluated the model according to each principle, using an online survey. Principal component analysis resulted in two of the 10 principles (equity and effectiveness) each being split into two categories, leading to 12 governance principles. Five of the 12 criteria received scores towards good governance: effectiveness outcome; equity general; strategic vision; responsiveness; and effectiveness process. One criterion, public participation, was on the neutral point. Six criteria received scores below neutral, more towards weak governance: transparency; rule of law; accountability; efficiency; consensus orientation; and, equity finance. The five stakeholder groups differed significantly on 10 of the 12 principles ( P < .05). The 2 exceptions were for efficiency and effectiveness process. Seven of the 12 criteria followed a pattern wherein government employees and contractors reported positive scores, visitors and representatives of NGOs reported more negative scores, and nearby residents reported mid-range scores. Three criteria had government employees and contractors reporting the most positive scores, residents and visitors the most negative scores, and NGO respondents reporting mid-range scores. This research found evidence that perceptions of governance related to this outsourcing model differed significantly amongst various constituent groups.

[Scoring systems in intensive care medicine : principles, models, application and limits].

PubMed

Fleig, V; Brenck, F; Wolff, M; Weigand, M A

2011-10-01

Scoring systems are used in all diagnostic areas of medicine. Several parameters are evaluated and rated with points according to their value in order to simplify a complex clinical situation with a score. The application ranges from the classification of disease severity through determining the number of staff for the intensive care unit (ICU) to the evaluation of new therapies under study conditions. Since the introduction of scoring systems in the 1980's a variety of different score models has been developed. The scoring systems that are employed in intensive care and are discussed in this article can be categorized into prognostic scores, expenses scores and disease-specific scores. Since the introduction of compulsory recording of two scoring systems for accounting in the German diagnosis-related groups (DRG) system, these tools have gained more importance for all intensive care physicians. Problems remain in the valid calculation of scores and interpretation of the results.

Sex is associated with differences in individual trajectories of change in social health after implantable cardioverter-defibrillator.

PubMed

Lauck, Sandra B; Sawatzky, Richard; Johnson, Joy L; Humphries, Karin; Bennett, Matthew T; Chakrabarti, Santabhanu; Kerr, Charles R; Tung, Stanley; Yeung-Lai-Wah, John A; Ratner, Pamela A

2015-03-01

Social health is a dimension of quality of life, and refers to people's involvement in, and satisfaction with social roles, responsibilities, and activities. The implantable cardioverter-defibrillator is associated with changes in overall quality of life, but little is known about sex differences in individual trajectories of change in social health. We prospectively measured changes in 3 subscales of the SF-36v2 generic health questionnaire (role physical, role emotional, and social functioning), 2 Patient-Reported Outcomes Measurement Information System short forms (satisfaction with participation in social roles and satisfaction with participation in discretionary social activities), and the Florida Patient Acceptance Survey before and at 1, 2, and 6 months after implantation. Individual growth models of temporal change were estimated. The scores of the 6 indicators improved with time. The unconditional model demonstrated significant (fixed effects: P<0.05; covariance parameters: P<0.10) residual variability in the individual trajectories. In the conditional model, men and women differed significantly in their rates of change in the scores of 3 of the 6 measures. Although men's mean scores exceeded women's mean scores on all indicators at baseline (range of relative mean difference: 11.0% to 17.8%), the rate of women's change resulted in a reversal in relative standing at 6 months after implantation, with the mean scores of women exceeding the men's by 4.5% to 5.6%. Men and women differed in their trajectories of change in social health, both in terms of their starting points (ie, baseline scores) and their rates of change. © 2015 American Heart Association, Inc.

Method Development for Clinical Comprehensive Evaluation of Pediatric Drugs Based on Multi-Criteria Decision Analysis: Application to Inhaled Corticosteroids for Children with Asthma.

PubMed

Yu, Yuncui; Jia, Lulu; Meng, Yao; Hu, Lihua; Liu, Yiwei; Nie, Xiaolu; Zhang, Meng; Zhang, Xuan; Han, Sheng; Peng, Xiaoxia; Wang, Xiaoling

2018-04-01

Establishing a comprehensive clinical evaluation system is critical in enacting national drug policy and promoting rational drug use. In China, the 'Clinical Comprehensive Evaluation System for Pediatric Drugs' (CCES-P) project, which aims to compare drugs based on clinical efficacy and cost effectiveness to help decision makers, was recently proposed; therefore, a systematic and objective method is required to guide the process. An evidence-based multi-criteria decision analysis model that involved an analytic hierarchy process (AHP) was developed, consisting of nine steps: (1) select the drugs to be reviewed; (2) establish the evaluation criterion system; (3) determine the criterion weight based on the AHP; (4) construct the evidence body for each drug under evaluation; (5) select comparative measures and calculate the original utility score; (6) place a common utility scale and calculate the standardized utility score; (7) calculate the comprehensive utility score; (8) rank the drugs; and (9) perform a sensitivity analysis. The model was applied to the evaluation of three different inhaled corticosteroids (ICSs) used for asthma management in children (a total of 16 drugs with different dosage forms and strengths or different manufacturers). By applying the drug analysis model, the 16 ICSs under review were successfully scored and evaluated. Budesonide suspension for inhalation (drug ID number: 7) ranked the highest, with comprehensive utility score of 80.23, followed by fluticasone propionate inhaled aerosol (drug ID number: 16), with a score of 79.59, and budesonide inhalation powder (drug ID number: 6), with a score of 78.98. In the sensitivity analysis, the ranking of the top five and lowest five drugs remains unchanged, suggesting this model is generally robust. An evidence-based drug evaluation model based on AHP was successfully developed. The model incorporates sufficient utility and flexibility for aiding the decision-making process, and can be a useful tool for the CCES-P.

Multiparametric and semiquantitative scoring systems for the evaluation of mouse model histopathology - a systematic review

PubMed Central

2013-01-01

Background Histopathology has initially been and is still used to diagnose infectious, degenerative or neoplastic diseases in humans or animals. In addition to qualitative diagnoses semiquantitative scoring of a lesion`s magnitude on an ordinal scale is a commonly demanded task for histopathologists. Multiparametric, semiquantitative scoring systems for mouse models histopathology are a common approach to handle these questions and to include histopathologic information in biomedical research. Results Inclusion criteria for scoring systems were a first description of a multiparametric, semiquantiative scoring systems which comprehensibly describe an approach to evaluate morphologic lesion. A comprehensive literature search using these criteria identified 153 originally designed semiquantitative scoring systems for the analysis of morphologic changes in mouse models covering almost all organs systems and a wide variety of disease models. Of these, colitis, experimental autoimmune encephalitis, lupus nephritis and collagen induced osteoarthritis colitis were the disease models with the largest number of different scoring systems. Closer analysis of the identified scoring systems revealed a lack of a rationale for the selection of the scoring parameters or a correlation between scoring parameter value and the magnitude of the clinical symptoms in most studies. Conclusion Although a decision for a particular scoring system is clearly dependent on the respective scientific question this review gives an overview on currently available systems and may therefore allow for a better choice for the respective project. PMID:23800279

Investigating Supervisory Relationships and Therapeutic Alliances Using Structural Equation Modeling

ERIC Educational Resources Information Center

DePue, Mary Kristina; Lambie, Glenn W.; Liu, Ren; Gonzalez, Jessica

2016-01-01

The authors used structural equation modeling to examine the contribution of supervisees' supervisory relationship levels to therapeutic alliance (TA) scores with their clients in practicum. Results showed that supervisory relationship scores positively contributed to the TA. Client and counselor ratings of the TA also differed.

Accuracy, calibration and clinical performance of the EuroSCORE: can we reduce the number of variables?

PubMed

Ranucci, Marco; Castelvecchio, Serenella; Menicanti, Lorenzo; Frigiola, Alessandro; Pelissero, Gabriele

2010-03-01

The European system for cardiac operative risk evaluation (EuroSCORE) is currently used in many institutions and is considered a reference tool in many countries. We hypothesised that too many variables were included in the EuroSCORE using limited patient series. We tested different models using a limited number of variables. A total of 11150 adult patients undergoing cardiac operations at our institution (2001-2007) were retrospectively analysed. The 17 risk factors composing the EuroSCORE were separately analysed and ranked for accuracy of prediction of hospital mortality. Seventeen models were created by progressively including one factor at a time. The models were compared for accuracy with a receiver operating characteristics (ROC) analysis and area under the curve (AUC) evaluation. Calibration was tested with Hosmer-Lemeshow statistics. Clinical performance was assessed by comparing the predicted with the observed mortality rates. The best accuracy (AUC 0.76) was obtained using a model including only age, left ventricular ejection fraction, serum creatinine, emergency operation and non-isolated coronary operation. The EuroSCORE AUC (0.75) was not significantly different. Calibration and clinical performance were better in the five-factor model than in the EuroSCORE. Only in high-risk patients were 12 factors needed to achieve a good performance. Including many factors in multivariable logistic models increases the risk for overfitting, multicollinearity and human error. A five-factor model offers the same level of accuracy but demonstrated better calibration and clinical performance. Models with a limited number of factors may work better than complex models when applied to a limited number of patients. Copyright (c) 2009 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Alkaline phosphatase: the next independent predictor of the poor 90-day outcome in alcoholic hepatitis.

PubMed

Kasztelan-Szczerbinska, Beata; Slomka, Maria; Celinski, Krzysztof; Szczerbinski, Mariusz

2013-01-01

Determination of risk factors relevant to 90-day prognosis in AH. Comparison of the conventional prognostic models such as Maddrey's modified discriminant function (mDF) and Child-Pugh-Turcotte (CPT) score with newer ones: the Glasgow Alcoholic Hepatitis Score (GAHS); Age, Bilirubin, INR, Creatinine (ABIC) score, Model for End-Stage Liver Disease (MELD), and MELD-Na in the death prediction. The clinical and laboratory variables obtained at admission were assessed. The mDF, CPT, GAHS, ABIC, MELD, and MELD-Na scores' different areas under the curve (AUCs) and the best threshold values were compared. Logistic regression was used to assess predictors of the 90-day outcome. One hundred sixteen pts fulfilled the inclusion criteria. Twenty (17.4%) pts died and one underwent orthotopic liver transplantation (OLT) within 90 days of follow-up. No statistically significant differences in the models' performances were found. Multivariate logistic regression identified CPT score, alkaline phosphatase (AP) level higher than 1.5 times the upper limit of normal (ULN), and corticosteroids (CS) nonresponse as independent predictors of mortality. The CPT score, AP > 1.5 ULN, and the CS nonresponse had an independent impact on the 90-day survival in AH. Accuracy of all studied scoring systems was comparable.

A comparison of three developmental stage scoring systems.

PubMed

Dawson, Theo Linda

2002-01-01

In social psychological research the stage metaphor has fallen into disfavor due to concerns about bias, reliability, and validity. To address some of these issues, I employ a multidimensional partial credit analysis comparing moral judgment interviews scored with the Standard Issue Scoring System (SISS) (Colby and Kohlberg, 1987b), evaluative reasoning interviews scored with the Good Life Scoring System (GLSS) (Armon, 1984b), and Good Education interviews scored with the Hierarchical Complexity Scoring System (HCSS) (Commons, Danaher, Miller, and Dawson, 2000). A total of 209 participants between the ages of 5 and 86 were interviewed. The multidimensional model reveals that even though the scoring systems rely upon different criteria and the data were collected using different methods and scored by different teams of raters, the SISS, GLSS, and HCSS all appear to measure the same latent variable. The HCSS exhibits more internal consistency than the SISS and GLSS, and solves some methodological problems introduced by the content dependency of the SISS and GLSS. These results and their implications are elaborated.

Differential item functioning magnitude and impact measures from item response theory models.

PubMed

Kleinman, Marjorie; Teresi, Jeanne A

2016-01-01

Measures of magnitude and impact of differential item functioning (DIF) at the item and scale level, respectively are presented and reviewed in this paper. Most measures are based on item response theory models. Magnitude refers to item level effect sizes, whereas impact refers to differences between groups at the scale score level. Reviewed are magnitude measures based on group differences in the expected item scores and impact measures based on differences in the expected scale scores. The similarities among these indices are demonstrated. Various software packages are described that provide magnitude and impact measures, and new software presented that computes all of the available statistics conveniently in one program with explanations of their relationships to one another.

Evaluation of visual acuity measurements after autorefraction vs manual refraction in eyes with and without diabetic macular edema.

PubMed

Sun, Jennifer K; Qin, Haijing; Aiello, Lloyd Paul; Melia, Michele; Beck, Roy W; Andreoli, Christopher M; Edwards, Paul A; Glassman, Adam R; Pavlica, Michael R

2012-04-01

To compare visual acuity (VA) scores after autorefraction vs manual refraction in eyes of patients with diabetes mellitus and a wide range of VAs. The letter score from the Electronic Visual Acuity (EVA) test from the electronic Early Treatment Diabetic Retinopathy Study was measured after autorefraction (AR-EVA score) and after manual refraction (MR-EVA score), which is the research protocol of the Diabetic Retinopathy Clinical Research Network. Testing order was randomized, study participants and VA examiners were masked to refraction source, and a second EVA test using an identical supplemental manual refraction (MR-EVAsuppl score) was performed to determine test-retest variability. In 878 eyes of 456 study participants, the median MR-EVA score was 74 (Snellen equivalent, approximately 20/32). The spherical equivalent was often similar for manual refraction and autorefraction (median difference, 0.00; 5th-95th percentile range, -1.75 to 1.13 diopters). However, on average, the MR-EVA scores were slightly better than the AR-EVA scores, across the entire VA range. Furthermore, the variability between the AR-EVA scores and the MR-EVA scores was substantially greater than the test-retest variability of the MR-EVA scores (P < .001). The variability of differences was highly dependent on the autorefractor model. Across a wide range of VAs at multiple sites using a variety of autorefractors, VA measurements tend to be worse with autorefraction than manual refraction. Differences between individual autorefractor models were identified. However, even among autorefractor models that compare most favorably with manual refraction, VA variability between autorefraction and manual refraction is higher than the test-retest variability of manual refraction. The results suggest that, with current instruments, autorefraction is not an acceptable substitute for manual refraction for most clinical trials with primary outcomes dependent on best-corrected VA.

A Cognitive Diagnosis Model for Continuous Response

ERIC Educational Resources Information Center

Minchen, Nathan D.; de la Torre, Jimmy; Liu, Ying

2017-01-01

Nondichotomous response models have been of greater interest in recent years due to the increasing use of different scoring methods and various performance measures. As an important alternative to dichotomous scoring, the use of continuous response formats has been found in the literature. To assess finer-grained skills or attributes and to…

Gender, family, and the nutritional status of children in three culturally contrasting states of India.

PubMed

Griffiths, Paula; Matthews, Zoë; Hinde, Andrew

2002-09-01

This paper has three main aims: to measure the clustering of children with low weight for age z-scores within families, to establish whether significant differences exist by gender in weight for age z-scores, and to demonstrate whether the presence of a mother-in-law in the household has any significant impact on the nutritional status of young children. Regression modelling is used to examine the weight for age z-scores of children under the age of four years in Maharashtra, Tamil Nadu and Uttar Pradesh using the 1992-93 Indian National Family Health Survey data. Random effects models measure the clustering of children with low weight for age z-scores in families, controlling for a number of other family factors. Our findings do not reveal significant gender differences in weight for age z-scores. Although little variation was found between family structures in the nutritional status of children, there were significant differences between families after controlling for family type. This suggests that there are differences between families that cannot be explained by a cross-sectional demographic survey. The evidence from this work suggests that nutrition programs need to adopt community nutrition interventions that aim resources at young children from families where children with low weight for age z-scores are found to cluster. However, there is a need for further inter-disciplinary research to collect data from families on behavioural factors and resource allocation in order that we might better understand why some families are more prone to having children with low weight for age z-scores. The diversity in the significant covariates between the three states in the models has shown the need for Indian nutrition programs to adopt state-specific approaches to tackling malnutrition.

East meets West: the influence of racial, ethnic and cultural risk factors on cardiac surgical risk model performance.

PubMed

Soo-Hoo, Sarah; Nemeth, Samantha; Baser, Onur; Argenziano, Michael; Kurlansky, Paul

2018-01-01

To explore the impact of racial and ethnic diversity on the performance of cardiac surgical risk models, the Chinese SinoSCORE was compared with the Society of Thoracic Surgeons (STS) risk model in a diverse American population. The SinoSCORE risk model was applied to 13 969 consecutive coronary artery bypass surgery patients from twelve American institutions. SinoSCORE risk factors were entered into a logistic regression to create a 'derived' SinoSCORE whose performance was compared with that of the STS risk model. Observed mortality was 1.51% (66% of that predicted by STS model). The SinoSCORE 'low-risk' group had a mortality of 0.15%±0.04%, while the medium-risk and high-risk groups had mortalities of 0.35%±0.06% and 2.13%±0.14%, respectively. The derived SinoSCORE model had a relatively good discrimination (area under of the curve (AUC)=0.785) compared with that of the STS risk score (AUC=0.811; P=0.18 comparing the two). However, specific factors that were significant in the original SinoSCORE but that lacked significance in our derived model included body mass index, preoperative atrial fibrillation and chronic obstructive pulmonary disease. SinoSCORE demonstrated limited discrimination when applied to an American population. The derived SinoSCORE had a discrimination comparable with that of the STS, suggesting underlying similarities of physiological substrate undergoing surgery. However, differential influence of various risk factors suggests that there may be varying degrees of importance and interactions between risk factors. Clinicians should exercise caution when applying risk models across varying populations due to potential differences that racial, ethnic and geographic factors may play in cardiac disease and surgical outcomes.

Propensity Score Estimation With Boosted Regression for Evaluating Causal Effects in Observational Studies

ERIC Educational Resources Information Center

McCaffrey, Daniel F.; Ridgeway, Greg; Morral, Andrew R.

2004-01-01

Causal effect modeling with naturalistic rather than experimental data is challenging. In observational studies participants in different treatment conditions may also differ on pretreatment characteristics that influence outcomes. Propensity score methods can theoretically eliminate these confounds for all observed covariates, but accurate…

Measurement Error Correction Formula for Cluster-Level Group Differences in Cluster Randomized and Observational Studies

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.

2016-01-01

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

Anomalous diffusion in the evolution of soccer championship scores: Real data, mean-field analysis, and an agent-based model

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Vainstein, Mendeli H.; Gonçalves, Sebastián; Paula, Felipe S. F.

2013-08-01

Statistics of soccer tournament scores based on the double round robin system of several countries are studied. Exploring the dynamics of team scoring during tournament seasons from recent years we find evidences of superdiffusion. A mean-field analysis results in a drift velocity equal to that of real data but in a different diffusion coefficient. Along with the analysis of real data we present the results of simulations of soccer tournaments obtained by an agent-based model which successfully describes the final scoring distribution [da Silva , Comput. Phys. Commun.CPHCBZ0010-465510.1016/j.cpc.2012.10.030 184, 661 (2013)]. Such model yields random walks of scores over time with the same anomalous diffusion as observed in real data.

Improved protein model quality assessments by changing the target function.

PubMed

Uziela, Karolis; Menéndez Hurtado, David; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne

2018-06-01

Protein modeling quality is an important part of protein structure prediction. We have for more than a decade developed a set of methods for this problem. We have used various types of description of the protein and different machine learning methodologies. However, common to all these methods has been the target function used for training. The target function in ProQ describes the local quality of a residue in a protein model. In all versions of ProQ the target function has been the S-score. However, other quality estimation functions also exist, which can be divided into superposition- and contact-based methods. The superposition-based methods, such as S-score, are based on a rigid body superposition of a protein model and the native structure, while the contact-based methods compare the local environment of each residue. Here, we examine the effects of retraining our latest predictor, ProQ3D, using identical inputs but different target functions. We find that the contact-based methods are easier to predict and that predictors trained on these measures provide some advantages when it comes to identifying the best model. One possible reason for this is that contact based methods are better at estimating the quality of multi-domain targets. However, training on the S-score gives the best correlation with the GDT_TS score, which is commonly used in CASP to score the global model quality. To take the advantage of both of these features we provide an updated version of ProQ3D that predicts local and global model quality estimates based on different quality estimates. © 2018 Wiley Periodicals, Inc.

Examining the Process of Responding to Circumplex Scales of Interpersonal Values Items: Should Ideal Point Scoring Methods Be Considered?

PubMed

Ling, Ying; Zhang, Minqiang; Locke, Kenneth D; Li, Guangming; Li, Zonglong

2016-01-01

The Circumplex Scales of Interpersonal Values (CSIV) is a 64-item self-report measure of goals from each octant of the interpersonal circumplex. We used item response theory methods to compare whether dominance models or ideal point models best described how people respond to CSIV items. Specifically, we fit a polytomous dominance model called the generalized partial credit model and an ideal point model of similar complexity called the generalized graded unfolding model to the responses of 1,893 college students. The results of both graphical comparisons of item characteristic curves and statistical comparisons of model fit suggested that an ideal point model best describes the process of responding to CSIV items. The different models produced different rank orderings of high-scoring respondents, but overall the models did not differ in their prediction of criterion variables (agentic and communal interpersonal traits and implicit motives).

Purposes and methods of scoring earthquake forecasts

NASA Astrophysics Data System (ADS)

Zhuang, J.

2010-12-01

There are two kinds of purposes in the studies on earthquake prediction or forecasts: one is to give a systematic estimation of earthquake risks in some particular region and period in order to give advice to governments and enterprises for the use of reducing disasters, the other one is to search for reliable precursors that can be used to improve earthquake prediction or forecasts. For the first case, a complete score is necessary, while for the latter case, a partial score, which can be used to evaluate whether the forecasts or predictions have some advantages than a well know model, is necessary. This study reviews different scoring methods for evaluating the performance of earthquake prediction and forecasts. Especially, the gambling scoring method, which is developed recently, shows its capacity in finding good points in an earthquake prediction algorithm or model that are not in a reference model, even if its overall performance is no better than the reference model.

Intelligence and Academic Achievement With Asymptomatic Congenital Cytomegalovirus Infection.

PubMed

Lopez, Adriana S; Lanzieri, Tatiana M; Claussen, Angelika H; Vinson, Sherry S; Turcich, Marie R; Iovino, Isabella R; Voigt, Robert G; Caviness, A Chantal; Miller, Jerry A; Williamson, W Daniel; Hales, Craig M; Bialek, Stephanie R; Demmler-Harrison, Gail

2017-11-01

To examine intelligence, language, and academic achievement through 18 years of age among children with congenital cytomegalovirus infection identified through hospital-based newborn screening who were asymptomatic at birth compared with uninfected infants. We used growth curve modeling to analyze trends in IQ (full-scale, verbal, and nonverbal intelligence), receptive and expressive vocabulary, and academic achievement in math and reading. Separate models were fit for each outcome, modeling the change in overall scores with increasing age for patients with normal hearing ( n = 78) or with sensorineural hearing loss (SNHL) diagnosed by 2 years of age ( n = 11) and controls ( n = 40). Patients with SNHL had full-scale intelligence and receptive vocabulary scores that were 7.0 and 13.1 points lower, respectively, compared with controls, but no significant differences were noted in these scores among patients with normal hearing and controls. No significant differences were noted in scores for verbal and nonverbal intelligence, expressive vocabulary, and academic achievement in math and reading among patients with normal hearing or with SNHL and controls. Infants with asymptomatic congenital cytomegalovirus infection identified through newborn screening with normal hearing by age 2 years do not appear to have differences in IQ, vocabulary or academic achievement scores during childhood, or adolescence compared with uninfected children. Copyright © 2017 by the American Academy of Pediatrics.

Histological and reference system for the analysis of mouse intervertebral disc.

PubMed

Tam, Vivian; Chan, Wilson C W; Leung, Victor Y L; Cheah, Kathryn S E; Cheung, Kenneth M C; Sakai, Daisuke; McCann, Matthew R; Bedore, Jake; Séguin, Cheryle A; Chan, Danny

2018-01-01

A new scoring system based on histo-morphology of mouse intervertebral disc (IVD) was established to assess changes in different mouse models of IVD degeneration and repair. IVDs from mouse strains of different ages, transgenic mice, or models of artificially induced IVD degeneration were assessed. Morphological features consistently observed in normal, and early/later stages of degeneration were categorized into a scoring system focused on nucleus pulposus (NP) and annulus fibrosus (AF) changes. "Normal NP" exhibited a highly cellularized cell mass that decreased with natural ageing and in disc degeneration. "Normal AF" consisted of distinct concentric lamellar structures, which was disrupted in severe degeneration. NP/AF clefts indicated more severe changes. Consistent scores were obtained between experienced and new users. Altogether, our scoring system effectively differentiated IVD changes in various strains of wild-type and genetically modified mice and in induced models of IVD degeneration, and is applicable from the post-natal stage to the aged mouse. This scoring tool and reference resource addresses a pressing need in the field for studying IVD changes and cross-study comparisons in mice, and facilitates a means to normalize mouse IVD assessment between different laboratories. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:233-243, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Haptic Recreation of Elbow Spasticity

PubMed Central

Kim, Jonghyun; Damiano, Diane L.

2013-01-01

The aim of this paper is to develop a haptic device capable of presenting standardized recreation of elbow spasticity. Using the haptic device, clinicians will be able to repeatedly practice the assessment of spasticity without requiring patient involvement, and these practice opportunities will help improve accuracy and reliability of the assessment itself. Haptic elbow spasticity simulator (HESS) was designed and prototyped according to mechanical requirements to recreate the feel of elbow spasticity. Based on the data collected from subjects with elbow spasticity, a mathematical model representing elbow spasticity is proposed. As an attempt to differentiate the feel of each score in Modified Ashworth Scale (MAS), parameters of the model were obtained respectively for three different MAS scores 1, 1+, and 2. The implemented haptic recreation was evaluated by experienced clinicians who were asked to give MAS scores by manipulating the haptic device. The clinicians who participated in the study were blinded to each other’s scores and to the given models. They distinguished the three models and the MAS scores given to the recreated models matched 100% with the original MAS scores from the patients. PMID:22275660

A test of the ABC model underlying rational emotive behavior therapy.

PubMed

Ziegler, Daniel J; Leslie, Yvonne M

2003-02-01

The ABC model underlying Ellis's Rational Emotive Behavior Therapy predicts that people who think more irrationally should respond to daily stressors or hassles differently than do people who think less irrationally. This study tested this aspect of the ABC model. 192 college students were administered the Survey of Personal Beliefs and the Hassles Scale to measure irrational thinking and daily hassles, respectively. Students who scored higher on overall irrational thinking reported a significantly higher frequency of hassles than did those who scored lower on overall irrational thinking, while students who scored higher on awfulizing and low frustration tolerance reported a significantly greater intensity of hassles than did those who scored lower on awfulizing and low frustration tolerance. This indicates support for the ABC model, especially Ellis's construct of irrational beliefs central to this model.

Comparative study analysing women's childbirth satisfaction and obstetric outcomes across two different models of maternity care

PubMed Central

Conesa Ferrer, Ma Belén; Canteras Jordana, Manuel; Ballesteros Meseguer, Carmen; Carrillo García, César; Martínez Roche, M Emilia

2016-01-01

Objectives To describe the differences in obstetrical results and women's childbirth satisfaction across 2 different models of maternity care (biomedical model and humanised birth). Setting 2 university hospitals in south-eastern Spain from April to October 2013. Design A correlational descriptive study. Participants A convenience sample of 406 women participated in the study, 204 of the biomedical model and 202 of the humanised model. Results The differences in obstetrical results were (biomedical model/humanised model): onset of labour (spontaneous 66/137, augmentation 70/1, p=0.0005), pain relief (epidural 172/132, no pain relief 9/40, p=0.0005), mode of delivery (normal vaginal 140/165, instrumental 48/23, p=0.004), length of labour (0–4 hours 69/93, >4 hours 133/108, p=0.011), condition of perineum (intact perineum or tear 94/178, episiotomy 100/24, p=0.0005). The total questionnaire score (100) gave a mean (M) of 78.33 and SD of 8.46 in the biomedical model of care and an M of 82.01 and SD of 7.97 in the humanised model of care (p=0.0005). In the analysis of the results per items, statistical differences were found in 8 of the 9 subscales. The highest scores were reached in the humanised model of maternity care. Conclusions The humanised model of maternity care offers better obstetrical outcomes and women's satisfaction scores during the labour, birth and immediate postnatal period than does the biomedical model. PMID:27566632

The variation in the eating quality of beef from different sexes and breed classes cannot be completely explained by carcass measurements.

PubMed

Bonny, S P F; Hocquette, J-F; Pethick, D W; Farmer, L J; Legrand, I; Wierzbicki, J; Allen, P; Polkinghorne, R J; Gardner, G E

2016-06-01

Delivering beef of consistent quality to the consumer is vital for consumer satisfaction and will help to ensure demand and therefore profitability within the beef industry. In Australia, this is being tackled with Meat Standards Australia (MSA), which uses carcass traits and processing factors to deliver an individual eating quality guarantee to the consumer for 135 different 'cut by cooking methods' from each carcass. The carcass traits used in the MSA model, such as ossification score, carcass weight and marbling explain the majority of the differences between breeds and sexes. Therefore, it was expected that the model would predict with eating quality of bulls and dairy breeds with good accuracy. In total, 8128 muscle samples from 482 carcasses from France, Poland, Ireland and Northern Ireland were MSA graded at slaughter then evaluated for tenderness, juiciness, flavour liking and overall liking by untrained consumers, according to MSA protocols. The scores were weighted (0.3, 0.1, 0.3, 0.3) and combined to form a global eating quality (meat quality (MQ4)) score. The carcasses were grouped into one of the three breed categories: beef breeds, dairy breeds and crosses. The difference between the actual and the MSA-predicted MQ4 scores were analysed using a linear mixed effects model including fixed effects for carcass hang method, cook type, muscle type, sex, country, breed category and postmortem ageing period, and random terms for animal identification, consumer country and kill group. Bulls had lower MQ4 scores than steers and females and were predicted less accurately by the MSA model. Beef breeds had lower eating quality scores than dairy breeds and crosses for five out of the 16 muscles tested. Beef breeds were also over predicted in comparison with the cross and dairy breeds for six out of the 16 muscles tested. Therefore, even after accounting for differences in carcass traits, bulls still differ in eating quality when compared with females and steers. Breed also influenced eating quality beyond differences in carcass traits. However, in this case, it was only for certain muscles. This should be taken into account when estimating the eating quality of meat. In addition, the coefficients used by the Australian MSA model for some muscles, marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this data set, and if this system was to be applied to Europe then the coefficients for these muscles and covariates would need further investigation.

Factor structure and convergent validity of the Derriford Appearance Scale-24 using standard scoring versus treating ‘not applicable’ responses as missing data: a Scleroderma Patient-centered Intervention Network (SPIN) cohort study

PubMed Central

Merz, Erin L; Kwakkenbos, Linda; Carrier, Marie-Eve; Gholizadeh, Shadi; Mills, Sarah D; Fox, Rina S; Jewett, Lisa R; Williamson, Heidi; Harcourt, Diana; Assassi, Shervin; Furst, Daniel E; Gottesman, Karen; Mayes, Maureen D; Moss, Tim P; Thombs, Brett D; Malcarne, Vanessa L

2018-01-01

Objective Valid measures of appearance concern are needed in systemic sclerosis (SSc), a rare, disfiguring autoimmune disease. The Derriford Appearance Scale-24 (DAS-24) assesses appearance-related distress related to visible differences. There is uncertainty regarding its factor structure, possibly due to its scoring method. Design Cross-sectional survey. Setting Participants with SSc were recruited from 27 centres in Canada, the USA and the UK. Participants who self-identified as having visible differences were recruited from community and clinical settings in the UK. Participants Two samples were analysed (n=950 participants with SSc; n=1265 participants with visible differences). Primary and secondary outcome measures The DAS-24 factor structure was evaluated using two scoring methods. Convergent validity was evaluated with measures of social interaction anxiety, depression, fear of negative evaluation, social discomfort and dissatisfaction with appearance. Results When items marked by respondents as ‘not applicable’ were scored as 0, per standard DAS-24 scoring, a one-factor model fit poorly; when treated as missing data, the one-factor model fit well. Convergent validity analyses revealed strong correlations that were similar across scoring methods. Conclusions Treating ‘not applicable’ responses as missing improved the measurement model, but did not substantively influence practical inferences that can be drawn from DAS-24 scores. Indications of item redundancy and poorly performing items suggest that the DAS-24 could be improved and potentially shortened. PMID:29511009

Glutamate-evoked jaw muscle pain as a model of persistent myofascial TMD pain?

PubMed Central

Castrillon, Eduardo E.; Cairns, Brian E.; Ernberg, Malin; Wang, Kelun; Sessle, Barry; Arendt-Nielsen, Lars; Svensson, Peter

2008-01-01

Objective Compare pain-related measures and psychosocial variables between glutamate-evoked jaw muscle pain in healthy subjects (HS) and patients with persistent myofascial temporomandibular disorder (TMD) pain. Design 47 female HS and 10 female patients with persistent myofascial TMD pain participated. The HS received an injection of glutamate into the masseter muscle to model persistent myofascial TMD pain. Participants filled out a coping strategies questionnaire (CSQ), the symptom checklist 90 (SCL-90) and McGill Pain Questionnaire (MPQ). Pain intensity was assessed on an electronic visual analog scale (VAS). Pain-drawing areas, Numerical Rating Scale (NRS) scores of unpleasantness, pressure pain thresholds (PPT) and tolerance (PPTOL) were measured. Unpaired t-tests and correlation tests were used for analyses. Results The groups were significantly different when comparing the CSQ scores of control, decrease, diverting attention, increase of behavioral activities and somatization. The peak VAS pain, NRS of unpleasantness and MPQ scores were not significantly different between groups, but PPT and PPTOL were significantly lower in the TMD patients. Significant positive correlations were found in the TMD patients between peak VAS pain and CSQ catastrophizing score and SCL-90 somatization. The scores of PPTs and PPTOLs, in patients showed positive correlations with CSQ reinterpreting pain sensations scores and PPTs correlated with CSQ praying/hoping scores. Conclusions Glutamate-evoked pain responses in HS and persistent myofascial TMD pain have similar sensory-discriminative and affective-unpleasantness components but differ in psycho-social features. This study suggests that experimental designs based on glutamate injection into muscle can provide an appropriate model for elucidating persistent myofascial pain conditions. PMID:18313028

A Risk Score Model for Evaluation and Management of Patients with Thyroid Nodules.

PubMed

Zhang, Yongwen; Meng, Fanrong; Hong, Lianqing; Chu, Lanfang

2018-06-12

The study is aimed to establish a simplified and practical tool for analyzing thyroid nodules. A novel risk score model was designed, risk factors including patient history, patient characteristics, physical examination, symptoms of compression, thyroid function, ultrasonography (US) of thyroid and cervical lymph nodes were evaluated and classified into high risk factors, intermediate risk factors, and low risk factors. A total of 243 thyroid nodules in 162 patients were assessed with risk score system and Thyroid Imaging-Reporting and Data System (TI-RADS). The diagnostic performance of risk score system and TI-RADS was compared. The accuracy in the diagnosis of thyroid nodules was 89.3% for risk score system, 74.9% for TI-RADS respectively. The specificity, accuracy and positive predictive value (PPV) of risk score system were significantly higher than the TI-RADS system (χ 2 =26.287, 17.151, 11.983; p <0.05), statistically significant differences were not observed in the sensitivity and negative predictive value (NPV) between the risk score system and TI-RADS (χ 2 =1.276, 0.290; p>0.05). The area under the curve (AUC) for risk score diagnosis system was 0.963, standard error 0.014, 95% confidence interval (CI)=0.934-0.991, the AUC for TI-RADS diagnosis system was 0.912 with standard error 0.021, 95% CI=0.871-0.953, the AUC for risk score system was significantly different from that of TI-RADS (Z=2.02; p <0.05). Risk score model is a reliable, simplified and cost-effective diagnostic tool used in diagnosis of thyroid cancer. The higher the score is, the higher the risk of malignancy will be. © Georg Thieme Verlag KG Stuttgart · New York.

MetaMQAP: a meta-server for the quality assessment of protein models.

PubMed

Pawlowski, Marcin; Gajda, Michal J; Matlak, Ryszard; Bujnicki, Janusz M

2008-09-29

Computational models of protein structure are usually inaccurate and exhibit significant deviations from the true structure. The utility of models depends on the degree of these deviations. A number of predictive methods have been developed to discriminate between the globally incorrect and approximately correct models. However, only a few methods predict correctness of different parts of computational models. Several Model Quality Assessment Programs (MQAPs) have been developed to detect local inaccuracies in unrefined crystallographic models, but it is not known if they are useful for computational models, which usually exhibit different and much more severe errors. The ability to identify local errors in models was tested for eight MQAPs: VERIFY3D, PROSA, BALA, ANOLEA, PROVE, TUNE, REFINER, PROQRES on 8251 models from the CASP-5 and CASP-6 experiments, by calculating the Spearman's rank correlation coefficients between per-residue scores of these methods and local deviations between C-alpha atoms in the models vs. experimental structures. As a reference, we calculated the value of correlation between the local deviations and trivial features that can be calculated for each residue directly from the models, i.e. solvent accessibility, depth in the structure, and the number of local and non-local neighbours. We found that absolute correlations of scores returned by the MQAPs and local deviations were poor for all methods. In addition, scores of PROQRES and several other MQAPs strongly correlate with 'trivial' features. Therefore, we developed MetaMQAP, a meta-predictor based on a multivariate regression model, which uses scores of the above-mentioned methods, but in which trivial parameters are controlled. MetaMQAP predicts the absolute deviation (in Angströms) of individual C-alpha atoms between the model and the unknown true structure as well as global deviations (expressed as root mean square deviation and GDT_TS scores). Local model accuracy predicted by MetaMQAP shows an impressive correlation coefficient of 0.7 with true deviations from native structures, a significant improvement over all constituent primary MQAP scores. The global MetaMQAP score is correlated with model GDT_TS on the level of 0.89. Finally, we compared our method with the MQAPs that scored best in the 7th edition of CASP, using CASP7 server models (not included in the MetaMQAP training set) as the test data. In our benchmark, MetaMQAP is outperformed only by PCONS6 and method QA_556 - methods that require comparison of multiple alternative models and score each of them depending on its similarity to other models. MetaMQAP is however the best among methods capable of evaluating just single models. We implemented the MetaMQAP as a web server available for free use by all academic users at the URL https://genesilico.pl/toolkit/

No Clinically Significant Difference Between Adult and Pediatric IKDC Subjective Knee Evaluation Scores in Adults.

PubMed

Stegmeier, Nicole; Oak, Sameer R; O'Rourke, Colin; Strnad, Greg; Spindler, Kurt P; Jones, Morgan; Farrow, Lutul D; Andrish, Jack; Saluan, Paul

Two versions of the International Knee Documentation Committee (IKDC) Subjective Knee Evaluation form currently exist: the original version (1999) and a recently modified pediatric-specific version (2011). Comparison of the pediatric IKDC with the adult version in the adult population may reveal that either version could be used longitudinally. We hypothesize that the scores for the adult IKDC and pediatric IKDC will not be clinically different among adult patients aged 18 to 50 years. Randomized crossover study design. Level 2. The study consisted of 100 participants, aged 18 to 50 years, who presented to orthopaedic outpatient clinics with knee problems. All participants completed both adult and pediatric versions of the IKDC in random order with a 10-minute break in between. We used a paired t test to test for a difference between the scores and a Welch's 2-sample t test to test for equivalence. A least-squares regression model was used to model adult scores as a function of pediatric scores, and vice versa. A paired t test revealed a statistically significant 1.6-point difference between the mean adult and pediatric scores. However, the 95% confidence interval (0.54-2.66) for this difference did not exceed our a priori threshold of 5 points, indicating that this difference was not clinically important. Equivalence testing with an equivalence region of 5 points further supported this finding. The adult and pediatric scores had a linear relationship and were highly correlated with an R 2 of 92.6%. There is no clinically relevant difference between the scores of the adult and pediatric IKDC forms in adults, aged 18 to 50 years, with knee conditions. Either form, adult or pediatric, of the IKDC can be used in this population for longitudinal studies. If the pediatric version is administered in adolescence, it can be used for follow-up into adulthood.

No Clinically Significant Difference Between Adult and Pediatric IKDC Subjective Knee Evaluation Scores in Adults

PubMed Central

Stegmeier, Nicole; Oak, Sameer R.; O’Rourke, Colin; Strnad, Greg; Spindler, Kurt P.; Jones, Morgan; Farrow, Lutul D.; Andrish, Jack; Saluan, Paul

2017-01-01

Background: Two versions of the International Knee Documentation Committee (IKDC) Subjective Knee Evaluation form currently exist: the original version (1999) and a recently modified pediatric-specific version (2011). Comparison of the pediatric IKDC with the adult version in the adult population may reveal that either version could be used longitudinally. Hypothesis: We hypothesize that the scores for the adult IKDC and pediatric IKDC will not be clinically different among adult patients aged 18 to 50 years. Study Design: Randomized crossover study design. Level of Evidence: Level 2. Methods: The study consisted of 100 participants, aged 18 to 50 years, who presented to orthopaedic outpatient clinics with knee problems. All participants completed both adult and pediatric versions of the IKDC in random order with a 10-minute break in between. We used a paired t test to test for a difference between the scores and a Welch’s 2-sample t test to test for equivalence. A least-squares regression model was used to model adult scores as a function of pediatric scores, and vice versa. Results: A paired t test revealed a statistically significant 1.6-point difference between the mean adult and pediatric scores. However, the 95% confidence interval (0.54-2.66) for this difference did not exceed our a priori threshold of 5 points, indicating that this difference was not clinically important. Equivalence testing with an equivalence region of 5 points further supported this finding. The adult and pediatric scores had a linear relationship and were highly correlated with an R2 of 92.6%. Conclusion: There is no clinically relevant difference between the scores of the adult and pediatric IKDC forms in adults, aged 18 to 50 years, with knee conditions. Clinical Relevance: Either form, adult or pediatric, of the IKDC can be used in this population for longitudinal studies. If the pediatric version is administered in adolescence, it can be used for follow-up into adulthood. PMID:28080306

Different personalities between depression and anxiety.

PubMed

Tanaka, E; Sakamoto, S; Kijima, N; Kitamura, T

1998-12-01

We examined the different personality dimensions between depression and anxiety with Cloninger's seven-factor model of temperament and character. The Temperament and Character Inventory (TCI), which measures four temperament and three character dimensions of Cloninger's personality theory (125-item short version), the Self-rating Depression Scale (SDS), and the State-Trait Anxiety Inventory (STAI) were administered to 223 Japanese students. With hierarchical regression analysis, the SDS score was predicted by scores of Harm-Avoidance, Self-Directedness, and Self-Transcendence, even after controlling for the STAI score. The STAI score was predicted by scores of Self-Directedness and Cooperativeness, even after controlling for the SDS score. More importance should be attached to these dimensions of character because they might contribute to both depression and anxiety.

[Opiate dependence type II or antisocial: Cloninger's Psychobiological Model and its usefullness in addictions].

PubMed

Benito, Ana; Haro, Gonzalo; Orengo, Teresa; González, Marisa; Fornés, Teresa; Mateu, César

2012-01-01

The aim was to analyze the relationship between Cloninger's dimensions and Personality Disorders (PD) (with DSM-IV criteria) in opiate dependents. The study was Cross-sectional. The sampling of 196 patients with opiate dependence was consecutive. All were receiving treatment in an inpatient detoxification unit. Cloninger's Temperament and Character Inventory (TCI), International Personality Disorders Examination (IPDE) and a Substance Use Questionnaire were used. Character's dimensions as Self-directness and Cooperation were related with PD when scored low. Opposite to Cloninger descriptions, high scores of Self-transcendence were related with presence of PD. Related to temperamental dimensions, cluster A was related with low scores of Reward Dependence (RD) and cluster C with high scores of Harm Avoidance (HA). Otherwise, in cluster B, while Borderline PD had high scores of Novelty Seeking (as high HA), the Antisocial PD only were related to low scores of RD. RD dimension seems useful to differ from presence or absence of Antisocial PD, also when alcohol consumption is considered. Cloninger's Model of Personality is useful in drug dependents for the definition of the different PD, as well as for probable PD's aggregation. This model also helps to create subtypes in opiate dependents as the antisocial or type II.

The relative efficiency of Iranian's rural traffic police: a three-stage DEA model.

PubMed

Rahimi, Habibollah; Soori, Hamid; Nazari, Seyed Saeed Hashemi; Motevalian, Seyed Abbas; Azar, Adel; Momeni, Eskandar; Javartani, Mehdi

2017-10-13

Road traffic Injuries (RTIs) as a health problem imposes governments to implement different interventions. Target achievement in this issue required effective and efficient measures. Efficiency evaluation of traffic police as one of the responsible administrators is necessary for resource management. Therefore, this study conducted to measure Iran's rural traffic police efficiency. This was an ecological study. To obtain pure efficiency score, three-stage DEA model was conducted with seven inputs and three output variables. At the first stage, crude efficiency score was measured with BCC-O model. Next, to extract the effects of socioeconomic, demographic, traffic count and road infrastructure as the environmental variables and statistical noise, the Stochastic Frontier Analysis (SFA) model was applied and the output values were modified according to similar environment and statistical noise conditions. Then, the pure efficiency score was measured using modified outputs and BCC-O model. In total, the efficiency score of 198 police stations from 24 provinces of 31 provinces were measured. The annual means (standard deviation) of damage, injury and fatal accidents were 247.7 (258.4), 184.9 (176.9), and 28.7 (19.5), respectively. Input averages were 5.9 (3.0) patrol teams, 0.5% (0.2) manpower proportions, 7.5 (2.9) patrol cars, 0.5 (1.3) motorcycles, 77,279.1 (46,794.7) penalties, 90.9 (2.8) cultural and educational activity score, 0.7 (2.4) speed cameras. The SFA model showed non-significant differences between police station performances and the most differences attributed to the environmental and random error. One-way main road, by road, traffic count and the number of household owning motorcycle had significant positive relations with inefficiency score. The length of freeway/highway and literacy rate variables had negative relations, significantly. Pure efficiency score was with mean of 0.95 and SD of 0.09. Iran's traffic police has potential opportunity to reduce RTIs. Adjusting police performance with environmental conditions is necessary. Capability of DEA method in setting quantitative targets for every station induces motivation for managers to reduce RTIs. Repetition of this study is recommended, annually.

Student Ranking Differences within Institutions Using Old and New SAT Scores

ERIC Educational Resources Information Center

Marini, Jessica P.; Beard, Jonathan; Shaw, Emily J.

2018-01-01

Admission offices at colleges and universities often use SAT® scores to make decisions about applicants for their incoming class. Many institutions use prediction models to quantify a student's potential for success using various measures, including SAT scores (NACAC, 2016). In March 2016, the College Board introduced a redesigned SAT that better…

Does the patient's inherent rating tendency influence reported satisfaction scores and affect division ranking?

PubMed

Francis, Patricia; Agoritsas, Thomas; Chopard, Pierre; Perneger, Thomas

2016-04-01

To determine the impact of adjusting for rating tendency (RT) on patient satisfaction scores in a large teaching hospital and to assess the impact of adjustment on the ranking of divisions. Cross-sectional survey. Large 2200-bed university teaching hospital. All adult patients hospitalized during a 1-month period in one of 20 medical divisions. None. Patient experience of care measured by the Picker Patient Experience questionnaire and RT scores. Problem scores were weakly but significantly associated with RT. Division ranking was slightly modified in RT adjusted models. Division ranking changed substantially in case-mix adjusted models. Adjusting patient self-reported problem scores for RT did impact ranking of divisions, although marginally. Further studies are needed to determine the impact of RT when comparing different institutions, particularly across inter-cultural settings, where the difference in RT may be more substantial. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

Clinical use of the ABO-Scoring Index: reliability and subtraction frequency.

PubMed

Lieber, William S; Carlson, Sean K; Baumrind, Sheldon; Poulton, Donald R

2003-10-01

This study tested the reliability and subtraction frequency of the study model-scoring system of the American Board of Orthodontists (ABO). We used a sample of 36 posttreatment study models that were selected randomly from six different orthodontic offices. Intrajudge and interjudge reliability was calculated using nonparametric statistics (Spearman rank coefficient, Wilcoxon, Kruskal-Wallis, and Mann-Whitney tests). We found differences ranging from 3 to 6 subtraction points (total score) for intrajudge scoring between two sessions. For overall total ABO score, the average correlation was .77. Intrajudge correlation was greatest for occlusal relationships and least for interproximal contacts. Interjudge correlation for ABO score averaged r = .85. Correlation was greatest for buccolingual inclination and least for overjet. The data show that some judges, on average, were much more lenient than others and that this resulted in a range of total scores between 19.7 and 27.5. Most of the deductions were found in the buccal segments and most were related to the second molars. We present these findings in the context of clinicians preparing for the ABO phase III examination and for orthodontists in their ongoing evaluation of clinical results.

An Analysis of Test Equating Models for the Alabama High School Graduation Examination.

ERIC Educational Resources Information Center

Glowacki, Margaret L.

The purpose of this study was to determine which equating models are appropriate for the Alabama High School Graduation Examination (AHSGE) by equating two previously administered fall forms for each subject area of the AHSGE and determining whether differences exist in the test score distributions or passing scores resulting from the equating…

The phase model of burnout and employee turnover.

PubMed

Goodman, Eric A; Boss, R Wayne

2002-01-01

This study explores the phase model of burnout and investigates its relationship to actual turnover in a hospital. The results indicate that employees who turnover have significantly higher burnout phase scores that those who stay in the organization. A further comparison of voluntary and involuntary turnover demonstrates that there is no significant differences on burnout phase scores. The findings lend support to the usefulness of the phase model of burnout.

Effect of mentoring on professional values in model C clinical nurse leader graduates.

PubMed

Gazaway, Shena B; Anderson, Lori; Schumacher, Autumn; Alichnie, Chris

2018-04-19

Nursing graduates acquire their nursing values by professional socialization. Mentoring is a crucial support mechanism for these novice nurses, yet little is known about the model C clinical nurse leader graduate and the effects of mentoring. This investigation examined how mentoring affected the development of professional nursing values in the model C clinical nurse leader graduate. A longitudinal design was used to survey model C clinical nurse leader graduates before and after graduation to determine how different types of mentoring relationships influenced professional values. Demographic surveys documented participant characteristics and the Nurses Professional Values Scale - Revised (NPVS-R) assessed professional nursing values. Mean NPVS-R scores increased after graduation for the formally mentored participants, while the NPVS-R scores decreased or remained unchanged for the other mentoring groups. However, no significant difference was found in NPVS-R scores over time (p = .092) or an interaction between the NPVS-R scores and type of mentoring relationships (p = .09). These results suggest that model C clinical nurse leader graduate participants experiencing formal mentoring may develop professional nursing values more than their colleagues. Formal mentoring relationships are powerful and should be used to promote professional values for model C clinical nurse leader graduates. © 2018 John Wiley & Sons Ltd.

Inclusion of Highest Glasgow Coma Scale Motor Component Score in Mortality Risk Adjustment for Benchmarking of Trauma Center Performance.

PubMed

Gomez, David; Byrne, James P; Alali, Aziz S; Xiong, Wei; Hoeft, Chris; Neal, Melanie; Subacius, Harris; Nathens, Avery B

2017-12-01

The Glasgow Coma Scale (GCS) is the most widely used measure of traumatic brain injury (TBI) severity. Currently, the arrival GCS motor component (mGCS) score is used in risk-adjustment models for external benchmarking of mortality. However, there is evidence that the highest mGCS score in the first 24 hours after injury might be a better predictor of death. Our objective was to evaluate the impact of including the highest mGCS score on the performance of risk-adjustment models and subsequent external benchmarking results. Data were derived from the Trauma Quality Improvement Program analytic dataset (January 2014 through March 2015) and were limited to the severe TBI cohort (16 years or older, isolated head injury, GCS ≤8). Risk-adjustment models were created that varied in the mGCS covariates only (initial score, highest score, or both initial and highest mGCS scores). Model performance and fit, as well as external benchmarking results, were compared. There were 6,553 patients with severe TBI across 231 trauma centers included. Initial and highest mGCS scores were different in 47% of patients (n = 3,097). Model performance and fit improved when both initial and highest mGCS scores were included, as evidenced by improved C-statistic, Akaike Information Criterion, and adjusted R-squared values. Three-quarters of centers changed their adjusted odds ratio decile, 2.6% of centers changed outlier status, and 45% of centers exhibited a ≥0.5-SD change in the odds ratio of death after including highest mGCS score in the model. This study supports the concept that additional clinical information has the potential to not only improve the performance of current risk-adjustment models, but can also have a meaningful impact on external benchmarking strategies. Highest mGCS score is a good potential candidate for inclusion in additional models. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Using implicit association tests in age-heterogeneous samples: The importance of cognitive abilities and quad model processes.

PubMed

Wrzus, Cornelia; Egloff, Boris; Riediger, Michaela

2017-08-01

Implicit association tests (IATs) are increasingly used to indirectly assess people's traits, attitudes, or other characteristics. In addition to measuring traits or attitudes, IAT scores also reflect differences in cognitive abilities because scores are based on reaction times (RTs) and errors. As cognitive abilities change with age, questions arise concerning the usage and interpretation of IATs for people of different age. To address these questions, the current study examined how cognitive abilities and cognitive processes (i.e., quad model parameters) contribute to IAT results in a large age-heterogeneous sample. Participants (N = 549; 51% female) in an age-stratified sample (range = 12-88 years) completed different IATs and 2 tasks to assess cognitive processing speed and verbal ability. From the IAT data, D2-scores were computed based on RTs, and quad process parameters (activation of associations, overcoming bias, detection, guessing) were estimated from individual error rates. Substantial IAT scores and quad processes except guessing varied with age. Quad processes AC and D predicted D2-scores of the content-specific IAT. Importantly, the effects of cognitive abilities and quad processes on IAT scores were not significantly moderated by participants' age. These findings suggest that IATs seem suitable for age-heterogeneous studies from adolescence to old age when IATs are constructed and analyzed appropriately, for example with D-scores and process parameters. We offer further insight into how D-scoring controls for method effects in IATs and what IAT scores capture in addition to implicit representations of characteristics. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Ossification score is a better indicator of maturity related changes in eating quality than animal age.

PubMed

Bonny, S P F; Pethick, D W; Legrand, I; Wierzbicki, J; Allen, P; Farmer, L J; Polkinghorne, R J; Hocquette, J-F; Gardner, G E

2016-04-01

Ossification score and animal age are both used as proxies for maturity-related collagen crosslinking and consequently decreases in beef tenderness. Ossification score is strongly influenced by the hormonal status of the animal and may therefore better reflect physiological maturity and consequently eating quality. As part of a broader cross-European study, local consumers scored 18 different muscle types cooked in three ways from 482 carcasses with ages ranging from 590 to 6135 days and ossification scores ranging from 110 to 590. The data were studied across three different maturity ranges; the complete range of maturities, a lesser range and a more mature range. The lesser maturity group consisted of carcasses having either an ossification score of 200 or less or an age of 987 days or less with the remainder in the greater maturity group. The three different maturity ranges were analysed separately with a linear mixed effects model. Across all the data, and for the greater maturity group, animal age had a greater magnitude of effect on eating quality than ossification score. This is likely due to a loss of sensitivity in mature carcasses where ossification approached and even reached the maximum value. In contrast, age had no relationship with eating quality for the lesser maturity group, leaving ossification score as the more appropriate measure. Therefore ossification score is more appropriate for most commercial beef carcasses, however it is inadequate for carcasses with greater maturity such as cull cows. Both measures may therefore be required in models to predict eating quality over populations with a wide range in maturity.

A method for modelling GP practice level deprivation scores using GIS

PubMed Central

Strong, Mark; Maheswaran, Ravi; Pearson, Tim; Fryers, Paul

2007-01-01

Background A measure of general practice level socioeconomic deprivation can be used to explore the association between deprivation and other practice characteristics. An area-based categorisation is commonly chosen as the basis for such a deprivation measure. Ideally a practice population-weighted area-based deprivation score would be calculated using individual level spatially referenced data. However, these data are often unavailable. One approach is to link the practice postcode to an area-based deprivation score, but this method has limitations. This study aimed to develop a Geographical Information Systems (GIS) based model that could better predict a practice population-weighted deprivation score in the absence of patient level data than simple practice postcode linkage. Results We calculated predicted practice level Index of Multiple Deprivation (IMD) 2004 deprivation scores using two methods that did not require patient level data. Firstly we linked the practice postcode to an IMD 2004 score, and secondly we used a GIS model derived using data from Rotherham, UK. We compared our two sets of predicted scores to "gold standard" practice population-weighted scores for practices in Doncaster, Havering and Warrington. Overall, the practice postcode linkage method overestimated "gold standard" IMD scores by 2.54 points (95% CI 0.94, 4.14), whereas our modelling method showed no such bias (mean difference 0.36, 95% CI -0.30, 1.02). The postcode-linked method systematically underestimated the gold standard score in less deprived areas, and overestimated it in more deprived areas. Our modelling method showed a small underestimation in scores at higher levels of deprivation in Havering, but showed no bias in Doncaster or Warrington. The postcode-linked method showed more variability when predicting scores than did the GIS modelling method. Conclusion A GIS based model can be used to predict a practice population-weighted area-based deprivation measure in the absence of patient level data. Our modelled measure generally had better agreement with the population-weighted measure than did a postcode-linked measure. Our model may also avoid an underestimation of IMD scores in less deprived areas, and overestimation of scores in more deprived areas, seen when using postcode linked scores. The proposed method may be of use to researchers who do not have access to patient level spatially referenced data. PMID:17822545

Age-related invariance of abilities measured with the Wechsler Adult Intelligence Scale-IV.

PubMed

Sudarshan, Navaneetham J; Bowden, Stephen C; Saklofske, Donald H; Weiss, Lawrence G

2016-11-01

Assessment of measurement invariance across populations is essential for meaningful comparison of test scores, and is especially relevant where repeated measurements are required for educational assessment or clinical diagnosis. Establishing measurement invariance legitimizes the assumption that test scores reflect the same psychological trait in different populations or across different occasions. Examination of Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) U.S. standardization samples revealed that a first-order 5-factor measurement model was best fitting across 9 age groups from 16 years to 69 years. Strong metric invariance was found for 3 of 5 factors and partial intercept invariance for the remaining 2. Pairwise comparisons of adjacent age groups supported the inference that cognitive-trait group differences are manifested by group differences in the test scores. In educational and clinical settings these findings provide theoretical and empirical support to interpret changes in the index or subtest scores as reflecting changes in the corresponding cognitive abilities. Further, where clinically relevant, the subtest score composites can be used to compare changes in respective cognitive abilities. The model was supported in the Canadian standardization data with pooled age groups but the sample sizes were not adequate for detailed examination of separate age groups in the Canadian sample. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods

PubMed Central

Stürmer, Til; Joshi, Manisha; Glynn, Robert J.; Avorn, Jerry; Rothman, Kenneth J.; Schneeweiss, Sebastian

2006-01-01

Objective Propensity score analyses attempt to control for confounding in non-experimental studies by adjusting for the likelihood that a given patient is exposed. Such analyses have been proposed to address confounding by indication, but there is little empirical evidence that they achieve better control than conventional multivariate outcome modeling. Study design and methods Using PubMed and Science Citation Index, we assessed the use of propensity scores over time and critically evaluated studies published through 2003. Results Use of propensity scores increased from a total of 8 papers before 1998 to 71 in 2003. Most of the 177 published studies abstracted assessed medications (N=60) or surgical interventions (N=51), mainly in cardiology and cardiac surgery (N=90). Whether PS methods or conventional outcome models were used to control for confounding had little effect on results in those studies in which such comparison was possible. Only 9 out of 69 studies (13%) had an effect estimate that differed by more than 20% from that obtained with a conventional outcome model in all PS analyses presented. Conclusions Publication of results based on propensity score methods has increased dramatically, but there is little evidence that these methods yield substantially different estimates compared with conventional multivariable methods. PMID:16632131

Associations of Anthropometric, Behavioral, and Social Factors on Level of Body Esteem in Peripubertal Girls.

PubMed

Szamreta, Elizabeth A; Qin, Bo; Ohman-Strickland, Pamela A; Devine, Katie A; Stapleton, Jerod L; Ferrante, Jeanne M; Bandera, Elisa V

2017-01-01

Lower body esteem may decrease self-esteem and lead to adverse health effects in children. This study explored the role of anthropometric, behavioral, and social factors on body esteem in peripubertal girls. We evaluated associations of body esteem (measured by the Revised Body Esteem Scale) with body mass index (BMI), mother's BMI, puberty, physical activity, role models for appearance, and screen time among girls (ages 9 and 10) participating in the Jersey Girl Study (n = 120). Linear models were used to evaluate differences in body esteem scores. Overweight/obese girls had a significantly lower mean body esteem score compared with underweight/healthy weight girls {14.09 (95% confidence interval [CI]: 12.53-15.27) vs. 17.17 (95% CI: 16.87-17.43)}. Girls who were physically active for at least 7 hours per week had a significantly higher body esteem score than those who were less active, after adjusting for BMI (17.00 [95% CI: 16.62-17.32] vs. 16.39 [95% CI: 15.82-16.86]). Girls whose mothers were overweight/obese, who had entered puberty, and who cited girls at school or females in the media as role models had lower body esteem scores, but differences disappeared after adjusting for girl's BMI. A trend of higher body esteem scores was found for girls whose mothers were role models. Lower BMI and higher levels of physical activity are independently associated with higher body esteem score. Having classmates or girls/women in the media as role models may detrimentally affect girls' body esteem, but having mothers as role models may have a positive effect.

Associations of anthropometric, behavioral, and social factors on level of body esteem in peripubertal girls

PubMed Central

Szamreta, Elizabeth A.; Qin, Bo; Ohman-Strickland, Pamela A.; Devine, Katie A.; Stapleton, Jerod L.; Ferrante, Jeanne M.; Bandera, Elisa V.

2016-01-01

Objective Lower body esteem may decrease self-esteem and lead to adverse health effects in children. This study explored the role of anthropometric, behavioral, and social factors on body esteem in peripubertal girls. Method We evaluated associations of body esteem (measured by the Revised Body Esteem Scale) with body mass index (BMI), mother’s BMI, puberty, physical activity, role models for appearance, and screen time among girls (ages 9 and 10) participating in the Jersey Girl Study (n=120). Linear models were used to evaluate differences in body esteem scores. Results Overweight/obese girls had a significantly lower mean body esteem score compared to underweight/healthy weight girls [14.09 (95% CI 12.53–15.27) vs. 17.17 (95% CI 16.87–17.43)]. Girls who were physically active for at least 7 hours per week had a significantly higher body esteem score than those who were less active, after adjusting for BMI [17.00 (95% CI 16.62–17.32) vs. 16.39 (95% CI 15.82–16.86)]. Girls whose mothers were overweight/obese, who had entered puberty, and who cited girls at school or females in the media as role models had lower body esteem scores, but differences disappeared after adjusting for girl’s BMI. A trend of higher body esteem scores was found for girls whose mothers were role models. Conclusion Lower BMI and higher levels of physical activity are independently associated with higher body esteem score. Having classmates or girls/women in the media as role models may detrimentally affect girls’ body esteem, but having mothers as role models may have a positive effect. PMID:27902543

Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression

NASA Astrophysics Data System (ADS)

Liu, Yongqi; Ye, Lei; Qin, Hui; Hong, Xiaofeng; Ye, Jiajun; Yin, Xingli

2018-06-01

Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum-Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM-GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM-GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM-GMR approach can handle multimodal and heteroscedastic data.

Estimating health state utility values for comorbid health conditions using SF-6D data.

PubMed

Ara, Roberta; Brazier, John

2011-01-01

When health state utility values for comorbid health conditions are not available, data from cohorts with single conditions are used to estimate scores. The methods used can produce very different results and there is currently no consensus on which is the most appropriate approach. The objective of the current study was to compare the accuracy of five different methods within the same dataset. Data collected during five Welsh Health Surveys were subgrouped by health status. Mean short-form 6 dimension (SF-6D) scores for cohorts with a specific health condition were used to estimate mean SF-6D scores for cohorts with comorbid conditions using the additive, multiplicative, and minimum methods, the adjusted decrement estimator (ADE), and a linear regression model. The mean SF-6D for subgroups with comorbid health conditions ranged from 0.4648 to 0.6068. The linear model produced the most accurate scores for the comorbid health conditions with 88% of values accurate to within the minimum important difference for the SF-6D. The additive and minimum methods underestimated or overestimated the actual SF-6D scores respectively. The multiplicative and ADE methods both underestimated the majority of scores. However, both methods performed better when estimating scores smaller than 0.50. Although the range in actual health state utility values (HSUVs) was relatively small, our data covered the lower end of the index and the majority of previous research has involved actual HSUVs at the upper end of possible ranges. Although the linear model gave the most accurate results in our data, additional research is required to validate our findings. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Incorporating Learning Characteristics into Automatic Essay Scoring Models: What Individual Differences and Linguistic Features Tell Us about Writing Quality

ERIC Educational Resources Information Center

Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S.

2016-01-01

This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…

Comparing Students' Scratch Skills with Their Computational Thinking Skills in Terms of Different Variables

ERIC Educational Resources Information Center

Oluk, Ali; Korkmaz, Özgen

2016-01-01

This study aimed to compare 5th graders' scores obtained from Scratch projects developed in the framework of Information Technologies and Software classes via Dr Scratch web tool with the scores obtained from Computational Thinking Levels Scale and to examine this comparison in terms of different variables. Correlational research model was…

Comparison of mortality prediction models in burns ICU patients in Pinderfields Hospital over 3 years.

PubMed

Douglas, Helen E; Ratcliffe, Andrew; Sandhu, Rajdeep; Anwar, Umair

2015-02-01

Many different burns mortality prediction models exist; however most agree that important factors that can be weighted include the age of the patient, the total percentage of body surface area burned and the presence or absence of smoke inhalation. A retrospective review of all burns primarily admitted to Pinderfields Burns ICU under joint care of burns surgeons and intensivists for the past 3 years was completed. Predicted mortality was calculated using the revised Baux score (2010), the Belgian Outcome in Burn Injury score (2009) and the Boston group score by Ryan et al. (1998). Additionally 28 of the 48 patients had APACHE II scores recorded on admission and the predicted and actual mortality of this group were compared. The Belgian score had the highest sensitivity and negative predictive value (72%/85%); followed by the Boston score (66%/78%) and then the revised Baux score (53%/70%). APACHE II scores had higher sensitivity (81%) and NPV (92%) than any of the burns scores. In our group of burns ICU patients the Belgian model was the most sensitive and specific predictor of mortality. In our subgroup of patients with APACHE II data, this score more accurately predicted survival and mortality. Copyright © 2014 Elsevier Ltd and ISBI. All rights reserved.

Prediction of consonant recognition in quiet for listeners with normal and impaired hearing using an auditory model.

PubMed

Jürgens, Tim; Ewert, Stephan D; Kollmeier, Birger; Brand, Thomas

2014-03-01

Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.

A comparison of item response models for accuracy and speed of item responses with applications to adaptive testing.

PubMed

van Rijn, Peter W; Ali, Usama S

2017-05-01

We compare three modelling frameworks for accuracy and speed of item responses in the context of adaptive testing. The first framework is based on modelling scores that result from a scoring rule that incorporates both accuracy and speed. The second framework is the hierarchical modelling approach developed by van der Linden (2007, Psychometrika, 72, 287) in which a regular item response model is specified for accuracy and a log-normal model for speed. The third framework is the diffusion framework in which the response is assumed to be the result of a Wiener process. Although the three frameworks differ in the relation between accuracy and speed, one commonality is that the marginal model for accuracy can be simplified to the two-parameter logistic model. We discuss both conditional and marginal estimation of model parameters. Models from all three frameworks were fitted to data from a mathematics and spelling test. Furthermore, we applied a linear and adaptive testing mode to the data off-line in order to determine differences between modelling frameworks. It was found that a model from the scoring rule framework outperformed a hierarchical model in terms of model-based reliability, but the results were mixed with respect to correlations with external measures. © 2017 The British Psychological Society.

Two-Year versus One-Year Head Start Program Impact: Addressing Selection Bias by Comparing Regression Modeling with Propensity Score Analysis

ERIC Educational Resources Information Center

Leow, Christine; Wen, Xiaoli; Korfmacher, Jon

2015-01-01

This article compares regression modeling and propensity score analysis as different types of statistical techniques used in addressing selection bias when estimating the impact of two-year versus one-year Head Start on children's school readiness. The analyses were based on the national Head Start secondary dataset. After controlling for…

Uncovering curvilinear relationships between conscientiousness and job performance: how theoretically appropriate measurement makes an empirical difference.

PubMed

Carter, Nathan T; Dalal, Dev K; Boyce, Anthony S; O'Connell, Matthew S; Kung, Mei-Chuan; Delgado, Kristin M

2014-07-01

The personality trait of conscientiousness has seen considerable attention from applied psychologists due to its efficacy for predicting job performance across performance dimensions and occupations. However, recent theoretical and empirical developments have questioned the assumption that more conscientiousness always results in better job performance, suggesting a curvilinear link between the 2. Despite these developments, the results of studies directly testing the idea have been mixed. Here, we propose this link has been obscured by another pervasive assumption known as the dominance model of measurement: that higher scores on traditional personality measures always indicate higher levels of conscientiousness. Recent research suggests dominance models show inferior fit to personality test scores as compared to ideal point models that allow for curvilinear relationships between traits and scores. Using data from 2 different samples of job incumbents, we show the rank-order changes that result from using an ideal point model expose a curvilinear link between conscientiousness and job performance 100% of the time, whereas results using dominance models show mixed results, similar to the current state of the literature. Finally, with an independent cross-validation sample, we show that selection based on predicted performance using ideal point scores results in more favorable objective hiring outcomes. Implications for practice and future research are discussed.

Conclusion of LOD-score analysis for family data generated under two-locus models.

PubMed

Dizier, M H; Babron, M C; Clerget-Darpoux, F

1996-06-01

The power to detect linkage by the LOD-score method is investigated here for diseases that depend on the effects of two genes. The classical strategy is, first, to detect a major-gene (MG) effect by segregation analysis and, second, to seek for linkage with genetic markers by the LOD-score method using the MG parameters. We already showed that segregation analysis can lead to evidence for a MG effect for many two-locus models, with the estimates of the MG parameters being very different from those of the two genes involved in the disease. We show here that use of these MG parameter estimates in the LOD-score analysis may lead to a failure to detect linkage for some two-locus models. For these models, use of the sib-pair method gives a non-negligible increase of power to detect linkage. The linkage-homogeneity test among subsamples differing for the familial disease distribution provides evidence of parameter misspecification, when the MG parameters are used. Moreover, for most of the models, use of the MG parameters in LOD-score analysis leads to a large bias in estimation of the recombination fraction and sometimes also to a rejection of linkage for the true recombination fraction. A final important point is that a strong evidence of an MG effect, obtained by segregation analysis, does not necessarily imply that linkage will be detected for at least one of the two genes, even with the true parameters and with a close informative marker.

Computerized summary scoring: crowdsourcing-based latent semantic analysis.

PubMed

Li, Haiying; Cai, Zhiqiang; Graesser, Arthur C

2017-11-03

In this study we developed and evaluated a crowdsourcing-based latent semantic analysis (LSA) approach to computerized summary scoring (CSS). LSA is a frequently used mathematical component in CSS, where LSA similarity represents the extent to which the to-be-graded target summary is similar to a model summary or a set of exemplar summaries. Researchers have proposed different formulations of the model summary in previous studies, such as pregraded summaries, expert-generated summaries, or source texts. The former two methods, however, require substantial human time, effort, and costs in order to either grade or generate summaries. Using source texts does not require human effort, but it also does not predict human summary scores well. With human summary scores as the gold standard, in this study we evaluated the crowdsourcing LSA method by comparing it with seven other LSA methods that used sets of summaries from different sources (either experts or crowdsourced) of differing quality, along with source texts. Results showed that crowdsourcing LSA predicted human summary scores as well as expert-good and crowdsourcing-good summaries, and better than the other methods. A series of analyses with different numbers of crowdsourcing summaries demonstrated that the number (from 10 to 100) did not significantly affect performance. These findings imply that crowdsourcing LSA is a promising approach to CSS, because it saves human effort in generating the model summary while still yielding comparable performance. This approach to small-scale CSS provides a practical solution for instructors in courses, and also advances research on automated assessments in which student responses are expected to semantically converge on subject matter content.

Personality correlates of the Five-Factor Model for a sample of business owners/managers: associations with scores on Self-Monitoring, Type A Behavior, Locus of Control, and Subjective Well-being.

PubMed

Morrison, K A

1997-02-01

Bivariate relationships were examined between scores on the Five-Factor Model of personality and four personality dimensions including Self-monitoring, Locus of Control, Type A Behavior, and Subjective Well-being. Data were collected from 307 franchise business owner/managers from four different industries. Scores for Self-monitoring were positively related to those on Extraversion; Self-monitoring was the only personality measure significantly correlated with scores on Openness to Experience. Scores for Type A Behavior, measured by the Jenkins Activity Survey, were negatively correlated with Agreeableness and positively correlated with those for Extraversion. Somewhat surprisingly, the score for Type A Behavior had a relatively low correlation with the score for Conscientiousness. Scores for Subjective Well-being and Locus of Control were most strongly correlated with the positive pole of Neuroticism (Emotional Stability), Conscientiousness, and Extraversion. Possible explanations for the observed relationships are discussed.

Inner strength in relation to age, gender and culture among old people--a cross-sectional population study in two Nordic countries.

PubMed

Viglund, Kerstin; Jonsén, Elisabeth; Lundman, Berit; Strandberg, Gunilla; Nygren, Björn

2013-01-01

The theoretical framework for the study was the Model of Inner Strength, and the Inner Strength Scale (ISS)developed based on the Model was used. The aim was to examine inner strength in relation to age, gender and culture among old people in Sweden and Finland. This study forms part of the GErontological Regional DAtabase (GERDA)-Botnia project that investigates healthy ageing with focus on the dignity, social participation and health of old people. The participants (N = 6119) were 65-, 70-, 75- and 80-year old and living in two counties in Sweden or Finland. The ISS consists of 20 items relating to four interrelated dimensions of inner strength, according to the Model of Inner Strength. The range of possible ISS scores is 20-120, a higher score denoting higher inner strength. The result showed that the 65-year-old participants had the highest mean ISS score, with a decrease in score for every subsequent age. The lowest score was achieved by the 80-year-old participants. Women had slightly but significantly higher mean ISS scores than men. Only small differences were found between the counties. The study population came from Sweden and Finland; still, despite the different backgrounds, patterns in the distribution of inner strength were largely similar. The present study provides basic and essential information about inner strength in a population of old people.

Pseudoautosomal region in schizophrenia: linkage analysis of seven loci by sib-pair and lod-score methods.

PubMed

d'Amato, T; Waksman, G; Martinez, M; Laurent, C; Gorwood, P; Campion, D; Jay, M; Petit, C; Savoye, C; Bastard, C

1994-05-01

In a previous study, we reported a nonrandom segregation between schizophrenia and the pseudoautosomal locus DXYS14 in a sample of 33 sibships. That study has been extended by the addition of 16 new sibships from 16 different families. Data from six other loci of the pseudoautosomal region and of the immediately adjacent part of the X specific region have also been analyzed. Two methods of linkage analysis were used: the affected sibling pair (ASP) method and the lod-score method. Lod-score analyses were performed on the basis of three different models--A, B, and C--all shown to be consistent with the epidemiological data on schizophrenia. No clear evidence for linkage was obtained with any of these models. However, whatever the genetic model and the disease classification, maximum lod scores were positive with most of the markers, with the highest scores generally being obtained for the DXYS14 locus. When the ASP method was used, the earlier finding of nonrandom segregation between schizophrenia and the DXYS14 locus was still supported in this larger data set, at an increased level of statistical significance. Findings of ASP analyses were not significant for the other loci. Thus, findings obtained from analyses using the ASP method, but not the lod-score method, were consistent with the pseudoautosomal hypothesis for schizophrenia.

An automated sleep-state classification algorithm for quantifying sleep timing and sleep-dependent dynamics of electroencephalographic and cerebral metabolic parameters

PubMed Central

Rempe, Michael J; Clegern, William C; Wisor, Jonathan P

2015-01-01

Introduction Rodent sleep research uses electroencephalography (EEG) and electromyography (EMG) to determine the sleep state of an animal at any given time. EEG and EMG signals, typically sampled at >100 Hz, are segmented arbitrarily into epochs of equal duration (usually 2–10 seconds), and each epoch is scored as wake, slow-wave sleep (SWS), or rapid-eye-movement sleep (REMS), on the basis of visual inspection. Automated state scoring can minimize the burden associated with state and thereby facilitate the use of shorter epoch durations. Methods We developed a semiautomated state-scoring procedure that uses a combination of principal component analysis and naïve Bayes classification, with the EEG and EMG as inputs. We validated this algorithm against human-scored sleep-state scoring of data from C57BL/6J and BALB/CJ mice. We then applied a general homeostatic model to characterize the state-dependent dynamics of sleep slow-wave activity and cerebral glycolytic flux, measured as lactate concentration. Results More than 89% of epochs scored as wake or SWS by the human were scored as the same state by the machine, whether scoring in 2-second or 10-second epochs. The majority of epochs scored as REMS by the human were also scored as REMS by the machine. However, of epochs scored as REMS by the human, more than 10% were scored as SWS by the machine and 18 (10-second epochs) to 28% (2-second epochs) were scored as wake. These biases were not strain-specific, as strain differences in sleep-state timing relative to the light/dark cycle, EEG power spectral profiles, and the homeostatic dynamics of both slow waves and lactate were detected equally effectively with the automated method or the manual scoring method. Error associated with mathematical modeling of temporal dynamics of both EEG slow-wave activity and cerebral lactate either did not differ significantly when state scoring was done with automated versus visual scoring, or was reduced with automated state scoring relative to manual classification. Conclusions Machine scoring is as effective as human scoring in detecting experimental effects in rodent sleep studies. Automated scoring is an efficient alternative to visual inspection in studies of strain differences in sleep and the temporal dynamics of sleep-related physiological parameters. PMID:26366107

Relationship of Echocardiographic Z Scores Adjusted for Body Surface Area to Age, Sex, Race, and Ethnicity: The Pediatric Heart Network Normal Echocardiogram Database.

PubMed

Lopez, Leo; Colan, Steven; Stylianou, Mario; Granger, Suzanne; Trachtenberg, Felicia; Frommelt, Peter; Pearson, Gail; Camarda, Joseph; Cnota, James; Cohen, Meryl; Dragulescu, Andreea; Frommelt, Michele; Garuba, Olukayode; Johnson, Tiffanie; Lai, Wyman; Mahgerefteh, Joseph; Pignatelli, Ricardo; Prakash, Ashwin; Sachdeva, Ritu; Soriano, Brian; Soslow, Jonathan; Spurney, Christopher; Srivastava, Shubhika; Taylor, Carolyn; Thankavel, Poonam; van der Velde, Mary; Minich, LuAnn

2017-11-01

Published nomograms of pediatric echocardiographic measurements are limited by insufficient sample size to assess the effects of age, sex, race, and ethnicity. Variable methodologies have resulted in a wide range of Z scores for a single measurement. This multicenter study sought to determine Z scores for common measurements adjusted for body surface area (BSA) and stratified by age, sex, race, and ethnicity. Data collected from healthy nonobese children ≤18 years of age at 19 centers with a normal echocardiogram included age, sex, race, ethnicity, height, weight, echocardiographic images, and measurements performed at the Core Laboratory. Z score models involved indexed parameters (X/BSA α ) that were normally distributed without residual dependence on BSA. The models were tested for the effects of age, sex, race, and ethnicity. Raw measurements from models with and without these effects were compared, and <5% difference was considered clinically insignificant because interobserver variability for echocardiographic measurements are reported as ≥5% difference. Of the 3566 subjects, 90% had measurable images. Appropriate BSA transformations (BSA α ) were selected for each measurement. Multivariable regression revealed statistically significant effects by age, sex, race, and ethnicity for all outcomes, but all effects were clinically insignificant based on comparisons of models with and without the effects, resulting in Z scores independent of age, sex, race, and ethnicity for each measurement. Echocardiographic Z scores based on BSA were derived from a large, diverse, and healthy North American population. Age, sex, race, and ethnicity have small effects on the Z scores that are statistically significant but not clinically important. © 2017 American Heart Association, Inc.

Radiological score for hemorrhage in the patients with portal hypertension.

PubMed

Ge, Wei; Wang, Yi; Cao, Ya-Juan; Xie, Min; Ding, Yi-Tao; Zhang, Ming; Yu, De-Cai

2015-01-01

To analyze the risk factors from radiological indices for hemorrhage in the patients with portal hypertension and weight risk factors. We retrospectively analyzed all cases of portal hypertension with hepatitis B from June 2008 to June 2014 in Nanjing Drum Tower hospital. Patients with hepatocellular carcinoma, portal vein thrombosis, or portal hypertension with other causes, such as autoimmune hepatitis, pancreatitis, or hematological diseases were excluded. Ninety-eight patients were recruited and divided into hemorrhage and non-hemorrhage groups. There were no statistical differences in clinical indexes such as age, prothrombin time, serum albumin, serum creatinine, serum sodium, hemameba, and blood platelet count. However, the differences were statistically significant in total bilirubin, hemoglobin, and liver function with the p values of 0.023, 0.000, and 0.039 respectively. For radiological indices, hemorrhage was correlated with diameter of inferior mesenteric vein (P=0.0528), posterior gastric vein (P=0.0283), and esophageal varices scores (P=0.0221). Logistic procedure was used to construct the model with stepwise selection and finally inferior mesenteric vein, posterior gastric vein, esophageal varices, and short gastric vein were enrolled into the model. These veins were scored according to the diameters and the rates of hemorrhage were increased with the score. We then validated the model with 26 patents from July 2014 to December 2014. The AUC value was 0.8849 in ROC curves for this radiological model. A risk model was constructed including inferior mesenteric vein, esophageal varices, posterior gastric vein, and short gastric vein. This radiological scoring model may be a valuable indicator for hemorrhage of portal hypertension.

Visuospatial Aptitude Testing Differentially Predicts Simulated Surgical Skill.

PubMed

Hinchcliff, Emily; Green, Isabel; Destephano, Christopher; Cox, Mary; Smink, Douglas; Kumar, Amanika; Hokenstad, Erik; Bengtson, Joan; Cohen, Sarah

2018-02-05

To determine if visuospatial perception (VSP) testing is correlated to simulated or intraoperative surgical performance as rated by the American College of Graduate Medical Education (ACGME) milestones. Classification II-2 SETTING: Two academic training institutions PARTICIPANTS: 41 residents, including 19 Brigham and Women's Hospital and 22 Mayo Clinic residents from three different specialties (OBGYN, general surgery, urology). Participants underwent three different tests: visuospatial perception testing (VSP), Fundamentals of Laparoscopic Surgery (FLS®) peg transfer, and DaVinci robotic simulation peg transfer. Surgical grading from the ACGME milestones tool was obtained for each participant. Demographic and subject background information was also collected including specialty, year of training, prior experience with simulated skills, and surgical interest. Standard statistical analysis using Student's t test were performed, and correlations were determined using adjusted linear regression models. In univariate analysis, BWH and Mayo training programs differed in both times and overall scores for both FLS® peg transfer and DaVinci robotic simulation peg transfer (p<0.05 for all). Additionally, type of residency training impacted time and overall score on robotic peg transfer. Familiarity with tasks correlated with higher score and faster task completion (p= 0.05 for all except VSP score). There was no difference in VSP scores by program, specialty, or year of training. In adjusted linear regression modeling, VSP testing was correlated only to robotic peg transfer skills (average time p=0.006, overall score p=0.001). Milestones did not correlate to either VSP or surgical simulation testing. VSP score was correlated with robotic simulation skills but not with FLS skills or ACGME milestones. This suggests that the ability of VSP score to predict competence differs between tasks. Therefore, further investigation is required into aptitude testing, especially prior to its integration as an entry examination into a surgical subspecialty. Copyright © 2018. Published by Elsevier Inc.

Effects of correcting for prematurity on cognitive test scores in childhood.

PubMed

Wilson-Ching, Michelle; Pascoe, Leona; Doyle, Lex W; Anderson, Peter J

2014-03-01

The American Academy of Pediatrics recommends that test scores should be corrected for prematurity up to 3 years of age, but this practice varies greatly in both clinical and research settings. The aim of this study was to contrast the effects of using chronological age and those of using corrected age on measures of cognitive outcome across childhood. A theoretical model was constructed using norms from the Bayley Scales of Infant and Toddler Development, Third Edition; the Wechsler Preschool and Primary Scale of Intelligence, Third Edition Australian; and the Wechsler Intelligence Scales for Children, Fourth Edition Australian. Baseline scores representing different levels of functioning (70, below average; 85, borderline; and 100, average) were recalculated using the normative data for ages 6 months to 16 years to account for 1, 2, 3 and 4 months of prematurity. The model created depicted the difference in standardised scores between chronological and corrected age. Compared with scores corrected for prematurity, the absolute reduction in scores using chronological age was greater for increasing degree of prematurity, younger ages at assessment and higher baseline scores and was substantial even beyond 3 years of age. However, the pattern was erratic, with considerable fluctuation evident across different ages and baseline scores. Chronological age results in a lowering of scores at all ages for preterm-born subjects that is greater in the first few years and in those born at earlier gestational ages. Whether or not to correct for prematurity depends upon the context of the assessment. © 2014 The Authors. Journal of Paediatrics and Child Health © 2014 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Direct-Access Online Care for the Management of Atopic Dermatitis: A Randomized Clinical Trial Examining Patient Quality of Life.

PubMed

Kornmehl, Heather; Singh, Sanminder; Johnson, Mary Ann; Armstrong, April W

2017-09-01

Atopic dermatitis (AD) is a chronic disease requiring regular follow-up. To increase access to dermatological care, online management of AD is being studied. However, a critical knowledge gap exists in determining AD patients' quality of life in direct-to-patient online models. In this study, we examined quality of life in AD patients managed through a direct-access online model. We randomized 156 patients to receiving care through a direct-access online platform or in person. Patients were seen for six visits over 12 months. At each visit, the patients completed Dermatology Life Quality Index/Children's Dermatology Life Quality Index (DLQI/CDLQI), and Short Form (SF-12). Between baseline and 12 months, the mean (standard deviation, SD) within-group difference in DLQI score in the online group was 4.1 (±2.3); for the in-person group, the within-group difference was 4.8 (±2.7). The mean (SD) within-group difference in CDLQI score in the online group was 4.7 (±2.8); for the in-person group, the within-group difference was 4.9 (±3.1). The mean (SD) within-group difference in physical component score (PCS) and mental component score (MCS) SF-12 scores in the online group was 6.5 (±3.8) and 8.6 (±4.3); for the in-person group, it was 6.8 (±3.2) and 9.1(±3.8), respectively. The difference in the change in DLQI, CDLQI, SF-12 PCS, and SF-12 MCS scores between the two groups was 0.72 (95% confidence interval [90% CI], -0.97 to 2.41), 0.23 (90% CI, -2.21 to 2.67), 0.34 (90% CI, -1.16 to 1.84), and 0.51 (90% CI, -1.11 to 2.13), respectively. All differences were contained within their equivalence margins. Adult and pediatric AD patients receiving direct-access online care had equivalent quality of life outcomes as those see in person. The direct-access online model has the potential to increase access to care for patients with chronic skin diseases.

A Bayesian hierarchical latent trait model for estimating rater bias and reliability in large-scale performance assessment

PubMed Central

2018-01-01

We propose a novel approach to modelling rater effects in scoring-based assessment. The approach is based on a Bayesian hierarchical model and simulations from the posterior distribution. We apply it to large-scale essay assessment data over a period of 5 years. Empirical results suggest that the model provides a good fit for both the total scores and when applied to individual rubrics. We estimate the median impact of rater effects on the final grade to be ± 2 points on a 50 point scale, while 10% of essays would receive a score at least ± 5 different from their actual quality. Most of the impact is due to rater unreliability, not rater bias. PMID:29614129

Knowledge management in Portuguese healthcare institutions.

PubMed

Cruz, Sofia Gaspar; Ferreira, Maria Manuela Frederico

2016-06-01

Knowledge management imposes itself as a pressing need for the organizations of several sectors of the economy, including healthcare. to evaluate the perception of healthcare institution collaborators in relation to knowledge management in the institution where they operate and analyze the existence of differences in this perception, based on the institution's management model. a study conducted in a sample consisting of 671 collaborators from 10 Portuguese healthcare institutions with different models of management. In order to assess the knowledge management perception, we used a score designed from and based on items from the scores available in the literature. the perception of moderate knowledge management on the healthcare institutions and the statistically significant differences in knowledge management perception were evidenced in each management model. management knowledge takes place in healthcare institutions, and the current management model determines the way staff at these institutions manage their knowledge.

Wellness coaching and health-related quality of life: a case-control difference-in-differences analysis.

PubMed

Menon, Jyothi; Paulet, Mindy; Thomas, Joseph

2012-10-01

Association between wellness coaching and changes in health-related quality of life over 1 year and 2 years was assessed. Difference-in-differences analysis of covariance assessed association between coaching and change in 8-item short-form health survey (SF-8) summary scores. Ordered logistic models assessed coaching and change in SF-8 individual domain scores. This was a case-control study. Participants in at least one coaching program were more likely to have increases in social functioning after 1 year and less likely to have increases in role physical after 2 years. Participants in nutrition coaching had more positive change in mental component summary scores after 1 year. Participants in stress management had more negative change in mental component summary scores after 1 year and after 2 years and had more negative change in physical component summary scores after 2 years. Findings were mixed regarding association between coaching and change in health-related quality of life.

Three sides to a story: Child, parent, and nurse perspectives on the child's experience during hematopoietic stem cell transplantation.

PubMed

Ullrich, Christina K; Rodday, Angie Mae; Bingen, Kristin M; Kupst, Mary Jo; Patel, Sunita K; Syrjala, Karen L; Harris, Lynnette L; Recklitis, Christopher J; Chang, Grace; Guinan, Eva C; Terrin, Norma; Tighiouart, Hocine; Phipps, Sean; Parsons, Susan K

2017-08-15

The experience of children undergoing hematopoietic stem cell transplantation (HSCT), including the ways in which different participants (ie, children, parents, and nurses) contribute to the overall picture of a child's experience, is poorly characterized. This study evaluated parent, child, and nurse perspectives on the experience of children during HSCT and factors contributing to interrater differences. Participants were enrolled in a multicenter, prospective study evaluating child and parent health-related quality of life over the year after HSCT. Children (n = 165) and their parents and nurses completed the Behavioral, Affective, and Somatic Experiences Scale (BASES) at baseline (before/during conditioning), 7 days after the stem cell infusion (day+7), and 21 days after the stem cell infusion (day+21). The BASES domains included Somatic Distress, Mood Disturbance, Cooperation, and Getting Along. Higher scores indicated more distress/impairment. Repeated measures models by domain assessed differences by raters and changes over time and identified other factors associated with raters' scores. Completion rates were high (≥73% across times and raters). Multivariate models revealed significant time-rater interactions, which varied by domain. For example, parent-rated Somatic Distress scores increased from baseline to day+7 and remained elevated at day+21 (P < .001); children's scores were lower than parents' scores across time points. Nurses' baseline scores were lower than parents' baseline scores, although by day+21 they were similar. Older child age was associated with higher Somatic Distress and Mood Disturbance scores. Worse parent emotional functioning was associated with lower scores across raters and domains except for Cooperation. Multirater assessments are highly feasible during HSCT. Ratings differ by several factors; considering ratings in light of such factors may deepen our understanding of the child's experience. Cancer 2017;123:3159-66. © 2017 American Cancer Society. © 2017 American Cancer Society.

On the Effectiveness of Security Countermeasures for Critical Infrastructures.

PubMed

Hausken, Kjell; He, Fei

2016-04-01

A game-theoretic model is developed where an infrastructure of N targets is protected against terrorism threats. An original threat score is determined by the terrorist's threat against each target and the government's inherent protection level and original protection. The final threat score is impacted by the government's additional protection. We investigate and verify the effectiveness of countermeasures using empirical data and two methods. The first is to estimate the model's parameter values to minimize the sum of the squared differences between the government's additional resource investment predicted by the model and the empirical data. The second is to develop a multivariate regression model where the final threat score varies approximately linearly relative to the original threat score, sectors, and threat scenarios, and depends nonlinearly on the additional resource investment. The model and method are offered as tools, and as a way of thinking, to determine optimal resource investments across vulnerable targets subject to terrorism threats. © 2014 Society for Risk Analysis.

An Evaluation of the Single-Group Growth Model as an Alternative to Common-Item Equating. Research Report. ETS RR-16-01

ERIC Educational Resources Information Center

Wei, Youhua; Morgan, Rick

2016-01-01

As an alternative to common-item equating when common items do not function as expected, the single-group growth model (SGGM) scaling uses common examinees or repeaters to link test scores on different forms. The SGGM scaling assumes that, for repeaters taking adjacent administrations, the conditional distribution of scale scores in later…

How to Get Really Smart: Modeling Retest and Training Effects in Ability Testing using Computer-Generated Figural Matrix Items

ERIC Educational Resources Information Center

Freund, Philipp Alexander; Holling, Heinz

2011-01-01

The interpretation of retest scores is problematic because they are potentially affected by measurement and predictive bias, which impact construct validity, and because their size differs as a function of various factors. This paper investigates the construct stability of scores on a figural matrices test and models retest effects at the level of…

Asymptomatic population reference values for three knee patient-reported outcomes measures: evaluation of an electronic data collection system and implications for future international, multi-centre cohort studies.

PubMed

McLean, James M; Brumby-Rendell, Oscar; Lisle, Ryan; Brazier, Jacob; Dunn, Kieran; Gill, Tiffany; Hill, Catherine L; Mandziak, Daniel; Leith, Jordan

2018-05-01

The aim was to assess whether the Knee Society Score, Oxford Knee Score (OKS) and Knee Injury and Osteoarthritis Outcome Score (KOOS) were comparable in asymptomatic, healthy, individuals of different age, gender and ethnicity, across two remote continents. The purpose of this study was to establish normal population values for these scores using an electronic data collection system. There is no difference in clinical knee scores in an asymptomatic population when comparing age, gender and ethnicity, across two remote continents. 312 Australian and 314 Canadian citizens, aged 18-94 years, with no active knee pain, injury or pathology in the ipsilateral knee corresponding to their dominant arm, were evaluated. A knee examination was performed and participants completed an electronically administered questionnaire covering the subjective components of the knee scores. The cohorts were age- and gender-matched. Chi-square tests, Fisher's exact test and Poisson regression models were used where appropriate, to investigate the association between knee scores, age, gender, ethnicity and nationality. There was a significant inverse relationship between age and all assessment tools. OKS recorded a significant difference between gender with females scoring on average 1% lower score. There was no significant difference between international cohorts when comparing all assessment tools. An electronic, multi-centre data collection system can be effectively utilized to assess remote international cohorts. Differences in gender, age, ethnicity and nationality should be taken into consideration when using knee scores to compare to pathological patient scores. This study has established an electronic, normal control group for future studies using the Knee society, Oxford, and KOOS knee scores. Diagnostic Level II.

Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

PubMed

Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

2015-05-01

The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Universality in the distance between two teams in a football tournament

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Dahmen, Silvio R.

2014-03-01

Is football (soccer) a universal sport? Beyond the question of geographical distribution, where the answer is most certainly yes, when looked at from a mathematical viewpoint the scoring process during a match can be thought of, in a first approximation, as being modeled by a Poisson distribution. Recently, it was shown that the scoring of real tournaments can be reproduced by means of an agent-based model (da Silva et al. (2013) [24]) based on two simple hypotheses: (i) the ability of a team to win a match is given by the rate of a Poisson distribution that governs its scoring during a match; and (ii) such ability evolves over time according to results of previous matches. In this article we are interested in the question of whether the time series represented by the scores of teams have universal properties. For this purpose we define a distance between two teams as the square root of the sum of squares of the score differences between teams over all rounds in a double-round-robin-system and study how this distance evolves over time. Our results suggest a universal distance distribution of tournaments of different major leagues which is better characterized by an exponentially modified Gaussian (EMG). This result is corroborated by our agent-based model.

Stratification for the propensity score compared with linear regression techniques to assess the effect of treatment or exposure.

PubMed

Senn, Stephen; Graf, Erika; Caputo, Angelika

2007-12-30

Stratifying and matching by the propensity score are increasingly popular approaches to deal with confounding in medical studies investigating effects of a treatment or exposure. A more traditional alternative technique is the direct adjustment for confounding in regression models. This paper discusses fundamental differences between the two approaches, with a focus on linear regression and propensity score stratification, and identifies points to be considered for an adequate comparison. The treatment estimators are examined for unbiasedness and efficiency. This is illustrated in an application to real data and supplemented by an investigation on properties of the estimators for a range of underlying linear models. We demonstrate that in specific circumstances the propensity score estimator is identical to the effect estimated from a full linear model, even if it is built on coarser covariate strata than the linear model. As a consequence the coarsening property of the propensity score-adjustment for a one-dimensional confounder instead of a high-dimensional covariate-may be viewed as a way to implement a pre-specified, richly parametrized linear model. We conclude that the propensity score estimator inherits the potential for overfitting and that care should be taken to restrict covariates to those relevant for outcome. Copyright (c) 2007 John Wiley & Sons, Ltd.

Parental involvement, child effort, and the development of immigrant boys’ and girls’ reading and mathematics skills: A latent difference score growth model

PubMed Central

Moon, Ui Jeong; Hofferth, Sandra L.

2016-01-01

Gender differences in elementary school performance among immigrant children have not yet been well documented. This study examined how differences in parental involvement, child effort, and family characteristics and resources contribute to immigrant boys’-and girls’ academic achievement from kindergarten through 5th-grade. The sample was drawn from the Early Childhood Longitudinal Study-Kindergarten cohort. Using a latent score growth model, this study found that parents’ involvement at home benefited boys’ reading and mathematics skills throughout all early elementary school years, but did not have the same benefit for girls. For both boys and girls, child effort in reading appears to be strongly linked to better reading and mathematics skills at kindergarten and to subsequent improvement between grades. The positive associations of parental involvement and child’s effort with test scores were greater during earlier years than during later years for boys, whereas there was no difference in the association over time for girls. PMID:26900304

Analysis of early life influences on cognitive development in childhood using multilevel ordinal models

PubMed Central

Li, Leah

2012-01-01

Summary Studies of cognitive development in children are often based on tests designed for specific ages. Examination of the changes of these scores over time may not be meaningful. This paper investigates the influence of early life factors on cognitive development using maths and reading test scores at ages 7, 11, and 16 years in a British birth cohort born in 1958. The distributions of these test scores differ between ages, for example, 20% participants scored the top mark in the reading test at 7 and the distribution of reading score at 16 is heavily skewed. In this paper, we group participants into 5 ordered categories, approximately 20% in each category according to their test scores at each age. Multilevel models for a repeated ordinal outcome are applied to relate the ordinal scale of maths and reading ability to early life factors. PMID:22661923

N-terminal fraction of pro-B-type natriuretic peptide versus clinical risk scores for prognostic stratification in chronic systolic heart failure.

PubMed

Arzilli, Chiara; Aimo, Alberto; Vergaro, Giuseppe; Ripoli, Andrea; Senni, Michele; Emdin, Michele; Passino, Claudio

2018-05-01

Background The Seattle heart failure model or the cardiac and comorbid conditions (3C-HF) scores may help define patient risk in heart failure. Direct comparisons between them or versus N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP) have never been performed. Methods Data from consecutive patients with stable systolic heart failure and 3C-HF data were examined. A subgroup of patients had the Seattle heart failure model data available. The endpoints were one year all-cause or cardiovascular death. Results The population included 2023 patients, aged 68 ± 12 years, 75% were men. At the one year time-point, 198 deaths were recorded (10%), 124 of them (63%) from cardiovascular causes. While areas under the curve were not significantly different, NT-proBNP displayed better reclassification capability than the 3C-HF score for the prediction of one year all-cause and cardiovascular death. Adding NT-proBNP to the 3C-HF score resulted in a significant improvement in risk prediction. Among patients with Seattle heart failure model data available ( n = 798), the area under the curve values for all-cause and cardiovascular death were similar for the Seattle heart failure model score (0.790 and 0.820), NT-proBNP (0.783 and 0.803), and the 3C-HF score (0.770 and 0.800). The combination of the 3C-HF score and NT-proBNP displayed a similar prognostic performance to the Seattle heart failure model score for both endpoints. Adding NT-proBNP to the Seattle heart failure model score performed better than the Seattle heart failure model alone in terms of reclassification, but not discrimination. Conclusions Among systolic heart failure patients, NT-proBNP levels had better reclassification capability for all-cause and cardiovascular death than the 3C-HF score. The inclusion of NT-proBNP to the 3C-HF and Seattle heart failure model score resulted in significantly better risk stratification.

Higher Mortality in registrants with sudden model for end-stage liver disease increase: Disadvantaged by the current allocation policy.

PubMed

Massie, Allan B; Luo, Xun; Alejo, Jennifer L; Poon, Anna K; Cameron, Andrew M; Segev, Dorry L

2015-05-01

Liver allocation is based on current Model for End-Stage Liver Disease (MELD) scores, with priority in the case of a tie being given to those waiting the longest with a given MELD score. We hypothesized that this priority might not reflect risk: registrants whose MELD score has recently increased receive lower priority but might have higher wait-list mortality. We studied wait-list and posttransplant mortality in 69,643 adult registrants from 2002 to 2013. By likelihood maximization, we empirically defined a MELD spike as a MELD increase ≥ 30% over the previous 7 days. At any given time, only 0.6% of wait-list patients experienced a spike; however, these patients accounted for 25% of all wait-list deaths. Registrants who reached a given MELD score after a spike had higher wait-list mortality in the ensuing 7 days than those with the same resulting MELD score who did not spike, but they had no difference in posttransplant mortality. The spike-associated wait-list mortality increase was highest for registrants with medium MELD scores: specifically, 2.3-fold higher (spike versus no spike) for a MELD score of 10, 4.0-fold higher for a MELD score of 20, and 2.5-fold higher for a MELD score of 30. A model incorporating the MELD score and spikes predicted wait-list mortality risk much better than a model incorporating only the MELD score. Registrants with a sudden MELD increase have a higher risk of short-term wait-list mortality than is indicated by their current MELD score but have no increased risk of posttransplant mortality; allocation policy should be adjusted accordingly. © 2015 American Association for the Study of Liver Diseases.

Individual Differences in Personality Masculinity-Femininity: Examining the Effects of Genes, Environment, and Prenatal Hormone Transfer.

PubMed

Verweij, Karin J H; Mosing, Miriam A; Ullén, Fredrik; Madison, Guy

2016-04-01

Males and females score differently on some personality traits, but the underlying etiology of these differences is not well understood. This study examined genetic, environmental, and prenatal hormonal influences on individual differences in personality masculinity-femininity (M-F). We used Big-Five personality inventory data of 9,520 Swedish twins (aged 27 to 54) to create a bipolar M-F personality scale. Using biometrical twin modeling, we estimated the influence of genetic and environmental factors on individual differences in a M-F personality score. Furthermore, we tested whether prenatal hormone transfer may influence individuals' M-F scores by comparing the scores of twins with a same-sex versus those with an opposite-sex co-twin. On average, males scored 1.09 standard deviations higher than females on the created M-F scale. Around a third of the variation in M-F personality score was attributable to genetic factors, while family environmental factors had no influence. Males and females from opposite-sex pairs scored significantly more masculine (both approximately 0.1 SD) than those from same-sex pairs. In conclusion, genetic influences explain part of the individual differences in personality M-F, and hormone transfer from the male to the female twin during pregnancy may increase the level of masculinization in females. Additional well-powered studies are needed to clarify this association and determine the underlying mechanisms in both sexes.

Effect Sizes for Growth-Modeling Analysis for Controlled Clinical Trials in the Same Metric as for Classical Analysis

PubMed Central

Feingold, Alan

2009-01-01

The use of growth-modeling analysis (GMA)--including Hierarchical Linear Models, Latent Growth Models, and General Estimating Equations--to evaluate interventions in psychology, psychiatry, and prevention science has grown rapidly over the last decade. However, an effect size associated with the difference between the trajectories of the intervention and control groups that captures the treatment effect is rarely reported. This article first reviews two classes of formulas for effect sizes associated with classical repeated-measures designs that use the standard deviation of either change scores or raw scores for the denominator. It then broadens the scope to subsume GMA, and demonstrates that the independent groups, within-subjects, pretest-posttest control-group, and GMA designs all estimate the same effect size when the standard deviation of raw scores is uniformly used. Finally, it is shown that the correct effect size for treatment efficacy in GMA--the difference between the estimated means of the two groups at end of study (determined from the coefficient for the slope difference and length of study) divided by the baseline standard deviation--is not reported in clinical trials. PMID:19271847

High accuracy of the nine equivalents of nursing manpower use score assessed by critical care nurses.

PubMed

Perren, Andreas; Previsdomini, Marco; Perren, Ilaria; Merlani, Paolo

2012-04-05

The nine equivalents of nursing manpower use score (NEMS) is frequently used to quantify, evaluate and allocate nursing workload at intensive care unit level. In Switzerland it has also become a key component in defining the degree of ICU hospital reimbursement. The accuracy of nurse registered NEMS scores in real life was assessed and error-prone variables were identified. In this retrospective multicentre audit three reviewers (1 nurse, 2 intensivists) independently reassessed a total of 529 NEMS scores. Correlation and agreement of the sum-scores and of the different variables among reviewers, as well as between nurses and the reviewers' reference value, were assessed (ICC, % agreement and kappa). Bland & Altman (reference value - nurses) of sum-scores and regression of the difference were determined and a logistic regression model identifying risk factors for erroneous assessments was calculated. Agreement for sum-scores among reviewers was almost perfect (mean ICC = 0.99 / significant correlation p <0.0001). The nurse registered NEMS score (mean ± SD) was 24.8 ± 8.6 points versus 24.0 ± 8.6 points (p <0.13 for difference) of the reference value, with a slightly lower ICC (0.83). The lowest agreement was found in intravenous medication (0.85). Bland & Altman was 0.84 ± 10, with a significant regression between the difference and the reference value, indicating overall an overestimation of lower scores (≤29 points) and underestimation of higher scores. Accuracy of scores or variables was not associated with nurses' characteristics. In real life, nurse registered NEMS scores are highly accurate. Lower (≤29 points) NEMS sum-scores are overestimated and higher underestimated. Accuracy of scores or variables was not associated with nurses' characteristics.

Statistical comparison of the pediatric versus adult IKDC subjective knee evaluation form in adolescents.

PubMed

Oak, Sameer R; O'Rourke, Colin; Strnad, Greg; Andrish, Jack T; Parker, Richard D; Saluan, Paul; Jones, Morgan H; Stegmeier, Nicole A; Spindler, Kurt P

2015-09-01

The International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form is a patient-reported outcome with adult (1998) and pediatric (2011) versions validated at different ages. Prior longitudinal studies of patients aged 13 to 17 years who tore their anterior cruciate ligament (ACL) have used the only available adult IKDC, whereas currently the pediatric IKDC is the accepted form of choice. This study compared the adult and pediatric IKDC forms and tested whether the differences were clinically significant. The hypothesis was that the pediatric and adult IKDC questionnaires would show no clinically significant differences in score when completed by patients aged 13 to 17 years. Cohort study (diagnosis); Level of evidence, 2. A total of 100 participants aged 13 to 17 years with knee injuries were split into 2 groups by use of simple randomization. One group answered the adult IKDC form first and then the pediatric form. The second group answered the pediatric IKDC form first and then the adult form. A 10-minute break was given between form administrations to prevent rote repetition of answers. Study design was based on established methods to compare 2 forms of patient-reported outcomes. A 5-point threshold for clinical significance was set below previously published minimum clinically important differences for the adult IKDC. Paired t tests were used to test both differences and equivalence between scores. By ordinary least-squares models, scores were modeled to predict adult scores given certain pediatric scores and vice versa. Comparison between adult and pediatric IKDC scores showed a statistically significant difference of 1.5 points; however, the 95% CI (0.3-2.6) fell below the threshold of 5 points set for clinical significance. Further equivalence testing showed the 95% CI (0.5-2.4) between adult and pediatric scores being within the defined 5-point equivalence region. The scores were highly correlated, with a linear relationship (R(2) = 92%). There was no clinically significant difference between the pediatric and adult IKDC form scores in adolescents aged 13 to 17 years. This result allows use of whichever form is most practical for long-term tracking of patients. A simple linear equation can convert one form into the other. If the adult questionnaire is used at this age, it can be consistently used during follow-up. © 2015 The Author(s).

Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.

PubMed

Li, Wenlin; Schaeffer, R Dustin; Otwinowski, Zbyszek; Grishin, Nick V

2016-01-01

The Critical Assessment of techniques for protein Structure Prediction (or CASP) is a community-wide blind test experiment to reveal the best accomplishments of structure modeling. Assessors have been using the Global Distance Test (GDT_TS) measure to quantify prediction performance since CASP3 in 1998. However, identifying significant score differences between close models is difficult because of the lack of uncertainty estimations for this measure. Here, we utilized the atomic fluctuations caused by structure flexibility to estimate the uncertainty of GDT_TS scores. Structures determined by nuclear magnetic resonance are deposited as ensembles of alternative conformers that reflect the structural flexibility, whereas standard X-ray refinement produces the static structure averaged over time and space for the dynamic ensembles. To recapitulate the structural heterogeneous ensemble in the crystal lattice, we performed time-averaged refinement for X-ray datasets to generate structural ensembles for our GDT_TS uncertainty analysis. Using those generated ensembles, our study demonstrates that the time-averaged refinements produced structure ensembles with better agreement with the experimental datasets than the averaged X-ray structures with B-factors. The uncertainty of the GDT_TS scores, quantified by their standard deviations (SDs), increases for scores lower than 50 and 70, with maximum SDs of 0.3 and 1.23 for X-ray and NMR structures, respectively. We also applied our procedure to the high accuracy version of GDT-based score and produced similar results with slightly higher SDs. To facilitate score comparisons by the community, we developed a user-friendly web server that produces structure ensembles for NMR and X-ray structures and is accessible at http://prodata.swmed.edu/SEnCS. Our work helps to identify the significance of GDT_TS score differences, as well as to provide structure ensembles for estimating SDs of any scores.

Ultrasound-detected subclinical inflammation was better reflected by the disease activity score (DAS-28) in patients with suspicion of inflammatory arthritis compared to established rheumatoid arthritis.

PubMed

Ciurtin, Coziana; Wyszynski, Karol; Clarke, Robert; Mouyis, Maria; Manson, Jessica; Marra, Giampiero

2016-10-01

Limited data are available about the ultrasound (US)-detected inflammatory features in patients with suspicion of inflammatory arthritis (S-IA) vs. established rheumatoid arthritis (RA). Our study aimed to assess if the presence of power Doppler (PD) can be predicted by a combination of clinical, laboratory and US parameters. We conducted a real-life, retrospective cohort study comparing clinical, laboratory and US parameters of 108 patients with established RA and 93 patients with S-IA. We propose a PD signal prediction model based on a beta-binomial distribution for PD variable using a mix of outcome measures. Patients with RA in clinical remission had significantly more active inflammation and erosions on US when compared with patients with S-IA with similar disease scores (p = 0.03 and p = 0.01, respectively); however, RA patients with different disease activity score (DAS-28) scores had similar PD scores (p = 0.058). The PD scores did not correlate with erosions (p = 0.38) or DAS-28 scores (p = 0.28) in RA patients, but they correlated with high disease activity in S-IA patients (p = 0.048). Subclinical inflammation is more common in patients with RA in clinical remission or with low disease activity than in patients with S-IA; therefore, US was more useful in assessing for true remission in RA rather than diagnosing IA in patients with low disease activity scores. This is the first study to propose a PD prediction model integrating several outcome measures in the two different groups of patients. Further research into validating this model can minimise the risk of underdiagnosing subclinical inflammation.

Validation of a Predictive Scoring System for Deep Sternal Wound Infection after Bilateral Internal Thoracic Artery Grafting in a Cohort of French Patients.

PubMed

Perrotti, Andrea; Gatti, Giuseppe; Dorigo, Enrica; Sinagra, Gianfranco; Pappalardo, Aniello; Chocron, Sidney

The Gatti score is a weighted scoring system based on risk factors for deep sternal wound infection (DSWI) that was created in an Italian center to predict DSWI risk after bilateral internal thoracic artery (BITA) grafting. No external evaluation based on validation samples derived from other surgical centers has been performed. The aim of this study is to perform this validation. During 2015, BITA grafts were used as skeletonized conduits in all 255 consecutive patients with multi-vessel coronary disease who underwent isolated coronary bypass surgery at the Department of Thoracic and Cardio-Vascular Surgery, University Hospital Jean Minjoz, Besançon, France. Baseline characteristics, operative data, and immediate outcomes of every patient were collected prospectively. A DSWI risk score was assigned to each patient pre-operatively. The discrimination power of both models, pre-operative and combined, of the Gatti score was assessed with the calculation of the area under the receiver operating characteristic curve. Fourteen (5.5%) patients had DSWI. Major differences both as the baseline characteristics of patients and surgical techniques were found between this series and the original series from which the Gatti score was derived. The area under the receiver operating characteristic curve was 0.78 (95% confidence interval: 0.64-0.92) for the pre-operative model and 0.84 (95% confidence interval: 0.69-0.98) for the combined model. The Gatti score has proven to be effective even in a cohort of French patients despite major differences from the original Italian series. Multi-center validation studies must be performed before introducing the score into clinical practice.

Impact of student ethnicity and primary childhood language on communication skill assessment in a clinical performance examination.

PubMed

Fernandez, Alicia; Wang, Frances; Braveman, Melissa; Finkas, Lindsay K; Hauer, Karen E

2007-08-01

Clinical performance examinations (CPX) with standardized patients (SPs) have become a preferred method to assess communication skills in US medical schools. Little is known about how trainees' backgrounds impact CPX performance. The objective of this paper is to examine the impact of student ethnicity, primary childhood language, and experience of diversity on the communication scores of a high-stakes CPX using SPs. This research was designed as an observational study. The participants of this study were third-year medical students at one US medical school. The measurements used in this study were CPX scores from mandatory exam, student demographics and experience with diversity measured by self-report on a survey, and Medical College Admission Test (MCAT) and United States Medical Licensing Examination (USMLE) scores. A total of 135 students participated. Asian and black students scored lower than white students on the communication portion of the CPX by approximately half a standard deviation (Asian, 67.4%; black, 64.4%; white, 69.4%, p < .05). There were no differences by ethnicity on history/physical exam scores. Multivariate analysis controlling for MCAT verbal scores reduced ethnic differences in communication scores (Asian-white mean differences = 1.95, p = 0.02), but Asian-white differences were eliminated only after sequential models included primary childhood language (difference = 0.57, p = 0.6). Even after controlling for English language knowledge as measured in MCAT verbal scores, speaking a primary childhood language other than English is associated with lower CPX communication scores for Asian students. While poorer communication skills cannot be ruled out, SP exams may contain measurement bias associated with differences in childhood language or culture. Caution is indicated when interpreting CPX communication scores among diverse examinees.

The New York risk score for in-hospital and 30-day mortality for coronary artery bypass graft surgery.

PubMed

Hannan, Edward L; Farrell, Louise Szypulski; Wechsler, Andrew; Jordan, Desmond; Lahey, Stephen J; Culliford, Alfred T; Gold, Jeffrey P; Higgins, Robert S D; Smith, Craig R

2013-01-01

Simplified risk scores for coronary artery bypass graft surgery are frequently in lieu of more complicated statistical models and are valuable for informed consent and choice of intervention. Previous risk scores have been based on in-hospital mortality, but a substantial number of patients die within 30 days of the procedure. These deaths should also be accounted for, so we have developed a risk score based on in-hospital and 30-day mortality. New York's Cardiac Surgery Reporting System was used to develop an in-hospital and 30-day logistic regression model for patients undergoing coronary artery bypass graft surgery in 2009, and this model was converted into a simple linear risk score that provides estimated in-hospital and 30-day mortality rates for different values of the score. The accuracy of the risk score in predicting mortality was tested. This score was also validated by applying it to 2008 New York coronary artery bypass graft data. Subsequent analyses evaluated the ability of the risk score to predict complications and length of stay. The overall in-hospital and 30-day mortality rate for the 10,148 patients in the study was 1.79%. There are seven risk factors comprising the score, with risk factor scores ranging from 1 to 5, and the highest possible total score is 23. The score accurately predicted mortality in 2009 as well as in 2008, and was strongly correlated with complications and length of stay. The risk score is a simple way of estimating short-term mortality that accurately predicts mortality in the year the model was developed as well as in the previous year. Perioperative complications and length of stay are also well predicted by the risk score. Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

A score card for upper GI endoscopy: Evaluation of interobserver variability in examiners with various levels of experience.

PubMed

Neumann, M; Friedl, S; Meining, A; Egger, K; Heldwein, W; Rey, J F; Hochberger, J; Classen, M; Hohenberger, W; Rösch, T

2002-10-01

In most European countries, training in GI endoscopy has largely been based on hands-on acquisition of experience in patients rather than on a structured training programme. With the development of training models systematic hands-on training in a variety of diagnostic and therapeutic endoscopy techniques was achieved. Little, however, is known about methods of objectively assessing trainees' performance. We therefore developed an assessment 'score card' for upper GI endoscopy and tested it in endoscopists with various levels of experience. The aim of the study was therefore to assess interobserver variations in the evaluation of trainees. On the basis of textbook and expert opinions a consensus group of eight experienced endoscopists developed a score card for diagnostic upper GI endoscopy with biopsy. The score card includes an assessment of the single steps of the procedure as well as of the times needed to complete each step. This score card was then evaluated in a further conference including ten experts who blindly assessed videotapes of 15 endoscopists performing upper GI endoscopy in a training bio-simulation model (the 'Erlangen Endo-Trainer'). On the basis of their previous experience (i. e. the number of endoscopies performed) these 15 endoscopists were classified into four groups: very experienced, experienced, having some experience and inexperienced. Interobserver variability (IOV) was tested for the various score card parameters (Kendall's rank-correlation coefficient 0.0-0.5 poor, 0.5-1.0 good agreement). In addition, the correlation between the score card assessment and the examiners' experience levels was analysed. Despite poor IOV results for all the parameters tested (Kendall coefficient < 0.3), the assessment parameters correlated well when the examiners' different experience levels were taken into account (correlation coefficient 0.59-0.89, p < 0.05). The score card parameters were suitable for differentiating between the four groups of examiners with different levels of endoscopic experience. As expected with scores involving subjective assessment of performance, the variability between reviewers was substantial. Nevertheless, the assessment score was capable of distinguishing reliably between different experience levels in terms of a good individual observer consistency. The score card can therefore be used to document both training status and progress during endoscopy training courses using bio-simulation models, and this might be able to provide improved quality assurance in GI endoscopy training.

People detection in crowded scenes using active contour models

NASA Astrophysics Data System (ADS)

Sidla, Oliver

2009-01-01

The detection of pedestrians in real-world scenes is a daunting task, especially in crowded situations. Our experience over the last years has shown that active shape models (ASM) can contribute significantly to a robust pedestrian detection system. The paper starts with an overview of shape model approaches, it then explains our approach which builds on top of Eigenshape models which have been trained using real-world data. These models are placed over candidate regions and matched to image gradients using a scoring function which integrates i) point distribution, ii) local gradient orientations iii) local image gradient strengths. A matching and shape model update process is iteratively applied in order to fit the flexible models to the local image content. The weights of the scoring function have a significant impact on the ASM performance. We analyze different settings of scoring weights for gradient magnitude, relative orientation differences, distance between model and gradient in an experiment which uses real-world data. Although for only one pedestrian model in an image computation time is low, the number of necessary processing cycles which is needed to track many people in crowded scenes can become the bottleneck in a real-time application. We describe the measures which have been taken in order to improve the speed of the ASM implementation and make it real-time capable.

Scoring systems for outcome prediction in patients with perforated peptic ulcer.

PubMed

Thorsen, Kenneth; Søreide, Jon Arne; Søreide, Kjetil

2013-04-10

Patients with perforated peptic ulcer (PPU) often present with acute, severe illness that carries a high risk for morbidity and mortality. Mortality ranges from 3-40% and several prognostic scoring systems have been suggested. The aim of this study was to review the available scoring systems for PPU patients, and to assert if there is evidence to prefer one to the other. We searched PubMed for the mesh terms "perforated peptic ulcer", "scoring systems", "risk factors", "outcome prediction", "mortality", "morbidity" and the combinations of these terms. In addition to relevant scores introduced in the past (e.g. Boey score), we included recent studies published between January 2000 and December 2012) that reported on scoring systems for prediction of morbidity and mortality in PPU patients. A total of ten different scoring systems used to predict outcome in PPU patients were identified; the Boey score, the Hacettepe score, the Jabalpur score the peptic ulcer perforation (PULP) score, the ASA score, the Charlson comorbidity index, the sepsis score, the Mannheim Peritonitis Index (MPI), the Acute physiology and chronic health evaluation II (APACHE II), the simplified acute physiology score II (SAPS II), the Mortality probability models II (MPM II), the Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity physical sub-score (POSSUM-phys score). Only four of the scores were specifically constructed for PPU patients. In five studies the accuracy of outcome prediction of different scoring systems was evaluated by receiver operating characteristics curve (ROC) analysis, and the corresponding area under the curve (AUC) among studies compared. Considerable variation in performance both between different scores and between different studies was found, with the lowest and highest AUC reported between 0.63 and 0.98, respectively. While the Boey score and the ASA score are most commonly used to predict outcome for PPU patients, considerable variations in accuracy for outcome prediction were shown. Other scoring systems are hampered by a lack of validation or by their complexity that precludes routine clinical use. While the PULP score seems promising it needs external validation before widespread use.

Scoring systems for outcome prediction in patients with perforated peptic ulcer

PubMed Central

2013-01-01

Background Patients with perforated peptic ulcer (PPU) often present with acute, severe illness that carries a high risk for morbidity and mortality. Mortality ranges from 3-40% and several prognostic scoring systems have been suggested. The aim of this study was to review the available scoring systems for PPU patients, and to assert if there is evidence to prefer one to the other. Material and methods We searched PubMed for the mesh terms “perforated peptic ulcer”, “scoring systems”, “risk factors”, ”outcome prediction”, “mortality”, ”morbidity” and the combinations of these terms. In addition to relevant scores introduced in the past (e.g. Boey score), we included recent studies published between January 2000 and December 2012) that reported on scoring systems for prediction of morbidity and mortality in PPU patients. Results A total of ten different scoring systems used to predict outcome in PPU patients were identified; the Boey score, the Hacettepe score, the Jabalpur score the peptic ulcer perforation (PULP) score, the ASA score, the Charlson comorbidity index, the sepsis score, the Mannheim Peritonitis Index (MPI), the Acute physiology and chronic health evaluation II (APACHE II), the simplified acute physiology score II (SAPS II), the Mortality probability models II (MPM II), the Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity physical sub-score (POSSUM-phys score). Only four of the scores were specifically constructed for PPU patients. In five studies the accuracy of outcome prediction of different scoring systems was evaluated by receiver operating characteristics curve (ROC) analysis, and the corresponding area under the curve (AUC) among studies compared. Considerable variation in performance both between different scores and between different studies was found, with the lowest and highest AUC reported between 0.63 and 0.98, respectively. Conclusion While the Boey score and the ASA score are most commonly used to predict outcome for PPU patients, considerable variations in accuracy for outcome prediction were shown. Other scoring systems are hampered by a lack of validation or by their complexity that precludes routine clinical use. While the PULP score seems promising it needs external validation before widespread use. PMID:23574922

Structure refinement of membrane proteins via molecular dynamics simulations.

PubMed

Dutagaci, Bercem; Heo, Lim; Feig, Michael

2018-07-01

A refinement protocol based on physics-based techniques established for water soluble proteins is tested for membrane protein structures. Initial structures were generated by homology modeling and sampled via molecular dynamics simulations in explicit lipid bilayer and aqueous solvent systems. Snapshots from the simulations were selected based on scoring with either knowledge-based or implicit membrane-based scoring functions and averaged to obtain refined models. The protocol resulted in consistent and significant refinement of the membrane protein structures similar to the performance of refinement methods for soluble proteins. Refinement success was similar between sampling in the presence of lipid bilayers and aqueous solvent but the presence of lipid bilayers may benefit the improvement of lipid-facing residues. Scoring with knowledge-based functions (DFIRE and RWplus) was found to be as good as scoring using implicit membrane-based scoring functions suggesting that differences in internal packing is more important than orientations relative to the membrane during the refinement of membrane protein homology models. © 2018 Wiley Periodicals, Inc.

An increase in visceral fat is associated with a decrease in the taste and olfactory capacity

PubMed Central

Fernandez-Garcia, Jose Carlos; Alcaide, Juan; Santiago-Fernandez, Concepcion; Roca-Rodriguez, MM.; Aguera, Zaida; Baños, Rosa; Botella, Cristina; de la Torre, Rafael; Fernandez-Real, Jose M.; Fruhbeck, Gema; Gomez-Ambrosi, Javier; Jimenez-Murcia, Susana; Menchon, Jose M.; Casanueva, Felipe F.; Fernandez-Aranda, Fernando; Tinahones, Francisco J.; Garrido-Sanchez, Lourdes

2017-01-01

Introduction Sensory factors may play an important role in the determination of appetite and food choices. Also, some adipokines may alter or predict the perception and pleasantness of specific odors. We aimed to analyze differences in smell–taste capacity between females with different weights and relate them with fat and fat-free mass, visceral fat, and several adipokines. Materials and methods 179 females with different weights (from low weight to morbid obesity) were studied. We analyzed the relation between fat, fat-free mass, visceral fat (indirectly estimated by bioelectrical impedance analysis with visceral fat rating (VFR)), leptin, adiponectin and visfatin. The smell and taste assessments were performed through the "Sniffin’ Sticks" and "Taste Strips" respectively. Results We found a lower score in the measurement of smell (TDI-score (Threshold, Discrimination and Identification)) in obese subjects. All the olfactory functions measured, such as threshold, discrimination, identification and the TDI-score, correlated negatively with age, body mass index (BMI), leptin, fat mass, fat-free mass and VFR. In a multiple linear regression model, VFR mainly predicted the TDI-score. With regard to the taste function measurements, the normal weight subjects showed a higher score of taste functions. However a tendency to decrease was observed in the groups with greater or lesser BMI. In a multiple linear regression model VFR and age mainly predicted the total taste scores. Discussion We show for the first time that a reverse relationship exists between visceral fat and sensory signals, such as smell and taste, across a population with different body weight conditions. PMID:28158237

Laparoscopic surgical box model training for surgical trainees with no prior laparoscopic experience.

PubMed

Nagendran, Myura; Toon, Clare D; Davidson, Brian R; Gurusamy, Kurinchi Selvan

2014-01-17

Surgical training has traditionally been one of apprenticeship, where the surgical trainee learns to perform surgery under the supervision of a trained surgeon. This is time consuming, costly, and of variable effectiveness. Training using a box model physical simulator - either a video box or a mirrored box - is an option to supplement standard training. However, the impact of this modality on trainees with no prior laparoscopic experience is unknown. To compare the benefits and harms of box model training versus no training, another box model, animal model, or cadaveric model training for surgical trainees with no prior laparoscopic experience. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and Science Citation Index Expanded to May 2013. We included all randomised clinical trials comparing box model trainers versus no training in surgical trainees with no prior laparoscopic experience. We also included trials comparing different methods of box model training. Two authors independently identified trials and collected data. We analysed the data with both the fixed-effect and the random-effects models using Review Manager for analysis. For each outcome, we calculated the standardised mean difference (SMD) with 95% confidence intervals (CI) based on intention-to-treat analysis whenever possible. Twenty-five trials contributed data to the quantitative synthesis in this review. All but one trial were at high risk of bias. Overall, 16 trials (464 participants) provided data for meta-analysis of box training (248 participants) versus no supplementary training (216 participants). All the 16 trials in this comparison used video trainers. Overall, 14 trials (382 participants) provided data for quantitative comparison of different methods of box training. There were no trials comparing box model training versus animal model or cadaveric model training. Box model training versus no training: The meta-analysis showed that the time taken for task completion was significantly shorter in the box trainer group than the control group (8 trials; 249 participants; SMD -0.48 seconds; 95% CI -0.74 to -0.22). Compared with the control group, the box trainer group also had lower error score (3 trials; 69 participants; SMD -0.69; 95% CI -1.21 to -0.17), better accuracy score (3 trials; 73 participants; SMD 0.67; 95% CI 0.18 to 1.17), and better composite performance scores (SMD 0.65; 95% CI 0.42 to 0.88). Three trials reported movement distance but could not be meta-analysed as they were not in a format for meta-analysis. There was significantly lower movement distance in the box model training compared with no training in one trial, and there were no significant differences in the movement distance between the two groups in the other two trials. None of the remaining secondary outcomes such as mortality and morbidity were reported in the trials when animal models were used for assessment of training, error in movements, and trainee satisfaction. Different methods of box training: One trial (36 participants) found significantly shorter time taken to complete the task when box training was performed using a simple cardboard box trainer compared with the standard pelvic trainer (SMD -3.79 seconds; 95% CI -4.92 to -2.65). There was no significant difference in the time taken to complete the task in the remaining three comparisons (reverse alignment versus forward alignment box training; box trainer suturing versus box trainer drills; and single incision versus multiport box model training). There were no significant differences in the error score between the two groups in any of the comparisons (box trainer suturing versus box trainer drills; single incision versus multiport box model training; Z-maze box training versus U-maze box training). The only trial that reported accuracy score found significantly higher accuracy score with Z-maze box training than U-maze box training (1 trial; 16 participants; SMD 1.55; 95% CI 0.39 to 2.71). One trial (36 participants) found significantly higher composite score with simple cardboard box trainer compared with conventional pelvic trainer (SMD 0.87; 95% CI 0.19 to 1.56). Another trial (22 participants) found significantly higher composite score with reverse alignment compared with forward alignment box training (SMD 1.82; 95% CI 0.79 to 2.84). There were no significant differences in the composite score between the intervention and control groups in any of the remaining comparisons. None of the secondary outcomes were adequately reported in the trials. The results of this review are threatened by both risks of systematic errors (bias) and risks of random errors (play of chance). Laparoscopic box model training appears to improve technical skills compared with no training in trainees with no previous laparoscopic experience. The impacts of this decreased time on patients and healthcare funders in terms of improved outcomes or decreased costs are unknown. There appears to be no significant differences in the improvement of technical skills between different methods of box model training. Further well-designed trials of low risk of bias and random errors are necessary. Such trials should assess the impacts of box model training on surgical skills in both the short and long term, as well as clinical outcomes when the trainee becomes competent to operate on patients.

Conclusion of LOD-score analysis for family data generated under two-locus models.

PubMed Central

Dizier, M. H.; Babron, M. C.; Clerget-Darpoux, F.

1996-01-01

The power to detect linkage by the LOD-score method is investigated here for diseases that depend on the effects of two genes. The classical strategy is, first, to detect a major-gene (MG) effect by segregation analysis and, second, to seek for linkage with genetic markers by the LOD-score method using the MG parameters. We already showed that segregation analysis can lead to evidence for a MG effect for many two-locus models, with the estimates of the MG parameters being very different from those of the two genes involved in the disease. We show here that use of these MG parameter estimates in the LOD-score analysis may lead to a failure to detect linkage for some two-locus models. For these models, use of the sib-pair method gives a non-negligible increase of power to detect linkage. The linkage-homogeneity test among subsamples differing for the familial disease distribution provides evidence of parameter misspecification, when the MG parameters are used. Moreover, for most of the models, use of the MG parameters in LOD-score analysis leads to a large bias in estimation of the recombination fraction and sometimes also to a rejection of linkage for the true recombination fraction. A final important point is that a strong evidence of an MG effect, obtained by segregation analysis, does not necessarily imply that linkage will be detected for at least one of the two genes, even with the true parameters and with a close informative marker. PMID:8651311

Comparison of two equivalent model for end-stage liver disease scores for hepatocellular carcinoma patients using data from the United Network for Organ Sharing liver transplant waiting list registry.

PubMed

Alver, Sarah K; Lorenz, Douglas J; Washburn, Kenneth; Marvin, Michael R; Brock, Guy N

2017-11-01

Patients with hepatocellular carcinoma (HCC) have been advantaged on the liver transplant waiting list within the United States, and a 6-month delay and exception point cap have recently been implemented to address this disparity. An alternative approach to prioritization is an HCC-specific scoring model such as the MELD Equivalent (MELD EQ ) and the mixed new deMELD. Using data on adult patients added to the UNOS waitlist between 30 September 2009 and 30 June 2014, we compared projected dropout and transplant probabilities for patients with HCC under these two models. Both scores matched actual non-HCC dropout in groups with scores <22 and improved equity with non-HCC transplant probabilities overall. However, neither score matched non-HCC dropout accurately for scores of 25-40 and projected dropout increased beyond non-HCC probabilities for scores <16. The main differences between the two scores were as follows: (i) the MELD EQ assigns 6.85 more points after 6 months on the waitlist and (ii) the deMELD gives greater weight to tumor size and laboratory MELD. Post-transplant survival was lower for patients with scores in the 22-30 range compared with those with scores <16 (P = 0.007, MELD EQ ; P = 0.015, deMELD). While both scores result in better equity of waitlist outcomes compared with scheduled progression, continued development and calibration is recommended. © 2017 Steunstichting ESOT.

Assessment of perioperative mortality risk in patients with infective endocarditis undergoing cardiac surgery: performance of the EuroSCORE I and II logistic models.

PubMed

Madeira, Sérgio; Rodrigues, Ricardo; Tralhão, António; Santos, Miguel; Almeida, Carla; Marques, Marta; Ferreira, Jorge; Raposo, Luís; Neves, José; Mendes, Miguel

2016-02-01

The European System for Cardiac Operative Risk Evaluation (EuroSCORE) has been established as a tool for assisting decision-making in surgical patients and as a benchmark for quality assessment. Infective endocarditis often requires surgical treatment and is associated with high mortality. This study was undertaken to (i) validate both versions of the EuroSCORE, the older logistic EuroSCORE I and the recently developed EuroSCORE II and to compare their performances; (ii) identify predictors other than those included in the EuroSCORE models that might further improve their performance. We retrospectively studied 128 patients from a single-centre registry who underwent heart surgery for active infective endocarditis between January 2007 and November 2014. Binary logistic regression was used to find independent predictors of mortality and to create a new prediction model. Discrimination and calibration of models were assessed by receiver-operating characteristic curve analysis, calibration curves and the Hosmer-Lemeshow test. The observed perioperative mortality was 16.4% (n = 21). The median EuroSCORE I and EuroSCORE II were 13.9% interquartile range (IQ) (7.0-35.0) and 6.6% IQ (3.5-18.2), respectively. Discriminative power was numerically higher for EuroSCORE II {area under the curve (AUC) of 0.83 [95% confidence interval (CI), 0.75-0.91]} than for EuroSCORE I [0.75 (95% CI, 0.66-0.85), P = 0.09]. The Hosmer-Lemeshow test showed good calibration for EuroSCORE II (P = 0.08) but not for EuroSCORE I (P = 0.04). EuroSCORE I tended to over-predict and EuroSCORE II to under-predict mortality. Among the variables known to be associated with greater infective endocarditis severity, only prosthetic valve infective endocarditis remained an independent predictor of mortality [odds ratio (OR) 6.6; 95% CI, 1.1-39.5; P = 0.04]. The new model including the EuroSCORE II variables and variables known to be associated with greater infective endocarditis severity showed an AUC of 0.87 (95% CI, 0.79-0.94) and differed significantly from EuroSCORE I (P = 0.03) but not from EuroSCORE II (P = 0.4). Both EuroSCORE I and II satisfactorily stratify risk in active infective endocarditis; however, EuroSCORE II performed better in the overall comparison. Specific endocarditis features will increase model complexity without an unequivocal improvement in predictive ability. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction.

PubMed

Schwabe, Inga; Boomsma, Dorret I; van den Berg, Stéphanie M

2017-12-01

Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2,110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences in mathematical ability in twin pairs with a low or average SES.

Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study.

PubMed

Pollock, Benjamin D; Hu, Tian; Chen, Wei; Harville, Emily W; Li, Shengxu; Webber, Larry S; Fonseca, Vivian; Bazzano, Lydia A

2017-01-01

To evaluate several adult diabetes risk calculation tools for predicting the development of incident diabetes and pre-diabetes in a bi-racial, young adult population. Surveys beginning in young adulthood (baseline age ≥18) and continuing across multiple decades for 2122 participants of the Bogalusa Heart Study were used to test the associations of five well-known adult diabetes risk scores with incident diabetes and pre-diabetes using separate Cox models for each risk score. Racial differences were tested within each model. Predictive utility and discrimination were determined for each risk score using the Net Reclassification Index (NRI) and Harrell's c-statistic. All risk scores were strongly associated (p<.0001) with incident diabetes and pre-diabetes. The Wilson model indicated greater risk of diabetes for blacks versus whites with equivalent risk scores (HR=1.59; 95% CI 1.11-2.28; p=.01). C-statistics for the diabetes risk models ranged from 0.79 to 0.83. Non-event NRIs indicated high specificity (non-event NRIs: 76%-88%), but poor sensitivity (event NRIs: -23% to -3%). Five diabetes risk scores established in middle-aged, racially homogenous adult populations are generally applicable to younger adults with good specificity but poor sensitivity. The addition of race to these models did not result in greater predictive capabilities. A more sensitive risk score to predict diabetes in younger adults is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

Usage of 3D models of tetralogy of Fallot for medical education: impact on learning congenital heart disease.

PubMed

Loke, Yue-Hin; Harahsheh, Ashraf S; Krieger, Axel; Olivieri, Laura J

2017-03-11

Congenital heart disease (CHD) is the most common human birth defect, and clinicians need to understand the anatomy to effectively care for patients with CHD. However, standard two-dimensional (2D) display methods do not adequately carry the critical spatial information to reflect CHD anatomy. Three-dimensional (3D) models may be useful in improving the understanding of CHD, without requiring a mastery of cardiac imaging. The study aimed to evaluate the impact of 3D models on how pediatric residents understand and learn about tetralogy of Fallot following a teaching session. Pediatric residents rotating through an inpatient Cardiology rotation were recruited. The sessions were randomized into using either conventional 2D drawings of tetralogy of Fallot or physical 3D models printed from 3D cardiac imaging data sets (cardiac MR, CT, and 3D echocardiogram). Knowledge acquisition was measured by comparing pre-session and post-session knowledge test scores. Learner satisfaction and self-efficacy ratings were measured with questionnaires filled out by the residents after the teaching sessions. Comparisons between the test scores, learner satisfaction and self-efficacy questionnaires for the two groups were assessed with paired t-test. Thirty-five pediatric residents enrolled into the study, with no significant differences in background characteristics, including previous clinical exposure to tetralogy of Fallot. The 2D image group (n = 17) and 3D model group (n = 18) demonstrated similar knowledge acquisition in post-test scores. Residents who were taught with 3D models gave a higher composite learner satisfaction scores (P = 0.03). The 3D model group also had higher self-efficacy aggregate scores, but the difference was not statistically significant (P = 0.39). Physical 3D models enhance resident education around the topic of tetralogy of Fallot by improving learner satisfaction. Future studies should examine the impact of models on teaching CHD that are more complex and elaborate.

Designing an iPad App to Monitor and Improve Classroom Behavior for Children with ADHD: iSelfControl Feasibility and Pilot Studies.

PubMed

Schuck, Sabrina; Emmerson, Natasha; Ziv, Hadar; Collins, Penelope; Arastoo, Sara; Warschauer, Mark; Crinella, Francis; Lakes, Kimberley

2016-01-01

Children with Attention Deficit/Hyperactivity Disorder (ADHD) receive approximately 80% of instruction in the general education classroom, where individualized behavioral management strategies may be difficult for teachers to consistently deliver. Mobile device apps provide promising platforms to manage behavior. This pilot study evaluated the utility of a web-based application (iSelfControl) designed to support classroom behavior management. iSelfControl prompted students every 'Center' (30-minutes) to self-evaluate using a universal token-economy classroom management system focused on compliance, productivity, and positive relationships. Simultaneously, the teacher evaluated each student on a separate iPad. Using Multi Level Modeling, we examined 13 days of data gathered from implementation with 5th grade students (N = 12) at a school for children with ADHD and related executive function difficulties. First, an unconditional growth model evaluated the overall amount of change in aggregated scores over time as well as the degree of systematic variation in scores within and across teacher-student dyads. Second, separate intercepts and slopes were estimated for teacher and student to estimate degree of congruency between trajectories. Finally, differences between teacher and student scores were tested at each time-point in separate models to examine unique 'Center' effects. 51% of the total variance in scores was attributed to differences between dyads. Trajectories of student and teacher scores remained relatively stable across seven time-points each day and did not statistically differ from each other. On any given day, students tended to evaluate their behaviors more positively (entered higher scores for themselves) compared to corresponding teacher scores. In summary, iSelfControl provides a platform for self and teacher evaluation that is an important adjunct to conventional classroom management strategies. The application captured teacher/student discrepancies and significant variations across the day. Future research with a larger, clinically diagnosed sample in multiple classrooms is needed to assess generalizability to a wider variety of classroom settings.

Establishment of an evaluation model for human milk fat substitutes.

PubMed

Wang, Yong-Hua; Mai, Qing-Yun; Qin, Xiao-Li; Yang, Bo; Wang, Zi-Lian; Chen, Hai-Tian

2010-01-13

Fatty acid composition and distribution of human milk fat (HMF), from mothers over different lactating periods in Guangzhou, China, were analyzed. The universal characteristics were consistent with previously reported results although the fatty acid content was within a different range and dependent on the local population (low saturated fatty acid and high oleic acid for Guangdong mothers' milk fat). Based on the composition of the total and sn-2 fatty acids of mature milk fat, an efficient evaluation model was innovatively established by adopting the "deducting score" principle. The model showed good agreement between the scores and the degree of similarity by assessing 15 samples from different sources including four samples of HMF, eight samples of human milk fat substitutes (HMFSs) and infant formulas, and three samples of fats and oils. This study would allow for the devolvement of individual human milk fat substitutes with different and specific fatty acid compositions for local infants.

Physician-Owned Surgical Hospitals Outperform Other Hospitals in Medicare Value-Based Purchasing Program.

PubMed

Ramirez, Adriana G; Tracci, Margaret C; Stukenborg, George J; Turrentine, Florence E; Kozower, Benjamin D; Jones, R Scott

2016-10-01

The Hospital Value-Based Purchasing Program measures value of care provided by participating Medicare hospitals and creates financial incentives for quality improvement and fosters increased transparency. Limited information is available comparing hospital performance across health care business models. The 2015 Hospital Value-Based Purchasing Program results were used to examine hospital performance by business model. General linear modeling assessed differences in mean total performance score, hospital case mix index, and differences after adjustment for differences in hospital case mix index. Of 3,089 hospitals with total performance scores, categories of representative health care business models included 104 physician-owned surgical hospitals, 111 University HealthSystem Consortium, 14 US News & World Report Honor Roll hospitals, 33 Kaiser Permanente, and 124 Pioneer accountable care organization affiliated hospitals. Estimated mean total performance scores for physician-owned surgical hospitals (64.4; 95% CI, 61.83-66.38) and Kaiser Permanente (60.79; 95% CI, 56.56-65.03) were significantly higher compared with all remaining hospitals, and University HealthSystem Consortium members (36.8; 95% CI, 34.51-39.17) performed below the mean (p < 0.0001). Significant differences in mean hospital case mix index included physician-owned surgical hospitals (mean 2.32; p < 0.0001), US News & World Report honorees (mean 2.24; p = 0.0140), and University HealthSystem Consortium members (mean 1.99; p < 0.0001), and Kaiser Permanente hospitals had lower case mix value (mean 1.54; p < 0.0001). Re-estimation of total performance scores did not change the original results after adjustment for differences in hospital case mix index. The Hospital Value-Based Purchasing Program revealed superior hospital performance associated with business model. Closer inspection of high-value hospitals can guide value improvement and policy-making decisions for all Medicare Value-Based Purchasing Program Hospitals. Copyright © 2016 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Comparing models of change to estimate the mediated effect in the pretest-posttest control group design

PubMed Central

Valente, Matthew J.; MacKinnon, David P.

2017-01-01

Models to assess mediation in the pretest-posttest control group design are understudied in the behavioral sciences even though it is the design of choice for evaluating experimental manipulations. The paper provides analytical comparisons of the four most commonly used models used to estimate the mediated effect in this design: Analysis of Covariance (ANCOVA), difference score, residualized change score, and cross-sectional model. Each of these models are fitted using a Latent Change Score specification and a simulation study assessed bias, Type I error, power, and confidence interval coverage of the four models. All but the ANCOVA model make stringent assumptions about the stability and cross-lagged relations of the mediator and outcome that may not be plausible in real-world applications. When these assumptions do not hold, Type I error and statistical power results suggest that only the ANCOVA model has good performance. The four models are applied to an empirical example. PMID:28845097

Comparing models of change to estimate the mediated effect in the pretest-posttest control group design.

PubMed

Valente, Matthew J; MacKinnon, David P

2017-01-01

Models to assess mediation in the pretest-posttest control group design are understudied in the behavioral sciences even though it is the design of choice for evaluating experimental manipulations. The paper provides analytical comparisons of the four most commonly used models used to estimate the mediated effect in this design: Analysis of Covariance (ANCOVA), difference score, residualized change score, and cross-sectional model. Each of these models are fitted using a Latent Change Score specification and a simulation study assessed bias, Type I error, power, and confidence interval coverage of the four models. All but the ANCOVA model make stringent assumptions about the stability and cross-lagged relations of the mediator and outcome that may not be plausible in real-world applications. When these assumptions do not hold, Type I error and statistical power results suggest that only the ANCOVA model has good performance. The four models are applied to an empirical example.

Mental health measures in predicting outcomes for the selection and training of navy divers.

PubMed

van Wijk, Charles H

2011-03-01

Two models have previously been enlisted to predict success in training using psychological markers. Both the Mental Health Model and Trait Anxiety Model have shown some success in predicting behaviours associated with arousal among student divers. This study investigated the potential of these two models to predict outcome in naval diving selection and training. Navy diving candidates (n = 137) completed the Brunel Mood Scale and the State-Trait Personality Inventory (trait-anxiety scale) prior to selection. The mean scores of the candidates accepted for training were compared to those who were not accepted. The mean scores of the candidates who passed training were then compared to those who failed. A number of trainees withdrew from training due to injury, and their scores were also compared to those who completed the training. Candidates who were not accepted were more depressed, fatigued and confused than those who were accepted for training, and reported higher trait anxiety. There were no significant differences between the candidates who passed training and those who did not. However, injured trainees were tenser, more fatigued and reported higher trait anxiety than the rest. Age, gender, home language, geographical region of origin and race had no significant interaction with outcome results. While the models could partially discriminate between the mean scores of different outcome groups, none of them contributed meaningfully to predicting individual outcome in diving training. Both models may have potential in identifying proneness to injury, and this requires further study.

A national internet survey on midlife women's attitudes toward physical activity.

PubMed

Im, Eun-Ok; Chang, Sun Ju; Ko, Young; Chee, Wonshik; Stuifbergen, Alexa; Walker, Lorraine

2012-01-01

Despite an increasing number of studies of midlife women's physical activity, little is known about how attitudes toward physical activity of midlife women from diverse ethnic groups influence the women's physical activity. To explore ethnic differences in midlife women's attitudes toward physical activity and determine the relationships between the attitudes and their actual participation in physical activity while considering other influencing factors. The Midlife Women's Attitudes Toward Physical Activity model was used to guide the study. This was a cross-sectional Internet survey study of 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Physical Activity Assessment Inventory; a modified Barriers to Health Activities Scale; the Questions on Attitudes Toward Physical Activity, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention; and the Kaiser Physical Activity Survey. The data were analyzed using ANOVA, correlation, hierarchical multiple regression, and path analyses. There were significant ethnic differences in the attitude scores (F = 2.58, p < .05), but no ethnic differences in the physical activity scores. Interestingly, there were significant ethnic differences in the occupational physical activity scores (F = 5.68, p < .01). Attitude scores accounted for 5% of total variances of the physical activity scores (F(ch) = 43.52, p < .01). The direct paths from the attitude scores (p < .01), the self-efficacy scores (p < .01), and the barrier scores (p < .05) to the physical activity scores were statistically significant. Ethnic differences in the women's attitudes toward physical activity need to be considered in promoting physical activity of midlife women.

A score model for the continuous grading of early allograft dysfunction severity.

PubMed

Pareja, Eugenia; Cortes, Miriam; Hervás, David; Mir, José; Valdivieso, Andrés; Castell, José V; Lahoz, Agustín

2015-01-01

Early allograft dysfunction (EAD) dramatically influences graft and patient outcomes. A lack of consensus on an EAD definition hinders comparisons of liver transplant outcomes and management of recipients among and within centers. We sought to develop a model for the quantitative assessment of early allograft function [Model for Early Allograft Function Scoring (MEAF)] after transplantation. A retrospective study including 1026 consecutive liver transplants was performed for MEAF score development. Multivariate data analysis was used to select a small number of postoperative variables that adequately describe EAD. Then, the distribution of these variables was mathematically modeled to assign a score for each actual variable value. A model, based on easily obtainable clinical parameters (ie, alanine aminotransferase, international normalized ratio, and bilirubin) and scoring liver function from 0 to 10, was built. The MEAF score showed a significant association with patient and graft survival at 3-, 6- and 12-month follow-ups. Hepatic steatosis and age for donors; cold/warm ischemia times and postreperfusion syndrome for surgery; and intensive care unit and hospital stays, Model for End-Stage Liver Disease and Child-Pugh scores, body mass index, and fresh frozen plasma transfusions for recipients were factors associated significantly with EAD. The model was satisfactorily validated by its application to an independent set of 200 patients who underwent liver transplantation at a different center. In conclusion, a model for the quantitative assessment of EAD severity has been developed and validated for the first time. The MEAF provides a more accurate graft function assessment than current categorical classifications and may help clinicians to make early enough decisions on retransplantation benefits. Furthermore, the MEAF score is a predictor of recipient and graft survival. The standardization of the criteria used to define EAD may allow reliable comparisons of recipients' treatments and transplant outcomes among and within centers. © 2014 American Association for the Study of Liver Diseases.

Population pharmacokinetic/pharmacodynamic model of clozapine for characterizing the relationship between accumulated exposure and PANSS scores in patients with schizophrenia.

PubMed

Shang, De-Wei; Li, Li-Jun; Wang, Xi-Pei; Wen, Yu-Guan; Ren, Yu-Peng; Guo, Wei; Li, Wen-Biao; Li, Liang; Zhou, Tian-Yan; Lu, Wei; Wang, Chuan-Yue

2014-06-01

The aim of this study was to characterize the relationship between accumulated exposure of clozapine and changes in Positive and Negative Syndrome Scale (PANSS) score in Chinese patients with schizophrenia by pharmacokinetic/pharmacodynamic (PK/PD) modeling. Sparse clozapine PK data and PANSS scores were collected from 2 clinical studies of Chinese inpatients with schizophrenia. Two other rich PK data sets were included for more accurate assessment of clozapine PK characteristics. The relationship between clozapine-accumulated exposure and PANSS score was investigated using linear, log-linear, E(max), and sigmoid models, and each model was evaluated using visual predictive condition and normalized prediction distribution error methods. Simulations based on the final PK/PD model were preformed to investigate the effect of clozapine on PANSS scores under different dose regimens. A total of 1391 blood clozapine concentrations from 198 subjects (180 patients and 18 healthy volunteers) and 576 PANSS scores from 137 patients were included for PK and PK/PD analysis. A first-order 2-compartment PK model with covariates gender and smoking status influencing systemic clearance adequately described the PK profile of clozapine. The decrease in total PANSS score during treatment was best characterized using cumulated clozapine area under the curve (AUC) data in the E(max) model. The maximum decrease in PANSS during clozapine treatment (Emax) was 55.4%, and the cumulated AUC(50) (cAUC(50)) required to attain half of E(max) was 296 mg·L(-1)·h(-1)·d(-1). The simulations demonstrated that the accelerated dose titration and constant dose regimens achieved a similar maximum drug response but with a slower relief of symptoms in dose titration regimen. The PK/PD model can describe the clinical response as measured by decreasing PANSS score during treatment and may be useful for optimizing the dose regimen for individual patients.

Assessing environmental inequalities in ambient air pollution across urban Australia.

PubMed

Knibbs, Luke D; Barnett, Adrian G

2015-04-01

Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of a prediction model for the progression of rheumatoid arthritis in patients with undifferentiated arthritis.

PubMed

Arana-Guajardo, Ana; Pérez-Barbosa, Lorena; Vega-Morales, David; Riega-Torres, Janett; Esquivel-Valerio, Jorge; Garza-Elizondo, Mario

2014-01-01

Different prediction rules have been applied to patients with undifferentiated arthritis (UA) to identify those that progress to rheumatoid arthritis (RA). The Leiden Prediction Rule (LPR) has proven useful in different UA cohorts. To apply the LPR to a cohort of patients with UA of northeastern Mexico. We included 47 patients with UA, LPR was applied at baseline. They were evaluated and then classified after one year of follow-up into two groups: those who progressed to RA (according to ACR 1987) and those who did not. 43% of the AI patients developed RA. In the RA group, 56% of patients obtained a score ≤ 6 and only 15% ≥ 8. 70% who did not progress to RA had a score between 6 and ≤ 8. There was no difference in median score of LPR between groups, p=0.940. Most patients who progressed to RA scored less than 6 points in the LPR. Unlike what was observed in other cohorts, the model in our population did not allow us to predict the progression of the disease. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Academic Outcome Measures of a Dedicated Education Unit Over Time: Help or Hinder?

PubMed

Smyer, Tish; Gatlin, Tricia; Tan, Rhigel; Tejada, Marianne; Feng, Du

2015-01-01

Critical thinking, nursing process, quality and safety measures, and standardized RN exit examination scores were compared between students (n = 144) placed in a dedicated education unit (DEU) and those in a traditional clinical model. Standardized test scores showed that differences between the clinical groups were not statistically significant. This study shows that the DEU model is 1 approach to clinical education that can enhance students' academic outcomes.

A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery.

PubMed

Shirk, Steven D; Mitchell, Meghan B; Shaughnessy, Lynn W; Sherman, Janet C; Locascio, Joseph J; Weintraub, Sandra; Atri, Alireza

2011-11-11

With the recent publication of new criteria for the diagnosis of preclinical Alzheimer's disease (AD), there is a need for neuropsychological tools that take premorbid functioning into account in order to detect subtle cognitive decline. Using demographic adjustments is one method for increasing the sensitivity of commonly used measures. We sought to provide a useful online z-score calculator that yields estimates of percentile ranges and adjusts individual performance based on sex, age and/or education for each of the neuropsychological tests of the National Alzheimer's Coordinating Center Uniform Data Set (NACC, UDS). In addition, we aimed to provide an easily accessible method of creating norms for other clinical researchers for their own, unique data sets. Data from 3,268 clinically cognitively-normal older UDS subjects from a cohort reported by Weintraub and colleagues (2009) were included. For all neuropsychological tests, z-scores were estimated by subtracting the raw score from the predicted mean and then dividing this difference score by the root mean squared error term (RMSE) for a given linear regression model. For each neuropsychological test, an estimated z-score was calculated for any raw score based on five different models that adjust for the demographic predictors of SEX, AGE and EDUCATION, either concurrently, individually or without covariates. The interactive online calculator allows the entry of a raw score and provides five corresponding estimated z-scores based on predictions from each corresponding linear regression model. The calculator produces percentile ranks and graphical output. An interactive, regression-based, normative score online calculator was created to serve as an additional resource for UDS clinical researchers, especially in guiding interpretation of individual performances that appear to fall in borderline realms and may be of particular utility for operationalizing subtle cognitive impairment present according to the newly proposed criteria for Stage 3 preclinical Alzheimer's disease.

Predictive effects of teachers and schools on test scores, college attendance, and earnings.

PubMed

Chamberlain, Gary E

2013-10-22

I studied predictive effects of teachers and schools on test scores in fourth through eighth grade and outcomes later in life such as college attendance and earnings. For example, predict the fraction of a classroom attending college at age 20 given the test score for a different classroom in the same school with the same teacher and given the test score for a classroom in the same school with a different teacher. I would like to have predictive effects that condition on averages over many classrooms, with and without the same teacher. I set up a factor model that, under certain assumptions, makes this feasible. Administrative school district data in combination with tax data were used to calculate estimates and do inference.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Validation of a Task Network Human Performance Model of Driving

DTIC Science & Technology

2007-04-01

34 Table 23. NASA - TLX scores for study conditions...35 Table 24. ANOVA for NASA - TLX scores for study conditions (α = 0.05)...............................35 Table 25...Significant difference between conditions for NASA - TLX in the simulator study.....36 Table 26. ANOVA table for mental demand subscale of NASA - TLX

Marked differences in core beliefs about self and others, between sociotropy and autonomy: personality vulnerabilities in the cognitive model of depression.

PubMed

Otani, Koichi; Suzuki, Akihito; Matsumoto, Yoshihiko; Shirata, Toshinori

2018-01-01

The cognitive model of depression posits two distinctive personality vulnerabilities termed sociotropy and autonomy, each of which is composed of a cluster of maladaptive self-schemas. It is postulated that negative core beliefs about self underlie maladaptive self-schemas as a whole, whereas those about others may be implicated in the autonomous self-schemas. Therefore, the present study examined the relations of sociotropy and autonomy with core beliefs about self and others. The sample of this study consisted of 321 healthy Japanese volunteers. Sociotropy and autonomy were evaluated by the corresponding subscales of the Sociotropy-Autonomy Scale. Core beliefs about self and others were assessed by the negative-self, positive-self, negative-other and positive-other subscales of the Brief Core Schema Scales. In the forced multiple regression analysis, sociotropy scores were correlated with negative-self scores ( β = 0.389, P < 0.001). Meanwhile, autonomy scores were correlated with positive-self scores ( β = 0.199, P < 0.01) and negative-other scores ( β = 0.191, P < 0.01). The present study suggests marked differences in core beliefs about self and others between sociotropy and autonomy, further contrasting the two personality vulnerabilities to depression.

Cultural differences in functional status measurement: analyses of person fit according to the Rasch model.

PubMed

Custers, J W; Hoijtink, H; van der Net, J; Helders, P J

2000-01-01

For many reasons it is preferable to use established health related outcome instruments. The validity of an instrument, however, can be affected when used in another culture or language other than what it was originally developed. In this paper, the outcome on functional status measurement using a preliminary version of the Dutch translated 'Pediatric Evaluation of Disability Inventory' (PEDI) was studied involving a sample of 20 non-disabled Dutch children and American peers, to see if a cross-cultural validation procedure is needed before using the instrument in the Netherlands. The Rasch model was used to analyse the Dutch data. Score profiles were not found to be compatible with the score profiles of American children. In particular, ten items were scored differently with strong indications that these were based on inter-cultural differences. Based on our study, it is argued that cross-cultural validation of the PEDI is necessary before using the instrument in the Netherlands.

Schooling as a Lottery: Racial Differences in School Advancement in Urban South Africa†

PubMed Central

Lam, David; Ardington, Cally; Leibbrandt, Murray

2010-01-01

This paper analyzes the large racial differences in progress through secondary school in South Africa. Using recently collected longitudinal data we find that grade advancement is strongly associated with scores on a baseline literacy and numeracy test. In grades 8-11 the effect of these scores on grade progression is much stronger for white and coloured students than for African students, while there is no racial difference in the impact of the scores on passing the nationally standardized grade 12 matriculation exam. We develop a stochastic model of grade repetition that generates predictions consistent with these results. The model predicts that a larger stochastic component in the link between learning and measured performance will generate higher enrollment, higher failure rates, and a weaker link between ability and grade progression. The results suggest that grade progression in African schools is poorly linked to actual ability and learning. The results point to the importance of considering the stochastic component of grade repetition in analyzing school systems with high failure rates. PMID:21499515

Integrating high dimensional bi-directional parsing models for gene mention tagging.

PubMed

Hsu, Chun-Nan; Chang, Yu-Ming; Kuo, Cheng-Ju; Lin, Yu-Shi; Huang, Han-Shen; Chung, I-Fang

2008-07-01

Tagging gene and gene product mentions in scientific text is an important initial step of literature mining. In this article, we describe in detail our gene mention tagger participated in BioCreative 2 challenge and analyze what contributes to its good performance. Our tagger is based on the conditional random fields model (CRF), the most prevailing method for the gene mention tagging task in BioCreative 2. Our tagger is interesting because it accomplished the highest F-scores among CRF-based methods and second over all. Moreover, we obtained our results by mostly applying open source packages, making it easy to duplicate our results. We first describe in detail how we developed our CRF-based tagger. We designed a very high dimensional feature set that includes most of information that may be relevant. We trained bi-directional CRF models with the same set of features, one applies forward parsing and the other backward, and integrated two models based on the output scores and dictionary filtering. One of the most prominent factors that contributes to the good performance of our tagger is the integration of an additional backward parsing model. However, from the definition of CRF, it appears that a CRF model is symmetric and bi-directional parsing models will produce the same results. We show that due to different feature settings, a CRF model can be asymmetric and the feature setting for our tagger in BioCreative 2 not only produces different results but also gives backward parsing models slight but constant advantage over forward parsing model. To fully explore the potential of integrating bi-directional parsing models, we applied different asymmetric feature settings to generate many bi-directional parsing models and integrate them based on the output scores. Experimental results show that this integrated model can achieve even higher F-score solely based on the training corpus for gene mention tagging. Data sets, programs and an on-line service of our gene mention tagger can be accessed at http://aiia.iis.sinica.edu.tw/biocreative2.htm.

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

PubMed

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.

The association of pain and fear of movement/reinjury with function during anterior cruciate ligament reconstruction rehabilitation.

PubMed

Chmielewski, Terese L; Jones, Debi; Day, Tim; Tillman, Susan M; Lentz, Trevor A; George, Steven Z

2008-12-01

Cross-sectional. To measure fear of movement/reinjury levels and determine the association with function at different timeframes during anterior cruciate ligament (ACL) reconstruction rehabilitation. We hypothesized that fear of movement/reinjury would decrease during rehabilitation and be inversely related with function. Fear of movement/reinjury can prevent return to sports after ACL reconstruction, but it has not been studied during rehabilitation. Demographic data and responses on the shortened version of Tampa Scale for Kinesiophobia (TSK-11), 8-Item Short-Form Health Survey (SF-8), and International Knee Documentation Committee (IKDC) subjective form were extracted from a clinical database for 97 patients in the first year after ACL reconstruction. Three groups were formed: group 1, less than or equal to 90 days; group 2, 91 to 180 days; group 3: 181 to 372 days post-ACL reconstruction. Group differences in TSK-11 score, SF-8 bodily pain rating, and IKDC scores were determined. Hierarchical linear regression models were created for each group, with IKDC score as the dependent variable and demographic factors, SF-8 bodily pain rating, and TSK-11 score as independent variables. TSK-11 score was higher in group 1 than in group 3 (P < .05). Across the groups, SF-8 bodily pain rating decreased (P < .001) and IKDC score increased (P < .001). SF-8 bodily pain rating was a significant factor in the regression model for all groups, whereas TSK-11 score only contributed to the regression model in group 3 (partial correlation, -0.529). Pain was consistently associated with function across the timeframes studied. Fear of movement/reinjury levels appear to decrease during ACL reconstruction rehabilitation and are associated with function in the timeframe when patients return to sports. Prognosis, level 4.

PACE Continuous Innovation Indicators—a novel tool to measure progress in cancer treatments

PubMed Central

Paddock, Silvia; Brum, Lauren; Sorrow, Kathleen; Thomas, Samuel; Spence, Susan; Maulbecker-Armstrong, Catharina; Goodman, Clifford; Peake, Michael; McVie, Gordon; Geipel, Gary; Li, Rose

2015-01-01

Concerns about rising health care costs and the often incremental nature of improvements in health outcomes continue to fuel intense debates about ‘progress’ and ‘value’ in cancer research. In times of tightening fiscal constraints, it is increasingly important for patients and their representatives to define what constitutes ’value’ to them. It is clear that diverse stakeholders have different priorities. Harmonisation of values may be neither possible nor desirable. Stakeholders lack tools to visualise or otherwise express these differences and to track progress in cancer treatments based on variable sets of values. The Patient Access to Cancer care Excellence (PACE) Continuous Innovation Indicators are novel, scientifically rigorous progress trackers that employ a three-step process to quantify progress in cancer treatments: 1) mine the literature to determine the strength of the evidence supporting each treatment; 2) allow users to weight the analysis according to their priorities and values; and 3) calculate Evidence Scores (E-Scores), a novel measure to track progress, based on the strength of the evidence weighted by the assigned value. We herein introduce a novel, flexible value model, show how the values from the model can be used to weight the evidence from the scientific literature to obtain E-Scores, and illustrate how assigning different values to new treatments influences the E-Scores. The Indicators allow users to learn how differing values lead to differing assessments of progress in cancer research and to check whether current incentives for innovation are aligned with their value model. By comparing E-Scores generated by this tool, users are able to visualise the relative pace of innovation across areas of cancer research and how stepwise innovation can contribute to substantial progress against cancer over time. Learning from experience and mapping current unmet needs will help to support a broad audience of stakeholders in their efforts to accelerate and maximise progress against cancer. PMID:25624879

PACE Continuous Innovation Indicators-a novel tool to measure progress in cancer treatments.

PubMed

Paddock, Silvia; Brum, Lauren; Sorrow, Kathleen; Thomas, Samuel; Spence, Susan; Maulbecker-Armstrong, Catharina; Goodman, Clifford; Peake, Michael; McVie, Gordon; Geipel, Gary; Li, Rose

2015-01-01

Concerns about rising health care costs and the often incremental nature of improvements in health outcomes continue to fuel intense debates about 'progress' and 'value' in cancer research. In times of tightening fiscal constraints, it is increasingly important for patients and their representatives to define what constitutes 'value' to them. It is clear that diverse stakeholders have different priorities. Harmonisation of values may be neither possible nor desirable. Stakeholders lack tools to visualise or otherwise express these differences and to track progress in cancer treatments based on variable sets of values. The Patient Access to Cancer care Excellence (PACE) Continuous Innovation Indicators are novel, scientifically rigorous progress trackers that employ a three-step process to quantify progress in cancer treatments: 1) mine the literature to determine the strength of the evidence supporting each treatment; 2) allow users to weight the analysis according to their priorities and values; and 3) calculate Evidence Scores (E-Scores), a novel measure to track progress, based on the strength of the evidence weighted by the assigned value. We herein introduce a novel, flexible value model, show how the values from the model can be used to weight the evidence from the scientific literature to obtain E-Scores, and illustrate how assigning different values to new treatments influences the E-Scores. The Indicators allow users to learn how differing values lead to differing assessments of progress in cancer research and to check whether current incentives for innovation are aligned with their value model. By comparing E-Scores generated by this tool, users are able to visualise the relative pace of innovation across areas of cancer research and how stepwise innovation can contribute to substantial progress against cancer over time. Learning from experience and mapping current unmet needs will help to support a broad audience of stakeholders in their efforts to accelerate and maximise progress against cancer.

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling.

PubMed

Odegård, J; Jensen, J; Madsen, P; Gianola, D; Klemetsdal, G; Heringstad, B

2003-11-01

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

The Importance of Non-accessible Crosslinks and Solvent Accessible Surface Distance in Modeling Proteins with Restraints From Crosslinking Mass Spectrometry*

PubMed Central

Bullock, Joshua Matthew Allen; Schwab, Jannik; Thalassinos, Konstantinos; Topf, Maya

2016-01-01

Crosslinking mass spectrometry (XL-MS) is becoming an increasingly popular technique for modeling protein monomers and complexes. The distance restraints garnered from these experiments can be used alone or as part of an integrative modeling approach, incorporating data from many sources. However, modeling practices are varied and the difference in their usefulness is not clear. Here, we develop a new scoring procedure for models based on crosslink data—Matched and Nonaccessible Crosslink score (MNXL). We compare its performance with that of other commonly-used scoring functions (Number of Violations and Sum of Violation Distances) on a benchmark of 14 protein domains, each with 300 corresponding models (at various levels of quality) and associated, previously published, experimental crosslinks (XLdb). The distances between crosslinked lysines are calculated either as Euclidean distances or Solvent Accessible Surface Distances (SASD) using a newly-developed method (Jwalk). MNXL takes into account whether a crosslink is nonaccessible, i.e. an experimentally observed crosslink has no corresponding SASD in a model due to buried lysines. This metric alone is shown to have a significant impact on modeling performance and is a concept that is not considered at present if only Euclidean distances are used. Additionally, a comparison between modeling with SASD or Euclidean distance shows that SASD is superior, even when factoring out the effect of the nonaccessible crosslinks. Our benchmarking also shows that MNXL outperforms the other tested scoring functions in terms of precision and correlation to Cα-RMSD from the crystal structure. We finally test the MNXL at different levels of crosslink recovery (i.e. the percentage of crosslinks experimentally observed out of all theoretical ones) and set a target recovery of ∼20% after which the performance plateaus. PMID:27150526

Metric and structural equivalence of core cognitive abilities measured with the Wechsler Adult Intelligence Scale-III in the United States and Australia.

PubMed

Bowden, Stephen C; Lissner, Dianne; McCarthy, Kerri A L; Weiss, Lawrence G; Holdnack, James A

2007-10-01

Equivalence of the psychological model underlying Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) scores obtained in the United States and Australia was examined in this study. Examination of metric invariance involves testing the hypothesis that all components of the measurement model relating observed scores to latent variables are numerically equal in different samples. The assumption of metric invariance is necessary for interpretation of scores derived from research studies that seek to generalize patterns of convergent and divergent validity and patterns of deficit or disability. An Australian community volunteer sample was compared to the US standardization data. A pattern of strict metric invariance was observed across samples. In addition, when the effects of different demographic characteristics of the US and Australian samples were included, structural parameters reflecting values of the latent cognitive variables were found not to differ. These results provide important evidence for the equivalence of measurement of core cognitive abilities with the WAIS-III and suggest that latent cognitive abilities in the US and Australia do not differ.

Do Hassles and Uplifts Change with Age? Longitudinal Findings from the VA Normative Aging Study

PubMed Central

Aldwin, Carolyn M.; Jeong, Yu-Jin; Igarashi, Heidi; Spiro, Avron

2014-01-01

To examine emotion regulation in later life, we contrasted the modified hedonic treadmill theory with developmental theories, using hassles and uplifts to assess emotion regulation in context. The sample was 1,315 men from the VA Normative Aging Study aged 53 to 85 years, who completed 3,894 observations between 1989 and 2004. We computed three scores for both hassles and uplifts: intensity (ratings reflecting appraisal processes), exposure (count), and summary (total) scores. Growth curves over age showed marked differences in trajectory patterns for intensity and exposure scores. Although exposure to hassles and uplifts decreased in later life, intensity scores increased. Growth based modelling showed individual differences in patterns of hassles and uplifts intensity and exposure, with relative stability in uplifts intensity, normative non-linear changes in hassles intensity, and complex patterns of individual differences in exposure for both hassles and uplifts. Analyses with the summary scores showed that emotion regulation in later life is a function of both developmental change and contextual exposure, with different patterns emerging for hassles and uplifts. Thus, support was found for both hedonic treadmill and developmental change theories, reflecting different aspects of emotion regulation in late life. PMID:24660796

Do hassles and uplifts change with age? Longitudinal findings from the VA normative aging study.

PubMed

Aldwin, Carolyn M; Jeong, Yu-Jin; Igarashi, Heidi; Spiro, Avron

2014-03-01

To examine emotion regulation in later life, we contrasted the modified hedonic treadmill theory with developmental theories, using hassles and uplifts to assess emotion regulation in context. The sample was 1,315 men from the VA Normative Aging Study aged 53 to 85 years, who completed 3,894 observations between 1989 and 2004. We computed 3 scores for both hassles and uplifts: intensity (ratings reflecting appraisal processes), exposure (count), and summary (total) scores. Growth curves over age showed marked differences in trajectory patterns for intensity and exposure scores. Although exposure to hassles and uplifts decreased in later life, intensity scores increased. Group-based modeling showed individual differences in patterns of hassles and uplifts intensity and exposure, with relative stability in uplifts intensity, normative nonlinear changes in hassles intensity, and complex patterns of individual differences in exposure for both hassles and uplifts. Analyses with the summary scores showed that emotion regulation in later life is a function of both developmental change and contextual exposure, with different patterns emerging for hassles and uplifts. Thus, support was found for both hedonic treadmill and developmental change theories, reflecting different aspects of emotion regulation in late life. (c) 2014 APA, all rights reserved.

Influence of credit scoring on the dynamics of Markov chain

NASA Astrophysics Data System (ADS)

Galina, Timofeeva

2015-11-01

Markov processes are widely used to model the dynamics of a credit portfolio and forecast the portfolio risk and profitability. In the Markov chain model the loan portfolio is divided into several groups with different quality, which determined by presence of indebtedness and its terms. It is proposed that dynamics of portfolio shares is described by a multistage controlled system. The article outlines mathematical formalization of controls which reflect the actions of the bank's management in order to improve the loan portfolio quality. The most important control is the organization of approval procedure of loan applications. The credit scoring is studied as a control affecting to the dynamic system. Different formalizations of "good" and "bad" consumers are proposed in connection with the Markov chain model.

The effects of modeling instruction on high school physics academic achievement

NASA Astrophysics Data System (ADS)

Wright, Tiffanie L.

The purpose of this study was to explore whether Modeling Instruction, compared to traditional lecturing, is an effective instructional method to promote academic achievement in selected high school physics classes at a rural middle Tennessee high school. This study used an ex post facto , quasi-experimental research methodology. The independent variables in this study were the instructional methods of teaching. The treatment variable was Modeling Instruction and the control variable was traditional lecture instruction. The Treatment Group consisted of participants in Physical World Concepts who received Modeling Instruction. The Control Group consisted of participants in Physical Science who received traditional lecture instruction. The dependent variable was gains scores on the Force Concepts Inventory (FCI). The participants for this study were 133 students each in both the Treatment and Control Groups (n = 266), who attended a public, high school in rural middle Tennessee. The participants were administered the Force Concepts Inventory (FCI) prior to being taught the mechanics of physics. The FCI data were entered into the computer-based Statistical Package for the Social Science (SPSS). Two independent samples t-tests were conducted to answer the research questions. There was a statistically significant difference between the treatment and control groups concerning the instructional method. Modeling Instructional methods were found to be effective in increasing the academic achievement of students in high school physics. There was no statistically significant difference between FCI gains scores for gender. Gender was found to have no effect on the academic achievement of students in high school physics classes. However, even though there was not a statistically significant difference, female students' gains scores were higher than male students' gains scores when Modeling Instructional methods of teaching were used. Based on these findings, it is recommended that high school science teachers should use Modeling Instructional methods of teaching daily in their classrooms. A recommendation for further research is to expand the Modeling Instructional methods of teaching into different content areas, (i.e., reading and language arts) to explore academic achievement gains.

BACHSCORE. A tool for evaluating efficiently and reliably the quality of large sets of protein structures

NASA Astrophysics Data System (ADS)

Sarti, E.; Zamuner, S.; Cossio, P.; Laio, A.; Seno, F.; Trovato, A.

2013-12-01

In protein structure prediction it is of crucial importance, especially at the refinement stage, to score efficiently large sets of models by selecting the ones that are closest to the native state. We here present a new computational tool, BACHSCORE, that allows its users to rank different structural models of the same protein according to their quality, evaluated by using the BACH++ (Bayesian Analysis Conformation Hunt) scoring function. The original BACH statistical potential was already shown to discriminate with very good reliability the protein native state in large sets of misfolded models of the same protein. BACH++ features a novel upgrade in the solvation potential of the scoring function, now computed by adapting the LCPO (Linear Combination of Pairwise Orbitals) algorithm. This change further enhances the already good performance of the scoring function. BACHSCORE can be accessed directly through the web server: bachserver.pd.infn.it. Catalogue identifier: AEQD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQD_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 130159 No. of bytes in distributed program, including test data, etc.: 24 687 455 Distribution format: tar.gz Programming language: C++. Computer: Any computer capable of running an executable produced by a g++ compiler (4.6.3 version). Operating system: Linux, Unix OS-es. RAM: 1 073 741 824 bytes Classification: 3. Nature of problem: Evaluate the quality of a protein structural model, taking into account the possible “a priori” knowledge of a reference primary sequence that may be different from the amino-acid sequence of the model; the native protein structure should be recognized as the best model. Solution method: The contact potential scores the occurrence of any given type of residue pair in 5 possible contact classes (α-helical contact, parallel β-sheet contact, anti-parallel β-sheet contact, side-chain contact, no contact). The solvation potential scores the occurrence of any residue type in 2 possible environments: buried and solvent exposed. Residue environment is assigned by adapting the LCPO algorithm. Residues present in the reference primary sequence and not present in the model structure contribute to the model score as solvent exposed and as non contacting all other residues. Restrictions: Input format file according to the Protein Data Bank standard Additional comments: Parameter values used in the scoring function can be found in the file /folder-to-bachscore/BACH/examples/bach_std.par. Running time: Roughly one minute to score one hundred structures on a desktop PC, depending on their size.

Rasch analysis of the UK Functional Assessment Measure in patients with complex disability after stroke.

PubMed

Medvedev, Oleg N; Turner-Stokes, Lynne; Ashford, Stephen; Siegert, Richard J

2018-02-28

To determine whether the UK Functional Assessment Measure (UK FIM+FAM) fits the Rasch model in stroke patients with complex disability and, if so, to derive a conversion table of Rasch-transformed interval level scores. The sample included a UK multicentre cohort of 1,318 patients admitted for specialist rehabilitation following a stroke. Rasch analysis was conducted for the 30-item scale including 3 domains of items measuring physical, communication and psychosocial functions. The fit of items to the Rasch model was examined using 3 different analytical approaches referred to as "pathways". The best fit was achieved in the pathway where responses from motor, communication and psychosocial domains were summarized into 3 super-items and where some items were split because of differential item functioning (DIF) relative to left and right hemisphere location (χ2 (10) = 14.48, p = 0.15). Re-scoring of items showing disordered thresholds did not significantly improve the overall model fit. The UK FIM+FAM with domain super-items satisfies expectations of the unidimensional Rasch model without the need for re-scoring. A conversion table was produced to convert the total scale scores into interval-level data based on person estimates of the Rasch model. The clinical benefits of interval-transformed scores require further evaluation.

Large unbalanced credit scoring using Lasso-logistic regression ensemble.

PubMed

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data.

Outcomes of different Class II treatments : Comparisons using the American Board of Orthodontics Model Grading System.

PubMed

Akinci Cansunar, Hatice; Uysal, Tancan

2016-07-01

The aim of this study was to evaluate the clinical outcomes of three different Class II treatment modalities followed by fixed orthodontic therapy, using the American Board of Orthodontics Model Grading System (ABO-MGS). As a retrospective study, files of patients treated at postgraduate orthodontic  clinics in different cities in Turkey was randomly selected. From 1684 posttreatment records, 669 patients were divided into three groups: 269 patients treated with extraction of two upper premolars, 198 patients treated with cervical headgear, and 202 patients treated with functional appliances. All the cases were evaluated by one researcher using ABO-MGS. The χ (2), Z test, and multivariate analysis of variance were used for statistical evaluation (p < 0.05). No significant differences were found among the groups in buccolingual inclination, overjet, occlusal relationship, and root angulation. However, there were significant differences in alignment, marginal ridge height, occlusal contact, interproximal contact measurements, and overall MGS average scores. The mean treatment time between the extraction and functional appliance groups was significantly different (p = 0.017). According to total ABO-MGS scores, headgear treatment had better results than functional appliances. The headgear group had better tooth alignment than the extraction group. Headgear treatment resulted in better occlusal contacts than the functional appliances and had lower average scores for interproximal contact measurements. Functional appliances had the worst average scores for marginal ridge height. Finally, the functional appliance group had the longest treatment times.

Development of Risk Score for Predicting 3-Year Incidence of Type 2 Diabetes: Japan Epidemiology Collaboration on Occupational Health Study

PubMed Central

Nanri, Akiko; Nakagawa, Tohru; Kuwahara, Keisuke; Yamamoto, Shuichiro; Honda, Toru; Okazaki, Hiroko; Uehara, Akihiko; Yamamoto, Makoto; Miyamoto, Toshiaki; Kochi, Takeshi; Eguchi, Masafumi; Murakami, Taizo; Shimizu, Chii; Shimizu, Makiko; Tomita, Kentaro; Nagahama, Satsue; Imai, Teppei; Nishihara, Akiko; Sasaki, Naoko; Hori, Ai; Sakamoto, Nobuaki; Nishiura, Chihiro; Totsuzaki, Takafumi; Kato, Noritada; Fukasawa, Kenji; Huanhuan, Hu; Akter, Shamima; Kurotani, Kayo; Kabe, Isamu; Mizoue, Tetsuya; Sone, Tomofumi; Dohi, Seitaro

2015-01-01

Objective Risk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population. Methods Participants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008–2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥126 mg/dl, random plasma glucose ≥200 mg/dl, glycated hemoglobin (HbA1c) ≥6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort. Results The area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703–0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883–0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715–0.753) and 0.882 (0.868–0.895), respectively. Participants with a non-invasive score of ≥15 and invasive score of ≥19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years. Conclusions The simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c. PMID:26558900

Development of Risk Score for Predicting 3-Year Incidence of Type 2 Diabetes: Japan Epidemiology Collaboration on Occupational Health Study.

PubMed

Nanri, Akiko; Nakagawa, Tohru; Kuwahara, Keisuke; Yamamoto, Shuichiro; Honda, Toru; Okazaki, Hiroko; Uehara, Akihiko; Yamamoto, Makoto; Miyamoto, Toshiaki; Kochi, Takeshi; Eguchi, Masafumi; Murakami, Taizo; Shimizu, Chii; Shimizu, Makiko; Tomita, Kentaro; Nagahama, Satsue; Imai, Teppei; Nishihara, Akiko; Sasaki, Naoko; Hori, Ai; Sakamoto, Nobuaki; Nishiura, Chihiro; Totsuzaki, Takafumi; Kato, Noritada; Fukasawa, Kenji; Huanhuan, Hu; Akter, Shamima; Kurotani, Kayo; Kabe, Isamu; Mizoue, Tetsuya; Sone, Tomofumi; Dohi, Seitaro

2015-01-01

Risk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population. Participants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008-2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dl, random plasma glucose ≥ 200 mg/dl, glycated hemoglobin (HbA1c) ≥ 6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort. The area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703-0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883-0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715-0.753) and 0.882 (0.868-0.895), respectively. Participants with a non-invasive score of ≥ 15 and invasive score of ≥ 19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years. The simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c.

A new algorithm to build bridges between two patient-reported health outcome instruments: the MOS SF-36® and the VR-12 Health Survey.

PubMed

Selim, Alfredo; Rogers, William; Qian, Shirley; Rothendler, James A; Kent, Erin E; Kazis, Lewis E

2018-04-19

To develop bridging algorithms to score the Veterans Rand-12 (VR-12) scales for comparability to those of the SF-36® for facilitating multi-cohort studies using data from the National Cancer Institute Surveillance, Epidemiology, and End Results Program (SEER) linked to Medicare Health Outcomes Survey (MHOS), and to provide a model for minimizing non-statistical error in pooled analyses stemming from changes to survey instruments over time. Observational study of MHOS cohorts 1-12 (1998-2011). We modeled 2-year follow-up SF-36 scale scores from cohorts 1-6 based on baseline SF-36 scores, age, and gender, yielding 100 clusters using Classification and Regression Trees. Within each cluster, we averaged follow-up SF-36 scores. Using the same cluster specifications, expected follow-up SF-36 scores, based on cohorts 1-6, were computed for cohorts 7-8 (where the VR-12 was the follow-up survey). We created a new criterion validity measure, termed "extensibility," calculated from the square root of the mean square difference between expected SF-36 scale averages and observed VR-12 item score from cohorts 7-8, weighted by cluster size. VR-12 items were rescored to minimize this quantity. Extensibility of rescored VR-12 items and scales was considerably improved from the "simple" scoring method for comparability to the SF-36 scales. The algorithms are appropriate across a wide range of potential subsamples within the MHOS and provide robust application for future studies that span the SF-36 and VR-12 eras. It is possible that these surveys in a different setting outside the MHOS, especially in younger age groups, could produce somewhat different results.

Predicting survival of patients with idiopathic pulmonary fibrosis using GAP score: a nationwide cohort study.

PubMed

Lee, Sang Hoon; Kim, Song Yee; Kim, Dong Soon; Kim, Young Whan; Chung, Man Pyo; Uh, Soo Taek; Park, Choon Sik; Jeong, Sung Hwan; Park, Yong Bum; Lee, Hong Lyeol; Shin, Jong Wook; Lee, Eun Joo; Lee, Jin Hwa; Jegal, Yangin; Lee, Hyun Kyung; Kim, Yong Hyun; Song, Jin Woo; Park, Sung Woo; Park, Moo Suk

2016-10-18

The clinical course of idiopathic pulmonary fibrosis (IPF) varies widely. Although the GAP model is useful for predicting mortality, survivals have not yet been validated for each GAP score. We aimed to elucidate how prognosis is related to GAP score and GAP stage in IPF patients. The Korean Interstitial Lung Disease Study Group conducted a national survey to evaluate various characteristics in IPF patients from 2003 to 2007. Patients were diagnosed according to the 2002 criteria of the ATS/ERS. We enrolled 1,685 patients with IPF; 1,262 had undergone DL CO measurement. Patients were stratified based on GAP score (0-7): GAP score Group 0 (n = 26), Group 1 (n = 150), Group 2 (n = 208), Group 3 (n = 376), Group 4 (n = 317), Group 5 (n = 138), Group 6 (n = 39), and Group 7 (n = 8). Higher GAP score and GAP stage were associated with a poorer prognosis (p < 0.001, respectively). Survival time in Group 3 was lower than those in Groups 1 and 2 (p = 0.043 and p = 0.039, respectively), and higher than those in groups 4, 5, and 6 (p = 0.043, p = 0.032, and p = 0.003, respectively). Gender, age, and DL CO (%) differed significantly between Groups 2 and 3. All four variables in the GAP model differed significantly between Groups 3 and 4. The GAP system showed significant predictive ability for mortality in IPF patients. However, prognosis in IPF patients with a GAP score of 3 were significantly different from those in the other stage I groups and stage II groups of Asian patients.

Peripheral T cell lymphoma, not otherwise specified (PTCL-NOS). A new prognostic model developed by the International T cell Project Network.

PubMed

Federico, Massimo; Bellei, Monica; Marcheselli, Luigi; Schwartz, Marc; Manni, Martina; Tarantino, Vittoria; Pileri, Stefano; Ko, Young-Hyeh; Cabrera, Maria E; Horwitz, Steven; Kim, Won S; Shustov, Andrei; Foss, Francine M; Nagler, Arnon; Carson, Kenneth; Pinter-Brown, Lauren C; Montoto, Silvia; Spina, Michele; Feldman, Tatyana A; Lechowicz, Mary J; Smith, Sonali M; Lansigan, Frederick; Gabus, Raul; Vose, Julie M; Advani, Ranjana H

2018-06-01

Different models to investigate the prognosis of peripheral T cell lymphoma not otherwise specified (PTCL-NOS) have been developed by means of retrospective analyses. Here we report on a new model designed on data from the prospective T Cell Project. Twelve covariates collected by the T Cell Project were analysed and a new model (T cell score), based on four covariates (serum albumin, performance status, stage and absolute neutrophil count) that maintained their prognostic value in multiple Cox proportional hazards regression analysis was proposed. Among patients registered in the T Cell Project, 311 PTCL-NOS were retained for study. At a median follow-up of 46 months, the median overall survival (OS) and progression-free survival (PFS) was 20 and 10 months, respectively. Three groups were identified at low risk (LR, 48 patients, 15%, score 0), intermediate risk (IR, 189 patients, 61%, score 1-2), and high risk (HiR, 74 patients, 24%, score 3-4), having a 3-year OS of 76% [95% confidence interval 61-88], 43% [35-51], and 11% [4-21], respectively (P < 0·001). Comparing the performance of the T cell score on OS to that of each of the previously developed models, it emerged that the new score had the best discriminant power. The new T cell score, based on clinical variables, identifies a group with very unfavourable outcomes. © 2018 The Authors. British Journal of Haematology published by John Wiley & Sons Ltd.

Performance of machine-learning scoring functions in structure-based virtual screening.

PubMed

Wójcikowski, Maciej; Ballester, Pedro J; Siedlecki, Pawel

2017-04-25

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and -0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary).

Review of Issues About Classical Change Scores: A Multilevel Modeling Perspective on Some Enduring Beliefs.

PubMed

Gu, Zhengguo; Emons, Wilco H M; Sijtsma, Klaas

2018-04-30

Change scores obtained in pretest-posttest designs are important for evaluating treatment effectiveness and for assessing change of individual test scores in psychological research. However, over the years the use of change scores has raised much controversy. In this article, from a multilevel perspective, we provide a structured treatise on several persistent negative beliefs about change scores and show that these beliefs originated from the confounding of the effects of within-person change on change-score reliability and between-person change differences. We argue that psychometric properties of change scores, such as reliability and measurement precision, should be treated at suitable levels within a multilevel framework. We show that, if examined at the suitable levels with such a framework, the negative beliefs about change scores can be renounced convincingly. Finally, we summarize the conclusions about change scores to dispel the myths and to promote the potential and practical usefulness of change scores.

Adaptive Modulation Approach for Robust MPEG-4 AAC Encoded Audio Transmission

DTIC Science & Technology

2011-11-01

as shown in Table 1. Table 1 specifies the perceptual interpretation of the ODG. Subjective Difference Grade ( SDG ) = Grade Signal under test... SDG using human hearing and cognitive model [8], [9]. Freely available PEAQ basic model, “PQevalAudio,” is used in this paper which is available as...PEAQ-ODG Score [6] Impairment ITU-R Five Grade Impairment Scale SDG /PEAQ-ODG Score Imperceptible 5.00 0.00 Perceptible, but not Annoying 4.00

Psychopathy, intelligence and conviction history.

PubMed

Heinzen, Hanna; Köhler, Denis; Godt, Nils; Geiger, Friedemann; Huchzermeier, Christian

2011-01-01

The current study examined the relationship between psychopathy, intelligence and two variables describing the conviction history (length of conviction and number of prior convictions). It was hypothesized that psychopathy factors (interpersonal and antisocial factors assuming a 2-factor model or interpersonal, affective, lifestyle and antisocial factors assuming a 4-factor model) would be related in different ways to IQ scores, length of conviction and number of prior convictions. Psychopathy and IQ were assessed using the PCL:SV and the CFT 20-R respectively. Results indicated no association between interpersonal psychopathy features (Factor 1, two-factor model), IQ and the number of prior convictions but a positive association between Factor 1 and the length of conviction. Antisocial features (Factor 2, two-factor model) were negatively related to IQ and the length of conviction and positively related to the number of prior convictions. Results were further differentiated for the four-factor model of psychopathy. The relationship between IQ and psychopathy features was further assessed by statistically isolating the effects of the two factors of psychopathy. It was found that individuals scoring high on interpersonal features of psychopathy are more intelligent than those scoring high on antisocial features, but less intelligent than those scoring low on both psychopathy features. The results underpin the importance of allocating psychopathic individuals to subgroups on the basis of personality characteristics and criminological features. These subgroups may identify different types of offenders and may be highly valuable for defining treatment needs and risk of future violence. Copyright © 2011 Elsevier Ltd. All rights reserved.

Emotion and the humors: scoring and classifying major characters from Shakespeare's comedies on the basis of their language.

PubMed

Whissell, Cynthia

2010-06-01

The theory of humors, which was the prevalent theory of affect in Shakespeare's day, was used to explain both states (moods, emotions) and traits (personalities). This article reports humoral scores appropriate to the major characters of Shakespeare's comedies. The Dictionary of Affect in Language was used to score all words (N = 180,243) spoken by 105 major characters in 13 comedies in terms of their emotional undertones. These were translated into humoral scores. Translation was possible because emotional undertones, humor, and personality (e.g., Eysenck's model) are defined by various axes in the same two-dimensional space. Humoral scores differed for different types of characters, e.g., Shakespeare's lovers used more Sanguine language and his clowns more Melancholy language than other characters. A study of Kate and Petruchio from The Taming of the Shrew demonstrated state-like changes in humor for characters as the play unfolded.

Development and Assessment of the Multiple Mini-Interview in a School of Pharmacy Admissions Model

PubMed Central

McLaughlin, Jacqueline E.; Singer, David; Lewis, Margaret; Dinkins, Melissa M.

2015-01-01

Objective. To describe the development, implementation, and evaluation of the multiple mini-interview (MMI) within a doctor of pharmacy (PharmD) admissions model. Methods. Demographic data and academic indicators were collected for all candidates who participated in Candidates’ Day (n=253), along with the score for each MMI station criteria (7 stations). A survey was administered to all candidates who completed the MMI, and another survey was administered to all interviewers to examine perceptions of the MMI. Results. Analyses suggest that MMI stations assessed different attributes as designed, with Cronbach alpha for each station ranging from 0.90 to 0.95. All correlations between MMI station scores and academic indicators were negligible. No significant differences in average station scores were found based on age, gender, or race. Conclusion. This study provides additional support for the use of the MMI as an admissions tool in pharmacy education. PMID:26089562

Feasibility of dynamic risk prediction for hepatocellular carcinoma development in patients with chronic hepatitis B.

PubMed

Jeon, Mi Young; Lee, Hye Won; Kim, Seung Up; Kim, Beom Kyung; Park, Jun Yong; Kim, Do Young; Han, Kwang-Hyub; Ahn, Sang Hoon

2018-04-01

Several risk prediction models for hepatocellular carcinoma (HCC) development are available. We explored whether the use of risk prediction models can dynamically predict HCC development at different time points in chronic hepatitis B (CHB) patients. Between 2006 and 2014, 1397 CHB patients were recruited. All patients underwent serial transient elastography at intervals of >6 months. The median age of this study population (931 males and 466 females) was 49.0 years. The median CU-HCC, REACH-B, LSM-HCC and mREACH-B score at enrolment were 4.0, 9.0, 10.0 and 8.0 respectively. During the follow-up period (median, 68.0 months), 87 (6.2%) patients developed HCC. All risk prediction models were successful in predicting HCC development at both the first liver stiffness (LS) measurement (hazard ratio [HR] = 1.067-1.467 in the subgroup without antiviral therapy [AVT] and 1.096-1.458 in the subgroup with AVT) and second LS measurement (HR = 1.125-1.448 in the subgroup without AVT and 1.087-1.249 in the subgroup with AVT). In contrast, neither the absolute nor percentage change in the scores from the risk prediction models predicted HCC development (all P > .05). The mREACH-B score performed similarly or significantly better than did the other scores (AUROCs at 5 years, 0.694-0.862 vs 0.537-0.875). Dynamic prediction of HCC development at different time points was achieved using four risk prediction models, but not using the changes in the absolute and percentage values between two time points. The mREACH-B score was the most appropriate prediction model of HCC development among four prediction models. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Longitudinal associations of sleep curtailment with metabolic risk in mid-childhood.

PubMed

Cespedes, Elizabeth M; Rifas-Shiman, Sheryl L; Redline, Susan; Gillman, Matthew W; Peña, Michelle-Marie; Taveras, Elsie M

2014-12-01

To examine associations of chronic insufficient sleep with mid-childhood cardiometabolic health. At 6 months and yearly from 1 to 7 years, mothers participating in the Project Viva cohort reported children's 24-h sleep duration. The main exposure was a sleep curtailment score, ranging from 0 (maximal curtailment) to 13 (never having curtailed sleep). The main outcome was a mid-childhood metabolic risk score, derived as the mean of five sex- and cohort-specific z scores for waist circumference, systolic blood pressure, HDL cholesterol (scaled inversely), and log-transformed triglycerides and HOMA-IR; higher scores indicate higher risk. The mean (SD) sleep score was 10.0 (2.8); 5.1% scored 0-4, 13.9% scored 5-7, 14.1% scored 8-9, 28.7% scored 10-11, and 38.3% scored 12-13. Mean (SD, range) metabolic risk score was -0.03 (0.6, -1.8 to 2.6). In multivariable models, the metabolic risk score difference for children with most versus least curtailed sleep was 0.29 units (95% confidence interval [CI]: 0.02, 0.57). Further adjustment for mid-childhood BMI z score attenuated this difference to 0.08 units (95% CI: -0.14, 0.30). Chronic insufficient sleep from infancy to school-age was associated with higher mid-childhood metabolic risk. This association was explained by sleep duration's influence on mid-childhood adiposity. © 2014 The Obesity Society.

Scoring annual earthquake predictions in China

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Jiang, Changsheng

2012-02-01

The Annual Consultation Meeting on Earthquake Tendency in China is held by the China Earthquake Administration (CEA) in order to provide one-year earthquake predictions over most China. In these predictions, regions of concern are denoted together with the corresponding magnitude range of the largest earthquake expected during the next year. Evaluating the performance of these earthquake predictions is rather difficult, especially for regions that are of no concern, because they are made on arbitrary regions with flexible magnitude ranges. In the present study, the gambling score is used to evaluate the performance of these earthquake predictions. Based on a reference model, this scoring method rewards successful predictions and penalizes failures according to the risk (probability of being failure) that the predictors have taken. Using the Poisson model, which is spatially inhomogeneous and temporally stationary, with the Gutenberg-Richter law for earthquake magnitudes as the reference model, we evaluate the CEA predictions based on 1) a partial score for evaluating whether issuing the alarmed regions is based on information that differs from the reference model (knowledge of average seismicity level) and 2) a complete score that evaluates whether the overall performance of the prediction is better than the reference model. The predictions made by the Annual Consultation Meetings on Earthquake Tendency from 1990 to 2003 are found to include significant precursory information, but the overall performance is close to that of the reference model.

Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study

PubMed Central

Lassale, Camille; Gunter, Marc J.; Romaguera, Dora; Peelen, Linda M.; Van der Schouw, Yvonne T.; Beulens, Joline W. J.; Freisling, Heinz; Muller, David C.; Ferrari, Pietro; Huybrechts, Inge; Fagherazzi, Guy; Boutron-Ruault, Marie-Christine; Affret, Aurélie; Overvad, Kim; Dahm, Christina C.; Olsen, Anja; Roswall, Nina; Tsilidis, Konstantinos K.; Katzke, Verena A.; Kühn, Tilman; Buijsse, Brian; Quirós, José-Ramón; Sánchez-Cantalejo, Emilio; Etxezarreta, Nerea; Huerta, José María; Barricarte, Aurelio; Bonet, Catalina; Khaw, Kay-Tee; Key, Timothy J.; Trichopoulou, Antonia; Bamia, Christina; Lagiou, Pagona; Palli, Domenico; Agnoli, Claudia; Tumino, Rosario; Fasanelli, Francesca; Panico, Salvatore; Bueno-de-Mesquita, H. Bas; Boer, Jolanda M. A.; Sonestedt, Emily; Nilsson, Lena Maria; Renström, Frida; Weiderpass, Elisabete; Skeie, Guri; Lund, Eiliv; Moons, Karel G. M.; Riboli, Elio; Tzoulaki, Ioanna

2016-01-01

Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI) in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre) was 0.75 (0.72–0.79) to 0.88 (0.84–0.92) for all-cause, 0.76 (0.69–0.83) to 0.84 (0.76–0.92) for CVD and 0.78 (0.73–0.83) to 0.91 (0.85–0.97) for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors. PMID:27409582

The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer.

PubMed

Thakur, Satbir Singh; Li, Haocheng; Chan, Angela M Y; Tudor, Roxana; Bigras, Gilbert; Morris, Don; Enwere, Emeka K; Yang, Hua

2018-01-01

Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates. The Ki67 indices calculated using this method were highly concordant with manual scoring by a pathologist (Pearson's r = 0.909) and between users (Pearson's r = 0.984). We assessed the clinical validity of this method by scoring Ki67 from 328 whole-slide sections of resected early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. All patients had Oncotype DX testing performed (Genomic Health) and available Recurrence Scores. High Ki67 indices correlated significantly with several clinico-pathological correlates, including higher tumor grade (1 versus 3, P<0.001), higher mitotic score (1 versus 3, P<0.001), and lower Allred scores for estrogen and progesterone receptors (P = 0.002, 0.008). High Ki67 indices were also significantly correlated with higher Oncotype DX risk-of-recurrence group (low versus high, P<0.001). Ki67 index was the major contributor to a machine learning model which, when trained solely on clinico-pathological data and Ki67 scores, identified Oncotype DX high- and low-risk patients with 97% accuracy, 98% sensitivity and 80% specificity. Automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy, in a manner that integrates readily into the workflow of a pathology laboratory. Furthermore, automated Ki67 scores contribute significantly to models that predict risk of recurrence in breast cancer.

The effect of time-of-flight and point spread function modeling on 82Rb myocardial perfusion imaging of obese patients.

PubMed

Dasari, Paul K R; Jones, Judson P; Casey, Michael E; Liang, Yuanyuan; Dilsizian, Vasken; Smith, Mark F

2018-06-15

The effect of time-of-flight (TOF) and point spread function (PSF) modeling in image reconstruction has not been well studied for cardiac PET. This study assesses their separate and combined influence on 82 Rb myocardial perfusion imaging in obese patients. Thirty-six obese patients underwent rest-stress 82 Rb cardiac PET. Images were reconstructed with and without TOF and PSF modeling. Perfusion was quantitatively compared using the AHA 17-segment model for patients grouped by BMI, cross-sectional body area in the scanner field of view, gender, and left ventricular myocardial volume. Summed rest scores (SRS), summed stress scores (SSS), and summed difference scores (SDS) were compared. TOF improved polar map visual uniformity and increased septal wall perfusion by up to 10%. This increase was greater for larger patients, more evident for patients grouped by cross-sectional area than by BMI, and more prominent for females. PSF modeling increased perfusion by about 1.5% in all cardiac segments. TOF modeling generally decreased SRS and SSS with significant decreases between 2.4 and 3.0 (P < .05), which could affect risk stratification; SDS remained about the same. With PSF modeling, SRS, SSS, and SDS were largely unchanged. TOF and PSF modeling affect regional and global perfusion, SRS, and SSS. Clinicians should consider these effects and gender-dependent differences when interpreting 82 Rb perfusion studies.

Five Methods for Estimating Angoff Cut Scores with IRT

ERIC Educational Resources Information Center

Wyse, Adam E.

2017-01-01

This article illustrates five different methods for estimating Angoff cut scores using item response theory (IRT) models. These include maximum likelihood (ML), expected a priori (EAP), modal a priori (MAP), and weighted maximum likelihood (WML) estimators, as well as the most commonly used approach based on translating ratings through the test…

Personality Patterns of Physicians in Person-Oriented and Technique-Oriented Specialties

ERIC Educational Resources Information Center

Borges, Nicole J.; Gibson, Denise D.

2005-01-01

This study investigated differences in personality patterns between person-oriented and technique-oriented physicians. It tested an integrative framework by converting the scores on the Personality Research Form (PRF) to the Big-Five factors and built a predictive model of group membership in clinical specialty area. PRF scores from 238 physicians…

Assessing Hourly Precipitation Forecast Skill with the Fractions Skill Score

NASA Astrophysics Data System (ADS)

Zhao, Bin; Zhang, Bo

2018-02-01

Statistical methods for category (yes/no) forecasts, such as the Threat Score, are typically used in the verification of precipitation forecasts. However, these standard methods are affected by the so-called "double-penalty" problem caused by slight displacements in either space or time with respect to the observations. Spatial techniques have recently been developed to help solve this problem. The fractions skill score (FSS), a neighborhood spatial verification method, directly compares the fractional coverage of events in windows surrounding the observations and forecasts. We applied the FSS to hourly precipitation verification by taking hourly forecast products from the GRAPES (Global/Regional Assimilation Prediction System) regional model and quantitative precipitation estimation products from the National Meteorological Information Center of China during July and August 2016, and investigated the difference between these results and those obtained with the traditional category score. We found that the model spin-up period affected the assessment of stability. Systematic errors had an insignificant role in the fraction Brier score and could be ignored. The dispersion of observations followed a diurnal cycle and the standard deviation of the forecast had a similar pattern to the reference maximum of the fraction Brier score. The coefficient of the forecasts and the observations is similar to the FSS; that is, the FSS may be a useful index that can be used to indicate correlation. Compared with the traditional skill score, the FSS has obvious advantages in distinguishing differences in precipitation time series, especially in the assessment of heavy rainfall.

Emotional intelligence and psychological health in a sample of Kuwaiti college students.

PubMed

Alkhadher, Othman

2007-06-01

This summary investigated correlations between emotional intelligence and psychological health amongst 191 Kuwaiti undergraduate students in psychology, 98 men and 93 women (M age=20.6 yr., SD=2.8). There were two measures of emotional intelligence, one based on the ability model, the Arabic Test for Emotional Intelligence, and the other on the mixed model, the Emotional Intelligence Questionnaire. Participants' psychological health was assessed using scales from the Personality Assessment Inventory. A weak relationship between the two types of emotional intelligence was found. A correlation for scores on the Emotional Intelligence Questionnaire with the Personality Assessment Inventory was found but not with those of the Arabic Test for Emotional Intelligence. Regression analysis indicated scores on Managing Emotions and Self-awareness accounted for most of the variance in the association with the Personality Assessment Inventory. Significant sex differences were found only on the Arabic Test for Emotional Intelligence; women scored higher than men. On Emotional Intelligence Questionnaire measures, men had significantly higher means on Managing Emotions and Self-motivation. However, no significant differences were found between the sexes on the Total Emotional Intelligence Questionnaire scores.

Agreement Between 35 Published Frailty Scores in the General Population

PubMed Central

Aguayo, Gloria A.; Donneau, Anne-Françoise; Vaillant, Michel T.; Schritz, Anna; Franco, Oscar H.; Stranges, Saverio; Malisoux, Laurent; Guillaume, Michèle; Witte, Daniel R.

2017-01-01

Abstract In elderly populations, frailty is associated with higher mortality risk. Although many frailty scores (FS) have been proposed, no single score is considered the gold standard. We aimed to evaluate the agreement between a wide range of FS in the English Longitudinal Study of Ageing (ELSA). Through a literature search, we identified 35 FS that could be calculated in ELSA wave 2 (2004–2005). We examined agreement between each frailty score and the mean of 35 FS, using a modified Bland-Altman model and Cohen's kappa (κ). Missing data were imputed. Data from 5,377 participants (ages ≥60 years) were analyzed (44.7% men, 55.3% women). FS showed widely differing degrees of agreement with the mean of all scores and between each pair of scores. Frailty classification also showed a very wide range of agreement (Cohen's κ = 0.10–0.83). Agreement was highest among “accumulation of deficits”-type FS, while accuracy was highest for multidimensional FS. There is marked heterogeneity in the degree to which various FS estimate frailty and in the identification of particular individuals as frail. Different FS are based on different concepts of frailty, and most pairs cannot be assumed to be interchangeable. Research results based on different FS cannot be compared or pooled. PMID:28633404

The CAD-score web server: contact area-based comparison of structures and interfaces of proteins, nucleic acids and their complexes.

PubMed

Olechnovič, Kliment; Venclovas, Ceslovas

2014-07-01

The Contact Area Difference score (CAD-score) web server provides a universal framework to compute and analyze discrepancies between different 3D structures of the same biological macromolecule or complex. The server accepts both single-subunit and multi-subunit structures and can handle all the major types of macromolecules (proteins, RNA, DNA and their complexes). It can perform numerical comparison of both structures and interfaces. In addition to entire structures and interfaces, the server can assess user-defined subsets. The CAD-score server performs both global and local numerical evaluations of structural differences between structures or interfaces. The results can be explored interactively using sortable tables of global scores, profiles of local errors, superimposed contact maps and 3D structure visualization. The web server could be used for tasks such as comparison of models with the native (reference) structure, comparison of X-ray structures of the same macromolecule obtained in different states (e.g. with and without a bound ligand), analysis of nuclear magnetic resonance (NMR) structural ensemble or structures obtained in the course of molecular dynamics simulation. The web server is freely accessible at: http://www.ibt.lt/bioinformatics/cad-score. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning.

PubMed

Munkhdalai, Tsendsuren; Liu, Feifan; Yu, Hong

2018-04-25

Medication and adverse drug event (ADE) information extracted from electronic health record (EHR) notes can be a rich resource for drug safety surveillance. Existing observational studies have mainly relied on structured EHR data to obtain ADE information; however, ADEs are often buried in the EHR narratives and not recorded in structured data. To unlock ADE-related information from EHR narratives, there is a need to extract relevant entities and identify relations among them. In this study, we focus on relation identification. This study aimed to evaluate natural language processing and machine learning approaches using the expert-annotated medical entities and relations in the context of drug safety surveillance, and investigate how different learning approaches perform under different configurations. We have manually annotated 791 EHR notes with 9 named entities (eg, medication, indication, severity, and ADEs) and 7 different types of relations (eg, medication-dosage, medication-ADE, and severity-ADE). Then, we explored 3 supervised machine learning systems for relation identification: (1) a support vector machines (SVM) system, (2) an end-to-end deep neural network system, and (3) a supervised descriptive rule induction baseline system. For the neural network system, we exploited the state-of-the-art recurrent neural network (RNN) and attention models. We report the performance by macro-averaged precision, recall, and F1-score across the relation types. Our results show that the SVM model achieved the best average F1-score of 89.1% on test data, outperforming the long short-term memory (LSTM) model with attention (F1-score of 65.72%) as well as the rule induction baseline system (F1-score of 7.47%) by a large margin. The bidirectional LSTM model with attention achieved the best performance among different RNN models. With the inclusion of additional features in the LSTM model, its performance can be boosted to an average F1-score of 77.35%. It shows that classical learning models (SVM) remains advantageous over deep learning models (RNN variants) for clinical relation identification, especially for long-distance intersentential relations. However, RNNs demonstrate a great potential of significant improvement if more training data become available. Our work is an important step toward mining EHRs to improve the efficacy of drug safety surveillance. Most importantly, the annotated data used in this study will be made publicly available, which will further promote drug safety research in the community. ©Tsendsuren Munkhdalai, Feifan Liu, Hong Yu. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 25.04.2018.

Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning

PubMed Central

Munkhdalai, Tsendsuren; Liu, Feifan

2018-01-01

Background Medication and adverse drug event (ADE) information extracted from electronic health record (EHR) notes can be a rich resource for drug safety surveillance. Existing observational studies have mainly relied on structured EHR data to obtain ADE information; however, ADEs are often buried in the EHR narratives and not recorded in structured data. Objective To unlock ADE-related information from EHR narratives, there is a need to extract relevant entities and identify relations among them. In this study, we focus on relation identification. This study aimed to evaluate natural language processing and machine learning approaches using the expert-annotated medical entities and relations in the context of drug safety surveillance, and investigate how different learning approaches perform under different configurations. Methods We have manually annotated 791 EHR notes with 9 named entities (eg, medication, indication, severity, and ADEs) and 7 different types of relations (eg, medication-dosage, medication-ADE, and severity-ADE). Then, we explored 3 supervised machine learning systems for relation identification: (1) a support vector machines (SVM) system, (2) an end-to-end deep neural network system, and (3) a supervised descriptive rule induction baseline system. For the neural network system, we exploited the state-of-the-art recurrent neural network (RNN) and attention models. We report the performance by macro-averaged precision, recall, and F1-score across the relation types. Results Our results show that the SVM model achieved the best average F1-score of 89.1% on test data, outperforming the long short-term memory (LSTM) model with attention (F1-score of 65.72%) as well as the rule induction baseline system (F1-score of 7.47%) by a large margin. The bidirectional LSTM model with attention achieved the best performance among different RNN models. With the inclusion of additional features in the LSTM model, its performance can be boosted to an average F1-score of 77.35%. Conclusions It shows that classical learning models (SVM) remains advantageous over deep learning models (RNN variants) for clinical relation identification, especially for long-distance intersentential relations. However, RNNs demonstrate a great potential of significant improvement if more training data become available. Our work is an important step toward mining EHRs to improve the efficacy of drug safety surveillance. Most importantly, the annotated data used in this study will be made publicly available, which will further promote drug safety research in the community. PMID:29695376

Docking and scoring protein complexes: CAPRI 3rd Edition.

PubMed

Lensink, Marc F; Méndez, Raúl; Wodak, Shoshana J

2007-12-01

The performance of methods for predicting protein-protein interactions at the atomic scale is assessed by evaluating blind predictions performed during 2005-2007 as part of Rounds 6-12 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). These Rounds also included a new scoring experiment, where a larger set of models contributed by the predictors was made available to groups developing scoring functions. These groups scored the uploaded set and submitted their own best models for assessment. The structures of nine protein complexes including one homodimer were used as targets. These targets represent biologically relevant interactions involved in gene expression, signal transduction, RNA, or protein processing and membrane maintenance. For all the targets except one, predictions started from the experimentally determined structures of the free (unbound) components or from models derived by homology, making it mandatory for docking methods to model the conformational changes that often accompany association. In total, 63 groups and eight automatic servers, a substantial increase from previous years, submitted docking predictions, of which 1994 were evaluated here. Fifteen groups submitted 305 models for five targets in the scoring experiment. Assessment of the predictions reveals that 31 different groups produced models of acceptable and medium accuracy-but only one high accuracy submission-for all the targets, except the homodimer. In the latter, none of the docking procedures reproduced the large conformational adjustment required for correct assembly, underscoring yet again that handling protein flexibility remains a major challenge. In the scoring experiment, a large fraction of the groups attained the set goal of singling out the correct association modes from incorrect solutions in the limited ensembles of contributed models. But in general they seemed unable to identify the best models, indicating that current scoring methods are probably not sensitive enough. With the increased focus on protein assemblies, in particular by structural genomics efforts, the growing community of CAPRI predictors is engaged more actively than ever in the development of better scoring functions and means of modeling conformational flexibility, which hold promise for much progress in the future. (c) 2007 Wiley-Liss, Inc.

Predictive effects of teachers and schools on test scores, college attendance, and earnings

PubMed Central

Chamberlain, Gary E.

2013-01-01

I studied predictive effects of teachers and schools on test scores in fourth through eighth grade and outcomes later in life such as college attendance and earnings. For example, predict the fraction of a classroom attending college at age 20 given the test score for a different classroom in the same school with the same teacher and given the test score for a classroom in the same school with a different teacher. I would like to have predictive effects that condition on averages over many classrooms, with and without the same teacher. I set up a factor model that, under certain assumptions, makes this feasible. Administrative school district data in combination with tax data were used to calculate estimates and do inference. PMID:24101492

A new risk prediction model for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model.

PubMed

Harrison, David A; Parry, Gareth J; Carpenter, James R; Short, Alasdair; Rowan, Kathy

2007-04-01

To develop a new model to improve risk prediction for admissions to adult critical care units in the UK. Prospective cohort study. The setting was 163 adult, general critical care units in England, Wales, and Northern Ireland, December 1995 to August 2003. Patients were 216,626 critical care admissions. None. The performance of different approaches to modeling physiologic measurements was evaluated, and the best methods were selected to produce a new physiology score. This physiology score was combined with other information relating to the critical care admission-age, diagnostic category, source of admission, and cardiopulmonary resuscitation before admission-to develop a risk prediction model. Modeling interactions between diagnostic category and physiology score enabled the inclusion of groups of admissions that are frequently excluded from risk prediction models. The new model showed good discrimination (mean c index 0.870) and fit (mean Shapiro's R 0.665, mean Brier's score 0.132) in 200 repeated validation samples and performed well when compared with recalibrated versions of existing published risk prediction models in the cohort of patients eligible for all models. The hypothesis of perfect fit was rejected for all models, including the Intensive Care National Audit & Research Centre (ICNARC) model, as is to be expected in such a large cohort. The ICNARC model demonstrated better discrimination and overall fit than existing risk prediction models, even following recalibration of these models. We recommend it be used to replace previously published models for risk adjustment in the UK.

The role of test-retest reliability in measuring individual and group differences in executive functioning.

PubMed

Paap, Kenneth R; Sawi, Oliver

2016-12-01

Studies testing for individual or group differences in executive functioning can be compromised by unknown test-retest reliability. Test-retest reliabilities across an interval of about one week were obtained from performance in the antisaccade, flanker, Simon, and color-shape switching tasks. There is a general trade-off between the greater reliability of single mean RT measures, and the greater process purity of measures based on contrasts between mean RTs in two conditions. The individual differences in RT model recently developed by Miller and Ulrich was used to evaluate the trade-off. Test-retest reliability was statistically significant for 11 of the 12 measures, but was of moderate size, at best, for the difference scores. The test-retest reliabilities for the Simon and flanker interference scores were lower than those for switching costs. Standard practice evaluates the reliability of executive-functioning measures using split-half methods based on data obtained in a single day. Our test-retest measures of reliability are lower, especially for difference scores. These reliability measures must also take into account possible day effects that classical test theory assumes do not occur. Measures based on single mean RTs tend to have acceptable levels of reliability and convergent validity, but are "impure" measures of specific executive functions. The individual differences in RT model shows that the impurity problem is worse than typically assumed. However, the "purer" measures based on difference scores have low convergent validity that is partly caused by deficiencies in test-retest reliability. Copyright © 2016 Elsevier B.V. All rights reserved.

Prognostic score–based balance measures for propensity score methods in comparative effectiveness research

PubMed Central

Stuart, Elizabeth A.; Lee, Brian K.; Leacy, Finbarr P.

2013-01-01

Objective Examining covariate balance is the prescribed method for determining when propensity score methods are successful at reducing bias. This study assessed the performance of various balance measures, including a proposed balance measure based on the prognostic score (also known as the disease-risk score), to determine which balance measures best correlate with bias in the treatment effect estimate. Study Design and Setting The correlations of multiple common balance measures with bias in the treatment effect estimate produced by weighting by the odds, subclassification on the propensity score, and full matching on the propensity score were calculated. Simulated data were used, based on realistic data settings. Settings included both continuous and binary covariates and continuous covariates only. Results The standardized mean difference in prognostic scores, the mean standardized mean difference, and the mean t-statistic all had high correlations with bias in the effect estimate. Overall, prognostic scores displayed the highest correlations of all the balance measures considered. Prognostic score measure performance was generally not affected by model misspecification and performed well under a variety of scenarios. Conclusion Researchers should consider using prognostic score–based balance measures for assessing the performance of propensity score methods for reducing bias in non-experimental studies. PMID:23849158

Evaluating the lexico-grammatical differences in the writing of native and non-native speakers of English in peer-reviewed medical journals in the field of pediatric oncology: Creation of the genuine index scoring system

PubMed Central

Gayle, Alberto Alexander; Shimaoka, Motomu

2017-01-01

Introduction The predominance of English in scientific research has created hurdles for “non-native speakers” of English. Here we present a novel application of native language identification (NLI) for the assessment of medical-scientific writing. For this purpose, we created a novel classification system whereby scoring would be based solely on text features found to be distinctive among native English speakers (NS) within a given context. We dubbed this the “Genuine Index” (GI). Methodology This methodology was validated using a small set of journals in the field of pediatric oncology. Our dataset consisted of 5,907 abstracts, representing work from 77 countries. A support vector machine (SVM) was used to generate our model and for scoring. Results Accuracy, precision, and recall of the classification model were 93.3%, 93.7%, and 99.4%, respectively. Class specific F-scores were 96.5% for NS and 39.8% for our benchmark class, Japan. Overall kappa was calculated to be 37.2%. We found significant differences between countries with respect to the GI score. Significant correlation was found between GI scores and two validated objective measures of writing proficiency and readability. Two sets of key terms and phrases differentiating NS and non-native writing were identified. Conclusions Our GI model was able to detect, with a high degree of reliability, subtle differences between the terms and phrasing used by native and non-native speakers in peer reviewed journals, in the field of pediatric oncology. In addition, L1 language transfer was found to be very likely to survive revision, especially in non-Western countries such as Japan. These findings show that even when the language used is technically correct, there may still be some phrasing or usage that impact quality. PMID:28212419

Evaluating the lexico-grammatical differences in the writing of native and non-native speakers of English in peer-reviewed medical journals in the field of pediatric oncology: Creation of the genuine index scoring system.

PubMed

Gayle, Alberto Alexander; Shimaoka, Motomu

2017-01-01

The predominance of English in scientific research has created hurdles for "non-native speakers" of English. Here we present a novel application of native language identification (NLI) for the assessment of medical-scientific writing. For this purpose, we created a novel classification system whereby scoring would be based solely on text features found to be distinctive among native English speakers (NS) within a given context. We dubbed this the "Genuine Index" (GI). This methodology was validated using a small set of journals in the field of pediatric oncology. Our dataset consisted of 5,907 abstracts, representing work from 77 countries. A support vector machine (SVM) was used to generate our model and for scoring. Accuracy, precision, and recall of the classification model were 93.3%, 93.7%, and 99.4%, respectively. Class specific F-scores were 96.5% for NS and 39.8% for our benchmark class, Japan. Overall kappa was calculated to be 37.2%. We found significant differences between countries with respect to the GI score. Significant correlation was found between GI scores and two validated objective measures of writing proficiency and readability. Two sets of key terms and phrases differentiating NS and non-native writing were identified. Our GI model was able to detect, with a high degree of reliability, subtle differences between the terms and phrasing used by native and non-native speakers in peer reviewed journals, in the field of pediatric oncology. In addition, L1 language transfer was found to be very likely to survive revision, especially in non-Western countries such as Japan. These findings show that even when the language used is technically correct, there may still be some phrasing or usage that impact quality.

Mid-Level Healthcare Personnel Training: An Evaluation of the Revised, Nationally-Standardized, Pre-Service Curriculum for Clinical Officers in Mozambique

PubMed Central

Feldacker, Caryl; Chicumbe, Sergio; Dgedge, Martinho; Augusto, Gerito; Cesar, Freide; Robertson, Molly; Mbofana, Francisco; O'Malley, Gabrielle

2014-01-01

Introduction Mozambique suffers from a critical shortage of healthcare workers. Mid-level healthcare workers, (Tecnicos de Medicina Geral (TMG)), in Mozambique require less money and time to train than physicians. From 2009–2010, the Mozambique Ministry of Health (MoH) and the International Training and Education Center for Health (I-TECH), University of Washington, Seattle, revised the TMG curriculum. To evaluate the effect of the curriculum revision, we used mixed methods to determine: 1) if TMGs meet the MoH's basic standards of clinical competency; and 2) do scores on measurements of clinical knowledge, physical exam, and clinical case scenarios differ by curriculum? Methods T-tests of differences in means examined differences in continuous score variables between curriculum groups. Univariate and multivariate linear regression models assess curriculum-related and demographic factors associated with assessment scores on each of the three evaluation methods at the p<0.05 level. Qualitative interviews and focus groups inform interpretation. Results We found no significant differences in sex, marital status and age between the 112 and 189 TMGs in initial and revised curriculum, respectively. Mean scores at graduation of initial curriculum TMGs were 56.7%, 63.5%, and 49.1% on the clinical cases, knowledge test, and physical exam, respectively. Scores did not differ significantly from TMGs in the revised curriculum. Results from linear regression models find that training institute was the most significant predictor of TMG scores on both the clinical cases and physical exam. Conclusion TMGs trained in either curriculum may be inadequately prepared to provide quality care. Curriculum changes are a necessary, but insufficient, part of improving TMG knowledge and skills overall. A more comprehensive, multi-level approach to improving TMG training that includes post-graduation mentoring, strengthening the pre-service internship training, and greater resources for training institute faculty may result in improvements in TMG capacity and patient care over time. PMID:25068590

Mid-level healthcare personnel training: an evaluation of the revised, nationally-standardized, pre-service curriculum for clinical officers in Mozambique.

PubMed

Feldacker, Caryl; Chicumbe, Sergio; Dgedge, Martinho; Augusto, Gerito; Cesar, Freide; Robertson, Molly; Mbofana, Francisco; O'Malley, Gabrielle

2014-01-01

Mozambique suffers from a critical shortage of healthcare workers. Mid-level healthcare workers, (Tecnicos de Medicina Geral (TMG)), in Mozambique require less money and time to train than physicians. From 2009-2010, the Mozambique Ministry of Health (MoH) and the International Training and Education Center for Health (I-TECH), University of Washington, Seattle, revised the TMG curriculum. To evaluate the effect of the curriculum revision, we used mixed methods to determine: 1) if TMGs meet the MoH's basic standards of clinical competency; and 2) do scores on measurements of clinical knowledge, physical exam, and clinical case scenarios differ by curriculum? T-tests of differences in means examined differences in continuous score variables between curriculum groups. Univariate and multivariate linear regression models assess curriculum-related and demographic factors associated with assessment scores on each of the three evaluation methods at the p<0.05 level. Qualitative interviews and focus groups inform interpretation. We found no significant differences in sex, marital status and age between the 112 and 189 TMGs in initial and revised curriculum, respectively. Mean scores at graduation of initial curriculum TMGs were 56.7%, 63.5%, and 49.1% on the clinical cases, knowledge test, and physical exam, respectively. Scores did not differ significantly from TMGs in the revised curriculum. Results from linear regression models find that training institute was the most significant predictor of TMG scores on both the clinical cases and physical exam. TMGs trained in either curriculum may be inadequately prepared to provide quality care. Curriculum changes are a necessary, but insufficient, part of improving TMG knowledge and skills overall. A more comprehensive, multi-level approach to improving TMG training that includes post-graduation mentoring, strengthening the pre-service internship training, and greater resources for training institute faculty may result in improvements in TMG capacity and patient care over time.

Modeling the Distribution of Nursing Effort Using Structured Labor and Delivery Documentation

PubMed Central

Hall, Eric S.; Poynton, Mollie R.; Narus, Scott P.; Thornton, Sidney N.

2008-01-01

Our study objectives included the development and evaluation of models for representing the distribution of shared unit-wide nursing care resources among individual Labor and Delivery patients using quantified measurements of nursing care, referred to as Nursing Effort. The models were intended to enable discrimination between the amounts of care delivered to patient subsets defined by attributes such as patient acuity. For each of five proposed models, scores were generated using an analysis set of 686,402 computerized nurse-documented events associated with 1,093 patients at three hospitals during January and February 2006. Significant differences were detected in Nursing Effort scores according to patient acuity, care facility, and in scores generated during shift-change versus non shift-change hours. The development of nursing care quantification strategies proposed in this study supports outcomes analysis by establishing a foundation for measuring the effect of patient-level nursing care on individual patient outcomes. PMID:18495549

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis

PubMed Central

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

Background The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. Methods and finding We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755–0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691–0.783) and 0.742 (0.698–0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. Conclusions According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction. PMID:28060903

The mortality risk score and the ADG score: two points-based scoring systems for the Johns Hopkins aggregated diagnosis groups to predict mortality in a general adult population cohort in Ontario, Canada.

PubMed

Austin, Peter C; Walraven, Carl van

2011-10-01

Logistic regression models that incorporated age, sex, and indicator variables for the Johns Hopkins' Aggregated Diagnosis Groups (ADGs) categories have been shown to accurately predict all-cause mortality in adults. To develop 2 different point-scoring systems using the ADGs. The Mortality Risk Score (MRS) collapses age, sex, and the ADGs to a single summary score that predicts the annual risk of all-cause death in adults. The ADG Score derives weights for the individual ADG diagnosis groups. : Retrospective cohort constructed using population-based administrative data. All 10,498,413 residents of Ontario, Canada, between the age of 20 and 100 years who were alive on their birthday in 2007, participated in this study. Participants were randomly divided into derivation and validation samples. : Death within 1 year. In the derivation cohort, the MRS ranged from -21 to 139 (median value 29, IQR 17 to 44). In the validation group, a logistic regression model with the MRS as the sole predictor significantly predicted the risk of 1-year mortality with a c-statistic of 0.917. A regression model with age, sex, and the ADG Score has similar performance. Both methods accurately predicted the risk of 1-year mortality across the 20 vigintiles of risk. The MRS combined values for a person's age, sex, and the John Hopkins ADGs to accurately predict 1-year mortality in adults. The ADG Score is a weighted score representing the presence or absence of the 32 ADG diagnosis groups. These scores will facilitate health services researchers conducting risk adjustment using administrative health care databases.

Clinical Score to Differentiate Scrub Typhus and Dengue: A Tool to Differentiate Scrub Typhus and Dengue.

PubMed

Mitra, Shubhanker; Gautam, Ira; Jambugulam, Mohan; Abhilash, Kundavaram Paul Prabhakar; Jayaseeelan, Vishalakshi

2017-01-01

Dengue and scrub typhus share similar clinical and epidemiological features, and are difficult to differentiate at initial presentation. Many places are endemic to both these infections where they comprise the majority of acute undifferentiated febrile illnesses. We aimed to develop a score that can differentiate scrub typhus from dengue. In this cross-sectional study, 188 cases of scrub typhus and 201 cases of dengue infection who presented to the emergency department or medicine outpatient clinic from September 2012 to April 2013 were included. Univariate followed by multivariate logistic regression analysis was performed to identify clinical features and laboratory results that were significantly different between the two groups. Each variable was assigned scores based on the strength of association and receiver operating characteristics area under the curve (ROC-AUC) was generated and compared. Six scoring models were explored to ascertain the model with the best fit. Model 2 was developed using the following six variables: oxygen saturation (>90%, ≤90%), total white blood cell count (<4000, 4001-7000 and >7000 cells/cumm), hemoglobin (≤14 and >14 g/dL), total bilirubin (<2 and ≥2 mg/dL), serum glutamic oxaloacetic transaminase (>200 and ≥200 IU/dL), and altered sensorium (present or absent). Each variable was assigned scores based on its strength of association. The AUC-ROC curve (95% confidence interval) for model 2 was 0.84 (0.79-0.89). At the cut off score of 13, the sensitivity and specificity were 85% and 77% respectively, with a higher score favoring dengue. In areas of high burden of ST and dengue, model 2 (the "clinical score to differentiate scrub typhus and dengue fever") is a simple and rapid clinical scoring system that may be used to differentiate scrub typhus and dengue at initial presentation.

Ethnic differences in cognitive development in the first 7 years: does maternal generational status matter?

PubMed

Smith, Neil R; Kelly, Yvonne J; Nazroo, James Y

2016-05-01

Differences in cognitive development have been observed across a variety of ethnic minority groups but relatively little is known about the persistence of these developmental inequalities over time or generations. A repeat cross-sectional analysis assessed cognitive ability scores of children aged 3, 5 and 7 years from the longitudinal UK Millennium Cohort Study (white UK born n=7630; Indian n=248; Pakistani n=328; Bangladeshi n=87; black Caribbean n=172; and black African n=136). Linear regression estimated ethnic differences in age normed scores at each time point. Multivariable logistic regression estimated within-group generational differences in test scores at each age adjusting stepwise for sociodemographic factors, maternal health behaviours, indicators of the home learning environment and parenting styles. The majority of ethnic minority groups scored lower than the white UK born reference group at 3 years with these differences narrowing incrementally at ages 5 and 7 years. However, the black Caribbean group scored significantly lower than the white UK born reference group throughout early childhood. At 3 years, Pakistani, black Caribbean and black African children with UK born mothers had significantly higher test scores than those with foreign born mothers after baseline adjustment for maternal age and child gender. Controlling for social, behavioural and parenting factors attenuated this generational advantage. By 7 years there were no significant generational differences in baseline models. Ethnic differences in cognitive development diminish throughout childhood for the majority of groups. Cumulative exposure to the UK environment may be associated with higher cognitive development scores. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Improving the Reliability of Student Scores from Speeded Assessments: An Illustration of Conditional Item Response Theory Using a Computer-Administered Measure of Vocabulary.

PubMed

Petscher, Yaacov; Mitchell, Alison M; Foorman, Barbara R

2015-01-01

A growing body of literature suggests that response latency, the amount of time it takes an individual to respond to an item, may be an important factor to consider when using assessment data to estimate the ability of an individual. Considering that tests of passage and list fluency are being adapted to a computer administration format, it is possible that accounting for individual differences in response times may be an increasingly feasible option to strengthen the precision of individual scores. The present research evaluated the differential reliability of scores when using classical test theory and item response theory as compared to a conditional item response model which includes response time as an item parameter. Results indicated that the precision of student ability scores increased by an average of 5 % when using the conditional item response model, with greater improvements for those who were average or high ability. Implications for measurement models of speeded assessments are discussed.

Improving the Reliability of Student Scores from Speeded Assessments: An Illustration of Conditional Item Response Theory Using a Computer-Administered Measure of Vocabulary

PubMed Central

Petscher, Yaacov; Mitchell, Alison M.; Foorman, Barbara R.

2016-01-01

A growing body of literature suggests that response latency, the amount of time it takes an individual to respond to an item, may be an important factor to consider when using assessment data to estimate the ability of an individual. Considering that tests of passage and list fluency are being adapted to a computer administration format, it is possible that accounting for individual differences in response times may be an increasingly feasible option to strengthen the precision of individual scores. The present research evaluated the differential reliability of scores when using classical test theory and item response theory as compared to a conditional item response model which includes response time as an item parameter. Results indicated that the precision of student ability scores increased by an average of 5 % when using the conditional item response model, with greater improvements for those who were average or high ability. Implications for measurement models of speeded assessments are discussed. PMID:27721568

Determining if Instructional Delivery Model Differences Exist in Remedial English

ERIC Educational Resources Information Center

Carter, LaTanya Woods

2012-01-01

The purpose of this causal comparative study is to test the theory of no significant difference that compares pre- and post-test assessment scores, controlling for the instructional delivery model of online and face-to-face students at a Mid-Atlantic university. Online education and virtual distance learning programs have increased in popularity…

Assessing the similarity of mental models of operating room team members and implications for patient safety: a prospective, replicated study.

PubMed

Nakarada-Kordic, Ivana; Weller, Jennifer M; Webster, Craig S; Cumin, David; Frampton, Christopher; Boyd, Matt; Merry, Alan F

2016-08-31

Patient safety depends on effective teamwork. The similarity of team members' mental models - or their shared understanding-regarding clinical tasks is likely to influence the effectiveness of teamwork. Mental models have not been measured in the complex, high-acuity environment of the operating room (OR), where professionals of different backgrounds must work together to achieve the best surgical outcome for each patient. Therefore, we aimed to explore the similarity of mental models of task sequence and of responsibility for task within multidisciplinary OR teams. We developed a computer-based card sorting tool (Momento) to capture the information on mental models in 20 six-person surgical teams, each comprised of three subteams (anaesthesia, surgery, and nursing) for two simulated laparotomies. Team members sorted 20 cards depicting key tasks according to when in the procedure each task should be performed, and which subteam was primarily responsible for each task. Within each OR team and subteam, we conducted pairwise comparisons of scores to arrive at mean similarity scores for each task. Mean similarity score for task sequence was 87 % (range 57-97 %). Mean score for responsibility for task was 70 % (range = 38-100 %), but for half of the tasks was only 51 % (range = 38-69 %). Participants believed their own subteam was primarily responsible for approximately half the tasks in each procedure. We found differences in the mental models of some OR team members about responsibility for and order of certain tasks in an emergency laparotomy. Momento is a tool that could help elucidate and better align the mental models of OR team members about surgical procedures and thereby improve teamwork and outcomes for patients.

Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble

PubMed Central

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data. PMID:25706988

The Association between Road Traffic Noise Exposure, Annoyance and Health-Related Quality of Life (HRQOL)

PubMed Central

Héritier, Harris; Vienneau, Danielle; Frei, Patrizia; Eze, Ikenna C.; Brink, Mark; Probst-Hensch, Nicole; Röösli, Martin

2014-01-01

The aim of this study is to investigate the relationships between road traffic noise exposure, annoyance caused by different noise sources and validated health indicators in a cohort of 1375 adults from the region of Basel, Switzerland. Road traffic noise exposure for each study participant was determined using modelling, and annoyance from various noise sources was inquired by means of a four-point Likert scale. Regression parameters from multivariable regression models for the von Zerssen score of somatic symptoms (point symptom score increase per annoyance category) showed strongest associations with annoyance from industry noise (2.36, 95% CI: 1.54, 3.17), neighbour noise (1.62, 95% CI: 1.17, 2.06) and road traffic noise (1.53, 95% CI: 1.09, 1.96). Increase in modelled noise exposure by 10 dB(A) resulted in a von Zerssen symptom score increase of 0.47 (95% CI: −0.01, 0.95) units. Subsequent structural equation modelling revealed that the association between physical noise exposure and health-related quality of life (HRQOL) is strongly mediated by annoyance and sleep disturbance. This study elucidates the complex interplay of different factors for the association between physical noise exposure and HRQOL. PMID:25489999

Learning to apply models of materials while explaining their properties

NASA Astrophysics Data System (ADS)

Karpin, Tiia; Juuti, Kalle; Lavonen, Jari

2014-09-01

Background:Applying structural models is important to chemistry education at the upper secondary level, but it is considered one of the most difficult topics to learn. Purpose:This study analyses to what extent in designed lessons students learned to apply structural models in explaining the properties and behaviours of various materials. Sample:An experimental group is 27 Finnish upper secondary school students and control group included 18 students from the same school. Design and methods:In quasi-experimental setting, students were guided through predict, observe, explain activities in four practical work situations. It was intended that the structural models would encourage students to learn how to identify and apply appropriate models when predicting and explaining situations. The lessons, organised over a one-week period, began with a teacher's demonstration and continued with student experiments in which they described the properties and behaviours of six household products representing three different materials. Results:Most students in the experimental group learned to apply the models correctly, as demonstrated by post-test scores that were significantly higher than pre-test scores. The control group showed no significant difference between pre- and post-test scores. Conclusions:The findings indicate that the intervention where students engage in predict, observe, explain activities while several materials and models are confronted at the same time, had a positive effect on learning outcomes.

s-core network decomposition: A generalization of k-core analysis to weighted networks

NASA Astrophysics Data System (ADS)

Eidsaa, Marius; Almaas, Eivind

2013-12-01

A broad range of systems spanning biology, technology, and social phenomena may be represented and analyzed as complex networks. Recent studies of such networks using k-core decomposition have uncovered groups of nodes that play important roles. Here, we present s-core analysis, a generalization of k-core (or k-shell) analysis to complex networks where the links have different strengths or weights. We demonstrate the s-core decomposition approach on two random networks (ER and configuration model with scale-free degree distribution) where the link weights are (i) random, (ii) correlated, and (iii) anticorrelated with the node degrees. Finally, we apply the s-core decomposition approach to the protein-interaction network of the yeast Saccharomyces cerevisiae in the context of two gene-expression experiments: oxidative stress in response to cumene hydroperoxide (CHP), and fermentation stress response (FSR). We find that the innermost s-cores are (i) different from innermost k-cores, (ii) different for the two stress conditions CHP and FSR, and (iii) enriched with proteins whose biological functions give insight into how yeast manages these specific stresses.

Effect of misspecification of gene frequency on the two-point LOD score.

PubMed

Pal, D K; Durner, M; Greenberg, D A

2001-11-01

In this study, we used computer simulation of simple and complex models to ask: (1) What is the penalty in evidence for linkage when the assumed gene frequency is far from the true gene frequency? (2) If the assumed model for gene frequency and inheritance are misspecified in the analysis, can this lead to a higher maximum LOD score than that obtained under the true parameters? Linkage data simulated under simple dominant, recessive, dominant and recessive with reduced penetrance, and additive models, were analysed assuming a single locus with both the correct and incorrect dominance model and assuming a range of different gene frequencies. We found that misspecifying the analysis gene frequency led to little penalty in maximum LOD score in all models examined, especially if the assumed gene frequency was lower than the generating one. Analysing linkage data assuming a gene frequency of the order of 0.01 for a dominant gene, and 0.1 for a recessive gene, appears to be a reasonable tactic in the majority of realistic situations because underestimating the gene frequency, even when the true gene frequency is high, leads to little penalty in the LOD score.

A comparison of different functions for predicted protein model quality assessment.

PubMed

Li, Juan; Fang, Huisheng

2016-07-01

In protein structure prediction, a considerable number of models are usually produced by either the Template-Based Method (TBM) or the ab initio prediction. The purpose of this study is to find the critical parameter in assessing the quality of the predicted models. A non-redundant template library was developed and 138 target sequences were modeled. The target sequences were all distant from the proteins in the template library and were aligned with template library proteins on the basis of the transformation matrix. The quality of each model was first assessed with QMEAN and its six parameters, which are C_β interaction energy (C_beta), all-atom pairwise energy (PE), solvation energy (SE), torsion angle energy (TAE), secondary structure agreement (SSA), and solvent accessibility agreement (SAE). Finally, the alignment score (score) was also used to assess the quality of model. Hence, a total of eight parameters (i.e., QMEAN, C_beta, PE, SE, TAE, SSA, SAE, score) were independently used to assess the quality of each model. The results indicate that SSA is the best parameter to estimate the quality of the model.

The Big-Five factor structure as an integrative framework: an analysis of Clarke's AVA model.

PubMed

Goldberg, L R; Sweeney, D; Merenda, P F; Hughes, J E

1996-06-01

Using a large (N = 3,629) sample of participants selected to be representative of U.S. working adults in the year 2,000, we provide links between the constructs in 2 personality models that have been derived from quite different rationales. We demonstrate the use of a novel procedure for providing orthogonal Big-Five factor scores and use those scores to analyze the scales of the Activity Vector Analysis (AVA). We discuss the implications of our many findings both for the science of personality assessment and for future research using the AVA model.

Dynamics of three-agent games

NASA Astrophysics Data System (ADS)

Mungan, Muhittin; Rador, Tonguç

2008-02-01

We study the dynamics and resulting score distribution of three-agent games where after each competition a single agent wins and scores a point. A single competition is described by a triplet of numbers p, t and q denoting the probabilities that the team with the highest, middle or lowest accumulated score wins. The three-agent game can be regarded as a social model where a player can be favored or disfavored for advancement, based on his/her accumulated score. We study the full family of solutions in the regime, where the number of agents and competitions is large, which can be regarded as a hydrodynamic limit. Depending on the parameter values (p, q, t), we find six qualitatively different asymptotic score distributions and we provide a qualitative explanation of these results. We also compare our analytical results against numerical simulations of the microscopic model and find these to be in excellent agreement. It is possible to decide the outcome of a three-agent game through a mini-tournament of two-agent competitions among the participating players and it turns out that the resulting possible score distributions are a subset of those obtained for the general three-agent games. We discuss how one can add a steady and democratic decline rate to the model and present a simple geometric construction that allows one to obtain the score evolution equations for n-agent games.

Predictive power of the grace score in population with diabetes.

PubMed

Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

2017-12-01

Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Evaluation of Linking Methods for Placing Three-Parameter Logistic Item Parameter Estimates onto a One-Parameter Scale

ERIC Educational Resources Information Center

Karkee, Thakur B.; Wright, Karen R.

2004-01-01

Different item response theory (IRT) models may be employed for item calibration. Change of testing vendors, for example, may result in the adoption of a different model than that previously used with a testing program. To provide scale continuity and preserve cut score integrity, item parameter estimates from the new model must be linked to the…

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

PubMed

Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

2018-01-01

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk assessment and risk scores in the management of aortic aneurysms.

PubMed

Von Meijenfeldt, Gerdine C I; Van Der Laan, Maarten J; Zeebregts, Clark J; Balm, Ron; Verhagen, Hence J M

2016-04-01

The decision whether to operate a patient or not can be challenging for a clinician for both ruptured abdominal aortic aneurysms (AAAs) as well as elective AAAs. Prior to surgical intervention it would be preferable that the clinician exactly knows which clinical variables lower or increase the chances of morbidity and mortality postintervention. To help in the preoperative counselling and shared decision making several clinical variables can be identified as risk factors and with these, risk models can be developed. An ideal risk score for aneurysm repair includes routinely obtained physiological and anatomical variables, has excellent discrimination and calibration, and is validated in different geographical areas. For elective AAA repair, several risk scores are available, for ruptured AAA treatment, these scores are far less well developed. In this manuscript, we describe the designs and results of published risk scores for elective and open repair. Also, suggestions for uniformly reporting of risk factors and their statistical analyses are described. Furthermore, the preliminary results of a new risk model for ruptured aortic aneurysm will be discussed. This score identifies age, hemoglobin, cardiopulmonary resuscitation and preoperative systolic blood pressure as risk factors after multivariate regression analysis. This new risk score can help to identify patients that would not benefit from repair, but it can also potentially identify patients who would benefit and therefore lower turndown rates. The challenge for further research is to expand on validation of already existing promising risk scores in order to come to a risk model with optimal discrimination and calibration.

Evaluation of a nurse-led management program to complement the treatment of adolescent acute lymphoblastic leukemia patients.

PubMed

Lin, Hailong; Zhou, Shiyan; Zhang, Dongxiu; Huang, Leting

2016-11-01

To evaluate a nurse-led management model of adolescent acute lymphoblastic leukemia (ALL) patients and improve their psychological care and quality of life. Seventy-three adolescent ALL patients participated in an open, controlled clinical trial and were randomized into a nurse-led management model group (n=36) and a doctor-led management model group (n=37). Two assessment questionnaires were administered to assess and compare the 2 models during a 1.5-year follow-up period: the hospital anxiety and depression scale (HADS) questionnaire was administered at 6 different time points, and the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) at 3 different time points. There were no differences in anxiety and depression between the groups according to the first-administered questionnaire (the mean anxiety and depression scores of the nurse-led group were 14.2±4.1 and 10.8±2.7, respectively; those of the doctor-led group were 13.8±3.8 and 10.6±2.2, respectively). However, repeated measures analysis of variance detected differences in subsequent HADS-based scores as a function of time between the 2 groups (p<0.05). Moreover, the Holm-Sidak's multiple comparisons tests showed that patients of the nurse-led group had significantly decreased mean anxiety scores compared to those in the doctor-led group at the third and subsequent sessions, as well as in mean depression scores from the second session onwards (all p<0.05). According to the last-administered EORTC QLQ-C30 questionnaire, there were statistical differences in cognitive, emotional, social, and quality of life scales between the 2 groups (all p<0.05), but not in role and physical scales (all p>0.05). It is necessary to offer unique cognitive, psychological, and behavioral management models to adolescent ALL patients that are tailored toward their age group. Strengthening such management is more conducive to alleviating or even reversing psychological problems, and to improving patients' quality of life while ensuring complication-free follow-up periods. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The relationship between odour annoyance scores and modelled ambient air pollution in Sarnia, "Chemical Valley", Ontario.

PubMed

Atari, Dominic Odwa; Luginaah, Isaac N; Fung, Karen

2009-10-01

This study aimed at establishing the relationship between annoyance scores and modelled air pollution in "Chemical Valley", Sarnia, Ontario (Canada). Annoyance scores were taken from a community health survey (N = 774); and respondents' exposure to nitrogen dioxide (NO(2)) and sulphur dioxide (SO(2)) were estimated using land use regression (LUR) models. The associations were examined by univariate analysis while multivariate logistic regression was used to examine the determinants of odour annoyance. The results showed that odour annoyance was significantly correlated to modelled pollutants at the individual (NO(2), r = 0.15; SO(2), r = 0.13) and census tract (NO(2), r = 0.56; SO(2), r = 0.67) levels. The exposure-response relationships show that residents of Sarnia react to very low pollution concentrations levels even if they are within the Ontario ambient air quality criteria. The study found that exposure to high NO(2) and SO(2) concentrations, gender, and perception of health effects were significant determinants of individual odour annoyance reporting. The observed association between odour annoyance and modelled ambient pollution suggest that individual and census tract level annoyance scores may serve as proxies for air quality in exposed communities because they capture the within area spatial variability of pollution. However, questionnaire-based odour annoyance scores need to be validated longitudinally and across different scales if they are to be adopted for use at the national level.

Test Scores, Dropout Rates, and Transfer Rates as Alternative Indicators of High School Performance

ERIC Educational Resources Information Center

Rumberger, Russell W.; Palardy, Gregory J.

2005-01-01

This study investigated the relationships among several different indicators of high school performance: test scores, dropout rates, transfer rates, and attrition rates. Hierarchical linear models were used to analyze panel data from a sample of 14,199 students who took part in the National Education Longitudinal Survey of 1988. The results…

Race, Poverty and SAT Scores: Modeling the Influences of Family Income on Black and White High School Students' SAT Performance

ERIC Educational Resources Information Center

Dixon-Roman, Ezekiel J.; Everson, Howard T.; McArdle, John J.

2013-01-01

Background: Educational policy makers and test critics often assert that standardized test scores are strongly influenced by factors beyond individual differences in academic achievement such as family income and wealth. Unfortunately, few empirical studies consider the simultaneous and related influences of family income, parental education, and…

TARPARE: a method for selecting target audiences for public health interventions.

PubMed

Donovan, R J; Egger, G; Francas, M

1999-06-01

This paper presents a model to assist the health promotion practitioner systematically compare and select what might be appropriate target groups when there are a number of segments competing for attention and resources. TARPARE assesses previously identified segments on the following criteria: T: The Total number of persons in the segment; AR: The proportion of At Risk persons in the segment; P: The Persuability of the target audience; A: The Accessibility of the target audience; R: Resources required to meet the needs of the target audience; and E: Equity, social justice considerations. The assessment can be applied qualitatively or can be applied such that scores can be assigned to each segment. Two examples are presented. TARPARE is a useful and flexible model for understanding the various segments in a population of interest and for assessing the potential viability of interventions directed at each segment. The model is particularly useful when there is a need to prioritise segments in terms of available budgets. The model provides a disciplined approach to target selection and forces consideration of what weights should be applied to the different criteria, and how these might vary for different issues or for different objectives. TARPARE also assesses segments in terms of an overall likelihood of optimal impact for each segment. Targeting high scoring segments is likely to lead to greater program success than targeting low scoring segments.

Performance of machine-learning scoring functions in structure-based virtual screening

PubMed Central

Wójcikowski, Maciej; Ballester, Pedro J.; Siedlecki, Pawel

2017-01-01

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and −0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary). PMID:28440302

Combination of synoptical-analogous and dynamical methods to increase skill score of monthly air temperature forecasts over Northern Eurasia

NASA Astrophysics Data System (ADS)

Khan, Valentina; Tscepelev, Valery; Vilfand, Roman; Kulikova, Irina; Kruglova, Ekaterina; Tischenko, Vladimir

2016-04-01

Long-range forecasts at monthly-seasonal time scale are in great demand of socio-economic sectors for exploiting climate-related risks and opportunities. At the same time, the quality of long-range forecasts is not fully responding to user application necessities. Different approaches, including combination of different prognostic models, are used in forecast centers to increase the prediction skill for specific regions and globally. In the present study, two forecasting methods are considered which are exploited in operational practice of Hydrometeorological Center of Russia. One of them is synoptical-analogous method of forecasting of surface air temperature at monthly scale. Another one is dynamical system based on the global semi-Lagrangian model SL-AV, developed in collaboration of Institute of Numerical Mathematics and Hydrometeorological Centre of Russia. The seasonal version of this model has been used to issue global and regional forecasts at monthly-seasonal time scales. This study presents results of the evaluation of surface air temperature forecasts generated with using above mentioned synoptical-statistical and dynamical models, and their combination to potentially increase skill score over Northern Eurasia. The test sample of operational forecasts is encompassing period from 2010 through 2015. The seasonal and interannual variability of skill scores of these methods has been discussed. It was noticed that the quality of all forecasts is highly dependent on the inertia of macro-circulation processes. The skill scores of forecasts are decreasing during significant alterations of synoptical fields for both dynamical and empirical schemes. Procedure of combination of forecasts from different methods, in some cases, has demonstrated its effectiveness. For this study the support has been provided by Grant of Russian Science Foundation (№14-37-00053).

Alternative configurations of Quantile Regression for estimating predictive uncertainty in water level forecasts for the Upper Severn River: a comparison

NASA Astrophysics Data System (ADS)

Lopez, Patricia; Verkade, Jan; Weerts, Albrecht; Solomatine, Dimitri

2014-05-01

Hydrological forecasting is subject to many sources of uncertainty, including those originating in initial state, boundary conditions, model structure and model parameters. Although uncertainty can be reduced, it can never be fully eliminated. Statistical post-processing techniques constitute an often used approach to estimate the hydrological predictive uncertainty, where a model of forecast error is built using a historical record of past forecasts and observations. The present study focuses on the use of the Quantile Regression (QR) technique as a hydrological post-processor. It estimates the predictive distribution of water levels using deterministic water level forecasts as predictors. This work aims to thoroughly verify uncertainty estimates using the implementation of QR that was applied in an operational setting in the UK National Flood Forecasting System, and to inter-compare forecast quality and skill in various, differing configurations of QR. These configurations are (i) 'classical' QR, (ii) QR constrained by a requirement that quantiles do not cross, (iii) QR derived on time series that have been transformed into the Normal domain (Normal Quantile Transformation - NQT), and (iv) a piecewise linear derivation of QR models. The QR configurations are applied to fourteen hydrological stations on the Upper Severn River with different catchments characteristics. Results of each QR configuration are conditionally verified for progressively higher flood levels, in terms of commonly used verification metrics and skill scores. These include Brier's probability score (BS), the continuous ranked probability score (CRPS) and corresponding skill scores as well as the Relative Operating Characteristic score (ROCS). Reliability diagrams are also presented and analysed. The results indicate that none of the four Quantile Regression configurations clearly outperforms the others.

Cardiovascular cast model fabrication and casting effectiveness evaluation in fetus with severe congenital heart disease or normal heart.

PubMed

Wang, Yu; Cao, Hai-yan; Xie, Ming-xing; He, Lin; Han, Wei; Hong, Liu; Peng, Yuan; Hu, Yun-fei; Song, Ben-cai; Wang, Jing; Wang, Bin; Deng, Cheng

2016-04-01

To investigate the application and effectiveness of vascular corrosion technique in preparing fetal cardiovascular cast models, 10 normal fetal heart specimens with other congenital disease (control group) and 18 specimens with severe congenital heart disease (case group) from induced abortions were enrolled in this study from March 2013 to June 2015 in our hospital. Cast models were prepared by injecting casting material into vascular lumen to demonstrate real geometries of fetal cardiovascular system. Casting effectiveness was analyzed in terms of local anatomic structures and different anatomical levels (including overall level, atrioventricular and great vascular system, left-sided and right-sided heart), as well as different trimesters of pregnancy. In our study, all specimens were successfully casted. Casting effectiveness analysis of local anatomic structures showed a mean score from 1.90±1.45 to 3.60±0.52, without significant differences between case and control groups in most local anatomic structures except left ventricle, which had a higher score in control group (P=0.027). Inter-group comparison of casting effectiveness in different anatomical levels showed no significant differences between the two groups. Intra-group comparison also revealed undifferentiated casting effectiveness between atrioventricular and great vascular system, or left-sided and right-sided heart in corresponding group. Third-trimester group had a significantly higher perfusion score in great vascular system than second-trimester group (P=0.046), while the other anatomical levels displayed no such difference. Vascular corrosion technique can be successfully used in fabrication of fetal cardiovascular cast model. It is also a reliable method to demonstrate three-dimensional anatomy of severe congenital heart disease and normal heart in fetus.

Growth charts of human development.

PubMed

van Buuren, Stef

2014-08-01

This article reviews and compares two types of growth charts for tracking human development over age. Both charts assume the existence of a continuous latent variable, but relate to the observed data in different ways. The D-score diagram summarizes developmental indicators into a single aggregate score measuring global development. The relations between the indicators should be consistent with the Rasch model. If true, the D-score is a measure with interval scale properties, and allows for the calculation of meaningful differences both within and across age. The stage line diagram describes the natural development of ordinal indicators. The method models the transition probabilities between successive stages of the indicator as smoothly varying functions of age. The location of each stage is quantified by the mid-P-value. Both types of diagrams assist in identifying early and delayed development, as well as finding differences in tempo. The relevant techniques are illustrated to track global development during infancy and early childhood (0-2 years) and Tanner pubertal stages (8-21 years). New reference values for both applications are provided. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Equipercentile Test Equating: The Effects of Presmoothing and Postsmoothing on the Magnitude of Sample-Dependent Errors.

DTIC Science & Technology

1985-04-01

EM 32 12 MICROCOP REOUTO TETCHR NTOA B URA FSA4ARS16- AFHRL-TR-84-64 9 AIR FORCE 6 __ H EQUIPERCENTILE TEST EQUATING: THE EFFECTS OF PRESMOOTHING AND...combined or compound presmoother and a presmoothing method based on a particular model of test scores. Of the seven methods of presmoothing the score...unsmoothed distributions, the smoothing of that sequence of differences by the same compound method, and, finally, adding the smoothed differences back

Antiretroviral therapy CNS penetration and HIV-1-associated CNS disease.

PubMed

Garvey, L; Winston, A; Walsh, J; Post, F; Porter, K; Gazzard, B; Fisher, M; Leen, C; Pillay, D; Hill, T; Johnson, M; Gilson, R; Anderson, J; Easterbrook, P; Bansi, L; Orkin, C; Ainsworth, J; Palfreeman, A; Gompels, M; Phillips, A N; Sabin, C A

2011-02-22

The impact of different antiretroviral agents on the risk of developing or surviving CNS disease remains unknown. The aim of this study was to investigate whether using antiretroviral regimens with higher CNS penetration effectiveness (CPE) scores was associated with reduced incidence of CNS disease and improved survival in the UK Collaborative HIV Cohort (CHIC) Study. Adults without previous CNS disease, who commenced combination antiretroviral therapy (cART) between 1996 and 2008, were included (n = 22,356). Initial and most recent cART CPE scores were calculated. CNS diseases were HIV encephalopathy (HIVe), progressive multifocal leukoencephalopathy (PML), cerebral toxoplasmosis (TOXO), and cryptococcal meningitis (CRYPTO). Incidence rates and overall survival were stratified by CPE score. A multivariable Poisson regression model was used to identify independent associations. The median (interquartile range) CPE score for initial cART regimen increased from 7 (5-8) in 1996-1997 to 9 (8-10) in 2000-2001 and subsequently declined to 6 (7-8) in 2006-2008. Differences in gender, HIV acquisition risk group, and ethnicity existed between CPE score strata. A total of 251 subjects were diagnosed with a CNS disease (HIVe 80; TOXO 59; CRYPTO 56; PML 54). CNS diseases occurred more frequently in subjects prescribed regimens with CPE scores ≤ 4, and less frequently in those with scores ≥ 10; however, these differences were nonsignificant. Initial and most recent cART CPE scores ≤ 4 were independently associated with increased risk of death. Clinical status at time of commencing cART influences antiretroviral selection and CPE score. This information should be considered when utilizing CPE scores for retrospective analyses.

From scores to face templates: a model-based approach.

PubMed

Mohanty, Pranab; Sarkar, Sudeep; Kasturi, Rangachar

2007-12-01

Regeneration of templates from match scores has security and privacy implications related to any biometric authentication system. We propose a novel paradigm to reconstruct face templates from match scores using a linear approach. It proceeds by first modeling the behavior of the given face recognition algorithm by an affine transformation. The goal of the modeling is to approximate the distances computed by a face recognition algorithm between two faces by distances between points, representing these faces, in an affine space. Given this space, templates from an independent image set (break-in) are matched only once with the enrolled template of the targeted subject and match scores are recorded. These scores are then used to embed the targeted subject in the approximating affine (non-orthogonal) space. Given the coordinates of the targeted subject in the affine space, the original template of the targeted subject is reconstructed using the inverse of the affine transformation. We demonstrate our ideas using three, fundamentally different, face recognition algorithms: Principal Component Analysis (PCA) with Mahalanobis cosine distance measure, Bayesian intra-extrapersonal classifier (BIC), and a feature-based commercial algorithm. To demonstrate the independence of the break-in set with the gallery set, we select face templates from two different databases: Face Recognition Grand Challenge (FRGC) and Facial Recognition Technology (FERET) Database (FERET). With an operational point set at 1 percent False Acceptance Rate (FAR) and 99 percent True Acceptance Rate (TAR) for 1,196 enrollments (FERET gallery), we show that at most 600 attempts (score computations) are required to achieve a 73 percent chance of breaking in as a randomly chosen target subject for the commercial face recognition system. With similar operational set up, we achieve a 72 percent and 100 percent chance of breaking in for the Bayesian and PCA based face recognition systems, respectively. With three different levels of score quantization, we achieve 69 percent, 68 percent and 49 percent probability of break-in, indicating the robustness of our proposed scheme to score quantization. We also show that the proposed reconstruction scheme has 47 percent more probability of breaking in as a randomly chosen target subject for the commercial system as compared to a hill climbing approach with the same number of attempts. Given that the proposed template reconstruction method uses distinct face templates to reconstruct faces, this work exposes a more severe form of vulnerability than a hill climbing kind of attack where incrementally different versions of the same face are used. Also, the ability of the proposed approach to reconstruct actual face templates of the users increases privacy concerns in biometric systems.

Sex-dependent correlations between the personality dimension of harm avoidance and the resting-state functional connectivity of amygdala subregions.

PubMed

Li, Ying; Qin, Wen; Jiang, Tianzi; Zhang, Yunting; Yu, Chunshui

2012-01-01

Harm avoidance (HA) is a personality dimension involving the tendency to respond intensely to signals of aversive stimuli. Many previous neuroimaging studies have associated HA scores with the structural and functional organization of the amygdala, but none of these studies have evaluated the correlation between HA score and amygdala resting-state functional connectivity (rsFC). Moreover, the amygdala is not a homogeneous structure, and it has been divided into several structurally and functionally distinct subregions. Investigating the associations between HA score and properties of subregions of the amygdala could greatly improve our understanding of HA. In the present study, using a large sample of 291 healthy young adults, we aimed to uncover correlations between HA scores and the rsFCs of each amygdala subregion and to uncover possible sex-based differences in these correlations. We found that subregions of the amygdala showed different rsFC patterns, which contributed differently to individual HA scores. More specifically, HA scores were correlated with rsFCs between the laterobasal amygdala subregion and temporal and occipital cortices related to emotional information input, between the centromedial subregion and the frontal cortices associated with emotional output control, and between the superficial subregion and the frontal and temporal areas involved in both functions. Moreover, significant gender-based differences were uncovered in these correlations. Our findings provide a more detailed model of association between HA scores and amygdala rsFC, extend our understanding of the connectivity of subregions of the amygdala, and confirm sex-based differences in HA associations.

Monte Carlo simulation of expert judgments on human errors in chemical analysis--a case study of ICP-MS.

PubMed

Kuselman, Ilya; Pennecchi, Francesca; Epstein, Malka; Fajgelj, Ales; Ellison, Stephen L R

2014-12-01

Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors. Copyright © 2014 Elsevier B.V. All rights reserved.

The Contributions of Memory and Vocabulary to Non-Verbal Ability Scores in Adolescents with Intellectual Disability

PubMed Central

Mungkhetklang, Chantanee; Bavin, Edith L.; Crewther, Sheila G.; Goharpey, Nahal; Parsons, Carl

2016-01-01

It is usually assumed that performance on non-verbal intelligence tests reflects visual cognitive processing and that aspects of working memory (WM) will be involved. However, the unique contribution of memory to non-verbal scores is not clear, nor is the unique contribution of vocabulary. Thus, we aimed to investigate these contributions. Non-verbal test scores for 17 individuals with intellectual disability (ID) and 39 children with typical development (TD) of similar mental age were compared to determine the unique contribution of visual and verbal short-term memory (STM) and WM and the additional variance contributed by vocabulary scores. No significant group differences were found in the non-verbal test scores or receptive vocabulary scores, but there was a significant difference in expressive vocabulary. Regression analyses indicate that for the TD group STM and WM (both visual and verbal) contributed similar variance to the non-verbal scores. For the ID group, visual STM and verbal WM contributed most of the variance to the non-verbal test scores. The addition of vocabulary scores to the model contributed greater variance for both groups. More unique variance was contributed by vocabulary than memory for the TD group, whereas for the ID group memory contributed more than vocabulary. Visual and auditory memory and vocabulary contributed significantly to solving visual non-verbal problems for both the TD group and the ID group. However, for each group, there were different weightings of these variables. Our findings indicate that for individuals with TD, vocabulary is the major factor in solving non-verbal problems, not memory, whereas for adolescents with ID, visual STM, and verbal WM are more influential than vocabulary, suggesting different pathways to achieve solutions to non-verbal problems. PMID:28082922

A comparison of health utility scores calculated using United Kingdom and Canadian preference weights in persons with alzheimer's disease and their caregivers.

PubMed

Fang, Mingying; Oremus, Mark; Tarride, Jean-Eric; Raina, Parminder

2016-07-18

The use of the EQ-5D to asses the economic benefits of health technologies has led to questions about the cross-population transferability of preference weights to calculate health utility scores. The aim of this study is to investigate whether the use of UK and Canadian preference weights will lead to the calculation of different health utility scores in a sample of persons with Alzheimer's disease (AD) and their primary informal caregivers. We recruited 216 patient-caregiver dyads from nine geriatric and memory clinics across Canada. Participants used the EQ-5D-3L to rate their health-related quality-of-life (HRQoL). EQ-5D-3L responses were transformed into health utility scores using UK and Canadian preference weights. The levels of agreement between the two sets of scores were assessed using intraclass correlation coefficients (ICCs). Bland-Altman plots depicted individual-level differences between the two sets of scores. Differences in health utility scores were tested using the Wilcoxon signed rank sum test. A generalized linear model with a gamma distribution was used to examine whether participants' socio-demographic characteristics were associated with their health utility scores. The distributions of health utility scores derived from both the UK and Canadian preference weights were skewed to the left. The intraclass correlation coefficient was 0.94 (95 % CI: 0.92, 0.95) for persons with AD and 0.92 (95 % CI: 0.88, 0.94) for the caregivers. The Canadian weights yielded slightly higher median health utility scores than the UK weights for caregivers (median difference: 0.009; 95 % confidence interval: 0.007, 0.013). This finding persisted after stratifying by disease severity. Few socio-demographic characteristics were associated with the two sets of health utility scores. Health utility scores exhibited small and clinically unimportant differences when calculated with UK versus Canadian preference weights in persons with AD and their caregivers. The original UK and Canadian population samples used to obtain the preference weights valued health states similarly.

A novel early risk assessment tool for detecting clinical outcomes in patients with heat-related illness (J-ERATO score): Development and validation in independent cohorts in Japan.

PubMed

Hayashida, Kei; Kondo, Yutaka; Hifumi, Toru; Shimazaki, Junya; Oda, Yasutaka; Shiraishi, Shinichiro; Fukuda, Tatsuma; Sasaki, Junichi; Shimizu, Keiki

2018-01-01

We sought to develop a novel risk assessment tool to predict the clinical outcomes after heat-related illness. Prospective, multicenter observational study. Patients who transferred to emergency hospitals in Japan with heat-related illness were registered. The sample was divided into two parts: 60% to construct the score and 40% to validate it. A binary logistic regression model was used to predict hospital admission as a primary outcome. The resulting model was transformed into a scoring system. A total of 3,001 eligible patients were analyzed. There was no difference in variables between development and validation cohorts. Based on the result of a logistic regression model in the development phase (n = 1,805), the J-ERATO score was defined as the sum of the six binary components in the prehospital setting (respiratory rate≥22 /min, Glasgow coma scale<15, systolic blood pressure≤100 mmHg, heart rate≥100 bpm, body temperature≥38°C, and age≥65 y), for a total score ranging from 0 to 6. In the validation phase (n = 1,196), the score had excellent discrimination (C-statistic 0.84; 95% CI 0.79-0.89, p<0.0001) and calibration (P>0.2 by Hosmer-Lemeshow test). The observed proportion of hospital admission increased with increasing J-ERATO score (score = 0, 5.0%; score = 1, 15.0%; score = 2, 24.6%; score = 3, 38.6%; score = 4, 68.0%; score = 5, 85.2%; score = 6, 96.4%). Multivariate analyses showed that the J-ERATO score was an independent positive predictor of hospital admission (adjusted OR, 2.43; 95% CI, 2.06-2.87; P<0.001), intensive care unit (ICU) admission (3.73; 2.95-4.72; P<0.001) and in-hospital mortality (1.65; 1.18-2.32; P = 0.004). The J-ERATO score is simply assessed and can facilitate the identification of patients with higher risk of heat-related hospitalization. This scoring system is also significantly associated with the higher likelihood of ICU admission and in-hospital mortality after heat-related hospitalization.

Proposal and validation of a new model to estimate survival for hepatocellular carcinoma patients.

PubMed

Liu, Po-Hong; Hsu, Chia-Yang; Hsia, Cheng-Yuan; Lee, Yun-Hsuan; Huang, Yi-Hsiang; Su, Chien-Wei; Lee, Fa-Yauh; Lin, Han-Chieh; Huo, Teh-Ia

2016-08-01

The survival of hepatocellular carcinoma (HCC) patients is heterogeneous. We aim to develop and validate a simple prognostic model to estimate survival for HCC patients (MESH score). A total of 3182 patients were randomised into derivation and validation cohort. Multivariate analysis was used to identify independent predictors of survival in the derivation cohort. The validation cohort was employed to examine the prognostic capabilities. The MESH score allocated 1 point for each of the following parameters: large tumour (beyond Milan criteria), presence of vascular invasion or metastasis, Child-Turcotte-Pugh score ≥6, performance status ≥2, serum alpha-fetoprotein level ≥20 ng/ml, and serum alkaline phosphatase ≥200 IU/L, with a maximal of 6 points. In the validation cohort, significant survival differences were found across all MESH scores from 0 to 6 (all p < 0.01). The MESH system was associated with the highest homogeneity and lowest corrected Akaike information criterion compared with Barcelona Clínic Liver Cancer, Hong Kong Liver Cancer (HKLC), Cancer of the Liver Italian Program, Taipei Integrated Scoring and model to estimate survival in ambulatory HCC Patients systems. The prognostic accuracy of the MESH scores remained constant in patients with hepatitis B- or hepatitis C-related HCC. The MESH score can also discriminate survival for patients from early to advanced stages of HCC. This newly proposed simple and accurate survival model provides enhanced prognostic accuracy for HCC. The MESH system is a useful supplement to the BCLC and HKLC classification schemes in refining treatment strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simple new risk score model for adult cardiac extracorporeal membrane oxygenation: simple cardiac ECMO score.

PubMed

Peigh, Graham; Cavarocchi, Nicholas; Keith, Scott W; Hirose, Hitoshi

2015-10-01

Although the use of cardiac extracorporeal membrane oxygenation (ECMO) is increasing in adult patients, the field lacks understanding of associated risk factors. While standard intensive care unit risk scores such as SAPS II (simplified acute physiology score II), SOFA (sequential organ failure assessment), and APACHE II (acute physiology and chronic health evaluation II), or disease-specific scores such as MELD (model for end-stage liver disease) and RIFLE (kidney risk, injury, failure, loss of function, ESRD) exist, they may not apply to adult cardiac ECMO patients as their risk factors differ from variables used in these scores. Between 2010 and 2014, 73 ECMOs were performed for cardiac support at our institution. Patient demographics and survival were retrospectively analyzed. A new easily calculated score for predicting ECMO mortality was created using identified risk factors from univariate and multivariate analyses, and model discrimination was compared with other scoring systems. Cardiac ECMO was performed on 73 patients (47 males and 26 females) with a mean age of 48 ± 14 y. Sixty-four percent of patients (47/73) survived ECMO support. Pre-ECMO SAPS II, SOFA, APACHE II, MELD, RIFLE, PRESERVE, and ECMOnet scores, were not correlated with survival. Univariate analysis of pre-ECMO risk factors demonstrated that increased lactate, renal dysfunction, and postcardiotomy cardiogenic shock were risk factors for death. Applying these data into a new simplified cardiac ECMO score (minimal risk = 0, maximal = 5) predicted patient survival. Survivors had a lower risk score (1.8 ± 1.2) versus the nonsurvivors (3.0 ± 0.99), P < 0.0001. Common intensive care unit or disease-specific risk scores calculated for cardiac ECMO patients did not correlate with ECMO survival, whereas a new simplified cardiac ECMO score provides survival predictability. Copyright © 2015 Elsevier Inc. All rights reserved.

The role of three-dimensional printed models of skull in anatomy education: a randomized controlled trail.

PubMed

Chen, Shi; Pan, Zhouxian; Wu, Yanyan; Gu, Zhaoqi; Li, Man; Liang, Ze; Zhu, Huijuan; Yao, Yong; Shui, Wuyang; Shen, Zhen; Zhao, Jun; Pan, Hui

2017-04-03

Three-dimensional (3D) printed models represent educational tools of high quality compared with traditional teaching aids. Colored skull models were produced by 3D printing technology. A randomized controlled trial (RCT) was conducted to compare the learning efficiency of 3D printed skulls with that of cadaveric skulls and atlas. Seventy-nine medical students, who never studied anatomy, were randomized into three groups by drawing lots, using 3D printed skulls, cadaveric skulls, and atlas, respectively, to study the anatomical structures in skull through an introductory lecture and small group discussions. All students completed identical tests, which composed of a theory test and a lab test, before and after a lecture. Pre-test scores showed no differences between the three groups. In post-test, the 3D group was better than the other two groups in total score (cadaver: 29.5 [IQR: 25-33], 3D: 31.5 [IQR: 29-36], atlas: 27.75 [IQR: 24.125-32]; p = 0.044) and scores of lab test (cadaver: 14 [IQR: 10.5-18], 3D: 16.5 [IQR: 14.375-21.625], atlas: 14.5 [IQR: 10-18.125]; p = 0.049). Scores involving theory test, however, showed no difference between the three groups. In this RCT, an inexpensive, precise and rapidly-produced skull model had advantages in assisting anatomy study, especially in structure recognition, compared with traditional education materials.

Baseline Levels, and Changes Over Time in Body Mass Index and Fasting Insulin, and Their Relationship to Change in Metabolic Trait Clustering

PubMed Central

Sullivan, Lisa M.; Fox, Caroline S.; Wilson, Peter W.F.; Nathan, David M.; Vasan, Ramachandran S.; D'Agostino, Ralph B.; Meigs, James B.

2014-01-01

Abstract Background: Multiple abnormal metabolic traits are found together or “cluster” within individuals more often than is predicted by chance. The individual and combined role of adiposity and insulin resistance (IR) on metabolic trait clustering is uncertain. We tested the hypothesis that change in trait clustering is a function of both baseline level and change in these measures. Methods: In 2616 nondiabetic Framingham Offspring Study participants, body mass index (BMI) and fasting insulin were related to a within-person 7-year change in a trait score of 0–4 Adult Treatment Panel III metabolic syndrome traits (hypertension, high triglycerides, low high-density lipoprotein cholesterol, hyperglycemia). Results: At baseline assessment, mean trait score was 1.4 traits, and 7-year mean (SEM) change in trait score was +0.25 (0.02) traits, P<0.0001. In models with BMI predictors only, for every quintile difference in baseline BMI, the 7-year trait score increase was 0.14 traits, and for every quintile increase in BMI during 7-year follow-up, the trait score increased by 0.3 traits. Baseline level and change in fasting insulin were similarly related to trait score change. In models adjusted for age–sex–baseline cluster score, 7-year change in trait score was significantly related to both a 1-quintile difference in baseline BMI (0.07 traits) and fasting insulin (0.18 traits), and to both a 1-quintile 7-year increase in BMI (0.21 traits) and fasting insulin (0.18 traits). Conclusions: Change in metabolic trait clustering was significantly associated with baseline levels and changes in both BMI and fasting insulin, highlighting the importance of both obesity and IR in the clustering of metabolic traits. PMID:25007010

Evaluation of a Jugular Venipuncture Alpaca Model to Teach the Technique of Blood Sampling in Adult Alpacas.

PubMed

Rousseau, Marjolaine; Beauchamp, Guy; Nichols, Sylvain

The effectiveness of teaching aids in veterinary medical education is not often assessed rigorously. The objective in the present study was to evaluate the effectiveness of a commercially available jugular venipuncture alpaca model as a complementary tool to teach veterinary students how to perform venipuncture in adult alpacas. We hypothesized that practicing on the model would allow veterinary students to draw blood in alpacas more rapidly with fewer attempts than students without previous practice on the model. Thirty-six third-year veterinary students were enrolled and randomly allocated to the model (group M; n=18) or the control group (group C; n=18). The venipuncture technique was taught to all students on day 0. Students in group M practiced on the model on day 2. On day 5, an evaluator blinded to group allocation evaluated the students' venipuncture skills during a practical examination using live alpacas. Success was defined as the aspiration of a 6-ml sample of blood. Measured outcomes included number of attempts required to achieve success (success score), total procedural time, and overall qualitative score. Success scores, total procedural time, and overall scores did not differ between groups. Use of restless alpacas reduced performance. The jugular venipuncture alpaca model failed to improve jugular venipuncture skills in this student population. Lack of movement represents a significant weakness of this training model.

A model for the adoption of ICT by health workers in Africa.

PubMed

Jimoh, Lanrewaju; Pate, Muhammad A; Lin, Li; Schulman, Kevin A

2012-11-01

To investigate the potential of information and communication technology (ICT) adoption among maternal and child health workers in rural Nigeria. A prospective, quantitative survey design was used to collect data from quasi-randomly selected clusters of 25 rural health facilities in 5 of the 36 states in Nigeria over a 2-month period from June to July 2010. A total of 200 maternal and child health workers were included in the survey, and the data were analyzed using a modified theory of acceptance model (TAM). There was no significant difference between ICT knowledge and attitude scores across states. There were significant differences in perceived ease of use (P<.001) and perceived usefulness scores (P=.001) across states. Midwives reported higher scores on all the constructs but a lower score on endemic barriers (which is a more positive outcome). However, the differences were only statistically significant for perceived usefulness (P=.05) and endemic barriers (P<.001). Regression analysis revealed that there was no interaction between worker group and age. Older workers were likely to have lower scores on knowledge and attitude but higher scores on perceived ease of use and perceived usefulness. Lastly, we found that worker preference for ICT application in health varied across worker groups and conflicted with government/employer priorities. Although the objective of this study was exploratory, the results provide insight into the intricacies involved in the deployment of ICT in low-resource settings. Use of an expanded TAM should be considered as a mandatory part of any pre-implementation study of ICT among health workers in sub-Saharan Africa. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Quantitative prediction of drug side effects based on drug-related features.

PubMed

Niu, Yanqing; Zhang, Wen

2017-09-01

Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.

Sub-classification of Advanced-Stage Hepatocellular Carcinoma: A Cohort Study Including 612 Patients Treated with Sorafenib.

PubMed

Yoo, Jeong-Ju; Chung, Goh Eun; Lee, Jeong-Hoon; Nam, Joon Yeul; Chang, Young; Lee, Jeong Min; Lee, Dong Ho; Kim, Hwi Young; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-04-01

Advanced hepatocellular carcinoma (HCC) is associated with various clinical conditions including major vessel invasion, metastasis, and poor performance status. The aim of this study was to establish a prognostic scoring system and to propose a sub-classification of the Barcelona-Clinic Liver Cancer (BCLC) stage C. This retrospective study included consecutive patientswho received sorafenib for BCLC stage C HCC at a single tertiary hospital in Korea. A Cox proportional hazard model was used to develop a scoring system, and internal validationwas performed by a 5-fold cross-validation. The performance of the model in predicting risk was assessed by the area under the curve and the Hosmer-Lemeshow test. A total of 612 BCLC stage C HCC patients were sub- classified into strata depending on their performance status. Five independent prognostic factors (Child-Pugh score, α-fetoprotein, tumor type, extrahepatic metastasis, and portal vein invasion) were identified and used in the prognostic scoring system. This scoring system showed good discrimination (area under the receiver operating characteristic curve, 0.734 to 0.818) and calibration functions (both p < 0.05 by the Hosmer-Lemeshow test at 1 month and 12 months, respectively). The differences in survival among the different risk groups classified by the total score were significant (p < 0.001 by the log-rank test in both the Eastern Cooperative Oncology Group 0 and 1 strata). The heterogeneity of patientswith BCLC stage C HCC requires sub-classification of advanced HCC. A prognostic scoring system with five independent factors is useful in predicting the survival of patients with BCLC stage C HCC.

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

Assessing Sexual Dicromatism: The Importance of Proper Parameterization in Tetrachromatic Visual Models

PubMed Central

Janisse, Kevyn; Doucet, Stéphanie M.

2017-01-01

Perceptual models of animal vision have greatly contributed to our understanding of animal-animal and plant-animal communication. The receptor-noise model of color contrasts has been central to this research as it quantifies the difference between two colors for any visual system of interest. However, if the properties of the visual system are unknown, assumptions regarding parameter values must be made, generally with unknown consequences. In this study, we conduct a sensitivity analysis of the receptor-noise model using avian visual system parameters to systematically investigate the influence of variation in light environment, photoreceptor sensitivities, photoreceptor densities, and light transmission properties of the ocular media and the oil droplets. We calculated the chromatic contrast of 15 plumage patches to quantify a dichromatism score for 70 species of Galliformes, a group of birds that display a wide range of sexual dimorphism. We found that the photoreceptor densities and the wavelength of maximum sensitivity of the short-wavelength-sensitive photoreceptor 1 (SWS1) can change dichromatism scores by 50% to 100%. In contrast, the light environment, transmission properties of the oil droplets, transmission properties of the ocular media, and the peak sensitivities of the cone photoreceptors had a smaller impact on the scores. By investigating the effect of varying two or more parameters simultaneously, we further demonstrate that improper parameterization could lead to differences between calculated and actual contrasts of more than 650%. Our findings demonstrate that improper parameterization of tetrachromatic visual models can have very large effects on measures of dichromatism scores, potentially leading to erroneous inferences. We urge more complete characterization of avian retinal properties and recommend that researchers either determine whether their species of interest possess an ultraviolet or near-ultraviolet sensitive SWS1 photoreceptor, or present models for both. PMID:28076391

The Sport Participation Model Questionnaire: A Tool for the Assessment of Sport Orientations

ERIC Educational Resources Information Center

Aicinena, Steve; Eldridge, James

2006-01-01

The Sport Participation Model Questionnaire (SPMQ) was given to two hundred and sixty-four subjects to determine if significant differences existed in the composite scores of parents, coaches, youth sport participants, high school participants and college students; if the groups differed in their responses to pooled items; and if subject groups…

Robust scoring functions for protein-ligand interactions with quantum chemical charge models.

PubMed

Wang, Jui-Chih; Lin, Jung-Hsin; Chen, Chung-Ming; Perryman, Alex L; Olson, Arthur J

2011-10-24

Ordinary least-squares (OLS) regression has been used widely for constructing the scoring functions for protein-ligand interactions. However, OLS is very sensitive to the existence of outliers, and models constructed using it are easily affected by the outliers or even the choice of the data set. On the other hand, determination of atomic charges is regarded as of central importance, because the electrostatic interaction is known to be a key contributing factor for biomolecular association. In the development of the AutoDock4 scoring function, only OLS was conducted, and the simple Gasteiger method was adopted. It is therefore of considerable interest to see whether more rigorous charge models could improve the statistical performance of the AutoDock4 scoring function. In this study, we have employed two well-established quantum chemical approaches, namely the restrained electrostatic potential (RESP) and the Austin-model 1-bond charge correction (AM1-BCC) methods, to obtain atomic partial charges, and we have compared how different charge models affect the performance of AutoDock4 scoring functions. In combination with robust regression analysis and outlier exclusion, our new protein-ligand free energy regression model with AM1-BCC charges for ligands and Amber99SB charges for proteins achieve lowest root-mean-squared error of 1.637 kcal/mol for the training set of 147 complexes and 2.176 kcal/mol for the external test set of 1427 complexes. The assessment for binding pose prediction with the 100 external decoy sets indicates very high success rate of 87% with the criteria of predicted root-mean-squared deviation of less than 2 Å. The success rates and statistical performance of our robust scoring functions are only weakly class-dependent (hydrophobic, hydrophilic, or mixed).

Item hierarchy-based analysis of the Rivermead Mobility Index resulted in improved interpretation and enabled faster scoring in patients undergoing rehabilitation after stroke.

PubMed

Roorda, Leo D; Green, John R; Houwink, Annemieke; Bagley, Pam J; Smith, Jane; Molenaar, Ivo W; Geurts, Alexander C

2012-06-01

To enable improved interpretation of the total score and faster scoring of the Rivermead Mobility Index (RMI) by studying item ordering or hierarchy and formulating start-and-stop rules in patients after stroke. Cohort study. Rehabilitation center in the Netherlands; stroke rehabilitation units and the community in the United Kingdom. Item hierarchy of the RMI was studied in an initial group of patients (n=620; mean age ± SD, 69.2±12.5y; 297 [48%] men; 304 [49%] left hemisphere lesion, and 269 [43%] right hemisphere lesion), and the adequacy of the item hierarchy-based start-and-stop rules was checked in a second group of patients (n=237; mean age ± SD, 60.0±11.3y; 139 [59%] men; 103 [44%] left hemisphere lesion, and 93 [39%] right hemisphere lesion) undergoing rehabilitation after stroke. Not applicable. Mokken scale analysis was used to investigate the fit of the double monotonicity model, indicating hierarchical item ordering. The percentages of patients with a difference between the RMI total score and the scores based on the start-and-stop rules were calculated to check the adequacy of these rules. The RMI had good fit of the double monotonicity model (coefficient H(T)=.87). The interpretation of the total score improved. Item hierarchy-based start-and-stop rules were formulated. The percentages of patients with a difference between the RMI total score and the score based on the recommended start-and-stop rules were 3% and 5%, respectively. Ten of the original 15 items had to be scored after applying the start-and-stop rules. Item hierarchy was established, enabling improved interpretation and faster scoring of the RMI. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

A Comparison of Student Understanding of Seasons Using Inquiry and Didactic Teaching Methods

NASA Astrophysics Data System (ADS)

Ashcraft, Paul G.

2006-02-01

Student performance on open-ended questions concerning seasons in a university physical science content course was examined to note differences between classes that experienced inquiry using a 5-E lesson planning model and those that experienced the same content with a traditional, didactic lesson. The class examined is a required content course for elementary education majors and understanding the seasons is part of the university's state's elementary science standards. The two self-selected groups of students showed no statistically significant differences in pre-test scores, while there were statistically significant differences between the groups' post-test scores with those who participated in inquiry-based activities scoring higher. There were no statistically significant differences between the pre-test and the post-test for the students who experienced didactic teaching, while there were statistically significant improvements for the students who experienced the 5-E lesson.

Associations between body condition, rumen fill, diarrhoea and lameness and ruminal acidosis in Australian dairy herds.

PubMed

Bramley, E; Costa, N D; Fulkerson, W J; Lean, I J

2013-11-01

To investigate associations between ruminal acidosis and body condition score (BCS), prevalence of poor rumen fill, diarrhoea and lameness in dairy cows in New South Wales and Victoria, Australia. This was a cross-sectional study conducted in 100 dairy herds in five regions of Australia. Feeding practices, diets and management practices of herds were assessed. Lactating cows within herds were sampled for rumen biochemistry (n = 8 per herd) and scored for body condition, rumen fill and locomotion (n = 15 per herd). The consistency of faecal pats (n = 20 per herd) from the lactating herd was also scored. A perineal faecal staining score was given to each herd. Herds were classified as subclinically acidotic (ACID), suboptimal (SO) and non-acidotic (Normal) when ≥3/8 cows per herd were allocated to previously defined categories based on rumen biochemical measures. Multivariate logistic regression models were used to examine associations between the prevalence of conditions within a herd and explanatory variables. Median BCS and perineal staining score were not associated with herd category (p >0.05). In the multivariate models, herds with a high prevalence of low rumen fill scores (≤2/5) were more likely to be categorised Normal than SO with an associated increased risk of 69% (p = 0.05). Herds that had a greater prevalence of lame cows (locomotion scores ≥3/5), had 103% higher risk of being categorised as ACID than SO (p = 0.034). In a multivariate logistic regression model, with herd modelled as a random effect, an increase of 1% of pasture in the diet was associated with a 5.5% increase in risk of high faecal scores (≥4/5) indicating diarrhoea (p = 0.001). This study confirmed that herd categories based on rumen function are associated with biological outcomes consistent with acidosis. Herds that had a higher risk of lameness also had a much higher risk of being categorised ACID than SO. Herds with a high prevalence of low rumen scores were more likely to be categorised Normal than SO. The findings indicate that differences in rumen metabolism identified for herd categories ACID, SO and Normal were associated with differences in disease risk and physiology. The study also identified an association between pasture feeding and higher faecal scores. This study suggests that there is a challenge for farmers seeking to increase milk production of cows on pasture to maintain the health of cattle.

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy.

PubMed

Alexander, Joe; Edwards, Roger A; Savoldelli, Alberto; Manca, Luigi; Grugni, Roberto; Emir, Birol; Whalen, Ed; Watt, Stephen; Brodsky, Marina; Parsons, Bruce

2017-07-20

More patient-specific medical care is expected as more is learned about variations in patient responses to medical treatments. Analytical tools enable insights by linking treatment responses from different types of studies, such as randomized controlled trials (RCTs) and observational studies. Given the importance of evidence from both types of studies, our goal was to integrate these types of data into a single predictive platform to help predict response to pregabalin in individual patients with painful diabetic peripheral neuropathy (pDPN). We utilized three pivotal RCTs of pregabalin (398 North American patients) and the largest observational study of pregabalin (3159 German patients). We implemented a hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM) technique, thereby creating a matched dataset. We then developed autoregressive moving average models (ARMAXs) to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method. Finally, we validated ARMAX models using Observational Study patients who had not matched with RCT patients, using t tests between observed and predicted pain scores. Cluster analysis yielded six clusters (287-777 patients each) with the following clustering variables: gender, age, pDPN duration, body mass index, depression history, pregabalin monotherapy, prior gabapentin use, baseline pain score, and baseline sleep interference. CEM yielded 1528 unique patients in the matched dataset. The reduction in global imbalance scores for the clusters after adding the RCT patients (ranging from 6 to 63% depending on the cluster) demonstrated that the process reduced the bias of covariates in five of the six clusters. ARMAX models of pain score performed well (R 2 : 0.85-0.91; root mean square errors: 0.53-0.57). t tests did not show differences between observed and predicted pain scores in the 1955 patients who had not matched with RCT patients. The combination of cluster analyses, CEM, and ARMAX modeling enabled strong predictive capabilities with respect to pain scores. Integrating RCT and Observational Study data using CEM enabled effective use of Observational Study data to predict patient responses.

Toward automated assessment of health Web page quality using the DISCERN instrument.

PubMed

Allam, Ahmed; Schulz, Peter J; Krauthammer, Michael

2017-05-01

As the Internet becomes the number one destination for obtaining health-related information, there is an increasing need to identify health Web pages that convey an accurate and current view of medical knowledge. In response, the research community has created multicriteria instruments for reliably assessing online medical information quality. One such instrument is DISCERN, which measures health Web page quality by assessing an array of features. In order to scale up use of the instrument, there is interest in automating the quality evaluation process by building machine learning (ML)-based DISCERN Web page classifiers. The paper addresses 2 key issues that are essential before constructing automated DISCERN classifiers: (1) generation of a robust DISCERN training corpus useful for training classification algorithms, and (2) assessment of the usefulness of the current DISCERN scoring schema as a metric for evaluating the performance of these algorithms. Using DISCERN, 272 Web pages discussing treatment options in breast cancer, arthritis, and depression were evaluated and rated by trained coders. First, different consensus models were compared to obtain a robust aggregated rating among the coders, suitable for a DISCERN ML training corpus. Second, a new DISCERN scoring criterion was proposed (features-based score) as an ML performance metric that is more reflective of the score distribution across different DISCERN quality criteria. First, we found that a probabilistic consensus model applied to the DISCERN instrument was robust against noise (random ratings) and superior to other approaches for building a training corpus. Second, we found that the established DISCERN scoring schema (overall score) is ill-suited to measure ML performance for automated classifiers. Use of a probabilistic consensus model is advantageous for building a training corpus for the DISCERN instrument, and use of a features-based score is an appropriate ML metric for automated DISCERN classifiers. The code for the probabilistic consensus model is available at https://bitbucket.org/A_2/em_dawid/ . © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Towards an understanding of dimensions, predictors, and gender gap in written composition

PubMed Central

Kim, Young-Suk; Al Otaiba, Stephanie; Wanzek, Jeanne; Gatlin, Brandy

2014-01-01

We had three aims in the present study: (1) to examine the dimensionality of various evaluative approaches to scoring writing samples (e.g., quality, productivity, and curriculum based writing [CBM]) , (2) to investigate unique language and cognitive predictors of the identified dimensions, and (3) to examine gender gap in the identified dimensions of writing. These questions were addressed using data from second and third grade students (N = 494). Data were analyzed using confirmatory factor analysis and multilevel modeling. Results showed that writing quality, productivity, and CBM scoring were dissociable constructs, but that writing quality and CBM scoring were highly related (r = .82). Language and cognitive predictors differed among the writing outcomes. Boys had lower writing scores than girls even after accounting for language, reading, attention, spelling, handwriting automaticity, and rapid automatized naming. Results are discussed in light of writing evaluation and a developmental model of writing. PMID:25937667

Comparison of gait and pathology outcomes of three meniscal procedures for induction of knee osteoarthritis in sheep.

PubMed

Cake, M A; Read, R A; Corfield, G; Daniel, A; Burkhardt, D; Smith, M M; Little, C B

2013-01-01

Meniscectomy (MX) of sheep induces a well-established animal model of human osteoarthritis (OA). This study compared the clinical (lameness) and pathological outcomes of unilateral, complete medial MX vs two less traumatic and more easily performed meniscal destabilisation procedures. Four-year old wethers (n = 6/group) underwent sham operation, cranial pole release (CPR), mid-body transection (MBT) or total MX of the medial meniscus. Joints were assessed for gross pathology (cartilage erosion and osteophytes), histomorphometry, two histopathology scoring methods (modified Mankin-type and Pritzker score), and immunohistology for ADAMTS- and MMP-cleaved neoepitopes, at 12 weeks post-op. Ground reaction forces (GRFs) were determined by force plate in a subset (n = 4/group) at baseline, 2.5, 8, and 12 weeks post-op. Gross pathology scores of operated groups differed significantly from sham animals (P < 0.05) but not from each other, though qualitative differences were noted: CPR sheep developed more cranial and focal lesions, while MBT and MX joints showed more widespread lesions and osteophyte formation. Similarly, histopathology scores were significantly elevated vs sham but did not differ between operated groups at P < 0.05, except for a trend for lower tibial cartilage histopathology in MBT consistent with the immunohistologic pattern of reduced aggrecanase-cleavage neoepitope in that model. CPR sheep developed less femoral subchondral sclerosis, suggesting some residual biomechanical effect from the destabilised but intact meniscus. Few significant differences were noted between operated groups in force plate analyses, though gait abnormalities appeared to be least in CPR sheep, and most persistent (>12 weeks) in MBT animals. The well-validated ovine MX model and the simpler meniscal destabilisation procedures resulted in broadly similar joint pathology and lameness. Meniscal CPR or MBT, as easier and more clinically relevant procedures, may represent preferred models for the induction of OA and evaluation of potential disease-modifying therapies. Copyright © 2012 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

The multidimensional nature of ageism: construct validity and group differences.

PubMed

Rupp, Deborah E; Vodanovich, Stephen J; Credé, Marcus

2005-06-01

The authors investigated the factor structure and construct validity of the Fraboni Scale of Ageism and the age and gender differences in ageism scores. Confirmatory factor analyses supported the multidimensional nature of FSA scores and generally corroborated the initial factor structure reported by M. Fraboni, with some notable exceptions. Essentially, the present findings were aligned with theoretical models of ageism that emphasize both cognitive facets and affective facets. That is, on the basis of their factor analytic findings, the authors redefined Fraboni's original factors of Antilocution, Avoidance, and Discrimination as Stereotypes, Separation, and Affective Attitudes, respectively, because of the clustering of items within factors. The revised 3-factor structure accounted for 36.4% of the variance in FSA scores. FSA factor scores significantly related to other scores from other measures of age-related attitudes, with higher correlations among factors that were similar in terms of their cognitive nature versus their affective nature. Finally, younger individuals and men had significantly higher ageism scores on the FSA than older individuals and women. The authors discussed the importance of adequately assessing ageism, with particular emphasis devoted to the understanding of age bias.

Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

PubMed

Rios, Anthony; Kavuluru, Ramakanth

2017-11-01

The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task. Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification. In this effort, we study ordinal regression problems with text data where misclassifications are penalized differently based on how far apart the ground truth and model predictions are on the ordinal scale. Specifically, we present our entries (methods and results) in the N-GRID shared task in predicting research domain criteria (RDoC) positive valence ordinal symptom severity scores (absent, mild, moderate, and severe) from psychiatric notes. We propose a novel convolutional neural network (CNN) model designed to handle ordinal regression tasks on psychiatric notes. Broadly speaking, our model combines an ordinal loss function, a CNN, and conventional feature engineering (wide features) into a single model which is learned end-to-end. Given interpretability is an important concern with nonlinear models, we apply a recent approach called locally interpretable model-agnostic explanation (LIME) to identify important words that lead to instance specific predictions. Our best model entered into the shared task placed third among 24 teams and scored a macro mean absolute error (MMAE) based normalized score (100·(1-MMAE)) of 83.86. Since the competition, we improved our score (using basic ensembling) to 85.55, comparable with the winning shared task entry. Applying LIME to model predictions, we demonstrate the feasibility of instance specific prediction interpretation by identifying words that led to a particular decision. In this paper, we present a method that successfully uses wide features and an ordinal loss function applied to convolutional neural networks for ordinal text classification specifically in predicting psychiatric symptom severity scores. Our approach leads to excellent performance on the N-GRID shared task and is also amenable to interpretability using existing model-agnostic approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

Training model for laparoscopic Heller and Dor fundoplication: a tool for laparoscopic skills training and assessment-construct validity using the GOALS score.

PubMed

Bellorin, Omar; Kundel, Anna; Sharma, Saurabh; Ramirez-Valderrama, Alexander; Lee, Paul

2016-08-01

Laparoscopic training demands practice. The transfer of laparoscopic skills from training models to real surgical procedures has been proven. The global operative assessment of laparoscopic skills (GOALS) score is a 5-item global rating scale developed to evaluate laparoscopic skills by direct observation. This scale has been used to demonstrate construct validity of several laparoscopic training models. Here, we present a low-cost model of laparoscopic Heller-Dor for advanced laparoscopic training. The aim of this study was to determine the capability of a training model for laparoscopic Heller-Dor to discriminate between different levels of laparoscopic expertise. The performance of two groups with different levels of expertise, novices (<30 laparoscopic procedures PGY1-2) and experts (>300 laparoscopic procedures PGY4-5) was assessed. All participants were instructed to perform two tasks (esophageal myotomy and fundoplication). All the performances were recorded in a digital format. A laparoscopic expert who was blinded to subject's identity evaluated the recordings using the GOALS score. Autonomy, one of the five items of GOALS, was removed since the evaluator and the trainee did not have interaction. The time required to finish each task was also recorded. Performance was compared using the Mann-Whitney U test (p < 0.05 was significant). Twenty subjects were evaluated: ten in each group, using the GOALS score. The mean total GOALS score for novices was 7.5 points (SD: 1.64) and 13.9 points (SD: 1.66) for experts (p < 0.05).The expert group was superior in each domain of the GOALS score compared to novices: depth perception (mean: 3.3 vs 2 p < 0.05), bimanual dexterity (mean 3.4 vs 2.1 p < 0.05), efficiency (mean 3.4 vs 1.7 p < 0.05) and tissue handling (mean 3.6 vs 1.7 p < 0.05). With regard to time, experts were superior in task 1 (mean 9.7 vs 14.9 min p < 0.05) and task 2 (mean 24 vs 47.1 min p < 0.05) compared to novices. The laparoscopic Heller-Dor training model has construct validity. The model may be used as a tool for training of the surgical resident.

A robust collagen scoring method for human liver fibrosis by second harmonic microscopy.

PubMed

Guilbert, Thomas; Odin, Christophe; Le Grand, Yann; Gailhouste, Luc; Turlin, Bruno; Ezan, Frédérick; Désille, Yoann; Baffet, Georges; Guyader, Dominique

2010-12-06

Second Harmonic Generation (SHG) microscopy offers the opportunity to image collagen of type I without staining. We recently showed that a simple scoring method, based on SHG images of histological human liver biopsies, correlates well with the Metavir assessment of fibrosis level (Gailhouste et al., J. Hepatol., 2010). In this article, we present a detailed study of this new scoring method with two different objective lenses. By using measurements of the objectives point spread functions and of the photomultiplier gain, and a simple model of the SHG intensity, we show that our scoring method, applied to human liver biopsies, is robust to the objective's numerical aperture (NA) for low NA, the choice of the reference sample and laser power, and the spatial sampling rate. The simplicity and robustness of our collagen scoring method may open new opportunities in the quantification of collagen content in different organs, which is of main importance in providing diagnostic information and evaluation of therapeutic efficiency.

Five-Factor Model personality disorder prototypes: a review of their development, validity, and comparison to alternative approaches.

PubMed

Miller, Joshua D

2012-12-01

In this article, the development of Five-Factor Model (FFM) personality disorder (PD) prototypes for the assessment of DSM-IV PDs are reviewed, as well as subsequent procedures for scoring individuals' FFM data with regard to these PD prototypes, including similarity scores and simple additive counts that are based on a quantitative prototype matching methodology. Both techniques, which result in very strongly correlated scores, demonstrate convergent and discriminant validity, and provide clinically useful information with regard to various forms of functioning. The techniques described here for use with FFM data are quite different from the prototype matching methods used elsewhere. © 2012 The Author. Journal of Personality © 2012, Wiley Periodicals, Inc.

Health-related quality of life of infants from ethnic minority groups: the Generation R Study.

PubMed

Flink, Ilse J E; Beirens, Tinneke M J; Looman, Caspar; Landgraf, Jeanne M; Tiemeier, Henning; Mol, Henriette A; Jaddoe, Vincent W V; Hofman, Albert; Mackenbach, Johan P; Raat, Hein

2013-04-01

To assess whether the health-related quality of life of infants from ethnic minority groups differs from the health-related quality of life of native Dutch infants and to evaluate whether infant health and family characteristics explain the potential differences. We included 4,506 infants participating in the Generation R Study, a longitudinal birth cohort. When the child was 12 months, parents completed the Infant Toddler Quality of Life Questionnaire (ITQOL); ITQOL scale scores in each ethnic subgroup were compared with scores in the Dutch reference population. Influence of infant health and family characteristics on ITQOL scale scores were evaluated using multivariate regression models. Infants from ethnic minority groups presented significantly lower ITQOL scale scores compared to the Dutch subgroup (e.g., Temperament and Moods scale: median score of Turkish subgroup, 70.8 (IQR, 15.3); median score of Dutch subgroup, 80.6 (IQR, 13.9; P < 0.001)). Infant health and family characteristics mediated an important part of the association between the ethnic minority status and infant health-related quality of life. However, these factors could not fully explain all the differences in the ITQOL scale scores. Parent-reported health-related quality of life is lower in infants from ethnic minority groups compared to native Dutch infants, which could partly be explained by infant health and by family characteristics.

The trend of changes in the evaluation scores of faculty members from administrators' and students' perspectives at the medical school over 10 years.

PubMed

Yamani, Nikoo; Changiz, Tahereh; Feizi, Awat; Kamali, Farahnaz

2018-01-01

To assess the trend of changes in the evaluation scores of faculty members and discrepancy between administrators' and students' perspectives in a medical school from 2006 to 2015. This repeated cross-sectional study was conducted on the 10-year evaluation scores of all faculty members of a medical school (n=579) in an urban area of Iran. Data on evaluation scores given by students and administrators and the total of these scores were evaluated. Data were analyzed using descriptive and inferential statistics including linear mixed effect models for repeated measures via the SPSS software. There were statistically significant differences between the students' and administrators' perspectives over time ( p <0.001). The mean of the total evaluation scores also showed a statistically significant change over time ( p <0.001). Furthermore, the mean of changes over time in the total evaluation score between different departments was statistically significant ( p <0.001). The trend of changes in the student's evaluations was clear and positive, but the trend of administrators' evaluation was unclear. Since the evaluation of faculty members is affected by many other factors, there is a need for more future studies.

Cross-cultural measurement equivalence of the 5-level EQ-5D (EQ-5D-5L) in patients with type 2 diabetes mellitus in Singapore.

PubMed

Wang, Ye; Tan, Ngiap-Chuan; Tay, Ee-Guan; Thumboo, Julian; Luo, Nan

2015-07-16

This study aimed to assess the measurement equivalence of the 5-level EQ-5D (EQ-5D-5L) among the English, Chinese, and Malay versions. A convenience sample of patients with type 2 diabetes mellitus were enrolled from a public primary health care institution in Singapore. The survey questionnaire comprised the EQ-5D-5L and questions assessing participants' socio-demographic and clinical characteristics. Multiple linear regression models were used to assess the difference in EQ-5D-5L index (calculated using an interim algorithm) and EQ-visual analog scale (EQ-VAS) scores across survey language (Chinese vs. English, Malay vs. English, and Malay vs. Chinese). Measurement equivalence was examined by comparing the 90% confidence interval of difference in the EQ-5D-5L index and EQ-VAS scores with a pre-determined equivalence margin. Multiple logistic regression models were used to assess the response patterns of the 5 Likert-type items of the EQ-5D-5L across survey language. Equivalence was demonstrated between the Chinese and English versions and between the Malay and English versions of the EQ-5D-5L index scores. Equivalence was also demonstrated between the Chinese and English versions and between the Malay and Chinese versions of the EQ-VAS scores. Equivalence could not be determined between the Malay and Chinese versions of the EQ-5D-5L index score and between the Malay and English versions of the EQ-VAS score. No significant difference was found in responses to EQ-5D-5L items between any languages, except that patients who chose to complete the Chinese version were more likely to report "no problems" in mobility compared to those who completed the Malay version of the questionnaire. This study provided evidence for the measurement equivalence of the different language versions of EQ-5D-5L in Singapore.

Risk selection into consumer-directed health plans: an analysis of family choices within large employers.

PubMed

McDevitt, Roland D; Haviland, Amelia M; Lore, Ryan; Laudenberger, Laura; Eisenberg, Matthew; Sood, Neeraj

2014-04-01

To identify the degree of selection into consumer-directed health plans (CDHPs) versus traditional plans over time, and factors that influence choice and temper risk selection. Sixteen large employers offering both CDHP and traditional plans during the 2004–2007 period, more than 200,000 families. We model CDHP choice with logistic regression; predictors include risk scores, in addition to family, choice setting, and plan characteristics. Additional models stratify by account type or single enrollee versus family. Risk scores, family characteristics, and enrollment decisions are derived from medical claims and enrollment files. Interviews with human resources executives provide additional data. CDHP risk scores were 74 percent of traditional plan scores in the first year, and this difference declined over time. Employer contributions to accounts and employee premium savings fostered CDHP enrollment and reduced risk selection. Having to make an active choice of plan increased CDHP enrollment but also increased risk selection. Risk selection was greater for singles than families and did not differ between HRA and HSA-based CDHPs. Risk selection was not severe and it was well managed. Employers have effective methods to encourage CDHP enrollment and temper selection against traditional plans.

Developmental Trajectories in Toddlers’ Self-restraint Predict Individual Differences in Executive Functions 14 Years Later: A Behavioral Genetic Analysis

PubMed Central

Friedman, Naomi P.; Miyake, Akira; Robinson, JoAnn L.; Hewitt, John K.

2011-01-01

We examined whether self-restraint in early childhood predicted individual differences in three executive functions (EFs; inhibiting prepotent responses, updating working memory, and shifting task sets) in late adolescence in a sample of ~950 twins. At ages 14, 20, 24, and 36 months, the children were shown an attractive toy and told not to touch it for 30 seconds. Latency to touch the toy increased with age, and latent class growth modeling distinguished two groups of children that differed in their latencies to touch the toy at all 4 time points. Using confirmatory factor analysis, the three EFs (measured with latent variables at age 17 years) were decomposed into a Common EF factor (isomorphic to response inhibition ability) and two factors specific to updating and shifting, respectively. Less restrained children had significantly lower scores on the Common EF factor, equivalent scores on the Updating-specific factor, and higher scores on the Shifting-specific factor than the more restrained children. The less restrained group also had lower IQ scores, but this effect was entirely mediated by the EF components. Twin models indicated that the associations were primarily genetic in origin for the Common EF variable but split between genetics and nonshared environment for the Shifting-specific variable. These results suggest a biological relation between individual differences in self-restraint and EFs, one that begins early in life and persists into late adolescence. PMID:21668099

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.

What does my patient's coronary artery calcium score mean? Combining information from the coronary artery calcium score with information from conventional risk factors to estimate coronary heart disease risk

PubMed Central

Pletcher, Mark J; Tice, Jeffrey A; Pignone, Michael; McCulloch, Charles; Callister, Tracy Q; Browner, Warren S

2004-01-01

Background The coronary artery calcium (CAC) score is an independent predictor of coronary heart disease. We sought to combine information from the CAC score with information from conventional cardiac risk factors to produce post-test risk estimates, and to determine whether the score may add clinically useful information. Methods We measured the independent cross-sectional associations between conventional cardiac risk factors and the CAC score among asymptomatic persons referred for non-contrast electron beam computed tomography. Using the resulting multivariable models and published CAC score-specific relative risk estimates, we estimated post-test coronary heart disease risk in a number of different scenarios. Results Among 9341 asymptomatic study participants (age 35–88 years, 40% female), we found that conventional coronary heart disease risk factors including age, male sex, self-reported hypertension, diabetes and high cholesterol were independent predictors of the CAC score, and we used the resulting multivariable models for predicting post-test risk in a variety of scenarios. Our models predicted, for example, that a 60-year-old non-smoking non-diabetic women with hypertension and high cholesterol would have a 47% chance of having a CAC score of zero, reducing her 10-year risk estimate from 15% (per Framingham) to 6–9%; if her score were over 100, however (a 17% chance), her risk estimate would be markedly higher (25–51% in 10 years). In low risk scenarios, the CAC score is very likely to be zero or low, and unlikely to change management. Conclusion Combining information from the CAC score with information from conventional risk factors can change assessment of coronary heart disease risk to an extent that may be clinically important, especially when the pre-test 10-year risk estimate is intermediate. The attached spreadsheet makes these calculations easy. PMID:15327691

Neyman-Pearson biometric score fusion as an extension of the sum rule

NASA Astrophysics Data System (ADS)

Hube, Jens Peter

2007-04-01

We define the biometric performance invariance under strictly monotonic functions on match scores as normalization symmetry. We use this symmetry to clarify the essential difference between the standard score-level fusion approaches of sum rule and Neyman-Pearson. We then express Neyman-Pearson fusion assuming match scores defined using false acceptance rates on a logarithmic scale. We show that by stating Neyman-Pearson in this form, it reduces to sum rule fusion for ROC curves with logarithmic slope. We also introduce a one parameter model of biometric performance and use it to express Neyman-Pearson fusion as a weighted sum rule.

A novel computer algorithm for modeling and treating mandibular fractures: A pilot study.

PubMed

Rizzi, Christopher J; Ortlip, Timothy; Greywoode, Jewel D; Vakharia, Kavita T; Vakharia, Kalpesh T

2017-02-01

To describe a novel computer algorithm that can model mandibular fracture repair. To evaluate the algorithm as a tool to model mandibular fracture reduction and hardware selection. Retrospective pilot study combined with cross-sectional survey. A computer algorithm utilizing Aquarius Net (TeraRecon, Inc, Foster City, CA) and Adobe Photoshop CS6 (Adobe Systems, Inc, San Jose, CA) was developed to model mandibular fracture repair. Ten different fracture patterns were selected from nine patients who had already undergone mandibular fracture repair. The preoperative computed tomography (CT) images were processed with the computer algorithm to create virtual images that matched the actual postoperative three-dimensional CT images. A survey comparing the true postoperative image with the virtual postoperative images was created and administered to otolaryngology resident and attending physicians. They were asked to rate on a scale from 0 to 10 (0 = completely different; 10 = identical) the similarity between the two images in terms of the fracture reduction and fixation hardware. Ten mandible fracture cases were analyzed and processed. There were 15 survey respondents. The mean score for overall similarity between the images was 8.41 ± 0.91; the mean score for similarity of fracture reduction was 8.61 ± 0.98; and the mean score for hardware appearance was 8.27 ± 0.97. There were no significant differences between attending and resident responses. There were no significant differences based on fracture location. This computer algorithm can accurately model mandibular fracture repair. Images created by the algorithm are highly similar to true postoperative images. The algorithm can potentially assist a surgeon planning mandibular fracture repair. 4. Laryngoscope, 2016 127:331-336, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

[Evaluation of scientific production in different subareas of Public Health: limits of the current model and contributions to the debate].

PubMed

Iriart, Jorge Alberto Bernstein; Deslandes, Suely Ferreira; Martin, Denise; Camargo, Kenneth Rochel de; Carvalho, Marilia Sá; Coeli, Cláudia Medina

2015-10-01

The aim of this study was to discuss the limits of the quantitative evaluation model for scientific production in Public Health. An analysis of the scientific production of professors from the various subareas of Public Health was performed for 2010-2012. Distributions of the mean annual score for professors were compared according to subareas. The study estimated the likelihood that 60% of the professors in the graduate studies programs scored P50 (Very Good) or higher in their area. Professors of Epidemiology showed a significantly higher median annual score. Graduate studies programs whose faculty included at least 60% of Epidemiology professors and fewer than 10% from the subarea Social and Human Sciences in Health were significantly more likely to achieve a "Very Good" classification. The observed inequalities in scientific production between different subareas of Public Health point to the need to rethink their evaluation in order to avoid reproducing iniquities that have harmful consequences for the field's diversity.

Comparison of the vaginal environment in rhesus and cynomolgus macaques pre- and post-lactobacillus colonization.

PubMed

Daggett, Gregory J; Zhao, Chunxia; Connor-Stroud, Fawn; Oviedo-Moreno, Patricia; Moon, Hojin; Cho, Michael W; Moench, Thomas; Anderson, Deborah J; Villinger, Francois

2017-10-01

Rhesus and cynomologus macaques are valuable animal models for the study of human immunodeficiency virus (HIV) prevention strategies. However, for such studies focused on the vaginal route of infection, differences in vaginal environment may have deterministic impact on the outcome of such prevention, providing the rationale for this study. We tested the vaginal environment of rhesus and cynomolgus macaques longitudinally to characterize the normal microflora based on Nugent scores and pH. This evaluation was extended after colonization of the vaginal space with Lactobacilli in an effort to recreate NHP models representing the healthy human vaginal environment. Nugent scores and pH differed significantly between species, although data from both species were suggestive of stable bacterial vaginosis. Colonization with Lactobacilli was successful in both species leading to lower Nugent score and pH, although rhesus macaques appeared better able to sustain Lactobacillus spp over time. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Zuckerman's revised alternative five-factor model: validation of the Zuckerman-Kuhlman-Aluja Personality Questionnaire in four French-speaking countries.

PubMed

Rossier, Jérôme; Hansenne, Michel; Baudin, Nicolas; Morizot, Julien

2012-01-01

The aim of this study was to analyze the replicability of Zuckerman's revised Alternative Five-factor model in a French-speaking context by validating the Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ) simultaneously in 4 French-speaking countries. The total sample was made up of 1,497 subjects from Belgium, Canada, France, and Switzerland. The internal consistencies for all countries were generally similar to those found for the normative U.S. and Spanish samples. A factor analysis confirmed that the normative structure replicated well and was stable within this French-speaking context. Moreover, multigroup confirmatory factor analyses have shown that the ZKA-PQ reaches scalar invariance across these 4 countries. Mean scores were slightly different for women and men, with women scoring higher on Neuroticism but lower on Sensation Seeking. Globally, mean score differences across countries were small. Overall, the ZKA-PQ seems an interesting alternative to assess both lower and higher order personality traits for applied or research purposes.

Monitoring the progression of erosive tooth wear (ETW) using BEWE index in casts and their 3D images: A retrospective longitudinal study.

PubMed

Marro, Francisca; De Lat, Liesa; Martens, Luc; Jacquet, Wolfgang; Bottenberg, Peter

2018-04-13

To determine if the Basic erosive tooth wear index (BEWE index) is able to assess and monitor ETW changes in two consecutive cast models, and detect methodological differences when using the corresponding 3D image replicas. A total of 480 pre-treatment and 2-year post-treatment orthodontic models (n = 240 cast models and n = 240 3D image replicas) from 120 adolescents treated between 2002 and 2013 at the Gent Dental Clinic, Belgium, were scored using the BEWE index. For data analysis only posterior sextants were considered, and inter-method differences were evaluated using Wilcoxon Signed Rank test, Kappa values and Mc Nemar tests (p < 0.05). Correlations between methods were determined using Kendall tau correlation test. Significant changes of ETW were detected between two consecutive models when BEWE index was used to score cast models or their 3D image replicas (p < 0.001). A strong significant correlation (τb: 0.74; p < 0.001) was shown between both methods However, 3D image-BEWE index combination showed a higher probability for detecting initial surface changes, and scored significantly higher than casts (p < 0.001). Incidence and progression of ETW using 3D images was 13.3% (n = 16) and 60.9% (n = 56) respectively, with two subjects developing BEWE = 3 in at least one tooth surface. BEWE index is a suitable tool for the scoring of ETW lesions in 3D images and cast. The combination of both digital 3D records and index, can be used for the monitoring of ETW in a longitudinal approach. The higher sensibility of BEWE index when scoring 3D images might improve the early diagnosis of ETW lesions. The BEWE index combined with digital 3D records of oral conditions might improve the practitioner performance with respect to early diagnosis, monitoring and managing ETW. Copyright © 2018 Elsevier Ltd. All rights reserved.

Liver Surface Nodularity Score Allows Prediction of Cirrhosis Decompensation and Death.

PubMed

Smith, Andrew D; Zand, Kevin A; Florez, Edward; Sirous, Reza; Shlapak, Darya; Souza, Frederico; Roda, Manohar; Bryan, Jason; Vasanji, Amit; Griswold, Michael; Lirette, Seth T

2017-06-01

Purpose To determine whether use of the liver surface nodularity (LSN) score, a quantitative biomarker derived from routine computed tomographic (CT) images, allows prediction of cirrhosis decompensation and death. Materials and Methods For this institutional review board-approved HIPAA-compliant retrospective study, adult patients with cirrhosis and Model for End-Stage Liver Disease (MELD) score within 3 months of initial liver CT imaging between January 3, 2006, and May 30, 2012, were identified from electronic medical records (n = 830). The LSN score was measured by using CT images and quantitative software. Competing risk regression was used to determine the association of the LSN score with hepatic decompensation and overall survival. A risk model combining LSN scores (<3 or ≥3) and MELD scores (<10 or ≥10) was created for predicting liver-related events. Results In patients with compensated cirrhosis, 40% (129 of 326) experienced decompensation during a median follow-up period of 4.22 years. After adjustment for competing risks including MELD score, LSN score (hazard ratio, 1.38; 95% confidence interval: 1.06, 1.79) was found to be independently predictive of hepatic decompensation. Median times to decompensation of patients at high (1.76 years, n = 48), intermediate (3.79 years, n = 126), and low (6.14 years, n = 152) risk of hepatic decompensation were significantly different (P < .001). Among the full cohort with compensated or decompensated cirrhosis, 61% (504 of 830) died during the median follow-up period of 2.26 years. After adjustment for competing risks, LSN score (hazard ratio, 1.22; 95% confidence interval: 1.11, 1.33) and MELD score (hazard ratio, 1.08; 95% confidence interval: 1.06, 1.11) were found to be independent predictors of death. Median times to death of patients at high (0.94 years, n = 315), intermediate (2.79 years, n = 312), and low (4.69 years, n = 203) risk were significantly different (P < .001). Conclusion The LSN score derived from routine CT images allows prediction of cirrhosis decompensation and death. © RSNA, 2016 Online supplemental material is available for this article.

Impact of Different Creatinine Measurement Methods on Liver Transplant Allocation

PubMed Central

Kaiser, Thorsten; Kinny-Köster, Benedict; Bartels, Michael; Parthaune, Tanja; Schmidt, Michael; Thiery, Joachim

2014-01-01

Introduction The model for end-stage liver disease (MELD) score is used in many countries to prioritize organ allocation for the majority of patients who require orthotopic liver transplantation. This score is calculated based on the following laboratory parameters: creatinine, bilirubin and the international normalized ratio (INR). Consequently, high measurement accuracy is essential for equitable and fair organ allocation. For serum creatinine measurements, the Jaffé method and enzymatic detection are well-established routine diagnostic tests. Methods A total of 1,013 samples from 445 patients on the waiting list or in evaluation for liver transplantation were measured using both creatinine methods from November 2012 to September 2013 at the university hospital Leipzig, Germany. The measurements were performed in parallel according to the manufacturer’s instructions after the samples arrived at the institute of laboratory medicine. Patients who had required renal replacement therapy twice in the previous week were excluded from analyses. Results Despite the good correlation between the results of both creatinine quantification methods, relevant differences were observed, which led to different MELD scores. The Jaffé measurement led to greater MELD score in 163/1,013 (16.1%) samples with differences of up to 4 points in one patient, whereas differences of up to 2 points were identified in 15/1,013 (1.5%) samples using the enzymatic assay. Overall, 50/152 (32.9%) patients with MELD scores >20 had higher scores when the Jaffé method was used. Discussion Using the Jaffé method to measure creatinine levels in samples from patients who require liver transplantation may lead to a systematic preference in organ allocation. In this study, the differences were particularly pronounced in samples with MELD scores >20, which has clinical relevance in the context of urgency of transplantation. These data suggest that official recommendations are needed to determine which laboratory diagnostic methods should be used when calculating MELD scores. PMID:24587188

Enhancing the Value of Population-Based Risk Scores for Institutional-Level Use.

PubMed

Raza, Sajjad; Sabik, Joseph F; Rajeswaran, Jeevanantham; Idrees, Jay J; Trezzi, Matteo; Riaz, Haris; Javadikasgari, Hoda; Nowicki, Edward R; Svensson, Lars G; Blackstone, Eugene H

2016-07-01

We hypothesized that factors associated with an institution's residual risk unaccounted for by population-based models may be identifiable and used to enhance the value of population-based risk scores for quality improvement. From January 2000 to January 2010, 4,971 patients underwent aortic valve replacement (AVR), either isolated (n = 2,660) or with concomitant coronary artery bypass grafting (AVR+CABG; n = 2,311). Operative mortality and major morbidity and mortality predicted by The Society of Thoracic Surgeons (STS) risk models were compared with observed values. After adjusting for patients' STS score, additional and refined risk factors were sought to explain residual risk. Differences between STS model coefficients (risk-factor strength) and those specific to our institution were calculated. Observed operative mortality was less than predicted for AVR (1.6% [42 of 2,660] vs 2.8%, p < 0.0001) and AVR+CABG (2.6% [59 of 2,311] vs 4.9%, p < 0.0001). Observed major morbidity and mortality was also lower than predicted for isolated AVR (14.6% [389 of 2,660] vs 17.5%, p < 0.0001) and AVR+CABG (20.0% [462 of 2,311] vs 25.8%, p < 0.0001). Shorter height, higher bilirubin, and lower albumin were identified as additional institution-specific risk factors, and body surface area, creatinine, glomerular filtration rate, blood urea nitrogen, and heart failure across all levels of functional class were identified as refined risk-factor variables associated with residual risk. In many instances, risk-factor strength differed substantially from that of STS models. Scores derived from population-based models can be enhanced for institutional level use by adjusting for institution-specific additional and refined risk factors. Identifying these and measuring differences in institution-specific versus population-based risk-factor strength can identify areas to target for quality improvement initiatives. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Gender differences in multiple underlying dimensions of health-related quality of life are associated with sociodemographic and socioeconomic status.

PubMed

Cherepanov, Dasha; Palta, Mari; Fryback, Dennis G; Robert, Stephanie A; Hays, Ron D; Kaplan, Robert M

2011-11-01

The purpose of the study was to examine whether gender differences in summary health-related quality of life (HRQoL) are due to differences in specific dimensions of health, and whether they are explained by sociodemographic and socioeconomic (SES) variation. The National Health Measurement Study collected cross-sectional data on a national sample of 3648 black and white noninstitutionalized adults ages 35 to 89 years. Data included the Short Form 36-Item survey, which yielded separate Mental and Physical Component Summary scores (MCS and PCS, respectively), and five HRQoL indexes: Short Form 6 dimension, EuroQol 5 dimension, the Health Utilities Indexes Mark 2 and 3, and the Quality of Well-Being Scale Self-Administered form. Structural equation models were used to explore gender differences in physical, psychosocial, and pain latent dimensions of the 5 indexes, adjusting for sociodemographic and SES indicators. Observed MCS and PCS scores were examined in regression models to judge robustness of latent results. Men had better estimated physical and psychosocial health and less pain than women with similar trends on the MCS and PCS scores. Adjustments for marital status or income reduced gender differences more than did other indicators. Adjusting results for partial factorial invariance of HRQoL attributes supported the presence of gender differentials, but also indicated that these differences are impacted by dimensions being related to some HRQoL attributes differently by gender. Men have better estimated health on 3 latent dimensions of HRQoL-physical, psychosocial, and pain-comparable to gender differences on the observed MCS and PCS scores. Gender differences are partly explained by sociodemographic and SES factors, highlighting the role of socioeconomic inequalities in perpetuating gender differences in health outcomes across multiple domains. These results also emphasize the importance of accounting for measurement invariance for meaningful comparison of group differences in estimated means of self-reported measures of health.

Patient involvement in the decision-making process improves satisfaction and quality of life in postmastectomy breast reconstruction.

PubMed

Ashraf, Azra A; Colakoglu, Salih; Nguyen, John T; Anastasopulos, Alexandra J; Ibrahim, Ahmed M S; Yueh, Janet H; Lin, Samuel J; Tobias, Adam M; Lee, Bernard T

2013-09-01

The patient-physician relationship has evolved from the paternalistic, physician-dominant model to the shared-decision-making and informed-consumerist model. The level of patient involvement in this decision-making process can potentially influence patient satisfaction and quality of life. In this study, patient-physician decision models are evaluated in patients undergoing postmastectomy breast reconstruction. All women who underwent breast reconstruction at an academic hospital from 1999-2007 were identified. Patients meeting inclusion criteria were mailed questionnaires at a minimum of 1 y postoperatively with questions about decision making, satisfaction, and quality of life. There were 707 women eligible for our study and 465 completed surveys (68% response rate). Patients were divided into one of three groups: paternalistic (n = 18), informed-consumerist (n = 307), shared (n = 140). There were differences in overall general satisfaction (P = 0.034), specifically comparing the informed group to the paternalistic group (66.7% versus 38.9%, P = 0.020) and the shared to the paternalistic group (69.3% versus 38.9%, P = 0.016). There were no differences in aesthetic satisfaction. There were differences found in the SF-12 physical component summary score across all groups (P = 0.033), and a difference was found between the informed and paternalistic groups (P < 0.05). There were no differences in the mental component score (P = 0.42). Women undergoing breast reconstruction predominantly used the informed model of decision making. Patients who adopted a more active role, whether using an informed or shared approach, had higher general patient satisfaction and physical component summary scores compared with patients whose decision making was paternalistic. Copyright © 2013 Elsevier Inc. All rights reserved.

Critical overview of all available animal models for abdominal wall hernia research.

PubMed

Vogels, R R M; Kaufmann, R; van den Hil, L C L; van Steensel, S; Schreinemacher, M H F; Lange, J F; Bouvy, N D

2017-10-01

Since the introduction of the first prosthetic mesh for abdominal hernia repair, there has been a search for the "ideal mesh." The use of preclinical or animal models for assessment of necessary characteristics of new and existing meshes is an indispensable part of hernia research. Unfortunately, in our experience there is a lack of consensus among different research groups on which model to use. Therefore, we hypothesized that there is a lack of comparability within published animal research on hernia surgery due to wide range in experimental setup among different research groups. A systematic search of the literature was performed to provide a complete overview of all animal models published between 2000 and 2014. Relevant parameters on model characteristics and outcome measurement were scored on a standardized scoring sheet. Due to the wide range in different animals used, ranging from large animal models like pigs to rodents, we decided to limit the study to 168 articles concerning rat models. Within these rat models, we found wide range of baseline animal characteristics, operation techniques, and outcome measurements. Making reliable comparison of results among these studies is impossible. There is a lack of comparability among experimental hernia research, limiting the impact of this experimental research. We therefore propose the establishment of guidelines for experimental hernia research by the EHS.

The standardized live patient and mechanical patient models--their roles in trauma teaching.

PubMed

Ali, Jameel; Al Ahmadi, Khalid; Williams, Jack Ivan; Cherry, Robert Allen

2009-01-01

We have previously demonstrated improved medical student performance using standardized live patient models in the Trauma Evaluation and Management (TEAM) program. The trauma manikin has also been offered as an option for teaching trauma skills in this program. In this study, we compare performance using both models. Final year medical students were randomly assigned to three groups: group I (n = 22) with neither model, group II (n = 24) with patient model, and group III (n = 24) with mechanical model using the same clinical scenario. All students completed pre-TEAM and post-TEAM multiple choice question (MCQ) exams and an evaluation questionnaire scoring five items on a scale of 1 to 5 with 5 being the highest. The items were objectives were met, knowledge improved, skills improved, overall satisfaction, and course should be mandatory. Students (groups II and III) then switched models, rating preferences in six categories: more challenging, more interesting, more dynamic, more enjoyable learning, more realistic, and overall better model. Scores were analyzed by ANOVA with p < 0.05 being considered statistically significant. All groups had similar scores (means % +/- SD)in the pretest (group I - 50.8 +/- 7.4, group II - 51.3 +/- 6.4, group III - 51.1 +/- 6.6). All groups improved their post-test scores but groups II and III scored higher than group I with no difference in scores between groups II and III (group I - 77.5 +/- 3.8, group II - 84.8 +/- 3.6, group III - 86.3 +/- 3.2). The percent of students scoring 5 in the questionnaire are as follows: objectives met - 100% for all groups; knowledge improved: group I - 91%, group II - 96%, group III - 92%; skills improved: group I - 9%, group II - 83%, group III - 96%; overall satisfaction: group I - 91%, group II - 92%, group III - 92%; should be mandatory: group I - 32%, group II - 96%, group III - 100%. Student preferences (48 students) are as follows: the mechanical model was more challenging (44 of 48); more interesting (40 of 48); more dynamic (46 of 48); more enjoyable (48 of 48); more realistic (32/48), and better overall model (42 of 48). Using the TEAM program, we have demonstrated that improvement in knowledge and skills are equally enhanced by using mechanical or patient models in trauma teaching. However, students overwhelmingly preferred the mechanical model.

How education systems shape cross-national ethnic inequality in math competence scores: Moving beyond mean differences.

PubMed

Spörlein, Christoph; Schlueter, Elmar

2018-01-01

Here we examine a conceptualization of immigrant assimilation that is based on the more general notion that distributional differences erode across generations. We explore this idea by reinvestigating the efficiency-equality trade-off hypothesis, which posits that stratified education systems educate students more efficiently at the cost of increasing inequality in overall levels of competence. In the context of ethnic inequality in math achievement, this study explores the extent to which an education system's characteristics are associated with ethnic inequality in terms of both the group means and group variances in achievement. Based on data from the 2012 PISA and mixed-effect location scale models, our analyses revealed two effects: on average, minority students had lower math scores than majority students, and minority students' scores were more concentrated at the lower end of the distribution. However, the ethnic inequality in the distribution of scores declined across generations. We did not find compelling evidence that stratified education systems increase mean differences in competency between minority and majority students. However, our analyses revealed that in countries with early educational tracking, minority students' math scores tended to cluster at the lower end of the distribution, regardless of compositional and school differences between majority and minority students.

How education systems shape cross-national ethnic inequality in math competence scores: Moving beyond mean differences

PubMed Central

Spörlein, Christoph

2018-01-01

Here we examine a conceptualization of immigrant assimilation that is based on the more general notion that distributional differences erode across generations. We explore this idea by reinvestigating the efficiency-equality trade-off hypothesis, which posits that stratified education systems educate students more efficiently at the cost of increasing inequality in overall levels of competence. In the context of ethnic inequality in math achievement, this study explores the extent to which an education system’s characteristics are associated with ethnic inequality in terms of both the group means and group variances in achievement. Based on data from the 2012 PISA and mixed-effect location scale models, our analyses revealed two effects: on average, minority students had lower math scores than majority students, and minority students’ scores were more concentrated at the lower end of the distribution. However, the ethnic inequality in the distribution of scores declined across generations. We did not find compelling evidence that stratified education systems increase mean differences in competency between minority and majority students. However, our analyses revealed that in countries with early educational tracking, minority students’ math scores tended to cluster at the lower end of the distribution, regardless of compositional and school differences between majority and minority students. PMID:29494677

External validation of the HIT Expert Probability (HEP) score.

PubMed

Joseph, Lee; Gomes, Marcelo P V; Al Solaiman, Firas; St John, Julie; Ozaki, Asuka; Raju, Manjunath; Dhariwal, Manoj; Kim, Esther S H

2015-03-01

The diagnosis of heparin-induced thrombocytopenia (HIT) can be challenging. The HIT Expert Probability (HEP) Score has recently been proposed to aid in the diagnosis of HIT. We sought to externally and prospectively validate the HEP score. We prospectively assessed pre-test probability of HIT for 51 consecutive patients referred to our Consultative Service for evaluation of possible HIT between August 1, 2012 and February 1, 2013. Two Vascular Medicine fellows independently applied the 4T and HEP scores for each patient. Two independent HIT expert adjudicators rendered a diagnosis of HIT likely or unlikely. The median (interquartile range) of 4T and HEP scores were 4.5 (3.0, 6.0) and 5 (3.0, 8.5), respectively. There were no significant differences between area under receiver-operating characteristic curves of 4T and HEP scores against the gold standard, confirmed HIT [defined as positive serotonin release assay and positive anti-PF4/heparin ELISA] (0.74 vs 0.73, p = 0.97). HEP score ≥ 2 was 100 % sensitive and 16 % specific for determining the presence of confirmed HIT while a 4T score > 3 was 93 % sensitive and 35 % specific. In conclusion, the HEP and 4T scores are excellent screening pre-test probability models for HIT, however, in this prospective validation study, test characteristics for the diagnosis of HIT based on confirmatory laboratory testing and expert opinion are similar. Given the complexity of the HEP scoring model compared to that of the 4T score, further validation of the HEP score is warranted prior to widespread clinical acceptance.

Measurement and description of underlying dimensions of comorbid mental disorders using Factor Mixture Models: results of the ESEMeD project.

PubMed

Almansa, Josué; Vermunt, Jeroen K; Forero, Carlos G; Vilagut, Gemma; De Graaf, Ron; De Girolamo, Giovanni; Alonso, Jordi

2011-06-01

Epidemiological studies on mental health and mental comorbidity are usually based on prevalences and correlations between disorders, or some other form of bivariate clustering of disorders. In this paper, we propose a Factor Mixture Model (FMM) methodology based on conceptual models aiming to measure and summarize distinctive disorder information in the internalizing and externalizing dimensions. This methodology includes explicit modelling of subpopulations with and without 12 month disorders ("ill" and "healthy") by means of latent classes, as well as assessment of model invariance and estimation of dimensional scores. We applied this methodology with an internalizing/externalizing two-factor model, to a representative sample gathered in the European Study of the Epidemiology of Mental Disorders (ESEMeD) study -- which includes 8796 individuals from six countries, and used the CIDI 3.0 instrument for disorder assessment. Results revealed that southern European countries have significantly higher mental health levels concerning internalizing/externalizing disorders than central countries; males suffered more externalizing disorders than women did, and conversely, internalizing disorders were more frequent in women. Differences in mental-health level between socio-demographic groups were due to different proportions of healthy and ill individuals and, noticeably, to the ameliorating influence of marital status on severity. An advantage of latent model-based scores is that the inclusion of additional mental-health dimensional information -- other than diagnostic data -- allows for greater precision within a target range of scores. Copyright © 2011 John Wiley & Sons, Ltd.

A systematic analysis of scoring functions in rigid-body protein docking: The delicate balance between the predictive rate improvement and the risk of overtraining.

PubMed

Barradas-Bautista, Didier; Moal, Iain H; Fernández-Recio, Juan

2017-07-01

Protein-protein interactions play fundamental roles in biological processes including signaling, metabolism, and trafficking. While the structure of a protein complex reveals crucial details about the interaction, it is often difficult to acquire this information experimentally. As the number of interactions discovered increases faster than they can be characterized, protein-protein docking calculations may be able to reduce this disparity by providing models of the interacting proteins. Rigid-body docking is a widely used docking approach, and is often capable of generating a pool of models within which a near-native structure can be found. These models need to be scored in order to select the acceptable ones from the set of poses. Recently, more than 100 scoring functions from the CCharPPI server were evaluated for this task using decoy structures generated with SwarmDock. Here, we extend this analysis to identify the predictive success rates of the scoring functions on decoys from three rigid-body docking programs, ZDOCK, FTDock, and SDOCK, allowing us to assess the transferability of the functions. We also apply set-theoretic measure to test whether the scoring functions are capable of identifying near-native poses within different subsets of the benchmark. This information can provide guides for the use of the most efficient scoring function for each docking method, as well as instruct future scoring functions development efforts. Proteins 2017; 85:1287-1297. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Rasch analysis of the Edmonton Symptom Assessment System and research implications.

PubMed

Cheifetz, O; Packham, T L; Macdermid, J C

2014-04-01

Reliable and valid assessment of the disease burden across all forms of cancer is critical to the evaluation of treatment effectiveness and patient progress. The Edmonton Symptom Assessment System (esas) is used for routine evaluation of people attending for cancer care. In the present study, we used Rasch analysis to explore the measurement properties of the esas and to determine the effect of using Rasch-proposed interval-level esas scoring compared with traditional scoring when evaluating the effects of an exercise program for cancer survivors. Polytomous Rasch analysis (Andrich's rating-scale model) was applied to data from 26,645 esas questionnaires completed at the Juravinski Cancer Centre. The fit of the esas to the polytomous Rasch model was investigated, including evaluations of differential item functioning for sex, age, and disease group. The research implication was investigated by comparing the results of an observational research study previously analysed using a traditional approach with the results obtained by Rasch-proposed interval-level esas scoring. The Rasch reliability index was 0.73, falling short of the desired 0.80-0.90 level. However, the esas was found to fit the Rasch model, including the criteria for uni-dimensional data. The analysis suggests that the current esas scoring system of 0-10 could be collapsed to a 6-point scale. Use of the Rasch-proposed interval-level scoring yielded results that were different from those calculated using summarized ordinal-level esas scores. Differential item functioning was not found for sex, age, or diagnosis groups. The esas is a moderately reliable uni-dimensional measure of cancer disease burden and can provide interval-level scaling with Rasch-based scoring. Further, our study indicates that, compared with the traditional scoring metric, Rasch-based scoring could result in substantive changes to conclusions.

Estimating EQ-5D values from the Neck Disability Index and numeric rating scales for neck and arm pain.

PubMed

Carreon, Leah Y; Bratcher, Kelly R; Das, Nandita; Nienhuis, Jacob B; Glassman, Steven D

2014-09-01

The Neck Disability Index (NDI) and numeric rating scales (0 to 10) for neck pain and arm pain are widely used cervical spine disease-specific measures. Recent studies have shown that there is a strong relationship between the SF-6D and the NDI such that using a simple linear regression allows for the estimation of an SF-6D value from the NDI alone. Due to ease of administration and scoring, the EQ-5D is increasingly being used as a measure of utility in the clinical setting. The purpose of this study is to determine if the EQ-5D values can be estimated from commonly available cervical spine disease-specific health-related quality of life measures, much like the SF-6D. The EQ-5D, NDI, neck pain score, and arm pain score were prospectively collected in 3732 patients who presented to the authors' clinic with degenerative cervical spine disorders. Correlation coefficients for paired observations from multiple time points between the NDI, neck pain and arm pain scores, and EQ-5D were determined. Regression models were built to estimate the EQ-5D values from the NDI, neck pain, and arm pain scores. The mean age of the 3732 patients was 53.3 ± 12.2 years, and 43% were male. Correlations between the EQ-5D and the NDI, neck pain score, and arm pain score were statistically significant (p < 0.0001), with correlation coefficients of -0.77, -0.62, and -0.50, respectively. The regression equation 0.98947 + (-0.00705 × NDI) + (-0.00875 × arm pain score) + (-0.00877 × neck pain score) to predict EQ-5D had an R-square of 0.62 and a root mean square error (RMSE) of 0.146. The model using NDI alone had an R-square of 0.59 and a RMSE of 0.150. The model using the individual NDI items had an R-square of 0.46 and an RMSE of 0.172. The correlation coefficient between the observed and estimated EQ-5D scores was 0.79. There was no statistically significant difference between the actual EQ-5D score (0.603 ± 0.235) and the estimated EQ-5D score (0.603 ± 0.185) using the NDI, neck pain score, and arm pain score regression model. However, rounding off the coefficients to fewer than 5 decimal places produced less accurate results. The regression model estimating the EQ-5D from the NDI, neck pain score, and arm pain score accounted for 60% of the variability of the EQ-5D with a relatively large RMSE. This regression model may not be sufficient to accurately or reliably estimate actual EQ-5D values.

Mortality Probability Model III and Simplified Acute Physiology Score II

PubMed Central

Vasilevskis, Eduard E.; Kuzniewicz, Michael W.; Cason, Brian A.; Lane, Rondall K.; Dean, Mitzi L.; Clay, Ted; Rennie, Deborah J.; Vittinghoff, Eric; Dudley, R. Adams

2009-01-01

Background: To develop and compare ICU length-of-stay (LOS) risk-adjustment models using three commonly used mortality or LOS prediction models. Methods: Between 2001 and 2004, we performed a retrospective, observational study of 11,295 ICU patients from 35 hospitals in the California Intensive Care Outcomes Project. We compared the accuracy of the following three LOS models: a recalibrated acute physiology and chronic health evaluation (APACHE) IV-LOS model; and models developed using risk factors in the mortality probability model III at zero hours (MPM0) and the simplified acute physiology score (SAPS) II mortality prediction model. We evaluated models by calculating the following: (1) grouped coefficients of determination; (2) differences between observed and predicted LOS across subgroups; and (3) intraclass correlations of observed/expected LOS ratios between models. Results: The grouped coefficients of determination were APACHE IV with coefficients recalibrated to the LOS values of the study cohort (APACHE IVrecal) [R2 = 0.422], mortality probability model III at zero hours (MPM0 III) [R2 = 0.279], and simplified acute physiology score (SAPS II) [R2 = 0.008]. For each decile of predicted ICU LOS, the mean predicted LOS vs the observed LOS was significantly different (p ≤ 0.05) for three, two, and six deciles using APACHE IVrecal, MPM0 III, and SAPS II, respectively. Plots of the predicted vs the observed LOS ratios of the hospitals revealed a threefold variation in LOS among hospitals with high model correlations. Conclusions: APACHE IV and MPM0 III were more accurate than SAPS II for the prediction of ICU LOS. APACHE IV is the most accurate and best calibrated model. Although it is less accurate, MPM0 III may be a reasonable option if the data collection burden or the treatment effect bias is a consideration. PMID:19363210

Item response analysis of the Positive and Negative Syndrome Scale

PubMed Central

Santor, Darcy A; Ascher-Svanum, Haya; Lindenmayer, Jean-Pierre; Obenchain, Robert L

2007-01-01

Background Statistical models based on item response theory were used to examine (a) the performance of individual Positive and Negative Syndrome Scale (PANSS) items and their options, (b) the effectiveness of various subscales to discriminate among individual differences in symptom severity, and (c) the appropriateness of cutoff scores recently recommended by Andreasen and her colleagues (2005) to establish symptom remission. Methods Option characteristic curves were estimated using a nonparametric item response model to examine the probability of endorsing each of 7 options within each of 30 PANSS items as a function of standardized, overall symptom severity. Our data were baseline PANSS scores from 9205 patients with schizophrenia or schizoaffective disorder who were enrolled between 1995 and 2003 in either a large, naturalistic, observational study or else in 1 of 12 randomized, double-blind, clinical trials comparing olanzapine to other antipsychotic drugs. Results Our analyses show that the majority of items forming the Positive and Negative subscales of the PANSS perform very well. We also identified key areas for improvement or revision in items and options within the General Psychopathology subscale. The Positive and Negative subscale scores are not only more discriminating of individual differences in symptom severity than the General Psychopathology subscale score, but are also more efficient on average than the 30-item total score. Of the 8 items recently recommended to establish symptom remission, 1 performed markedly different from the 7 others and should either be deleted or rescored requiring that patients achieve a lower score of 2 (rather than 3) to signal remission. Conclusion This first item response analysis of the PANSS supports its sound psychometric properties; most PANSS items were either very good or good at assessing overall severity of illness. These analyses did identify some items which might be further improved for measuring individual severity differences or for defining remission thresholds. Findings also suggest that the Positive and Negative subscales are more sensitive to change than the PANSS total score and, thus, may constitute a "mini PANSS" that may be more reliable, require shorter administration and training time, and possibly reduce sample sizes needed for future research. PMID:18005449

The long-term cognitive consequences of early childhood malnutrition: the case of famine in Ghana.

PubMed

Ampaabeng, Samuel K; Tan, Chih Ming

2013-12-01

We examine the role of early childhood health in human capital accumulation. Using a unique data set from Ghana with comprehensive information on individual, family, community, school quality characteristics and a direct measure of intelligence together with test scores, we examine the long-term cognitive effects of the 1983 famine on survivors. We show that differences in intelligence test scores can be robustly explained by the differential impact of the famine in different parts of the country and the impacts are most severe for children under two years of age during the famine. We also account for model uncertainty by using Bayesian Model Averaging. Copyright © 2013 Elsevier B.V. All rights reserved.

The factor structure and screening utility of the Social Interaction Anxiety Scale.

PubMed

Rodebaugh, Thomas L; Woods, Carol M; Heimberg, Richard G; Liebowitz, Michael R; Schneier, Franklin R

2006-06-01

The widely used Social Interaction Anxiety Scale (SIAS; R. P. Mattick & J. C. Clarke, 1998) possesses favorable psychometric properties, but questions remain concerning its factor structure and item properties. Analyses included 445 people with social anxiety disorder and 1,689 undergraduates. Simple unifactorial models fit poorly, and models that accounted for differences due to item wording (i.e., reverse scoring) provided superior fit. It was further found that clients and undergraduates approached some items differently, and the SIAS may be somewhat overly conservative in selecting analogue participants from an undergraduate sample. Overall, this study provides support for the excellent properties of the SIAS's straightforwardly worded items, although questions remain regarding its reverse-scored items. Copyright 2006 APA, all rights reserved.

Propensity score analysis with partially observed covariates: How should multiple imputation be used?

PubMed

Leyrat, Clémence; Seaman, Shaun R; White, Ian R; Douglas, Ian; Smeeth, Liam; Kim, Joseph; Resche-Rigon, Matthieu; Carpenter, James R; Williamson, Elizabeth J

2017-01-01

Inverse probability of treatment weighting is a popular propensity score-based approach to estimate marginal treatment effects in observational studies at risk of confounding bias. A major issue when estimating the propensity score is the presence of partially observed covariates. Multiple imputation is a natural approach to handle missing data on covariates: covariates are imputed and a propensity score analysis is performed in each imputed dataset to estimate the treatment effect. The treatment effect estimates from each imputed dataset are then combined to obtain an overall estimate. We call this method MIte. However, an alternative approach has been proposed, in which the propensity scores are combined across the imputed datasets (MIps). Therefore, there are remaining uncertainties about how to implement multiple imputation for propensity score analysis: (a) should we apply Rubin's rules to the inverse probability of treatment weighting treatment effect estimates or to the propensity score estimates themselves? (b) does the outcome have to be included in the imputation model? (c) how should we estimate the variance of the inverse probability of treatment weighting estimator after multiple imputation? We studied the consistency and balancing properties of the MIte and MIps estimators and performed a simulation study to empirically assess their performance for the analysis of a binary outcome. We also compared the performance of these methods to complete case analysis and the missingness pattern approach, which uses a different propensity score model for each pattern of missingness, and a third multiple imputation approach in which the propensity score parameters are combined rather than the propensity scores themselves (MIpar). Under a missing at random mechanism, complete case and missingness pattern analyses were biased in most cases for estimating the marginal treatment effect, whereas multiple imputation approaches were approximately unbiased as long as the outcome was included in the imputation model. Only MIte was unbiased in all the studied scenarios and Rubin's rules provided good variance estimates for MIte. The propensity score estimated in the MIte approach showed good balancing properties. In conclusion, when using multiple imputation in the inverse probability of treatment weighting context, MIte with the outcome included in the imputation model is the preferred approach.

Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

ERIC Educational Resources Information Center

Lu, Yi

2016-01-01

To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

Antiretroviral therapy CNS penetration and HIV-1–associated CNS disease

PubMed Central

Winston, A.; Walsh, J.; Post, F.; Porter, K.; Gazzard, B.; Fisher, M.; Leen, C.; Pillay, D.; Hill, T.; Johnson, M.; Gilson, R.; Anderson, J.; Easterbrook, P.; Bansi, L.; Orkin, C.; Ainsworth, J.; Palfreeman, A.; Gompels, M.; Phillips, A.N.; Sabin, C.A.

2011-01-01

Objective: The impact of different antiretroviral agents on the risk of developing or surviving CNS disease remains unknown. The aim of this study was to investigate whether using antiretroviral regimens with higher CNS penetration effectiveness (CPE) scores was associated with reduced incidence of CNS disease and improved survival in the UK Collaborative HIV Cohort (CHIC) Study. Methods: Adults without previous CNS disease, who commenced combination antiretroviral therapy (cART) between 1996 and 2008, were included (n = 22,356). Initial and most recent cART CPE scores were calculated. CNS diseases were HIV encephalopathy (HIVe), progressive multifocal leukoencephalopathy (PML), cerebral toxoplasmosis (TOXO), and cryptococcal meningitis (CRYPTO). Incidence rates and overall survival were stratified by CPE score. A multivariable Poisson regression model was used to identify independent associations. Results: The median (interquartile range) CPE score for initial cART regimen increased from 7 (5–8) in 1996–1997 to 9 (8–10) in 2000–2001 and subsequently declined to 6 (7–8) in 2006–2008. Differences in gender, HIV acquisition risk group, and ethnicity existed between CPE score strata. A total of 251 subjects were diagnosed with a CNS disease (HIVe 80; TOXO 59; CRYPTO 56; PML 54). CNS diseases occurred more frequently in subjects prescribed regimens with CPE scores ≤4, and less frequently in those with scores ≥10; however, these differences were nonsignificant. Initial and most recent cART CPE scores ≤4 were independently associated with increased risk of death. Conclusion: Clinical status at time of commencing cART influences antiretroviral selection and CPE score. This information should be considered when utilizing CPE scores for retrospective analyses. PMID:21339496

[Establishment of risk evaluation model of peritoneal metastasis in gastric cancer and its predictive value].

PubMed

Zhao, Junjie; Zhou, Rongjian; Zhang, Qi; Shu, Ping; Li, Haojie; Wang, Xuefei; Shen, Zhenbin; Liu, Fenglin; Chen, Weidong; Qin, Jing; Sun, Yihong

2017-01-25

To establish an evaluation model of peritoneal metastasis in gastric cancer, and to assess its clinical significance. Clinical and pathologic data of the consecutive cases of gastric cancer admitted between April 2015 and December 2015 in Department of General Surgery, Zhongshan Hospital of Fudan University were analyzed retrospectively. A total of 710 patients were enrolled in the study after 18 patients with other distant metastasis were excluded. The correlations between peritoneal metastasis and different factors were studied through univariate (Pearson's test or Fisher's exact test) and multivariate analyses (Binary Logistic regression). Independent predictable factors for peritoneal metastasis were combined to establish a risk evaluation model (nomogram). The nomogram was created with R software using the 'rms' package. In the nomogram, each factor had different scores, and every patient could have a total score by adding all the scores of each factor. A higher total score represented higher risk of peritoneal metastasis. Receiver operating characteristic (ROC) curve analysis was used to compare the sensitivity and specificity of the established nomogram. Delong. Delong. Clarke-Pearson test was used to compare the difference of the area under the curve (AUC). The cut-off value was determined by the AUC, when the ROC curve had the biggest AUC, the model had the best sensitivity and specificity. Among 710 patients, 47 patients had peritoneal metastasis (6.6%), including 30 male (30/506, 5.9%) and 17 female (17/204, 8.3%); 31 were ≥ 60 years old (31/429, 7.2%); 38 had tumor ≥ 3 cm(38/461, 8.2%). Lauren classification indicated that 2 patients were intestinal type(2/245, 0.8%), 8 patients were mixed type(8/208, 3.8%), 11 patients were diffuse type(11/142, 7.7%), and others had no associated data. CA19-9 of 13 patients was ≥ 37 kU/L(13/61, 21.3%); CA125 of 11 patients was ≥ 35 kU/L(11/36, 30.6%); CA72-4 of 11 patients was ≥ 10 kU/L(11/39, 28.2%). Neutrophil/lymphocyte ratio (NLR) of 26 patients was ≥ 2.37(26/231, 11.3%). Multivariate analysis showed that Lauren classification (HR=8.95, 95%CI:1.32-60.59, P=0.025), CA125(HR=17.45, 95%CI:5.54-54.89, P=0.001), CA72-4(HR=20.06, 95%CI:5.05-79.68, P=0.001), and NLR (HR=4.16, 95%CI:1.17-14.75, P=0.032) were independent risk factors of peritoneal metastasis in gastric cancer. In the nomogram, the highest score was 241, including diffuse or mixed Lauren classification (54 score), CA125 ≥ 35 kU/L (66 score), CA72-4 ≥ 10 kU/L (100 score), and NLR ≥ 2.37 (21 score), which represented a highest risk of peritoneal metastasis (more than 90%). The AUC of nomogram was 0.912, which was superior than any single variable (AUC of Lauren classification: 0.678; AUC of CA125: 0.720; AUC of CA72-4: 0.792; AUC of NLR: 0.613, all P=0.000). The total score of nomogram increased according to the TNM stage, and was highest in the peritoneal metastasis group (F=49.1, P=0.000). When the cut-off value calculated by ROC analysis was set at 140, the model could best balanced the sensitivity (0.79) and the specificity (0.87). Only 5% of patients had peritoneal metastasis when their nomogram scores were lower than 140, while 58% of patients had peritoneal metastasis when their scores were ≥ 140(χ 2 =69.1, P=0.000). The risk evaluation model established with Lauren classification, CA125, CA72-4 and NLR can effectively predict the risk of peritoneal metastasis in gastric cancer, and provide the reference to preoperative staging and choice of therapeutic strategy.

Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease.

PubMed

Lin, Qi; Rosenberg, Monica D; Yoo, Kwangsun; Hsu, Tiffany W; O'Connell, Thomas P; Chun, Marvin M

2018-01-01

Resting-state functional connectivity (rs-FC) is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11) scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV) significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

Collaborative Audit of Risk Evaluation in Medical Emergency Treatment (CARE-MET I) - an international pilot.

PubMed

Subbe, C P; Gauntlett, W; Kellett, J G

2010-06-01

The absence of an accepted model for risk-adjustment of acute medical admissions leads to suboptimal clinical triage and serves as a disincentive to compare outcomes in different hospitals. The Simple Clinical Score (SCS) is a model based on 16 clinical parameters affecting hospital mortality. We undertook a feasibility pilot in 21 hospitals in Europe and New Zealand each collecting data for 12 or more consecutive medical emergency admissions. Data from 281 patients was analysed. Severity of illness as estimated by SCS was related to risk of admission to the Intensive Care Unit (p<0.001) but not to the Coronary Care Unit. Mortality increased from 0% in the Very Low Risk group to 22% in the Very High Risk Group (p<0.0001). Very low scores were associated with earlier discharge as opposed to very high scores (mean length of stay of 2.4 days vs 5.6 days, p<0.001). There were differences in the pattern of discharges in different hospitals with comparable SCS data. Clinicians reported no significant problems with the collection of data for the score in a number of different health care settings. The SCS appears to be a feasible tool to assist clinical triage of medical emergency admissions. The ability to view the profile of the SCS for different clinical centres opens up the possibility of accurate comparison of outcomes across clinical centres without distortion by different regional standards of health care. This pilot study demonstrates that the adoption of the SCS is practical across an international range of hospitals. Copyright 2010 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Psychometric Properties of the Bermond-Vorst Alexithymia Questionnaire (BVAQ) in the General Population and a Clinical Population.

PubMed

de Vroege, Lars; Emons, Wilco H M; Sijtsma, Klaas; van der Feltz-Cornelis, Christina M

2018-01-01

The Bermond-Vorst Alexithymia Questionnaire (BVAQ) has been validated in student samples and small clinical samples, but not in the general population; thus, representative general-population norms are lacking. We examined the factor structure of the BVAQ in Longitudinal Internet Studies for the Social Sciences panel data from the Dutch general population ( N  = 974). Factor analyses revealed a first-order five-factor model and a second-order two-factor model. However, in the second-order model, the factor interpreted as analyzing ability loaded on both the affective factor and the cognitive factor. Further analyses showed that the first-order test scores are more reliable than the second-order test scores. External and construct validity were addressed by comparing BVAQ scores with a clinical sample of patients suffering from somatic symptom and related disorder (SSRD) ( N  = 235). BVAQ scores differed significantly between the general population and patients suffering from SSRD, suggesting acceptable construct validity. Age was positively associated with alexithymia. Males showed higher levels of alexithymia. The BVAQ is a reliable alternative measure for measuring alexithymia.

A Comparison of the Forecast Skills among Three Numerical Models

NASA Astrophysics Data System (ADS)

Lu, D.; Reddy, S. R.; White, L. J.

2003-12-01

Three numerical weather forecast models, MM5, COAMPS and WRF, operating with a joint effort of NOAA HU-NCAS and Jackson State University (JSU) during summer 2003 have been chosen to study their forecast skills against observations. The models forecast over the same region with the same initialization, boundary condition, forecast length and spatial resolution. AVN global dataset have been ingested as initial conditions. Grib resolution of 27 km is chosen to represent the current mesoscale model. The forecasts with the length of 36h are performed to output the result with 12h interval. The key parameters used to evaluate the forecast skill include 12h accumulated precipitation, sea level pressure, wind, surface temperature and dew point. Precipitation is evaluated statistically using conventional skill scores, Threat Score (TS) and Bias Score (BS), for different threshold values based on 12h rainfall observations whereas other statistical methods such as Mean Error (ME), Mean Absolute Error(MAE) and Root Mean Square Error (RMSE) are applied to other forecast parameters.

Protein model discrimination using mutational sensitivity derived from deep sequencing.

PubMed

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

Outcomes of subsequent non-muscle-invasive bladder cancer treated with intravesical Bacillus Calmette-Guérin after radical nephroureterectomy for upper urinary tract urothelial carcinoma.

PubMed

Miyake, Makito; Tatsumi, Yoshihiro; Matsumoto, Hiroaki; Nagao, Kazuhiro; Matsuyama, Hideyasu; Inamoto, Teruo; Azuma, Haruhito; Yasumoto, Hiroaki; Shiina, Hiroaki; Fujimoto, Kiyohide

2018-05-01

To describe the clinicopathological characteristics and prognosis of subsequent non-muscle-invasive bladder cancer (NMIBC) after radical nephroureterectomy (RNU) for upper urinary tract urothelial carcinoma (UTUC), and particularly its response to intravesical Bacillus Calmette-Guérin (BCG). An observational study was conducted in 1463 patients with UTUC who had undergone RNU and in 1555 patients with primary NMIBC. Of the 1463 patients with UTUC, 256 (17%) subsequently developed NMIBC (UTUC-NMIBC group) and were available for the analysis. The clinicopathological background and outcomes, including intravesical recurrence-free survival and bladder progression-free survival, were compared between the patients with UTUC-NMIBC and the patients with primary NMIBC treated with intravesical BCG. Propensity score matching was performed to adjust for the potential differences in the backgrounds of the two groups. To validate the utility of the CUETO scoring model in the UTUC-NMIBC group, risk scores were calculated and compared with the published probabilities for recurrence and progression. Compared with the unadjusted primary NMIBC group (n = 352), the UTUC-NMIBC group (n = 75) were found to have a worse prognosis for intravesical recurrence and progression, before propensity score matching. After propensity score matching for potential confounding factors, however, a worse prognosis was observed only for intravesical recurrence. The validation test of the CUETO scoring model for the UTUC-NMIBC group showed a significant difference in the rate of intravesical recurrence and progression for the 0-4 and 5-6 score groups between the UTUC-NMIBC group and the CUETO risk table reference data. Compared with the primary NMIBC group, the UTUC-NMIBC group had a worse prognosis after intravesical BCG, especially with regard to intravesical recurrence. This suggests that patients with UTUC-NMIBC are inherently poor responders to BCG exposure. An optimal treatment strategy and risk scoring model to select patients for adjuvant intravesical BCG, chemotherapy or immediate radical cystectomy should be established. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Uncertainties in Decadal Model Evaluation due to the Choice of Different Reanalysis Products

NASA Astrophysics Data System (ADS)

Illing, Sebastian; Kadow, Christopher; Kunst, Oliver; Cubasch, Ulrich

2014-05-01

In recent years decadal predictions have become very popular in the climate science community. A major task is the evaluation and validation of a decadal prediction system. Therefore hindcast experiments are performed and evaluated against observation based or reanalysis data-sets. That is, various metrics and skill scores like the anomaly correlation or the mean squared error skill score (MSSS) are calculated to estimate potential prediction skill of the model system. Our results will mostly feature the Baseline 1 hindcast experiments from the MiKlip decadal prediction system. MiKlip (www.fona-miklip.de) is a project for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) and has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. There are various reanalysis and observation based products covering at least the last forty years which can be used for model evaluation, for instance the 20th Century Reanalysis from NOAA-CIRES, the Climate Forecast System Reanalysis from NCEP or the Interim Reanalysis from ECMWF. Each of them is based on different climate models and observations. We will show that the choice of the reanalysis product has a huge impact on the value of various skill metrics. In some cases this may actually lead to a change in the interpretation of the results, e.g. when one tries to compare two model versions and the anomaly correlation difference changes its sign for two different reanalysis products. We will also show first results of our studies investigating the influence and effect of this source of uncertainty for decadal model evaluation. Furthermore we point out regions which are most affected by this uncertainty and where one has to cautious interpreting skill scores. In addition we introduce some strategies to overcome or at least reduce this source of uncertainty.

Numerical scoring for the Classic BILAG index.

PubMed

Cresswell, Lynne; Yee, Chee-Seng; Farewell, Vernon; Rahman, Anisur; Teh, Lee-Suan; Griffiths, Bridget; Bruce, Ian N; Ahmad, Yasmeen; Prabu, Athiveeraramapandian; Akil, Mohammed; McHugh, Neil; Toescu, Veronica; D'Cruz, David; Khamashta, Munther A; Maddison, Peter; Isenberg, David A; Gordon, Caroline

2009-12-01

To develop an additive numerical scoring scheme for the Classic BILAG index. SLE patients were recruited into this multi-centre cross-sectional study. At every assessment, data were collected on disease activity and therapy. Logistic regression was used to model an increase in therapy, as an indicator of active disease, by the Classic BILAG score in eight systems. As both indicate inactivity, scores of D and E were set to 0 and used as the baseline in the fitted model. The coefficients from the fitted model were used to determine the numerical values for Grades A, B and C. Different scoring schemes were then compared using receiver operating characteristic (ROC) curves. Validation analysis was performed using assessments from a single centre. There were 1510 assessments from 369 SLE patients. The currently used coding scheme (A = 9, B = 3, C = 1 and D/E = 0) did not fit the data well. The regression model suggested three possible numerical scoring schemes: (i) A = 11, B = 6, C = 1 and D/E = 0; (ii) A = 12, B = 6, C = 1 and D/E = 0; and (iii) A = 11, B = 7, C = 1 and D/E = 0. These schemes produced comparable ROC curves. Based on this, A = 12, B = 6, C = 1 and D/E = 0 seemed a reasonable and practical choice. The validation analysis suggested that although the A = 12, B = 6, C = 1 and D/E = 0 coding is still reasonable, a scheme with slightly less weighting for B, such as A = 12, B = 5, C = 1 and D/E = 0, may be more appropriate. A reasonable additive numerical scoring scheme based on treatment decision for the Classic BILAG index is A = 12, B = 5, C = 1, D = 0 and E = 0.

Numerical scoring for the Classic BILAG index

PubMed Central

Cresswell, Lynne; Yee, Chee-Seng; Farewell, Vernon; Rahman, Anisur; Teh, Lee-Suan; Griffiths, Bridget; Bruce, Ian N.; Ahmad, Yasmeen; Prabu, Athiveeraramapandian; Akil, Mohammed; McHugh, Neil; Toescu, Veronica; D’Cruz, David; Khamashta, Munther A.; Maddison, Peter; Isenberg, David A.

2009-01-01

Objective. To develop an additive numerical scoring scheme for the Classic BILAG index. Methods. SLE patients were recruited into this multi-centre cross-sectional study. At every assessment, data were collected on disease activity and therapy. Logistic regression was used to model an increase in therapy, as an indicator of active disease, by the Classic BILAG score in eight systems. As both indicate inactivity, scores of D and E were set to 0 and used as the baseline in the fitted model. The coefficients from the fitted model were used to determine the numerical values for Grades A, B and C. Different scoring schemes were then compared using receiver operating characteristic (ROC) curves. Validation analysis was performed using assessments from a single centre. Results. There were 1510 assessments from 369 SLE patients. The currently used coding scheme (A = 9, B = 3, C = 1 and D/E = 0) did not fit the data well. The regression model suggested three possible numerical scoring schemes: (i) A = 11, B = 6, C = 1 and D/E = 0; (ii) A = 12, B = 6, C = 1 and D/E = 0; and (iii) A = 11, B = 7, C = 1 and D/E = 0. These schemes produced comparable ROC curves. Based on this, A = 12, B = 6, C = 1 and D/E = 0 seemed a reasonable and practical choice. The validation analysis suggested that although the A = 12, B = 6, C = 1 and D/E = 0 coding is still reasonable, a scheme with slightly less weighting for B, such as A = 12, B = 5, C = 1 and D/E = 0, may be more appropriate. Conclusions. A reasonable additive numerical scoring scheme based on treatment decision for the Classic BILAG index is A = 12, B = 5, C = 1, D = 0 and E = 0. PMID:19779027

Development and reliability of a multi-modality scoring system for evaluation of disease progression in pre-clinical models of osteoarthritis: celecoxib may possess disease-modifying properties.

PubMed

Panahifar, A; Jaremko, J L; Tessier, A G; Lambert, R G; Maksymowych, W P; Fallone, B G; Doschak, M R

2014-10-01

We sought to develop a comprehensive scoring system for evaluation of pre-clinical models of osteoarthritis (OA) progression, and use this to evaluate two different classes of drugs for management of OA. Post-traumatic OA (PTOA) was surgically induced in skeletally mature rats. Rats were randomly divided in three groups receiving either glucosamine (high dose of 192 mg/kg) or celecoxib (clinical dose) or no treatment. Disease progression was monitored utilizing micro-magnetic resonance imaging (MRI), micro-computed tomography (CT) and histology. Pertinent features such as osteophytes, subchondral sclerosis, joint effusion, bone marrow lesion (BML), cysts, loose bodies and cartilage abnormalities were included in designing a sensitive multi-modality based scoring system, termed the rat arthritis knee scoring system (RAKSS). Overall, an inter-observer correlation coefficient (ICC) of greater than 0.750 was achieved for each scored feature. None of the treatments prevented cartilage loss, synovitis, joint effusion, or sclerosis. However, celecoxib significantly reduced osteophyte development compared to placebo. Although signs of inflammation such as synovitis and joint effusion were readily identified at 4 weeks post-operation, we did not detect any BML. We report the development of a sensitive and reliable multi-modality scoring system, the RAKSS, for evaluation of OA severity in pre-clinical animal models. Using this scoring system, we found that celecoxib prevented enlargement of osteophytes in this animal model of PTOA, and thus it may be useful in preventing OA progression. However, it did not show any chondroprotective effect using the recommended dose. In contrast, high dose glucosamine had no measurable effects. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Interpreting the g loadings of intelligence test composite scores in light of Spearman's law of diminishing returns.

PubMed

Reynolds, Matthew R

2013-03-01

The linear loadings of intelligence test composite scores on a general factor (g) have been investigated recently in factor analytic studies. Spearman's law of diminishing returns (SLODR), however, implies that the g loadings of test scores likely decrease in magnitude as g increases, or they are nonlinear. The purpose of this study was to (a) investigate whether the g loadings of composite scores from the Differential Ability Scales (2nd ed.) (DAS-II, C. D. Elliott, 2007a, Differential Ability Scales (2nd ed.). San Antonio, TX: Pearson) were nonlinear and (b) if they were nonlinear, to compare them with linear g loadings to demonstrate how SLODR alters the interpretation of these loadings. Linear and nonlinear confirmatory factor analysis (CFA) models were used to model Nonverbal Reasoning, Verbal Ability, Visual Spatial Ability, Working Memory, and Processing Speed composite scores in four age groups (5-6, 7-8, 9-13, and 14-17) from the DAS-II norming sample. The nonlinear CFA models provided better fit to the data than did the linear models. In support of SLODR, estimates obtained from the nonlinear CFAs indicated that g loadings decreased as g level increased. The nonlinear portion for the nonverbal reasoning loading, however, was not statistically significant across the age groups. Knowledge of general ability level informs composite score interpretation because g is less likely to produce differences, or is measured less, in those scores at higher g levels. One implication is that it may be more important to examine the pattern of specific abilities at higher general ability levels. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The “Dry-Run” Analysis: A Method for Evaluating Risk Scores for Confounding Control

PubMed Central

Wyss, Richard; Hansen, Ben B.; Ellis, Alan R.; Gagne, Joshua J.; Desai, Rishi J.; Glynn, Robert J.; Stürmer, Til

2017-01-01

Abstract A propensity score (PS) model's ability to control confounding can be assessed by evaluating covariate balance across exposure groups after PS adjustment. The optimal strategy for evaluating a disease risk score (DRS) model's ability to control confounding is less clear. DRS models cannot be evaluated through balance checks within the full population, and they are usually assessed through prediction diagnostics and goodness-of-fit tests. A proposed alternative is the “dry-run” analysis, which divides the unexposed population into “pseudo-exposed” and “pseudo-unexposed” groups so that differences on observed covariates resemble differences between the actual exposed and unexposed populations. With no exposure effect separating the pseudo-exposed and pseudo-unexposed groups, a DRS model is evaluated by its ability to retrieve an unconfounded null estimate after adjustment in this pseudo-population. We used simulations and an empirical example to compare traditional DRS performance metrics with the dry-run validation. In simulations, the dry run often improved assessment of confounding control, compared with the C statistic and goodness-of-fit tests. In the empirical example, PS and DRS matching gave similar results and showed good performance in terms of covariate balance (PS matching) and controlling confounding in the dry-run analysis (DRS matching). The dry-run analysis may prove useful in evaluating confounding control through DRS models. PMID:28338910

A rat hysteropexy model for evaluating adhesion formation and comparison of two different structured meshes.

PubMed

Gokmen-Karasu, Ayse Filiz; Aydin, Serdar; Sonmez, Fatma Cavide; Adanir, Ilknur; Ilhan, Gulsah; Ates, Seda

2017-11-01

Peritonization of mesh during sacrohysteropexy is generally advocated to prevent adhesions to the viscera; however, randomized clinical trials are lacking, and peritonization may not be completely possible in a laparoscopic hysteropexy procedure. Our main objective was to describe a basic experimental rat sacrohysteropexy model. We hypothesized that even when peritoneal closure was omitted, using composite mesh would result in less adhesions to the viscera. Twenty in-bred female virgin Wistar Hannover rats were used in this study. Standardized hysteropexy procedure and adhesion model is described step by step with two different mesh materials: polypropylene and a composite polyester. Mesh was anchored between the posterior cervix and anterior longitudinal ligament of the lumbar vertebrae. Macroscopic adhesion scores and histopathological tissue reaction was investigated. Macroscopically, the surface area involved in adhesions was similar between groups. However, adhesions in the polypropylene group were more dense, required sharp dissection for lysis, and yielded higher total macroscopic adhesion scores (p < 0.001). Histologically, a more pronounced host inflammatory response was encountered in the polyester group (p < 0.001). We describe a rat hysteropexy model and a previously established uterine adhesion model. Adhesion scores in the composite mesh group were lower, and bowel involvement was not seen. Our findings are promising, and further research investigating antiadhesive composite mesh use for hysterosacropexy would be appropriate, especially when peritoneal closure is omitted.

Effect of a Lower Extremity Preventive Training Program on Physical Performance Scores in Military Recruits.

PubMed

Peck, Karen Y; DiStefano, Lindsay J; Marshall, Stephen W; Padua, Darin A; Beutler, Anthony I; de la Motte, Sarah J; Frank, Barnett S; Martinez, Jessica C; Cameron, Kenneth L

2017-11-01

Peck, KY, DiStefano, LJ, Marshall, SW, Padua, DA, Beutler, AI, de la Motte, SJ, Frank, BS, Martinez, JC, and Cameron, KL. Effect of a lower extremity preventive training program on physical performance scores in military recruits. J Strength Cond Res 31(11): 3146-3157, 2017-Exercise-based preventive training programs are designed to improve movement patterns associated with lower extremity injury risk; however, the impact of these programs on general physical fitness has not been evaluated. The purpose of this study was to compare fitness scores between participants in a preventive training program and a control group. One thousand sixty-eight freshmen from a U.S. Service Academy were cluster-randomized into either the intervention or control group during 6 weeks of summer training. The intervention group performed a preventive training program, specifically the Dynamic Integrated Movement Enhancement (DIME), which is designed to improve lower extremity movement patterns. The control group performed the Army Preparation Drill (PD), a warm-up designed to prepare soldiers for training. Main outcome measures were the Army Physical Fitness Test (APFT) raw and scaled (for age and sex) scores. Independent t tests were used to assess between-group differences. Multivariable logistic regression models were used to control for the influence of confounding variables. Dynamic Integrated Movement Enhancement group participants completed the APFT 2-mile run 20 seconds faster compared with the PD group (p < 0.001), which corresponded with significantly higher scaled scores (p < 0.001). Army Physical Fitness Test push-up scores were significantly higher in the DIME group (p = 0.041), but there were no significant differences in APFT sit-up scores. The DIME group had significantly higher total APFT scores compared with the PD group (p < 0.001). Similar results were observed in multivariable models after controlling for sex and body mass index (BMI). Committing time to the implementation of a preventive training program does not appear to negatively affect fitness test scores.

Comparison of the Full Outline of UnResponsiveness score and the Glasgow Coma Scale in predicting mortality in critically ill patients*.

PubMed

Wijdicks, Eelco F M; Kramer, Andrew A; Rohs, Thomas; Hanna, Susan; Sadaka, Farid; O'Brien, Jacklyn; Bible, Shonna; Dickess, Stacy M; Foss, Michelle

2015-02-01

Impaired consciousness has been incorporated in prediction models that are used in the ICU. The Glasgow Coma Scale has value but is incomplete and cannot be assessed in intubated patients accurately. The Full Outline of UnResponsiveness score may be a better predictor of mortality in critically ill patients. Thirteen ICUs at five U.S. hospitals. One thousand six hundred ninety-five consecutive unselected ICU admissions during a six-month period in 2012. Glasgow Coma Scale and Full Outline of UnResponsiveness score were recorded within 1 hour of admission. Baseline characteristics and physiologic components of the Acute Physiology and Chronic Health Evaluation system, as well as mortality were linked to Glasgow Coma Scale/Full Outline of UnResponsiveness score information. None. We recruited 1,695 critically ill patients, of which 1,645 with complete data could be linked to data in the Acute Physiology and Chronic Health Evaluation system. The area under the receiver operating characteristic curve of predicting ICU mortality using the Glasgow Coma Scale was 0.715 (95% CI, 0.663-0.768) and using the Full Outline of UnResponsiveness score was 0.742 (95% CI, 0.694-0.790), statistically different (p = 0.001). A similar but nonsignificant difference was found for predicting hospital mortality (p = 0.078). The respiratory and brainstem reflex components of the Full Outline of UnResponsiveness score showed a much wider range of mortality than the verbal component of Glasgow Coma Scale. In multivariable models, the Full Outline of UnResponsiveness score was more useful than the Glasgow Coma Scale for predicting mortality. The Full Outline of UnResponsiveness score might be a better prognostic tool of ICU mortality than the Glasgow Coma Scale in critically ill patients, most likely a result of incorporating brainstem reflexes and respiration into the Full Outline of UnResponsiveness score.

Satisfaction with life after burn: A Burn Model System National Database Study.

PubMed

Goverman, J; Mathews, K; Nadler, D; Henderson, E; McMullen, K; Herndon, D; Meyer, W; Fauerbach, J A; Wiechman, S; Carrougher, G; Ryan, C M; Schneider, J C

2016-08-01

While mortality rates after burn are low, physical and psychosocial impairments are common. Clinical research is focusing on reducing morbidity and optimizing quality of life. This study examines self-reported Satisfaction With Life Scale scores in a longitudinal, multicenter cohort of survivors of major burns. Risk factors associated with Satisfaction With Life Scale scores are identified. Data from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) Burn Model System (BMS) database for burn survivors greater than 9 years of age, from 1994 to 2014, were analyzed. Demographic and medical data were collected on each subject. The primary outcome measures were the individual items and total Satisfaction With Life Scale (SWLS) scores at time of hospital discharge (pre-burn recall period) and 6, 12, and 24 months after burn. The SWLS is a validated 5-item instrument with items rated on a 1-7 Likert scale. The differences in scores over time were determined and scores for burn survivors were also compared to a non-burn, healthy population. Step-wise regression analysis was performed to determine predictors of SWLS scores at different time intervals. The SWLS was completed at time of discharge (1129 patients), 6 months after burn (1231 patients), 12 months after burn (1123 patients), and 24 months after burn (959 patients). There were no statistically significant differences between these groups in terms of medical or injury demographics. The majority of the population was Caucasian (62.9%) and male (72.6%), with a mean TBSA burned of 22.3%. Mean total SWLS scores for burn survivors were unchanged and significantly below that of a non-burn population at all examined time points after burn. Although the mean SWLS score was unchanged over time, a large number of subjects demonstrated improvement or decrement of at least one SWLS category. Gender, TBSA burned, LOS, and school status were associated with SWLS scores at 6 months; scores at 12 months were associated with LOS, school status, and amputation; scores at 24 months were associated with LOS, school status, and drug abuse. In this large, longitudinal, multicenter cohort of burn survivors, satisfaction with life after burn was consistently lower than that of non-burn norms. Furthermore mean SWLS scores did not improve over the two-year follow-up period. This study demonstrates the need for continued efforts to improve patient-centered long term satisfaction with life after burn. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

THE IMPACT OF MEASURES OF SOCIOECONOMIC STATUS ON HOSPITAL PROFILING IN NEW YORK CITY

PubMed Central

Blum, Alexander B.; Egorova, Natalia N.; Sosunov, Eugene A.; Gelijns, Annetine C.; DuPree, Erin; Moskowitz, Alan J.; Federman, Alex D.; Ascheim, Deborah D.; Keyhani, Salomeh

2014-01-01

Background Current 30-day readmission models used by the Center for Medicare and Medicaid Services for the purpose of hospital-level comparisons lack measures of socioeconomic status (SES). We examined whether the inclusion of a SES measure in 30-day congestive heart failure (CHF) readmission models changed hospital risk standardized readmission rates (RSRR) in New York City (NYC) hospitals. Methods and Results Using a Centers for Medicare & Medicaid Services (CMS)-like model we estimated 30-day hospital-level RSRR by adjusting for age, gender and comorbid conditions. Next, we examined how hospital RSRRs changed relative to the New York City mean with inclusion of the Agency for Healthcare Research and Quality (AHRQ) validated SES index score. In a secondary analysis, we examined whether inclusion of the AHRQ SES Index score in 30-day readmission models disproportionately impacted the RSRR of minority-serving hospitals. Higher AHRQ SES scores, indicators of higher socioeconomic status, were associated with lower odds, 0.99, of 30-day readmission (p< 0.019). The addition of the AHRQ SES index did not change the model’s C statistic (0.63). After adjustment for the AHRQ SES index, one hospital changed status from “worse than the NYC average” to “no different than the NYC average”. After adjustment for the AHRQ SES index, one NYC minority-serving hospital was re-classified from “worse” to “no different than average”. Conclusions While patients with higher SES were less likely to be admitted, the impact of SES on readmission was very small. In NYC, inclusion of the AHRQ SES score in a CMS based model did not impact hospital-level profiling based on 30-day readmission. PMID:24823956

Non-stationarities in the relationships of heavy precipitation events in the Mediterranean area and the large-scale circulation in the second half of the 20th century

NASA Astrophysics Data System (ADS)

Merkenschlager, Christian; Hertig, Elke; Jacobeit, Jucundus

2017-04-01

In the context of analyzing temporal varying relationships of heavy precipitation events in the Mediterranean area and associated anomalies of the large-scale circulation, quantile regression models were established. The models were calibrated using different circulation and thermodynamic variables at the 700 hPa and 850 hPa levels as predictors as well as daily precipitation time series at different stations in the Mediterranean area as predictand. Analyses were done for the second half of the 20th century. In the scope of assessing non-stationarities in the predictor-predictand relationships the time series were divided into calibration and validation periods. 100 randomized subsamples were used to calibrate/validate the models under stationary conditions. The highest and lowest skill score of the 100 random samples was used to determine the range of random variability. The model performance under non-stationary conditions was derived from the skill scores of cross-validated running subintervals. If the skill scores of several consecutive years are outside the range of random variability a non-stationarity was declaimed. Particularly the Iberian Peninsula and the Levant region were affected by non-stationarities, the former with significant positive deviations of the skill scores, the latter with significant negative deviations. By means of a case study for the Levant region we determined three possible reasons for non-stationary behavior in the predictor-predictand relationships. The Mediterranean Oscillation as a superordinate system affects the cyclone activity in the Mediterranean basin and the location and intensity of the Cyprus low. Overall, it is demonstrated that non-stationarities have to be taken into account within statistical downscaling model development.

Does a socio-ecological school model promote resilience in primary schools?

PubMed

Lee, Patricia C; Stewart, Donald E

2013-11-01

This research investigates the extent to which the holistic, multistrategy "health-promoting school" (HPS) model using a resilience intervention can lead to improved resilience among students. A quasi-experimental design using a study cohort selected from 20 primary schools in Queensland, Australia was employed. Ten intervention schools using HPS protocols, with training support, were compared with 10 control schools in student resilience scores and protective factors. Baseline data explored the interactive effect of protective factors on overall resilience scores. Postintervention analysis compared changes in protective factors and resilience, after implementing the HPS project. Baseline data analysis indicated no significant differences in the mean scores of protective factors and resilience scores between intervention and control groups (except for school connection). After 18 months of implementation, a resurvey showed that the intervention group had significantly higher scores than the control group on students' family connection, community connection, peer support, and their overall resilience. Results showed that students in the HPS group had significantly higher scores on resilience than did students in the control group. A comprehensive, whole-school approach to building resilience that integrates students, staff, and community can strengthen important protective factors and build student resilience. © 2013, American School Health Association.

Discriminative value of FRAX for fracture prediction in a cohort of Chinese postmenopausal women.

PubMed

Cheung, E Y N; Bow, C H; Cheung, C L; Soong, C; Yeung, S; Loong, C; Kung, A

2012-03-01

We followed 2,266 postmenopausal Chinese women for 4.5 years to determine which model best predicts osteoporotic fracture. A model that contains ethnic-specific risk factors, some of which reflect frailty, performed as well as or better than the well-established FRAX model. Clinical risk assessment, with or without T-score, can predict fractures in Chinese postmenopausal women although it is unknown which combination of clinical risk factors is most effective. This prospective study sought to compare the accuracy for fracture prediction using various models including FRAX, our ethnic-specific clinical risk factors (CRF) and other simple models. This study is part of the Hong Kong Osteoporosis Study. A total of 2,266 treatment naïve postmenopausal women underwent clinical risk factor and bone mineral density assessment. Subjects were followed up for outcome of major osteoporotic fracture and receiver operating characteristic (ROC) curves for different models were compared. The percentage of subjects in different quartiles of risk according to various models who actually fractured was also compared. The mean age at baseline was 62.1 ± 8.5 years and mean follow-up time was 4.5 ± 2.8 years. A total of 106 new major osteoporotic fractures were reported, of which 21 were hip fractures. Ethnic-specific CRF with T-score performed better than FRAX with T-score (based on both Chinese normative and National Health and Nutrition Examination Survey (NHANES) databases) in terms of AUC comparison for prediction of major osteoporotic fracture. The two models were similar in hip fracture prediction. The ethnic-specific CRF model had a 10% higher sensitivity than FRAX at a specificity of 0.8 or above. CRF related to frailty and differences in lifestyle between populations are likely to be important in fracture prediction. Further work is required to determine which and how CRF can be applied to develop a fracture prediction model in our population.

Ischemic stroke risk in East Asian patients with CHA2DS2-VASc score of 1: systematic review and meta-analysis.

PubMed

Bai, Ying; Shantsila, Alena; Lip, Gregory Y H

2017-02-01

The use of anticoagulation for stroke prevention in patients with atrial fibrillation (AF) and CHA 2 DS 2 -VASc score of 1 has been debated, partially due to limited data on ischemic stroke risk and specific clinical trials in these patients. East Asian patients have a different stroke risk profile compared to non-East Asians. We performed a systematic review and meta-analysis of ischemic stroke risk in AF patients with a CHA 2 DS 2 -VASc score of 1 in East Asian countries. A comprehensive literature search for studies evaluating ischemic stroke risk related with AF with CHA 2 DS 2 -VASc score of 1 was conducted by two reviewers. We used a fixed-effect model first, then a random-effect model if heterogeneity was assessed with I 2 . After pooling 6 studies, the annual rate of ischemic stroke in East Asian patients with AF and a CHA 2 DS 2 -VASc score of 1 was 1.66% (95% CI: 0.71%-2.61%, I2 = 98.4%). There was a wide range in reported pooled rates between countries, from 0.59% to 3.13%. Significant difference existed not only in the community-based studies (Chinese: 2.10% vs. Japanese: 0.60%), but also from the hospital-based studies (Chinese: 3.55% vs. Japanese: 0.42%). Confining the analysis to those on no antithrombotic treatment had limited effect on the summary estimate (eg. Chinese: 4.28% vs. Japanese: 0.6%). In Chinese studies, ischemic stroke rate was lower in females than males (female: 1.40% vs. male: 1.79%). However, the low event rate in Japanese studies may reflect unrecorded anticoagulation status at follow-up. Some regional differences between East Asian countries were observed for ischemic stroke risk in patients with a CHA 2 DS 2 -VASc score of 1. This may reflect methodological differences in studies and unrecorded anticoagulation use at followup, but further prospective studies are required to ascertain ischemic stroke risks, as well as the differences and reasons for this between East Asians and non-East Asians.

Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

PubMed Central

Wang, Yunpeng; Thompson, Wesley K.; Schork, Andrew J.; Holland, Dominic; Chen, Chi-Hua; Bettella, Francesco; Desikan, Rahul S.; Li, Wen; Witoelar, Aree; Zuber, Verena; Devor, Anna; Nöthen, Markus M.; Rietschel, Marcella; Chen, Qiang; Werge, Thomas; Cichon, Sven; Weinberger, Daniel R.; Djurovic, Srdjan; O’Donovan, Michael; Visscher, Peter M.; Andreassen, Ole A.; Dale, Anders M.

2016-01-01

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3. PMID:26808560

Comparative study of the Aristotle Comprehensive Complexity and the Risk Adjustment in Congenital Heart Surgery scores.

PubMed

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

2011-09-01

The Aristotle Comprehensive Complexity (ACC) and the Risk Adjustment in Congenital Heart Surgery (RACHS-1) scores have been proposed for complexity adjustment in the analysis of outcome after congenital heart surgery. Previous studies found RACHS-1 to be a better predictor of outcome than the Aristotle Basic Complexity score. We compared the ability to predict operative mortality and morbidity between ACC, the latest update of the Aristotle method and RACHS-1. Morbidity was assessed by length of intensive care unit stay. We retrospectively enrolled patients undergoing congenital heart surgery. We modeled each score as a continuous variable, mortality as a binary variable, and length of stay as a censored variable. We compared performance between mortality and morbidity models using likelihood ratio tests for nested models and paired concordance statistics. Among all 1,384 patients enrolled, 30-day mortality rate was 3.5% and median length of intensive care unit stay was 3 days. Both scores strongly related to mortality, but ACC made better prediction than RACHS-1; c-indexes 0.87 (0.84, 0.91) vs 0.75 (0.65, 0.82). Both scores related to overall length of stay only during the first postoperative week, but ACC made better predictions than RACHS-1; U statistic=0.22, p<0.001. No significant difference was noted after adjusting RACHS-1 models on age, prematurity, and major extracardiac abnormalities. The ACC was a better predictor of operative mortality and length of intensive care unit stay than RACHS-1. In order to achieve similar performance, regression models including RACHS-1 need to be further adjusted on age, prematurity, and major extracardiac abnormalities. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Incorporating sequence information into the scoring function: a hidden Markov model for improved peptide identification.

PubMed

Khatun, Jainab; Hamlett, Eric; Giddings, Morgan C

2008-03-01

The identification of peptides by tandem mass spectrometry (MS/MS) is a central method of proteomics research, but due to the complexity of MS/MS data and the large databases searched, the accuracy of peptide identification algorithms remains limited. To improve the accuracy of identification we applied a machine-learning approach using a hidden Markov model (HMM) to capture the complex and often subtle links between a peptide sequence and its MS/MS spectrum. Our model, HMM_Score, represents ion types as HMM states and calculates the maximum joint probability for a peptide/spectrum pair using emission probabilities from three factors: the amino acids adjacent to each fragmentation site, the mass dependence of ion types and the intensity dependence of ion types. The Viterbi algorithm is used to calculate the most probable assignment between ion types in a spectrum and a peptide sequence, then a correction factor is added to account for the propensity of the model to favor longer peptides. An expectation value is calculated based on the model score to assess the significance of each peptide/spectrum match. We trained and tested HMM_Score on three data sets generated by two different mass spectrometer types. For a reference data set recently reported in the literature and validated using seven identification algorithms, HMM_Score produced 43% more positive identification results at a 1% false positive rate than the best of two other commonly used algorithms, Mascot and X!Tandem. HMM_Score is a highly accurate platform for peptide identification that works well for a variety of mass spectrometer and biological sample types. The program is freely available on ProteomeCommons via an OpenSource license. See http://bioinfo.unc.edu/downloads/ for the download link.

Parents’ Differential Treatment and Adolescents’ Delinquent Behaviors: Direct and Indirect Effects of Difference Score- and Perception-Based Measures

PubMed Central

Jensen, Alexander C.; Whiteman, Shawn D.

2014-01-01

A body of work reveals that parents’ differential treatment (PDT) is linked to adolescents’ adjustment. To date, researchers have generally used one of two different methods of assessing PDT--difference scores or perception-based measures--yet, have largely failed to consider whether these measures index similar or distinct aspects of PDT. The current study examined these distinctions and the conceptual and empirical links between these two approaches by assessing the direct and indirect associations (difference scores via perceptions) of PDT and adolescents’ delinquency and substance use. Furthermore, we explored whether these within-family differences were moderated by between-family differences in levels of parenting. Data were analyzed from 282 adolescent sibling pairs (N = 564; older siblings, M = 17.17 years old, SD = .94; younger siblings, M = 14.52 years old, SD = 1.27). Results from structural equation models revealed that for youth in affectively mild (low in conflict and intimacy) and intense families (high in conflict and intimacy), difference scores and perceptions were uniquely and directly linked to adjustment, such that less favored treatment and the perception of less favored treatment was linked to greater participation in delinquent activities and substance use. Additionally, in several instances difference scores for youth in affectively mild and intense families were indirectly linked to delinquency and substance use through the perception of PDT. Discussion focuses on the distinctions and links between these two approaches within the Social Comparison Theory framework and the greater context of family levels of conflict and intimacy. PMID:24821522

A Comparison of Methods for Estimating Conditional Item Score Differences in Differential Item Functioning (DIF) Assessments. Research Report. ETS RR-10-15

ERIC Educational Resources Information Center

Moses, Tim; Miao, Jing; Dorans, Neil

2010-01-01

This study compared the accuracies of four differential item functioning (DIF) estimation methods, where each method makes use of only one of the following: raw data, logistic regression, loglinear models, or kernel smoothing. The major focus was on the estimation strategies' potential for estimating score-level, conditional DIF. A secondary focus…

Three models intercomparison for Quantitative Precipitation Forecast over Calabria

NASA Astrophysics Data System (ADS)

Federico, S.; Avolio, E.; Bellecci, C.; Colacino, M.; Lavagnini, A.; Accadia, C.; Mariani, S.; Casaioli, M.

2004-11-01

In the framework of the National Project “Sviluppo di distretti industriali per le Osservazioni della Terra” (Development of Industrial Districts for Earth Observations) funded by MIUR (Ministero dell'Università e della Ricerca Scientifica --Italian Ministry of the University and Scientific Research) two operational mesoscale models were set-up for Calabria, the southernmost tip of the Italian peninsula. Models are RAMS (Regional Atmospheric Modeling System) and MM5 (Mesoscale Modeling 5) that are run every day at Crati scrl to produce weather forecast over Calabria (http://www.crati.it). This paper reports model intercomparison for Quantitative Precipitation Forecast evaluated for a 20 month period from 1th October 2000 to 31th May 2002. In addition to RAMS and MM5 outputs, QBOLAM rainfall fields are available for the period selected and included in the comparison. This model runs operationally at “Agenzia per la Protezione dell'Ambiente e per i Servizi Tecnici”. Forecasts are verified comparing models outputs with raingauge data recorded by the regional meteorological network, which has 75 raingauges. Large-scale forcing is the same for all models considered and differences are due to physical/numerical parameterizations and horizontal resolutions. QPFs show differences between models. Largest differences are for BIA compared to the other considered scores. Performances decrease with increasing forecast time for RAMS and MM5, whilst QBOLAM scores better for second day forecast.

The effect of pre-service training on post-graduation skill and knowledge retention among mid-level healthcare providers in Mozambique.

PubMed

Feldacker, Caryl; Chicumbe, Sergio; Dgedge, Martinho; Cesar, Freide; Augusto, Gerito; Robertson, Molly; Mbofana, Francisco; O'Malley, Gabrielle

2015-04-16

Mozambique suffers from critical shortages of healthcare workers including non-physician clinicians, Tecnicos de Medicina Geral (TMGs), who are often senior clinicians in rural health centres. The Mozambique Ministry of Health and the International Training and Education Center for Health, University of Washington, Seattle, revised the national curriculum to improve TMG clinical knowledge and skills. To evaluate the effort, data was collected at graduation and 10 months later from pre-revision (initial) and revised curriculum TMGs to determine the following: (1) Did cohorts trained in the revised curriculum score higher on measurements of clinical knowledge, physical exam procedures, and solving clinical case scenarios than those trained in the initial curriculum; (2) Did TMGs in both curricula retain their knowledge over time (from baseline to follow-up); and (3) Did skills and knowledge retention differ over time by curricula? Post-graduation and over time results are presented. t-tests examine differences in scores between curriculum groups. Univariate and multivariate linear regression models assess curriculum-related, demographic, and workplace factors associated with scores on each of three evaluation methods at the p < 0.05 level. Paired t-tests examine within-group changes over time. ANOVA models explore differences between Health Training Institutes (HTIs). Generalized estimating equations determine whether change in scores over time differed by curricula. Mean scores of initial curriculum TMGs at follow-up were 52.7%, 62.6%, and 40.0% on the clinical cases, knowledge test, and physical exam, respectively. Averages were significantly higher among the revised group for clinical cases (60.2%; p < 0.001) and physical exam (47.6%; p < 0.001). HTI was influential on clinical case and physical exam scores. Between graduation and follow-up, clinical case and physical exam scores decreased significantly for initial curriculum students; clinical case scores increased significantly among revised curriculum TMGs. Although curriculum revision had limited effect, marginal improvements in the revised group show promise that these TMGs may have increased ability to synthesize clinical information. Weaknesses in curriculum and practicum implementation likely compromised the effect of curriculum revision. An improvement strategy that includes strengthened TMG training, greater attention to pre-service clinical practice, and post-graduation mentoring may be more advantageous than curriculum revision, alone, to improve care provided by TMGs.

Stress response and communication in surgeons undergoing training in endoscopic management of major vessel hemorrhage: a mixed methods study.

PubMed

Jukes, Alistair K; Mascarenhas, Annika; Murphy, Jae; Stepan, Lia; Muñoz, Tamara N; Callejas, Claudio A; Valentine, Rowan; Wormald, P J; Psaltis, Alkis J

2017-06-01

Major vessel hemorrhage in endoscopic, endonasal skull-base surgery is a rare but potentially fatal event. Surgical simulation models have been developed to train surgeons in the techniques required to manage this complication. This mixed-methods study aims to quantify the stress responses the model induces, determine how realistic the experience is, and how it changes the confidence levels of surgeons in their ability to deal with major vascular injury in an endoscopic setting. Forty consultant surgeons and surgeons in training underwent training on an endoscopic sheep model of jugular vein and carotid artery injury. Pre-course and post-course questionnaires providing demographics, experience level, confidence, and realism scores were taken, based on a 5-point Likert scale. Objective markers of stress response including blood pressure, heart rate, and salivary alpha-amylase levels were measured. Mean "realism" score assessed posttraining showed the model to be perceived as highly realistic by the participants (score 4.02). Difference in participant self-rated pre-course and post-course confidence levels was significant (p < 0.0001): mean pre-course confidence level 1.66 (95% confidence interval [CI], 1.43 to 1.90); mean post-course confidence level 3.42 (95% CI, 3.19 to 3.65). Differences in subjects' heart rates (HRs) and mean arterial blood pressures (MAPs) were significant between injury models (p = 0.0008, p = 0.0387, respectively). No statistically significant difference in salivary alpha-amylase levels pretraining and posttraining was observed. Results from this study indicate that this highly realistic simulation model provides surgeons with an increased level of confidence in their ability to deal with the rare but potentially catastrophic event of major vessel injury in endoscopic skull-base surgery. © 2017 ARS-AAOA, LLC.

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

PubMed

Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

2016-05-20

Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Serial evaluation of the MODS, SOFA and LOD scores to predict ICU mortality in mixed critically ill patients.

PubMed

Khwannimit, Bodin

2008-09-01

To perform a serial assessment and compare ability in predicting the intensive care unit (ICU) mortality of the multiple organ dysfunction score (MODS), sequential organ failure assessment (SOFA) and logistic organ dysfunction (LOD) score. The data were collected prospectively on consecutive ICU admissions over a 24-month period at a tertiary referral university hospital. The MODS, SOFA, and LOD scores were calculated on initial and repeated every 24 hrs. Two thousand fifty four patients were enrolled in the present study. The maximum and delta-scores of all the organ dysfunction scores correlated with ICU mortality. The maximum score of all models had better ability for predicting ICU mortality than initial or delta score. The areas under the receiver operating characteristic curve (AUC) for maximum scores was 0.892 for the MODS, 0.907 for the SOFA, and 0.92for the LOD. No statistical difference existed between all maximum scores and Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Serial assessment of organ dysfunction during the ICU stay is reliable with ICU mortality. The maximum scores is the best discrimination comparable with APACHE II score in predicting ICU mortality.

[Effects of transtheoretical model intervention on improving self-esteem of obese children].

PubMed

Zhang, Xueyan; Zhou, Leshan; Li, Chenchen

2013-07-01

To explore the effects of transtheoretical model (TTM) intervention on improving self-esteem status of obese children. A quasi-experimental research was conducted using a repeated-measure, pretest-posttest control group design in one randomly-selected boarding school of Changsha, Hunan Province in China. Seventy-three obesity students (54 males, 19 females) among grade three to six were included. All participants received first assessment, including: demographic data, stage of change questionnaire, and the Self-Esteem Scale (SES). According to the baseline data, different intervention measures based on TTM were given to different students to promote them to begin exercise and improve their self-esteem status. Follow-up assessments were collected respectively at 1- and 6- month after intervention. Intervention effects on proportion of obese children and self-esteem status as well as BMI were explored. All analyses were conducted using SPSS 17.0. After intervention, the proportion of obese children in precontemplation and maintenance stages was significantly different (P < 0.001). BMI and SES scores didn't change significantly. SES score was significantly different in five stages among three intervention points (P < 0.001). Obesity children who are in the later stages have higher self-esteem scores than those in former stages. Intervention based on TTM can help obese children move through the stages of change.

Discover cervical disc arthroplasty versus anterior cervical discectomy and fusion in symptomatic cervical disc diseases: A meta-analysis.

PubMed

Shangguan, Lei; Ning, Guang-Zhi; Tang, Yu; Wang, Zhe; Luo, Zhuo-Jing; Zhou, Yue

2017-01-01

Symptomatic cervical disc disease (SCDD) is a common degenerative disease, and Discover artificial cervical disc, a new-generation nonconstrained artificial disk, has been developed and performed gradually to treat it. We performed this meta-analysis to compare the efficacy and safety between Discover cervical disc arthroplasty (DCDA) and anterior cervical discectomy and fusion (ACDF) for SCDD. An exhaustive literature search of PubMed, EMBASE, and the Cochrane Library was conducted to identify randomized controlled trials that compared DCDA with ACDF for patients suffering SCDD. A random-effect model was used. Results were reported as standardized mean difference or risk ratio with 95% confidence interval. Of 33 articles identified, six studies were included. Compared with ACDF, DCDA demonstrated shorter operation time (P < 0.0001), and better range of motion (ROM) at the operative level (P < 0.00001). But no significant differences were observed in blood loss, neck disability index (NDI) scores, neck and arm pain scores, Japanese orthopaedic association (JOA) scores, secondary surgery procedures and adverse events (P > 0.05). Subgroup analyses did not demonstrated significant differences. In conclusion, DCDA presented shorter operation time, and better ROM at the operative level. However, no significant differences were observed in blood loss, NDI scores, neck and arm pain scores, JOA scores, secondary surgery procedures and adverse events between the two groups. Additionally, more studies of high quality with mid- to long-term follow-up are required in future.

Psychometric evaluation of the WHOQOL-BREF, Taiwan version, across five kinds of Taiwanese cancer survivors: Rasch analysis and confirmatory factor analysis.

PubMed

Lin, Chung-Ying; Hwang, Jing-Shiang; Wang, Wen-Chung; Lai, Wu-Wei; Su, Wu-Chou; Wu, Tzu-Yi; Yao, Grace; Wang, Jung-Der

2018-04-13

Quality of life (QoL) is important for clinicians to evaluate how cancer survivors judge their sense of well-being, and WHOQOL-BREF may be a good tool for clinical use. However, at least three issues remain unresolved: (1) the psychometric properties of the WHOQOL-BREF for cancer patients are insufficient; (2) the scoring method used for WHOQOL-BREF needs to be clarify; (3) whether different types of cancer patients interpret the WHOQOL-BREF similarly. We recruited 1000 outpatients with head/neck cancer, 1000 with colorectal cancer, 965 with liver cancer, 1438 with lung cancer and 1299 with gynecologic cancers in a medical center. Data analyses included Rasch models, confirmatory factor analysis (CFA), and Pearson correlations. The mean WHOQOL-BREF domain scores were between 13.34 and 14.77 among all participants. CFA supported construct validity; Rasch models revealed that almost all items were embedded in their expected domains and were interpreted similarly across five types of cancer patients; all correlation coefficients between Rasch scores and original domain scores were above 0.9. The linear relationship between Rasch scores and domain scores suggested that the current calculations for domain scores were applicable and without serious bias. Clinical practitioners may regularly collect and record the WHOQOL-BREF domain scores into electronic health records. Copyright © 2018. Published by Elsevier B.V.

Mortality Risk After Transcatheter Aortic Valve Implantation: Analysis of the Predictive Accuracy of the Transcatheter Valve Therapy Registry Risk Assessment Model.

PubMed

Codner, Pablo; Malick, Waqas; Kouz, Remi; Patel, Amisha; Chen, Cheng-Han; Terre, Juan; Landes, Uri; Vahl, Torsten Peter; George, Isaac; Nazif, Tamim; Kirtane, Ajay J; Khalique, Omar K; Hahn, Rebecca T; Leon, Martin B; Kodali, Susheel

2018-05-08

Risk assessment tools currently used to predict mortality in transcatheter aortic valve implantation (TAVI) were designed for patients undergoing cardiac surgery. We aim to assess the accuracy of the TAVI dedicated American College of Cardiology / Transcatheter Valve Therapies (ACC/TVT) risk score in predicting mortality outcomes. Consecutive patients (n=1038) undergoing TAVI at a single institution from 2014 to 2016 were included. The ACC/TVT registry mortality risk score, the Society of Thoracic Surgeons - Patient Reported Outcomes (STS-PROM) score and the EuroSCORE II were calculated for all patients. In hospital and 30-day all-cause mortality rates were 1.3% and 2.9%, respectively. The ACC/TVT risk stratification tool scored higher for patients who died in-hospital than in those who survived the index hospitalization (6.4 ± 4.6 vs. 3.5 ± 1.6, p = 0.03; respectively). The ACC/TVT score showed a high level of discrimination, C-index for in-hospital mortality 0.74, 95% CI [0.59 - 0.88]. There were no significant differences between the performance of the ACC/TVT registry risk score, the EuroSCORE II and the STS-PROM for in hospital and 30-day mortality rates. The ACC/TVT registry risk model is a dedicated tool to aid in the prediction of in-hospital mortality risk after TAVI.

Confounder summary scores when comparing the effects of multiple drug exposures.

PubMed

Cadarette, Suzanne M; Gagne, Joshua J; Solomon, Daniel H; Katz, Jeffrey N; Stürmer, Til

2010-01-01

Little information is available comparing methods to adjust for confounding when considering multiple drug exposures. We compared three analytic strategies to control for confounding based on measured variables: conventional multivariable, exposure propensity score (EPS), and disease risk score (DRS). Each method was applied to a dataset (2000-2006) recently used to examine the comparative effectiveness of four drugs. The relative effectiveness of risedronate, nasal calcitonin, and raloxifene in preventing non-vertebral fracture, were each compared to alendronate. EPSs were derived both by using multinomial logistic regression (single model EPS) and by three separate logistic regression models (separate model EPS). DRSs were derived and event rates compared using Cox proportional hazard models. DRSs derived among the entire cohort (full cohort DRS) was compared to DRSs derived only among the referent alendronate (unexposed cohort DRS). Less than 8% deviation from the base estimate (conventional multivariable) was observed applying single model EPS, separate model EPS or full cohort DRS. Applying the unexposed cohort DRS when background risk for fracture differed between comparison drug exposure cohorts resulted in -7 to + 13% deviation from our base estimate. With sufficient numbers of exposed and outcomes, either conventional multivariable, EPS or full cohort DRS may be used to adjust for confounding to compare the effects of multiple drug exposures. However, our data also suggest that unexposed cohort DRS may be problematic when background risks differ between referent and exposed groups. Further empirical and simulation studies will help to clarify the generalizability of our findings.

Reading component skills of learners in adult basic education.

PubMed

MacArthur, Charles A; Konold, Timothy R; Glutting, Joseph J; Alamprese, Judith A

2010-01-01

The purposes of this study were to investigate the reliability and construct validity of measures of reading component skills with a sample of adult basic education (ABE) learners, including both native and nonnative English speakers, and to describe the performance of those learners on the measures. Investigation of measures of reading components is needed because available measures were neither developed for nor normed on ABE populations or with nonnative speakers of English. The study included 486 students, 334 born or educated in the United States (native) and 152 not born or educated in the United States (nonnative) but who spoke English well enough to participate in English reading classes. All students had scores on 11 measures covering five constructs: decoding, word recognition, spelling, fluency, and comprehension. Confirmatory factor analysis (CFA) was used to test three models: a two-factor model with print and meaning factors; a three-factor model that separated out a fluency factor; and a five-factor model based on the hypothesized constructs. The five-factor model fit best. In addition, the CFA model fit both native and nonnative populations equally well without modification, showing that the tests measure the same constructs with the same accuracy for both groups. Group comparisons found no difference between the native and nonnative samples on word recognition, but the native sample scored higher on fluency and comprehension and lower on decoding than did the nonnative sample. Students with self-reported learning disabilities scored lower on all reading components. Differences by age and gender were also analyzed.

Vocational interests in the United States: Sex, age, ethnicity, and year effects.

PubMed

Morris, Michael L

2016-10-01

Vocational interests predict educational and career choices, job performance, and career success (Rounds & Su, 2014). Although sex differences in vocational interests have long been observed (Thorndike, 1911), an appropriate overall measure has been lacking from the literature. Using a cross-sectional sample of United States residents aged 14 to 63 who completed the Strong Interest Inventory assessment between 2005 and 2014 (N = 1,283,110), I examined sex, age, ethnicity, and year effects on work related interest levels using both multivariate and univariate effect size estimates of individual dimensions (Holland's Realistic, Investigative, Artistic, Social, Enterprising, and Conventional). Men scored higher on Realistic (d = -1.14), Investigative (d = -.32), Enterprising (d = -.22), and Conventional (d = -.23), while women scored higher on Artistic (d = .19) and Social (d = .38), mostly replicating previous univariate findings. Multivariate, overall sex differences were very large (disattenuated Mahalanobis' D = 1.61; 27% overlap). Interest levels were slightly lower and overall sex differences larger in younger samples. Overall sex differences have narrowed slightly for 18-22 year-olds in more recent samples. Generally very small ethnicity effects included relatively higher Investigative and Enterprising scores for Asians, Indians, and Middle Easterners, lower Realistic scores for Blacks and Native Americans, higher Realistic, Artistic, and Social scores for Pacific Islanders, and lower Conventional scores for Whites. Using Prediger's (1982) model, women were more interested in people (d = 1.01) and ideas (d = .18), while men were more interested in things and data. These results, consistent with previous reviews showing large sex differences and small year effects, suggest that large sex differences in work related interests will continue to be observed for decades. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Model to Determine Risk of Pancreatic Cancer in Patients with New-onset Diabetes.

PubMed

Sharma, Ayush; Kandlakunta, Harika; Singh Nagpal, Sajan Jiv; Ziding, Feng; Hoos, William; Petersen, Gloria M; Chari, Suresh T

2018-05-15

Of subjects with new-onset diabetes (based on glycemia) over the age of 50 years, approximately 1% are diagnosed with pancreatic cancer within 3 years. We aimed to develop and validate a model to determine risk of pancreatic cancer in individuals with new-onset diabetes. We retrospectively collected data from 4 independent, non-overlapping cohorts of patients (n=1561) with new-onset diabetes (based on glycemia; data collected at date of diagnosis and 12 months before) in the Rochester Epidemiology Project, from January 1, 2000 through December 31, 2015 to create our model. The model weighed scores for the 3 factors identified in the discovery cohort to be most strongly associated with pancreatic cancer (64 patients with pancreatic cancer and 192 with type-2 diabetes): change in weight, change in blood glucose, and age at onset of diabetes. We called our model enriching new-onset diabetes for pancreatic cancer (END-PAC). We validated the locked-down model and cutoff score in an independent population-based cohort of 1096 patients with diabetes; of these 9 patients (.82%) had pancreatic within 3 years of meeting the criteria for new-onset diabetes. In the discovery cohort the END-PAC model identified patients who developed pancreatic cancer within 3 years of onset of diabetes with an area under the receiver operating characteristic curve value of 0.87; a score of >3 identified patients who developed pancreatic cancer with 80% sensitivity and specificity. In the validation cohort, a score of >3 identified 7/9 patients with pancreatic cancer (78%), with 85% specificity; the prevalence of pancreatic cancer in subjects with score of >3 (3.6%) was 4.4-fold more than in patients with new-onset diabetes. A high END-PAC score in subjects who did not have pancreatic cancer (false positives) was often due to such factors as recent steroid use or different malignancy. An END-PAC score <0 (in 49% of subjects) meant that patients had an extremely low-risk for pancreatic cancer. An END-PAC score >3 identified 75% of subjects in the discovery cohort >6 months before a diagnosis of pancreatic cancer. Based on change in weight, change in blood glucose, and age at onset of diabetes, we developed and validated a model to determine risk of pancreatic cancer in patients with new-onset diabetes, based on glycemia (the END-PAC model). An independent, prospective study is needed to further validate this model, which could contribute to early detection of pancreatic cancer. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

From neural oscillations to reasoning ability: Simulating the effect of the theta-to-gamma cycle length ratio on individual scores in a figural analogy test.

PubMed

Chuderski, Adam; Andrelczyk, Krzysztof

2015-02-01

Several existing computational models of working memory (WM) have predicted a positive relationship (later confirmed empirically) between WM capacity and the individual ratio of theta to gamma oscillatory band lengths. These models assume that each gamma cycle represents one WM object (e.g., a binding of its features), whereas the theta cycle integrates such objects into the maintained list. As WM capacity strongly predicts reasoning, it might be expected that this ratio also predicts performance in reasoning tasks. However, no computational model has yet explained how the differences in the theta-to-gamma ratio found among adult individuals might contribute to their scores on a reasoning test. Here, we propose a novel model of how WM capacity constraints figural analogical reasoning, aimed at explaining inter-individual differences in reasoning scores in terms of the characteristics of oscillatory patterns in the brain. In the model, the gamma cycle encodes the bindings between objects/features and the roles they play in the relations processed. Asynchrony between consecutive gamma cycles results from lateral inhibition between oscillating bindings. Computer simulations showed that achieving the highest WM capacity required reaching the optimal level of inhibition. When too strong, this inhibition eliminated some bindings from WM, whereas, when inhibition was too weak, the bindings became unstable and fell apart or became improperly grouped. The model aptly replicated several empirical effects and the distribution of individual scores, as well as the patterns of correlations found in the 100-people sample attempting the same reasoning task. Most importantly, the model's reasoning performance strongly depended on its theta-to-gamma ratio in same way as the performance of human participants depended on their WM capacity. The data suggest that proper regulation of oscillations in the theta and gamma bands may be crucial for both high WM capacity and effective complex cognition. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Proposal for a New Predictive Model of Short-Term Mortality After Living Donor Liver Transplantation due to Acute Liver Failure.

PubMed

Chung, Hyun Sik; Lee, Yu Jung; Jo, Yun Sung

2017-02-21

BACKGROUND Acute liver failure (ALF) is known to be a rapidly progressive and fatal disease. Various models which could help to estimate the post-transplant outcome for ALF have been developed; however, none of them have been proved to be the definitive predictive model of accuracy. We suggest a new predictive model, and investigated which model has the highest predictive accuracy for the short-term outcome in patients who underwent living donor liver transplantation (LDLT) due to ALF. MATERIAL AND METHODS Data from a total 88 patients were collected retrospectively. King's College Hospital criteria (KCH), Child-Turcotte-Pugh (CTP) classification, and model for end-stage liver disease (MELD) score were calculated. Univariate analysis was performed, and then multivariate statistical adjustment for preoperative variables of ALF prognosis was performed. A new predictive model was developed, called the MELD conjugated serum phosphorus model (MELD-p). The individual diagnostic accuracy and cut-off value of models in predicting 3-month post-transplant mortality were evaluated using the area under the receiver operating characteristic curve (AUC). The difference in AUC between MELD-p and the other models was analyzed. The diagnostic improvement in MELD-p was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS The MELD-p and MELD scores had high predictive accuracy (AUC >0.9). KCH and serum phosphorus had an acceptable predictive ability (AUC >0.7). The CTP classification failed to show discriminative accuracy in predicting 3-month post-transplant mortality. The difference in AUC between MELD-p and the other models had statistically significant associations with CTP and KCH. The cut-off value of MELD-p was 3.98 for predicting 3-month post-transplant mortality. The NRI was 9.9% and the IDI was 2.9%. CONCLUSIONS MELD-p score can predict 3-month post-transplant mortality better than other scoring systems after LDLT due to ALF. The recommended cut-off value of MELD-p is 3.98.

Family Characteristics and Intellectual Growth: An Examination by Race.

ERIC Educational Resources Information Center

Barnes, Jonathan

1979-01-01

The confluence model for explaining the influence of birth order on intelligence was applied to a sample of 56 Black and 52 White students. The confluence model and parental occupation were deemed insufficient in accounting for racial differences in intelligence scores. (Author/JKS)

Longitudinal associations between BMI, waist circumference, and cardiometabolic risk in US youth: monitoring implications.

PubMed

Jago, R; Mendoza, J A; Chen, T; Baranowski, T

2013-03-01

This study examined whether change in body mass index (BMI) or waist circumference (WC) is associated with change in cardiometabolic risk factors and differences between cardiovascular disease specific and diabetes specific risk factors among adolescents. We also sought to examine any differences by gender or baseline body mass status. The article is a longitudinal analysis of pre- and post-data collected in the HEALTHY trial. Participants were 4,603 ethnically diverse adolescents who provided complete data at 6th and 8th grade assessments. The main outcome measures were percent change in the following cardiometabolic risk factors: fasting triglycerides, systolic and diastolic blood pressure, high density lipoprotein cholesterol, and glucose as well as a clustered metabolic risk score. Main exposures were change in BMI or WC z-score. Models were run stratified by gender; secondary models were additionally stratified by baseline BMI group (normal, overweight, or obese). Analysis showed that when cardiometabolic risk factors were treated as continuous variables, there was strong evidence (P < 0.001) that change in BMI z-score was associated with change in the majority of the cardiovascular risk factors, except fasting glucose and the combined risk factor score for both boys and girls. There was some evidence that change in WC z-score was associated with some cardiovascular risk factors, but change in WC z-score was consistently associated with changes in fasting glucose. In conclusion, routine monitoring of BMI should be continued by health professionals, but additional information on disease risk may be provided by assessing WC. Copyright © 2013 The Obesity Society.

Assessing the impact of electronic health records as an enabler of hospital quality and patient satisfaction.

PubMed

Jarvis, Benjamin; Johnson, Tricia; Butler, Peter; O'Shaughnessy, Kathryn; Fullam, Francis; Tran, Lac; Gupta, Richa

2013-10-01

To assess the impact of using an advanced electronic health record (EHR) on hospital quality and patient satisfaction. This retrospective, cross-sectional analysis was conducted in 2012 to evaluate the association between advanced EHR use (Healthcare Information Management Systems Society [HIMSS] Stage 6 or 7 as of December 2012) and estimated process and experience of care scores for hospitals under the Medicare Hospital Value-Based Purchasing Program, using data from the American Hospital Association for 2008 to 2010. Generalized linear regression models were fit to test the association between advanced EHR use with process of care and experience of care, controlling for hospital characteristics. In a second analysis, the models included variables to account for HIMSS stage of advanced EHR use. The study included 2,988 hospitals, with 248 (8.3%) classified as advanced EHR users (HIMSS Stage 6 or 7). After controlling for hospital characteristics, advanced EHR use was associated with a 4.2-point-higher process of care score (P < .001). Hospitals with Stage 7 EHRs had 11.7 points higher process of care scores, but Stage 6 users had scores that were not substantially different from those of nonadvanced users. There was no significant difference in estimated experience of care scores by level of advanced EHR use. This study evaluated the effectiveness of the U.S. federal government's investment in hospital information technology infrastructure. Results suggest that the most advanced EHRs have the greatest payoff in improving clinical process of care scores, without detrimentally impacting the patient experience.

At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study.

PubMed

Hamaker, E L; Asparouhov, T; Brose, A; Schmiedek, F; Muthén, B

2018-04-06

With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent-but mostly unresolved-issues in the area of dynamic multilevel modeling.

Validity and Reliability of Baseline Testing in a Standardized Environment.

PubMed

Higgins, Kathryn L; Caze, Todd; Maerlender, Arthur

2017-08-11

The Immediate Postconcussion Assessment and Cognitive Testing (ImPACT) is a computerized neuropsychological test battery commonly used to determine cognitive recovery from concussion based on comparing post-injury scores to baseline scores. This model is based on the premise that ImPACT baseline test scores are a valid and reliable measure of optimal cognitive function at baseline. Growing evidence suggests that this premise may not be accurate and a large contributor to invalid and unreliable baseline test scores may be the protocol and environment in which baseline tests are administered. This study examined the effects of a standardized environment and administration protocol on the reliability and performance validity of athletes' baseline test scores on ImPACT by comparing scores obtained in two different group-testing settings. Three hundred-sixty one Division 1 cohort-matched collegiate athletes' baseline data were assessed using a variety of indicators of potential performance invalidity; internal reliability was also examined. Thirty-one to thirty-nine percent of the baseline cases had at least one indicator of low performance validity, but there were no significant differences in validity indicators based on environment in which the testing was conducted. Internal consistency reliability scores were in the acceptable to good range, with no significant differences between administration conditions. These results suggest that athletes may be reliably performing at levels lower than their best effort would produce. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Assessing Animal Welfare Impacts in the Management of European Rabbits (Oryctolagus cuniculus), European Moles (Talpa europaea) and Carrion Crows (Corvus corone)

PubMed Central

Baker, Sandra E.; Sharp, Trudy M.; Macdonald, David W.

2016-01-01

Human-wildlife conflict is a global issue. Attempts to manage this conflict impact upon wild animal welfare, an issue receiving little attention until relatively recently. Where human activities harm animal welfare these effects should be minimised where possible. However, little is known about the welfare impacts of different wildlife management interventions, and opinions on impacts vary widely. Welfare impacts therefore need to be assessed objectively. Our objectives were to: 1) establish whether an existing welfare assessment model could differentiate and rank the impacts of different wildlife management interventions (for decision-making purposes); 2) identify and evaluate any additional benefits of making formal welfare assessments; and 3) illustrate issues raised by application of the model. We applied the welfare assessment model to interventions commonly used with rabbits (Oryctolagus cuniculus), moles (Talpa europaea) and crows (Corvus corone) in the UK. The model ranked interventions for rabbits (least impact first: fencing, head shot, chest shot) and crows (shooting, scaring, live trapping with cervical dislocation). For moles, managing molehills and tunnels scored least impact. Both spring trapping, and live trapping followed by translocation, scored greater impacts, but these could not be compared directly as they scored on different axes of the model. Some rankings appeared counter-intuitive, highlighting the need for objective formal welfare assessments. As well as ranking the humaneness of interventions, the model highlighted future research needs and how Standard Operating Procedures might be improved. The model is a milestone in assessing wildlife management welfare impacts, but our research revealed some limitations of the model and we discuss likely challenges in resolving these. In future, the model might be developed to improve its utility, e.g. by refining the time-scales. It might also be used to reach consensus among stakeholders about relative welfare impacts or to identify ways of improving wildlife management practice in the field. PMID:26726808

Assessing Animal Welfare Impacts in the Management of European Rabbits (Oryctolagus cuniculus), European Moles (Talpa europaea) and Carrion Crows (Corvus corone).

PubMed

Baker, Sandra E; Sharp, Trudy M; Macdonald, David W

2016-01-01

Human-wildlife conflict is a global issue. Attempts to manage this conflict impact upon wild animal welfare, an issue receiving little attention until relatively recently. Where human activities harm animal welfare these effects should be minimised where possible. However, little is known about the welfare impacts of different wildlife management interventions, and opinions on impacts vary widely. Welfare impacts therefore need to be assessed objectively. Our objectives were to: 1) establish whether an existing welfare assessment model could differentiate and rank the impacts of different wildlife management interventions (for decision-making purposes); 2) identify and evaluate any additional benefits of making formal welfare assessments; and 3) illustrate issues raised by application of the model. We applied the welfare assessment model to interventions commonly used with rabbits (Oryctolagus cuniculus), moles (Talpa europaea) and crows (Corvus corone) in the UK. The model ranked interventions for rabbits (least impact first: fencing, head shot, chest shot) and crows (shooting, scaring, live trapping with cervical dislocation). For moles, managing molehills and tunnels scored least impact. Both spring trapping, and live trapping followed by translocation, scored greater impacts, but these could not be compared directly as they scored on different axes of the model. Some rankings appeared counter-intuitive, highlighting the need for objective formal welfare assessments. As well as ranking the humaneness of interventions, the model highlighted future research needs and how Standard Operating Procedures might be improved. The model is a milestone in assessing wildlife management welfare impacts, but our research revealed some limitations of the model and we discuss likely challenges in resolving these. In future, the model might be developed to improve its utility, e.g. by refining the time-scales. It might also be used to reach consensus among stakeholders about relative welfare impacts or to identify ways of improving wildlife management practice in the field.

Validation of the Lupus Nephritis Clinical Indices in Childhood-Onset Systemic Lupus Erythematosus.

PubMed

Mina, Rina; Abulaban, Khalid; Klein-Gitelman, Marisa S; Eberhard, Barbara A; Ardoin, Stacy P; Singer, Nora; Onel, Karen; Tucker, Lori; O'neil, Kathleen; Wright, Tracey; Brooks, Elizabeth; Rouster-Stevens, Kelly; Jung, Lawrence; Imundo, Lisa; Rovin, Brad; Witte, David; Ying, Jun; Brunner, Hermine I

2016-02-01

To validate clinical indices of lupus nephritis activity and damage when used in children against the criterion standard of kidney biopsy findings. In 83 children requiring kidney biopsy, the Systemic Lupus Erythematosus Disease Activity Index renal domain (SLEDAI-R), British Isles Lupus Assessment Group index renal domain (BILAG-R), Systemic Lupus International Collaborating Clinics (SLICC) renal activity score (SLICC-RAS), and SLICC Damage Index renal domain (SDI-R) were measured. Fixed effects and logistic models were calculated to predict International Society of Nephrology/Renal Pathology Society (ISN/RPS) class; low-to-moderate versus high lupus nephritis activity (National Institutes of Health [NIH] activity index [AI]) score: ≤10 versus >10; tubulointerstitial activity index (TIAI) score: ≤5 versus >5; or the absence versus presence of lupus nephritis chronicity (NIH chronicity index) score: 0 versus ≥1. There were 10, 50, and 23 patients with ISN/RPS class I/II, III/IV, and V, respectively. Scores of the clinical indices did not differentiate among patients by ISN/RPS class. The SLEDAI-R and SLICC-RAS but not the BILAG-R differed with lupus nephritis activity status defined by NIH-AI scores, while only the SLEDAI-R scores differed between lupus nephritis activity status based on TIAI scores. The sensitivity and specificity of the SDI-R to capture lupus nephritis chronicity was 23.5% and 91.7%, respectively. Despite being designed to measure lupus nephritis activity, SLICC-RAS and SLEDAI-R scores significantly differed with lupus nephritis chronicity status. Current clinical indices of lupus nephritis fail to discriminate ISN/RPS class in children. Despite its shortcomings, the SLEDAI-R appears best for measuring lupus nephritis activity in a clinical setting. The SDI-R is a poor correlate of lupus nephritis chronicity. © 2016, American College of Rheumatology.

[Efficacy and safety of tertiary hospital guided and community-driven family self-help cardiac rehabilitation model].

PubMed

Ding, R J; Gao, L M; Chu, L; Xie, W L; Wang, X R; Tang, Q; Wang, H L; Hu, D Y

2017-03-24

Objective: To explore the efficacy and safety of tertiary hospital guided and community-driven family self-help cardiac rehabilitation model. Methods: This study was a prospective randomized controlled study, 80 patients from Beijing Electrical Power Hospital and Beijing Jingmei Group General Hospital with acute coronary syndrome were included from June to December 2015 and divided into 2 groups. Patients in rehabilitation group ( n =52) received tertiary hospital(Peiking University Peoples' Hospital) guided and community-driven family self-help cardiac rehabilitation for 3 months, and patients in control group ( n =28) received routine secondary treatment for 3 months. Following parameters including 6 minutes walk distance, score of life quality (evaluated by Short Form-12), score of anxiety (evaluated by Generalized Anxiety Disorder-7), score of depression (evaluated by Perceived Health Questionnaire-9), self-management competency (evaluated by questionnaire) were collected at baseline and after treatment for 3 months. Results: Compared with control group, 6 minutes walk distance was longer in rehabilitation group((60.2±6.8) meters vs. (24.9±10.5)meters, P <0.01). The difference values between after and before intervention of life quality scores((0.14±3.90)scores vs.(-7.44±5.85)scores, P >0.05), anxiety scores((-0.16±2.12 ) scores vs.(0.70±1.13)scores, P >0.05) and depression scores((-1.17±2.79) scores vs.(0.60±0.36)scores, P >0.05) were similar between the 2 groups. The amplification of patients with regular exercise (50.26% vs. 0, P <0.05), limit sugary foods usually and always (53.22% vs. 3.98%, P <0.05), eat 200-400 g fruits usually and always (78.61 % vs. 0, P <0.05), eat 300-500 g vegetables usually and always (9.74% vs. 0, P <0.05), and answering very confident to questions such as let the physicians know about your diseases (40.17% vs. 5.00%, P <0.05), know how to take medicines (44.52% vs. 5.00%, P <0.05), know how much exercise was right for yourself (26.43% vs.0, P <0.05) were significantly higher in rehabilitation group than in control group. There were no cardiac rehabilitation training related cardiovascular events. Conclusion: Tertiary hospital guided and community-driven family self-help cardiac rehabilitation model is an effective and safe management model of cardiovascular disease in chronic phase, and it is necessary to further expand the study population to verify the efficacy of this model.

Gender Differences in Cognition among Older Adults in China.

PubMed

Lei, Xiaoyan; Hu, Yuqing; McArdle, John J; Smith, James P; Zhao, Yaohui

2012-01-01

In this paper, we model gender differences in cognitive ability in China using a new sample of middle-aged and older Chinese respondents. Modeled after the American Health and Retirement Study (HRS), the CHARLS Pilot survey respondents are 45 years and older in two quite distinct provinces-Zhejiang, a high-growth industrialized province on the East Coast, and Gansu, a largely agricultural and poor province in the West-in a sense new and old China. Our cognition measures proxy for two different dimensions of adult cognition-episodic memory and intact mental status. On both measures, Chinese women score much lower than do Chinese men, a gender difference that grows among older Chinese cohorts. We relate both these cognition scores to schooling, urban residence, family and community levels of economic resources, and height. We find that cognition is more closely related to mean community resources than to family resources, especially for women, suggesting that in traditional poor Chinese communities there are strong economic incentives to favor boys at the expense of girls. We also find that these gender differences in cognitive ability have been steadily decreasing across birth cohorts as the economy of China grew rapidly. Among cohorts of young adults in China, there is no longer any gender disparity in cognitive ability. This parallels the situation in the United States where cognition scores of adult women actually exceed those of adult men.

Observational learning of fly casting using traditional and virtual modeling with and without authority figure.

PubMed

Kernodle, Michael W; McKethan, Robert N; Rabinowitz, Erik

2008-10-01

Traditional and virtual modeling were compared during learning of a multiple degree-of-freedom skill (fly casting) to assess the effect of the presence or absence of an authority figure on observational learning via virtual modeling. Participants were randomly assigned to one of four groups: Virtual Modeling with an authority figure present (VM-A) (n = 16), Virtual Modeling without an authority figure (VM-NA) (n = 16), Traditional Instruction (n = 17), and Control (n = 19). Results showed significant between-group differences on Form and Skill Acquisition scores. Except for one instance, all three learning procedures resulted in significant learning of fly casting. Virtual modeling with or without an authority figure present was as effective as traditional instruction; however, learning without an authority figure was less effective with regard to Accuracy scores.

Roy's Adaptation Model-Guided Education and Promoting the Adaptation of Veterans With Lower Extremities Amputation.

PubMed

Azarmi, Somayeh; Farsi, Zahra

2015-10-01

Any defect in extremities of the body can affect different life aspects. The purpose of this study was to investigate the effect of Roy's adaptation model-guided education on promoting the adaptation of veterans with lower extremities amputation. In a randomized clinical trial, 60 veterans with lower extremities amputation referring to Kowsar Orthotics and Prosthetics Center of veterans clinic in Tehran, Iran, were recruited with convenience method and were randomly assigned to intervention and control groups during 2013 - 2014. For data collection, Roy's adaptation model questionnaire was used. After completing the questionnaires in both groups, maladaptive behaviors were determined in the intervention group and an education program based on Roy's adaptation model was implemented. After two months, both groups completed the questionnaires again. Data was analyzed with SPSS software. Independent t-test showed statistically significant differences between the two groups in the post-test stage in terms of the total score of adaptation (P = 0.001) as well as physiologic (P = 0.0001) and role function modes (P = 0.004). The total score of adaptation (139.43 ± 5.45 to 127.54 ± 14.55, P = 0.006) as well as the scores of physiologic (60.26 ± 5.45 to 53.73 ± 7.79, P = 0.001) and role function (20.30 ± 2.42 to 18.13 ± 3.18, P = 0.01) modes in the intervention group significantly increased, whereas the scores of self-concept (42.10 ± 4.71 to 39.40 ± 5.67, P = 0.21) and interdependence (16.76 ± 2.22 to 16.30 ± 2.57, P = 0.44) modes in the two stages did not have a significant difference. Findings of this research indicated that the Roy's adaptation model-guided education promoted the adaptation level of physiologic and role function modes in veterans with lower extremities amputation. However, this intervention could not promote adaptation in self-concept and interdependence modes. More intervention is advised based on Roy's adaptation model for improving the adaptation of veterans with lower extremities.

International epidemiology of child and adolescent psychopathology ii: integration and applications of dimensional findings from 44 societies.

PubMed

Rescorla, Leslie; Ivanova, Masha Y; Achenbach, Thomas M; Begovac, Ivan; Chahed, Myriam; Drugli, May Britt; Emerich, Deisy Ribas; Fung, Daniel S S; Haider, Mariam; Hansson, Kjell; Hewitt, Nohelia; Jaimes, Stefanny; Larsson, Bo; Maggiolini, Alfio; Marković, Jasminka; Mitrović, Dragan; Moreira, Paulo; Oliveira, João Tiago; Olsson, Martin; Ooi, Yoon Phaik; Petot, Djaouida; Pisa, Cecilia; Pomalima, Rolando; da Rocha, Marina Monzani; Rudan, Vlasta; Sekulić, Slobodan; Shahini, Mimoza; de Mattos Silvares, Edwiges Ferreira; Szirovicza, Lajos; Valverde, José; Vera, Luis Anderssen; Villa, Maria Clara; Viola, Laura; Woo, Bernardine S C; Zhang, Eugene Yuqing

2012-12-01

To build on Achenbach, Rescorla, and Ivanova (2012) by (a) reporting new international findings for parent, teacher, and self-ratings on the Child Behavior Checklist, Youth Self-Report, and Teacher's Report Form; (b) testing the fit of syndrome models to new data from 17 societies, including previously underrepresented regions; (c) testing effects of society, gender, and age in 44 societies by integrating new and previous data; (d) testing cross-society correlations between mean item ratings; (e) describing the construction of multisociety norms; (f) illustrating clinical applications. Confirmatory factor analyses (CFAs) of parent, teacher, and self-ratings, performed separately for each society; tests of societal, gender, and age effects on dimensional syndrome scales, DSM-oriented scales, Internalizing, Externalizing, and Total Problems scales; tests of agreement between low, medium, and high ratings of problem items across societies. CFAs supported the tested syndrome models in all societies according to the primary fit index (Root Mean Square Error of Approximation [RMSEA]), but less consistently according to other indices; effect sizes were small-to-medium for societal differences in scale scores, but very small for gender, age, and interactions with society; items received similarly low, medium, or high ratings in different societies; problem scores from 44 societies fit three sets of multisociety norms. Statistically derived syndrome models fit parent, teacher, and self-ratings when tested individually in all 44 societies according to RMSEAs (but less consistently according to other indices). Small to medium differences in scale scores among societies supported the use of low-, medium-, and high-scoring norms in clinical assessment of individual children. Copyright © 2012 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Early sex differences are not autism-specific: A Baby Siblings Research Consortium (BSRC) study.

PubMed

Messinger, Daniel S; Young, Gregory S; Webb, Sara Jane; Ozonoff, Sally; Bryson, Susan E; Carter, Alice; Carver, Leslie; Charman, Tony; Chawarska, Katarzyna; Curtin, Suzanne; Dobkins, Karen; Hertz-Picciotto, Irva; Hutman, Ted; Iverson, Jana M; Landa, Rebecca; Nelson, Charles A; Stone, Wendy L; Tager-Flusberg, Helen; Zwaigenbaum, Lonnie

2015-01-01

The increased male prevalence of autism spectrum disorder (ASD) may be mirrored by the early emergence of sex differences in ASD symptoms and cognitive functioning. The female protective effect hypothesis posits that ASD recurrence and symptoms will be higher among relatives of female probands. This study examined sex differences and sex of proband differences in ASD outcome and in the development of ASD symptoms and cognitive functioning among the high-risk younger siblings of ASD probands and low-risk children. Prior to 18 months of age, 1824 infants (1241 high-risk siblings, 583 low-risk) from 15 sites were recruited. Hierarchical generalized linear model (HGLM) analyses of younger sibling and proband sex differences in ASD recurrence among high-risk siblings were followed by HGLM analyses of sex differences and group differences (high-risk ASD, high-risk non-ASD, and low-risk) on the Mullen Scales of Early Learning (MSEL) subscales (Expressive and Receptive Language, Fine Motor, and Visual Reception) at 18, 24, and 36 months and Autism Diagnostic Observation Schedule (ADOS) domain scores (social affect (SA) and restricted and repetitive behaviors (RRB)) at 24 and 36 months. Of 1241 high-risk siblings, 252 had ASD outcomes. Male recurrence was 26.7 % and female recurrence 10.3 %, with a 3.18 odds ratio. The HR-ASD group had lower MSEL subscale scores and higher RRB and SA scores than the HR non-ASD group, which had lower MSEL subscale scores and higher RRB scores than the LR group. Regardless of group, males obtained lower MSEL subscale scores, and higher ADOS RRB scores, than females. There were, however, no significant interactions between sex and group on either the MSEL or ADOS. Proband sex did not affect ASD outcome, MSEL subscale, or ADOS domain scores. A 3.2:1 male:female odds ratio emerged among a large sample of prospectively followed high-risk siblings. Sex differences in cognitive performance and repetitive behaviors were apparent not only in high-risk children with ASD, but also in high-risk children without ASD and in low-risk children. Sex differences in young children with ASD do not appear to be ASD-specific but instead reflect typically occurring sex differences seen in children without ASD. Results did not support a female protective effect hypothesis.

Performance of Disease-Specific Scoring Models in Intensive Care Patients with Severe Liver Diseases.

PubMed

El-Ghannam, Maged T; Hassanien, Moataz H; El-Talkawy, Mohamed D; Saleem, Abdel Aziz A; Sabry, Amal I; Abu Taleb, Hoda M

2017-06-01

Egypt has the highest prevalence of Hepatitis C Virus (HCV) in the world, estimated nationally at 14.7%. HCV treatment consumes 20% ($80 million) of Egypt's annual health budget. Outcomes of cirrhotic patients admitted to the ICU may, in fact, largely depend on differences in the state of the disease, criteria and indications for admission, resource utilization, and intensity of treatment. The aim of the present study was to evaluate the efficacy of liver specific scoring models in predicting the outcome of critically ill cirrhotic patients in the ICU as it may help in prioritization of high risk patients and preservation of ICU resources. Over one year, a total of 777 patients with End Stage Liver Disease (ESLD) due to HCV infection were included in this retrospective non-randomized human study. All statistical analyses were performed by the statistical software SPSS version 22.0 (SPSS, Chicago, IL, USA). Child Turcotte Pugh (CTP) score, MELD score, MELD-Na, MESO, iMELD, Refit MELD and Refit MELD-Na were calculated on ICU admission. ICU admission was mainly due to Gastrointestinal (GI) bleeding and Hepatic Encephalopathy (HE). Overall mortality was 27%. Age and sex showed no statistical difference between survivors and non survivors. Significantly higher mean values were observed for all models among individuals who died compared to survivors. MELD-Na was the most specific compared to the other scores. MELD-Na was highly predictive of mortality at an optimized cut-off value of 20.4 (AURC=0.789±0.03-CI 95%=0.711-0.865) while original MELD was highly predictive of mortality at an optimized cut-off value of 17.4 (AURC=0.678±0.01-CI 95%=0.613-0.682) denoting the importance of adding serum sodium to the original MELD. INR, serum creatinine, bilirubin, white blood cells count and hyponatremia were significantly higher in non survivors compared to survivors, while hypoalbuminemia showed no statistical difference. The advent of Hepatorenal Syndrome (HRS) and Spontaneous Bacterial Peritonitis (SBP) carried worse prognosis. Hyponatremia and number of transfused blood bags were additional independent predictors of mortality. In cirrhosis of liver, due to HCV infection, patients who died during their ICU stay displayed significantly higher values on all prognostic scores at admission. The addition of sodium to MELD score greatly improves the predictive accuracy of mortality. MELD-Na showed the highest predictive value of all scores.

Self-reported pain intensity with the numeric reporting scale in adult dengue.

PubMed

Wong, Joshua G X; Gan, Victor C; Ng, Ee-Ling; Leo, Yee-Sin; Chan, Siew-Pang; Choo, Robin; Lye, David C

2014-01-01

Pain is a prominent feature of acute dengue as well as a clinical criterion in World Health Organization guidelines in diagnosing dengue. We conducted a prospective cohort study to compare levels of pain during acute dengue between different ethnicities and dengue severity. Demographic, clinical and laboratory data were collected. Data on self-reported pain was collected using the 11-point Numerical Rating Scale. Generalized structural equation models were built to predict progression to severe disease. A total of 499 laboratory confirmed dengue patients were recruited in the Prospective Adult Dengue Study at Tan Tock Seng Hospital, Singapore. We found no statistically significant differences between pain score with age, gender, ethnicity or the presence of co-morbidity. Pain score was not predictive of dengue severity but highly correlated to patients' day of illness. Prevalence of abdominal pain in our cohort was 19%. There was no difference in abdominal pain score between grades of dengue severity. Dengue is a painful disease. Patients suffer more pain at the earlier phase of illness. However, pain score cannot be used to predict a patient's progression to severe disease.

Intensity of antianginal therapy in patients referred for coronary angiography: a comparison of fee-for-service and health maintenance organization therapeutic strategies.

PubMed

Samuels, B A; Diamond, G A; Mahrer, P R; Denton, T A

2000-03-01

No formal criteria have been developed to guide medical therapy for angina prior to revascularization, and no comparisons have been made between health maintenance organization (HMO) and fee-for-service (FFS) hospitals with respect to angina treatment. Using a literature-based measure of medical intensity, we tested the hypothesis that there is no difference in anginal medical therapeutic intensity between HMO and FFS systems. For each antianginal drug, we developed a model from which an intensity score between 0 and 100 could be calculated. Average and maximal daily doses of drug were fit to a sigmoid curve such that they represented scores of 50 and 99, respectively. Overall intensity scores were obtained by weighted and unweighted averaging of three scores from nitrates, calcium-channel blockers, and beta blockers. This model was applied to 199 patients undergoing angiography at an FFS and an HMO hospital. HMO patients were taking more classes of antianginal drug (1.9 vs. 1.0, p < 0.001). Overall unweighted (17.7 vs. 11.7, p = 0.02) and weighted (27.3 vs. 16.9, p = 0.003) intensity scores for both HMO and FFS patients were low. HMO intensity scores for the use of beta blockers were greater than FFS scores (19.2 vs. 9.6, p = 0.002). The intensity scores for the use of nitrates and calcium blockers were similar. Models for the measurement of anginal medical therapy intensity can provide important information regarding medical therapy prior to revascularization. The overall intensity of medical therapy was low in both health care systems. These findings have important implications for patient management, guideline development, and national healthcare policy.

The Model for End-stage Liver Disease score is potentially a useful predictor of hyperkalemia occurrence among hospitalized angiotensin receptor blocker users.

PubMed

Sheen, S S; Park, R W; Yoon, D; Shin, G-T; Kim, H; Park, I-W

2015-02-01

Angiotensin receptor blockers (ARBs) are medications commonly used for treating conditions such as hypertension. However, ARBs are frequently associated with hyperkalemia, a potentially critical adverse event, in high-risk patients. Although both the liver and the kidney are major elimination routes of ARBs, the relationship between hepatorenal function and ARB-related hyperkalemia has not yet been investigated. The purpose of this study was to evaluate the risk of hyperkalemia, in terms of various hepatorenal functions, for hospitalized patients newly initiated on ARB treatment. We evaluated ARB-related hyperkalemia in a cohort of 5530 hospitalized patients, who had not previously used ARBs, between 12 April 2004 and 31 May 2012. Hepatorenal function was assessed by the Model for End-stage Liver Disease (MELD) score. Hyperkalemia risk was assessed by hepatorenal function, risks were categorized into the four MELD scoring groups, and the groups were compared with one another. The MELD score was significantly different between the hyperkalemic and non-hyperkalemic groups (independent t-test, P < 0.001). The MELD score 10-14, 15-19 and ≥ 20 groups showed higher risks of hyperkalemia than the lowest MELD score group {log-rank test, P < 0.001; multiple Cox proportional hazard model, hazard ratios 1.478 (P = 0.003), 2.285 (P < 0.001) and 3.024 (P < 0.001), respectively}. The MELD score showed a stronger predictive performance for hyperkalemia than either serum creatinine or estimated glomerular filtration rate alone. Furthermore, the MELD score showed good predictive performance for ARB-related hyperkalemia among hospitalized patients. The clinical implications and reasons for these findings merit future investigation. © 2014 John Wiley & Sons Ltd.

When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values

PubMed Central

Baldi, Pierre

2010-01-01

As repositories of chemical molecules continue to expand and become more open, it becomes increasingly important to develop tools to search them efficiently and assess the statistical significance of chemical similarity scores. Here we develop a general framework for understanding, modeling, predicting, and approximating the distribution of chemical similarity scores and its extreme values in large databases. The framework can be applied to different chemical representations and similarity measures but is demonstrated here using the most common binary fingerprints with the Tanimoto similarity measure. After introducing several probabilistic models of fingerprints, including the Conditional Gaussian Uniform model, we show that the distribution of Tanimoto scores can be approximated by the distribution of the ratio of two correlated Normal random variables associated with the corresponding unions and intersections. This remains true also when the distribution of similarity scores is conditioned on the size of the query molecules in order to derive more fine-grained results and improve chemical retrieval. The corresponding extreme value distributions for the maximum scores are approximated by Weibull distributions. From these various distributions and their analytical forms, Z-scores, E-values, and p-values are derived to assess the significance of similarity scores. In addition, the framework allows one to predict also the value of standard chemical retrieval metrics, such as Sensitivity and Specificity at fixed thresholds, or ROC (Receiver Operating Characteristic) curves at multiple thresholds, and to detect outliers in the form of atypical molecules. Numerous and diverse experiments carried in part with large sets of molecules from the ChemDB show remarkable agreement between theory and empirical results. PMID:20540577

Racial differences in knee osteoarthritis pain: potential contribution of occupational and household tasks.

PubMed

Allen, Kelli D; Chen, Jiu-Chiuan; Callahan, Leigh F; Golightly, Yvonne M; Helmick, Charles G; Renner, Jordan B; Schwartz, Todd A; Jordan, Joanne M

2012-02-01

We examined whether occupational and household tasks contributed to differences in pain between African Americans and whites with radiographic knee osteoarthritis (OA). Participants from the Johnston County Osteoarthritis Project self-reported the frequency (often/always vs never/seldom/sometimes) of performing 9 occupational tasks involving lower extremity joint loading at their longest job (N = 868) and current job (N = 273), as well as 8 household tasks ever performed (N = 811) and currently being performed (N = 767). The associations of the numbers of occupational or household tasks with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale were first examined in simple linear regression models. If significantly associated with greater pain, each of these was included in adjusted linear regression models to examine whether the association of race with pain remained statistically significant. African Americans reported significantly greater WOMAC pain scores than whites. Exposures to more occupational tasks at the longest job and the current job were associated with greater WOMAC pain scores (p < 0.01). The association of race with greater pain scores remained statistically significant when controlling for occupational tasks at the longest job, but was reduced by 26% and no longer significant when controlling for the number of current occupational tasks. Exposures to an increasing number of household tasks were associated with lower pain scores and were not further analyzed. Current performance of physically demanding occupational tasks contributed to racial differences in pain severity among individuals with knee OA. Better workplace policies to accommodate OA-related limitations may help to reduce racial differences in pain.

Fold assessment for comparative protein structure modeling.

PubMed

Melo, Francisco; Sali, Andrej

2007-11-01

Accurate and automated assessment of both geometrical errors and incompleteness of comparative protein structure models is necessary for an adequate use of the models. Here, we describe a composite score for discriminating between models with the correct and incorrect fold. To find an accurate composite score, we designed and applied a genetic algorithm method that searched for a most informative subset of 21 input model features as well as their optimized nonlinear transformation into the composite score. The 21 input features included various statistical potential scores, stereochemistry quality descriptors, sequence alignment scores, geometrical descriptors, and measures of protein packing. The optimized composite score was found to depend on (1) a statistical potential z-score for residue accessibilities and distances, (2) model compactness, and (3) percentage sequence identity of the alignment used to build the model. The accuracy of the composite score was compared with the accuracy of assessment by single and combined features as well as by other commonly used assessment methods. The testing set was representative of models produced by automated comparative modeling on a genomic scale. The composite score performed better than any other tested score in terms of the maximum correct classification rate (i.e., 3.3% false positives and 2.5% false negatives) as well as the sensitivity and specificity across the whole range of thresholds. The composite score was implemented in our program MODELLER-8 and was used to assess models in the MODBASE database that contains comparative models for domains in approximately 1.3 million protein sequences.

Symptom dimensions and subgroups in childhood-onset schizophrenia.

PubMed

Craddock, Kirsten E S; Zhou, Xueping; Liu, Siyuan; Gochman, Peter; Dickinson, Dwight; Rapoport, Judith L

2017-11-13

This study investigated symptom dimensions and subgroups in the National Institute of Mental Health (NIMH) childhood-onset schizophrenia (COS) cohort and their similarities to adult-onset schizophrenia (AOS) literature. Scores from the Scales for the Assessment of Positive and Negative Symptoms (SAPS & SANS) from 125 COS patients were assessed for fit with previously established symptom dimensions from AOS literature using confirmatory factor analysis (CFA). K-means cluster analysis of each individual's scores on the best fitting set of dimensions was used to form patient clusters, which were then compared using demographic and clinical data. CFA showed the SAPS & SANS data was well suited to a 2-dimension solution, including positive and negative dimensions, out of five well established models. Cluster analysis identified three patient groups characterized by different dimension scores: (1) low scores on both dimensions, (2) high negative, low positive scores, and (3) high scores on both dimensions. These groups had different Full scale IQ, Children's Global Assessment Scale (CGAS) scores, ages of onset, and prevalence of some co-morbid behavior disorders (all p<3.57E-03). Our analysis found distinct symptom-based subgroups within the NIMH COS cohort using an established AOS symptom structure. These findings confirm the heterogeneity of COS and were generally consistent with AOS literature. Published by Elsevier B.V.

The role of social relationships among elderly community-dwelling and nursing-home residents: findings from a quality of life study.

PubMed

Scocco, Paolo; Nassuato, Mario

2017-07-01

In Western countries, older adults' needs are often managed through institutionalization. Based on the assumption that quality of life, particularly social relationships, may be perceived differently according to residential setting, the aims of this study were to compare World Health Organization Quality of Life brief version (WHOQOL-BREF) scores of elderly community-dwelling residents and nursing home residents. A sample of 207 older adults (135 community-dwelling residents, 72 nursing home residents) was evaluated with Mini-Mental State Examination (MMSE), WHOQOL-BREF, and Geriatric Depression Scale (GDS). Nursing home residents achieved lower WHOQOL-BREF scores on the physical health scale only (P = 0.002). In a linear regression model, physical score correlated negatively with GDS score (P = 0.0001) and Mini-Mental State Examination score (P = 0.04), but positively with male gender (P = 0.02) and community-dwelling residence (P = 0.001); psychological score correlated negatively with GDS score (P = 0.0001) and being married (P = 0.03), but positively with male gender (P = 0.009) and being unmarried (P = 0.03). The social relationships score correlated negatively with the GDS score (P = 0.0001) and male gender (P = 0.02), but positively with high education level (P = 0.04). The environment score negatively correlated with GDS score (P = 0.0001). In a logistic regression model, living in a nursing home correlated with female gender (P = 0.001), age (P = 0.0001), a lower physical score (P = 0.0001), and a higher social relationships score (P = 0.02). Depressive symptoms correlated with low scores in all WHOQOL-BREF domains. The variables that correlated with living conditions in a nursing home were older age, male gender, lower physical domain scores, and higher social relationship scores. Opportunities for socialization in nursing homes may thus improve perception of quality of life in this domain. © 2017 Japanese Psychogeriatric Society.

Exploring the gender gap in the conceptual survey of electricity and magnetism

NASA Astrophysics Data System (ADS)

Henderson, Rachel; Stewart, Gay; Stewart, John; Michaluk, Lynnette; Traxler, Adrienne

2017-12-01

The "gender gap" on various physics conceptual evaluations has been extensively studied. Men's average pretest scores on the Force Concept Inventory and Force and Motion Conceptual Evaluation are 13% higher than women's, and post-test scores are on average 12% higher than women's. This study analyzed the gender differences within the Conceptual Survey of Electricity and Magnetism (CSEM) in which the gender gap has been less well studied and is less consistent. In the current study, data collected from 1407 students (77% men, 23% women) in a calculus-based physics course over ten semesters showed that male students outperformed female students on the CSEM pretest (5%) and post-test (6%). Separate analyses were conducted for qualitative and quantitative problems on lab quizzes and course exams and showed that male students outperformed female students by 3% on qualitative quiz and exam problems. Male and female students performed equally on the quantitative course exam problems. The gender gaps within CSEM post-test scores, qualitative lab quiz scores, and qualitative exam scores were insignificant for students with a CSEM pretest score of 25% or less but grew as pretest scores increased. Structural equation modeling demonstrated that a latent variable, called Conceptual Physics Performance/Non-Quantitative (CPP/NonQnt), orthogonal to quantitative test performance was useful in explaining the differences observed in qualitative performance; this variable was most strongly related to CSEM post-test scores. The CPP/NonQnt of male students was 0.44 standard deviations higher than female students. The CSEM pretest measured CPP/NonQnt much less accurately for women (R2=4 % ) than for men (R2=17 % ). The failure to detect a gender gap for students scoring 25% or less on the pretest suggests that the CSEM instrument itself is not gender biased. The failure to find a performance difference in quantitative test performance while detecting a gap in qualitative performance suggests the qualitative differences do not result from psychological factors such as science anxiety or stereotype threat.

Assessment of body-powered upper limb prostheses by able-bodied subjects, using the Box and Blocks Test and the Nine-Hole Peg Test.

PubMed

Haverkate, Liz; Smit, Gerwin; Plettenburg, Dick H

2016-02-01

The functional performance of currently available body-powered prostheses is unknown. The goal of this study was to objectively assess and compare the functional performance of three commonly used body-powered upper limb terminal devices. Experimental trial. A total of 21 able-bodied subjects (n = 21, age = 22 ± 2) tested three different terminal devices: TRS voluntary closing Hook Grip 2S, Otto Bock voluntary opening hand and Hosmer Model 5XA hook, using a prosthesis simulator. All subjects used each terminal device nine times in two functional tests: the Nine-Hole Peg Test and the Box and Blocks Test. Significant differences were found between the different terminal devices and their scores on the Nine-Hole Peg Test and the Box and Blocks Test. The Hosmer hook scored best in both tests. The TRS Hook Grip 2S scored second best. The Otto Bock hand showed the lowest scores. This study is a first step in the comparison of functional performances of body-powered prostheses. The data can be used as a reference value, to assess the performance of a terminal device or an amputee. The measured scores enable the comparison of the performance of a prosthesis user and his or her terminal device relative to standard scores. © The International Society for Prosthetics and Orthotics 2014.

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.

PubMed

Parente, Daniel J; Ray, J Christian J; Swint-Kruse, Liskin

2015-12-01

As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions. © 2015 Wiley Periodicals, Inc.

An Improved Graph Model for Conflict Resolution Based on Option Prioritization and Its Application

PubMed Central

Yin, Kedong; Li, Xuemei

2017-01-01

In order to quantitatively depict differences regarding the preferences of decision makers for different states, a score function is proposed. As a foundation, coalition motivation and real-coalition analysis are discussed when external circumstance or opportunity costs are considering. On the basis of a confidence-level function, we establish the score function using a “preference tree”. We not only measure the preference for each state, but we also build a collation improvement function to measure coalition motivation and to construct a coordinate system in which to analyze real-coalition stability. All of these developments enhance the applicability of the graph model for conflict resolution (GMCR). Finally, an improved GMCR is applied in the “Changzhou Conflict” to demonstrate how it can be conveniently utilized in practice. PMID:29077049

An Improved Graph Model for Conflict Resolution Based on Option Prioritization and Its Application.

PubMed

Yin, Kedong; Yu, Li; Li, Xuemei

2017-10-27

In order to quantitatively depict differences regarding the preferences of decision makers for different states, a score function is proposed. As a foundation, coalition motivation and real-coalition analysis are discussed when external circumstance or opportunity costs are considering. On the basis of a confidence-level function, we establish the score function using a "preference tree". We not only measure the preference for each state, but we also build a collation improvement function to measure coalition motivation and to construct a coordinate system in which to analyze real-coalition stability. All of these developments enhance the applicability of the graph model for conflict resolution (GMCR). Finally, an improved GMCR is applied in the "Changzhou Conflict" to demonstrate how it can be conveniently utilized in practice.

Ecological and personal predictors of science achievement in an urban center

NASA Astrophysics Data System (ADS)

Guidubaldi, John Michael

This study sought to examine selected personal and environmental factors that predict urban students' achievement test scores on the science subject area of the Ohio standardized test. Variables examined were in the general categories of teacher/classroom, student, and parent/home. It assumed that these clusters might add independent variance to a best predictor model, and that discovering relative strength of different predictors might lead to better selection of intervention strategies to improve student performance. This study was conducted in an urban school district and was comprised of teachers and students enrolled in ninth grade science in three of this district's high schools. Consenting teachers (9), students (196), and parents (196) received written surveys with questions designed to examine the predictive power of each variable cluster. Regression analyses were used to determine which factors best correlate with student scores and classroom science grades. Selected factors were then compiled into a best predictive model, predicting success on standardized science tests. Students t tests of gender and racial subgroups confirmed that there were racial differences in OPT scores, and both gender and racial differences in science grades. Additional examinations were therefore conducted for all 12 variables to determine whether gender and race had an impact on the strength of individual variable predictions and on the final best predictor model. Of the 15 original OPT and cluster variable hypotheses, eight showed significant positive relationships that occurred in the expected direction. However, when more broadly based end-of-the-year science class grade was used as a criterion, 13 of the 15 hypotheses showed significant relationships in the expected direction. With both criteria, significant gender and racial differences were observed in the strength of individual predictors and in the composition of best predictor models.

Diabetes quality of life perception in a multiethnic population.

PubMed

Goh, S G K; Rusli, B N; Khalid, B A K

2015-07-01

The aim of this study was to determine ethnic differences and predictors of the perception of quality of life (QOL) in a multiethnic Malaysian population with type 2 diabetes. A population-based cross-sectional study was done in three different states in Malaysia. The Asian Diabetes Quality of Life (AsianDQOL) tool specific for type 2 diabetes is the primary outcome tool. One-way analysis of covariance was undertaken to examine ethnic differences on the total and component AsianDQOL scores controlling for important covariates. Stepwise multiple linear regression models were used for selecting predictors for the AsianDQOL score with stratification for ethnicity and language. A total of 647 subjects (338 Malays, 160 Chinese and 149 Indians) were recruited. Chinese scored significantly lower (78.1 ± 11.6) on the AsianDQOL (total) score compared to Malays (81.4 ± 9.0) and Indians (81.5 ± 9.2) (F = 3.060, p = 0.049, η (2) = 0.02). Likewise, Chinese scored significantly lower (21.0 ± 4.3) on the AsianDQOL (diet) score compared to Malays (22.8 ± 3.6) and Indians (22.5 ± 3.7) (F = 4.96, p = 0.008, η (2) = 0.04). The main predictors of AsianDQOL (total) score for the English language group of different ethnicities were sexual dysfunction (-4.5), having visual problems (-3.7), female (-2.8) and glycemic control (-1.6). Sexual dysfunction was negatively correlated with QOL in Malay, Chinese ethnic group and Indian ethnic groups. The perception of AsianDQOL is different across ethnic groups and languages spoken. Significant differences in the English-speaking group and the non-English-speaking group are detected within the same ethnicity. Sexual dysfunction severely impacts AsianDQOL in a multiethnic Asian population and remains an important determinant regardless of ethnicity and language.

Effective scoring of scapha prevents helix irregularity in prominent ear correction - a biomechanical study.

PubMed

Nagasao, Tomohisa; Miyamoto, Junpei; Shimizu, Yusuke; Kasai, Shogo; Kishi, Kazuo; Kaneko, Tsuyoshi

2014-09-01

As the antihelix is created in the operation for prominent ear, the helix often presents irregularities. This biomechanical study aims to elucidate effective techniques to prevent these irregularities. Finite element models were produced simulating 10 prominent ears. The scaphas of the 10 models were thinned to simulate scoring or abrasion of the cartilage. The thinning was conducted in four fashions. In the first group, no thinning was conducted (Non-Scoring Models); in the second group, the upper half of the scapha was thinned (Upper-Scoring Models); in the third group, the lower half of the scapha was thinned (Lower-Scoring Models); in the fourth group, the whole scapha was thinned (Whole-Scoring Models). Mattress sutures were applied to create the antihelix to simulate Mustarde's in-suture technique. Thereafter, transformation of the helix's contour was evaluated. Irregularity developed on the upper region of the helix with Non-Scoring and Lower-Scoring Models; the degree of the upper-region's irregularity was reduced with Upper-Scoring Models and Whole-Scoring Models. Although the edge of the helix moved in the posterior-medial direction with other type models, it moved in the anterior direction with Whole-Scoring Models. Irregularity of the upper region of the helix can be prevented by performing scoring or abrasion of the upper part of the scapha. The prominence of the helix and width of the auricle are adjustable by varying the areas of the scapha receiving scoring or abrasion. These findings are useful in improving operative outcomes in the treatment of prominent ears. Copyright © 2014 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Quality of life in breast cancer sufferers.

PubMed

Shouman, Ahmed Essmat; Abou El Ezz, Nahla Fawzy; Gado, Nivine; Ibrahim Goda, Amal Mahmoud

2016-08-08

Purpose - The purpose of this paper is to measure health-related quality of life (QOL) among patients with early stage cancer breast under curative treatment at department of oncology and nuclear medicine at Ain Shams University Hospitals. Identify factors affecting QOL among these patients. Design/methodology/approach - A cross-sectional study measured QOL among early stage female breast cancer (BC) patients and determined the main factors affecting their QOL. Three interviewer administered questionnaires were used. Findings - The physical domain mostly affected in BC patients and the functional domain least. Socio-demographic factors that significantly affected BC patients QOL scores were patient age, education, having children and family income. Specific patient characteristics include caregiver presence - a factor that affected different QOL scores. Age at diagnosis, affection in the side of the predominant hand, post-operative chemotherapy and difficulty in obtaining the medication were the disease-related factors that affected QOL scores. Originality/value - The final model predicting QOL for early stage female BC patients included age, education and difficulty in obtaining the medication as determinants for total QOL score. Carer presence was the specific patient characteristic that affected different QOL scores.

Item Response Theory Analysis of the Psychopathic Personality Inventory-Revised.

PubMed

Eichenbaum, Alexander E; Marcus, David K; French, Brian F

2017-06-01

This study examined item and scale functioning in the Psychopathic Personality Inventory-Revised (PPI-R) using an item response theory analysis. PPI-R protocols from 1,052 college student participants (348 male, 704 female) were analyzed. Analyses were conducted on the 131 self-report items comprising the PPI-R's eight content scales, using a graded response model. Scales collected a majority of their information about respondents possessing higher than average levels of the traits being measured. Each scale contained at least some items that evidenced limited ability to differentiate between respondents with differing levels of the trait being measured. Moreover, 80 items (61.1%) yielded significantly different responses between men and women presumably possessing similar levels of the trait being measured. Item performance was also influenced by the scoring format (directly scored vs. reverse-scored) of the items. Overall, the results suggest that the PPI-R, despite identifying psychopathic personality traits in individuals possessing high levels of those traits, may not identify these traits equally well for men and women, and scores are likely influenced by the scoring format of the individual item and scale.

Potential Utility of the SYNTAX Score 2 in Patients Undergoing Left Main Angioplasty

PubMed Central

Madeira, Sérgio; Raposo, Luís; Brito, João; Rodrigues, Ricardo; Gonçalves, Pedro; Teles, Rui; Gabriel, Henrique; Machado, Francisco; Almeida, Manuel; Mendes, Miguel

2016-01-01

Background The revascularization strategy of the left main disease is determinant for clinical outcomes. Objective We sought to 1) validate and compare the performance of the SYNTAX Score 1 and 2 for predicting major cardiovascular events at 4 years in patients who underwent unprotected left main angioplasty and 2) evaluate the long-term outcome according to the SYNTAX score 2-recommended revascularization strategy. Methods We retrospectively studied 132 patients from a single-centre registry who underwent unprotected left main angioplasty between March 1999 and December 2010. Discrimination and calibration of both models were assessed by ROC curve analysis, calibration curves and the Hosmer-Lemeshow test. Results Total event rate was 26.5% at 4 years.The AUC for the SYNTAX Score 1 and SYNTAX Score 2 for percutaneous coronary intervention, was 0.61 (95% CI: 0.49-0.73) and 0.67 (95% CI: 0.57-0.78), respectively. Despite a good overall adjustment for both models, the SYNTAX Score 2 tended to underpredict risk. In the 47 patients (36%) who should have undergone surgery according to the SYNTAX Score 2, event rate was numerically higher (30% vs. 25%; p=0.54), and for those with a higher difference between the two SYNTAX Score 2 scores (Percutaneous coronary intervention vs. Coronary artery by-pass graft risk estimation greater than 5.7%), event rate was almost double (40% vs. 22%; p=0.2). Conclusion The SYNTAX Score 2 may allow a better and individualized risk stratification of patients who need revascularization of an unprotected left main coronary artery. Prospective studies are needed for further validation. PMID:27007223

Further Simplification of the Simple Erosion Narrowing Score With Item Response Theory Methodology.

PubMed

Oude Voshaar, Martijn A H; Schenk, Olga; Ten Klooster, Peter M; Vonkeman, Harald E; Bernelot Moens, Hein J; Boers, Maarten; van de Laar, Mart A F J

2016-08-01

To further simplify the simple erosion narrowing score (SENS) by removing scored areas that contribute the least to its measurement precision according to analysis based on item response theory (IRT) and to compare the measurement performance of the simplified version to the original. Baseline and 18-month data of the Combinatietherapie Bij Reumatoide Artritis (COBRA) trial were modeled using longitudinal IRT methodology. Measurement precision was evaluated across different levels of structural damage. SENS was further simplified by omitting the least reliably scored areas. Discriminant validity of SENS and its simplification were studied by comparing their ability to differentiate between the COBRA and sulfasalazine arms. Responsiveness was studied by comparing standardized change scores between versions. SENS data showed good fit to the IRT model. Carpal and feet joints contributed the least statistical information to both erosion and joint space narrowing scores. Omitting the joints of the foot reduced measurement precision for the erosion score in cases with below-average levels of structural damage (relative efficiency compared with the original version ranged 35-59%). Omitting the carpal joints had minimal effect on precision (relative efficiency range 77-88%). Responsiveness of a simplified SENS without carpal joints closely approximated the original version (i.e., all Δ standardized change scores were ≤0.06). Discriminant validity was also similar between versions for both the erosion score (relative efficiency = 97%) and the SENS total score (relative efficiency = 84%). Our results show that the carpal joints may be omitted from the SENS without notable repercussion for its measurement performance. © 2016, American College of Rheumatology.

The Impact of Misspelled Words on Automated Computer Scoring: A Case Study of Scientific Explanations

NASA Astrophysics Data System (ADS)

Ha, Minsu; Nehm, Ross H.

2016-06-01

Automated computerized scoring systems (ACSSs) are being increasingly used to analyze text in many educational settings. Nevertheless, the impact of misspelled words (MSW) on scoring accuracy remains to be investigated in many domains, particularly jargon-rich disciplines such as the life sciences. Empirical studies confirm that MSW are a pervasive feature of human-generated text and that despite improvements, spell-check and auto-replace programs continue to be characterized by significant errors. Our study explored four research questions relating to MSW and text-based computer assessments: (1) Do English language learners (ELLs) produce equivalent magnitudes and types of spelling errors as non-ELLs? (2) To what degree do MSW impact concept-specific computer scoring rules? (3) What impact do MSW have on computer scoring accuracy? and (4) Are MSW more likely to impact false-positive or false-negative feedback to students? We found that although ELLs produced twice as many MSW as non-ELLs, MSW were relatively uncommon in our corpora. The MSW in the corpora were found to be important features of the computer scoring models. Although MSW did not significantly or meaningfully impact computer scoring efficacy across nine different computer scoring models, MSW had a greater impact on the scoring algorithms for naïve ideas than key concepts. Linguistic and concept redundancy in student responses explains the weak connection between MSW and scoring accuracy. Lastly, we found that MSW tend to have a greater impact on false-positive feedback. We discuss the implications of these findings for the development of next-generation science assessments.

The expected value of possession in professional rugby league match-play.

PubMed

Kempton, Thomas; Kennedy, Nicholas; Coutts, Aaron J

2016-01-01

This study estimated the expected point value for starting possessions in different field locations during rugby league match-play and calculated the mean expected points for each subsequent play during the possession. It also examined the origin of tries scored according to the method of gaining possession. Play-by-play data were taken from all 768 regular-season National Rugby League (NRL) matches during 2010-2013. A probabilistic model estimated the expected point outcome based on the net difference in points scored by a team in possession in a given situation. An iterative method was used to approximate the value of each situation based on actual scoring outcomes. Possessions commencing close to the opposition's goal-line had the highest expected point equity, which decreased as the location of the possession moved towards the team's own goal-line. Possessions following an opposition error, penalty or goal-line dropout had the highest likelihood of a try being scored on the set subsequent to their occurrence. In contrast, possessions that follow an opposition completed set or a restart were least likely to result in a try. The expected point values framework from our model has applications for informing playing strategy and assessing individual and team performance in professional rugby league.

Psychopathic personality development from ages 9 to 18: Genes and environment.

PubMed

Tuvblad, Catherine; Wang, Pan; Bezdjian, Serena; Raine, Adrian; Baker, Laura A

2016-02-01

The genetic and environmental etiology of individual differences was examined in initial level and change in psychopathic personality from ages 9 to 18 years. A piecewise growth curve model, in which the first change score (G1) influenced all ages (9-10, 11-13, 14-15, and 16-18 years) and the second change score (G2) only influenced ages 14-15 and 16-18 years, fit the data better did than the standard single slope model, suggesting a turning point from childhood to adolescence. The results indicated that variations in levels and both change scores were mainly due to genetic (A) and nonshared environmental (E) influences (i.e., AE structure for G0, G1, and G2). No sex differences were found except on the mean values of level and change scores. Based on caregiver ratings, about 81% of variance in G0, 89% of variance in G1, and 94% of variance in G2 were explained by genetic factors, whereas for youth self-reports, these three proportions were 94%, 71%, and 66%, respectively. The larger contribution of genetic variance and covariance in caregiver ratings than in youth self-reports may suggest that caregivers considered the changes in their children to be more similar as compared to how the children viewed themselves.

Assessment of the quality of primary care for the elderly according to the Chronic Care Model 1

PubMed Central

Silva, Líliam Barbosa; Soares, Sônia Maria; Silva, Patrícia Aparecida Barbosa; Santos, Joseph Fabiano Guimarães; Miranda, Lívia Carvalho Viana; Santos, Raquel Melgaço

2018-01-01

ABSTRACT Objective: to evaluate the quality of care provided to older people with diabetes mellitus and/or hypertension in the Primary Health Care (PHC) according to the Chronic Care Model (CCM) and identify associations with care outcomes. Method: cross-sectional study involving 105 older people with diabetes mellitus and/or hypertension. The Patient Assessment of Chronic Illness Care (PACIC) questionnaire was used to evaluate the quality of care. The total score was compared with care outcomes that included biochemical parameters, body mass index, pressure levels and quality of life. Data analysis was based on descriptive statistics and multiple logistic regression. Results: there was a predominance of females and a median age of 72 years. The median PACIC score was 1.55 (IQ 1.30-2.20). Among the PACIC dimensions, the “delivery system design/decision support” was the one that presented the best result. There was no statistical difference between the medians of the overall PACIC score and individual care outcomes. However, when the quality of life and health satisfaction were simultaneously evaluated, a statistical difference between the medians was observed. Conclusion: the low PACIC scores found indicate that chronic care according to the CCM in the PHC seems still to fall short of its assumptions. PMID:29538582

Risk Selection into Consumer-Directed Health Plans: An Analysis of Family Choices within Large Employers

PubMed Central

McDevitt, Roland D; Haviland, Amelia M; Lore, Ryan; Laudenberger, Laura; Eisenberg, Matthew; Sood, Neeraj

2014-01-01

Objective To identify the degree of selection into consumer-directed health plans (CDHPs) versus traditional plans over time, and factors that influence choice and temper risk selection. Data Sources/Study Setting Sixteen large employers offering both CDHP and traditional plans during the 2004–2007 period, more than 200,000 families. Study Design We model CDHP choice with logistic regression; predictors include risk scores, in addition to family, choice setting, and plan characteristics. Additional models stratify by account type or single enrollee versus family. Data Collection/Extraction Methods Risk scores, family characteristics, and enrollment decisions are derived from medical claims and enrollment files. Interviews with human resources executives provide additional data. Principal Findings CDHP risk scores were 74 percent of traditional plan scores in the first year, and this difference declined over time. Employer contributions to accounts and employee premium savings fostered CDHP enrollment and reduced risk selection. Having to make an active choice of plan increased CDHP enrollment but also increased risk selection. Risk selection was greater for singles than families and did not differ between HRA and HSA-based CDHPs. Conclusions Risk selection was not severe and it was well managed. Employers have effective methods to encourage CDHP enrollment and temper selection against traditional plans. PMID:24800305

Assessment of the quality of primary care for the elderly according to the Chronic Care Model.

PubMed

Silva, Líliam Barbosa; Soares, Sônia Maria; Silva, Patrícia Aparecida Barbosa; Santos, Joseph Fabiano Guimarães; Miranda, Lívia Carvalho Viana; Santos, Raquel Melgaço

2018-03-08

to evaluate the quality of care provided to older people with diabetes mellitus and/or hypertension in the Primary Health Care (PHC) according to the Chronic Care Model (CCM) and identify associations with care outcomes. cross-sectional study involving 105 older people with diabetes mellitus and/or hypertension. The Patient Assessment of Chronic Illness Care (PACIC) questionnaire was used to evaluate the quality of care. The total score was compared with care outcomes that included biochemical parameters, body mass index, pressure levels and quality of life. Data analysis was based on descriptive statistics and multiple logistic regression. there was a predominance of females and a median age of 72 years. The median PACIC score was 1.55 (IQ 1.30-2.20). Among the PACIC dimensions, the "delivery system design/decision support" was the one that presented the best result. There was no statistical difference between the medians of the overall PACIC score and individual care outcomes. However, when the quality of life and health satisfaction were simultaneously evaluated, a statistical difference between the medians was observed. the low PACIC scores found indicate that chronic care according to the CCM in the PHC seems still to fall short of its assumptions.

A Study of the Factors Associated with Risk for Development of Pressure Ulcers: A Longitudinal Analysis.

PubMed

Thomas, Elizebeth; Vinodkumar, Sudhaya; Mathew, Silvia; Setia, Maninder Singh

2015-01-01

Pressure ulcers (PUs) are prevalent in hospitalized patients; they may cause clinical, psychological, and economic problems in these patients. Previous studies are cross-sectional, have used pooled data, or cox-regression models to assess the risk for developing PU. However, PU risk scores change over time and models that account for time varying variables are useful for cohort analysis of data. The present longitudinal study was conducted to compare the risk of PU between surgical and nonsurgical patients, and to evaluate the factors associated with the development of these ulcers over a period of time. We evaluated 290 hospitalized patients over a 4 months period. The main outcomes for our analysis were: (1) Score on the pressure risk assessment scale; and (2) the proportion of individuals who were at severe risk for developing PUs. We used random effects models for longitudinal analysis of the data. The mean PU score was significantly higher in the nonsurgical patients compared with surgical patients at baseline (15.23 [3.86] vs. 9.33 [4.57]; P < 0.01). About 7% of the total patients had a score of >20 at baseline and were considered as being at high-risk for PU; the proportion was significantly higher among the nonsurgical patients compared with the surgical patients (14% vs. 4%, P = 0.003). In the adjusted models, there was no difference for severe risk for PU between surgical and nonsurgical patients (odds ratios [ORs]: 0.37, 95% confidence interval [CI]: 0.01-12.80). An additional day in the ward was associated with a significantly higher likelihood of being at high-risk for PU (OR: 1.47, 95% CI: 1.16-1.86). There were no significant differences between patients who were admitted for surgery compared with those who were not. An additional day in the ward, however, is important for developing a high-risk score for PU on the monitoring scale, and these patients require active interventions.

The Application of the Cumulative Logistic Regression Model to Automated Essay Scoring

ERIC Educational Resources Information Center

Haberman, Shelby J.; Sinharay, Sandip

2010-01-01

Most automated essay scoring programs use a linear regression model to predict an essay score from several essay features. This article applied a cumulative logit model instead of the linear regression model to automated essay scoring. Comparison of the performances of the linear regression model and the cumulative logit model was performed on a…

Expert opinion as 'validation' of risk assessment applied to calf welfare.

PubMed

Bracke, Marc B M; Edwards, Sandra A; Engel, Bas; Buist, Willem G; Algers, Bo

2008-07-14

Recently, a Risk Assessment methodology was applied to animal welfare issues in a report of the European Food Safety Authority (EFSA) on intensively housed calves. Because this is a new and potentially influential approach to derive conclusions on animal welfare issues, a so-called semantic-modelling type 'validation' study was conducted by asking expert scientists, who had been involved or quoted in the report, to give welfare scores for housing systems and for welfare hazards. Kendall's coefficient of concordance among experts (n = 24) was highly significant (P < 0.001), but low (0.29 and 0.18 for housing systems and hazards respectively). Overall correlations with EFSA scores were significant only for experts with a veterinary or mixed (veterinary and applied ethological) background. Significant differences in welfare scores were found between housing systems, between hazards, and between experts with different backgrounds. For example, veterinarians gave higher overall welfare scores for housing systems than ethologists did, probably reflecting a difference in their perception of animal welfare. Systems with the lowest scores were veal calves kept individually in so-called "baby boxes" (veal crates) or in small groups, and feedlots. A suckler herd on pasture was rated as the best for calf welfare. The main hazards were related to underfeeding, inadequate colostrum intake, poor stockperson education, insufficient space, inadequate roughage, iron deficiency, inadequate ventilation, poor floor conditions and no bedding. Points for improvement of the Risk Assessment applied to animal welfare include linking information, reporting uncertainty and transparency about underlying values. The study provides novel information on expert opinion in relation to calf welfare and shows that Risk Assessment applied to animal welfare can benefit from a semantic modelling approach.

Quantitative evaluation of expression difference in report assignments between nursing and radiologic technology departments.

PubMed

Nishimoto, Naoki; Yokooka, Yuki; Yagahara, Ayako; Uesugi, Masahito; Ogasawara, Katsuhiko

2011-01-01

Our purpose in this study was to investigate the expression differences in report assignments between students in nursing and radiologic technology departments. We have known that faculties could identify differences, such as word usage, through grading their students' assignments. However, there are no reports in the literature dealing with expression differences in vocabulary usage in medical informatics education based on statistical techniques or other quantitative measures. The report assignment asked for students' opinions in the event that they found a rare case of a disease in a hospital after they graduated from professional school. We processed student report data automatically, and we applied the space vector model and TF/IDF (term frequency/inverse document frequency) scoring to 129 report assignments. The similarity-score distributions among the assignments for these two departments were close to normal. We focused on the sets of terms that occurred exclusively in either department. For terms such as "radiation therapy" or "communication skills" that occurred in the radiologic technology department, the TF/IDF score was 8.01. The same score was obtained for terms such as "privacy guidelines" or "consent of patients" that occurred in the nursing department. These results will help faculties to provide a better education based on identified expression differences from students' background knowledge.

Male body dissatisfaction scale (MBDS): proposal for a reduced model.

PubMed

da Silva, Wanderson Roberto; Marôco, João; Ochner, Christopher N; Campos, Juliana Alvares Duarte Bonini

2017-09-01

To evaluate the psychometric properties of the male body dissatisfaction scale (MBDS) in Brazilian and Portuguese university students; to present a reduced model of the scale; to compare two methods of computing global scores for participants' body dissatisfaction; and to estimate the prevalence of participants' body dissatisfaction. A total of 932 male students participated in this study. A confirmatory factor analysis (CFA) was used to assess the scale's psychometric properties. Multi-group analysis was used to test transnational invariance and invariance in independent samples. The body dissatisfaction score was calculated using two methods (mean and matrix of weights in the CFA), which were compared. Finally, individuals were classified according to level of body dissatisfaction, using the best method. The MBDS model did not show adequate fit for the sample and was, therefore, refined. Thirteen items were excluded and two factors were combined. A reduced model of 12 items and 2 factors was proposed and shown to have adequate psychometric properties. There was a significant difference (p < 0.001) between the methods for calculating the score for body dissatisfaction, since the mean overestimated the scores. Among student participants, the prevalence of body dissatisfaction with musculature and general appearance was 11.2 and 5.3%, respectively. The reduced bi-factorial model of the MBDS showed adequate validity, reliability, and transnational invariance and invariance in independent samples for Brazilian and Portuguese students. The new proposal for calculating the global score was able to more accurately show their body dissatisfaction. No level of evidence Basic Science.

Cardiovascular risk assessment in elderly adults using SCORE OP model in a Latin American population: The experience from Ecuador.

PubMed

Sisa, Ivan

2018-02-09

Cardiovascular disease (CVD) mortality is predicted to increase in Latin America countries due to their rapidly aging population. However, there is very little information about CVD risk assessment as a primary preventive measure in this high-risk population. We predicted the national risk of developing CVD in Ecuadorian elderly population using the Systematic COronary Risk Evaluation in Older Persons (SCORE OP) High and Low models by risk categories/CVD risk region in 2009. Data on national cardiovascular risk factors were obtained from the Encuesta sobre Salud, Bienestar y Envejecimiento. We computed the predicted 5-year risk of CVD risk and compared the extent of agreement and reclassification in stratifying high-risk individuals between SCORE OP High and Low models. Analyses were done by risk categories, CVD risk region, and sex. In 2009, based on SCORE OP Low model almost 42% of elderly adults living in Ecuador were at high risk of suffering CVD over a 5-year period. The extent of agreement between SCORE OP High and Low risk prediction models was moderate (Cohen's kappa test of 0.5), 34% of individuals approximately were reclassified into different risk categories and a third of the population would benefit from a pharmacologic intervention to reduce the CVD risk. Forty-two percent of elderly Ecuadorians were at high risk of suffering CVD over a 5-year period, indicating an urgent need to tailor primary preventive measures for this vulnerable and high-risk population. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Clinical risk stratification model for advanced colorectal neoplasia in persons with negative fecal immunochemical test results.

PubMed

Jung, Yoon Suk; Park, Chan Hyuk; Kim, Nam Hee; Park, Jung Ho; Park, Dong Il; Sohn, Chong Il

2018-01-01

The fecal immunochemical test (FIT) has low sensitivity for detecting advanced colorectal neoplasia (ACRN); thus, a considerable portion of FIT-negative persons may have ACRN. We aimed to develop a risk-scoring model for predicting ACRN in FIT-negative persons. We reviewed the records of participants aged ≥40 years who underwent a colonoscopy and FIT during a health check-up. We developed a risk-scoring model for predicting ACRN in FIT-negative persons. Of 11,873 FIT-negative participants, 255 (2.1%) had ACRN. On the basis of the multivariable logistic regression model, point scores were assigned as follows among FIT-negative persons: age (per year from 40 years old), 1 point; current smoker, 10 points; overweight, 5 points; obese, 7 points; hypertension, 6 points; old cerebrovascular attack (CVA), 15 points. Although the proportion of ACRN in FIT-negative persons increased as risk scores increased (from 0.6% in the group with 0-4 points to 8.1% in the group with 35-39 points), it was significantly lower than that in FIT-positive persons (14.9%). However, there was no statistical difference between the proportion of ACRN in FIT-negative persons with ≥40 points and in FIT-positive persons (10.5% vs. 14.9%, P = 0.321). FIT-negative persons may need to undergo screening colonoscopy if they clinically have a high risk of ACRN. The scoring model based on age, smoking habits, overweight or obesity, hypertension, and old CVA may be useful in selecting and prioritizing FIT-negative persons for screening colonoscopy.

Exact calculation of distributions on integers, with application to sequence alignment.

PubMed

Newberg, Lee A; Lawrence, Charles E

2009-01-01

Computational biology is replete with high-dimensional discrete prediction and inference problems. Dynamic programming recursions can be applied to several of the most important of these, including sequence alignment, RNA secondary-structure prediction, phylogenetic inference, and motif finding. In these problems, attention is frequently focused on some scalar quantity of interest, a score, such as an alignment score or the free energy of an RNA secondary structure. In many cases, score is naturally defined on integers, such as a count of the number of pairing differences between two sequence alignments, or else an integer score has been adopted for computational reasons, such as in the test of significance of motif scores. The probability distribution of the score under an appropriate probabilistic model is of interest, such as in tests of significance of motif scores, or in calculation of Bayesian confidence limits around an alignment. Here we present three algorithms for calculating the exact distribution of a score of this type; then, in the context of pairwise local sequence alignments, we apply the approach so as to find the alignment score distribution and Bayesian confidence limits.

How is Family Centered Care Perceived by Healthcare Providers from Different Countries? An International Comparison Study.

PubMed

Feeg, Veronica D; Paraszczuk, Ann Marie; Çavuşoğlu, Hicran; Shields, Linda; Pars, Hatice; Al Mamun, Abdullah

2016-01-01

Family-centered care (FCC) is a healthcare delivery model in which planning care for a child incorporates the entire family. The purpose of this study was to describe and compare how healthcare providers from three countries with varied cultural and healthcare systems perceive the concept FCC by measuring attitudes, and to psychometrically identify a measure that would reflect "family-centeredness." The Working with Families questionnaire, translated when appropriate, was used to capture participants' perceptions of caring for hospitalized children and their parents from pediatric healthcare providers in the United States, Australia and Turkey (n=476). The results indicated significantly more positive attitudes reported for working with children than parents for all countries and individual score differences across countries: the U.S. and Turkey child scores were significantly higher than Australia, whereas the U.S. and Australia parent scores were both significantly higher than Turkey. Perceptions of working with families were different for nurses from the three countries that call for a clearer understanding about perceptions in relation to delivery systems. Further analyses revealed FCS scores to be significantly different between nurses and physicians and significantly correlated with age, number of children and education. The results of this study add to our understanding of influences on practice from different countries and healthcare systems. The FCS score may be useful to determine baseline beliefs and ascertain effectiveness of interventions designed to improve FCC implementation. Copyright © 2016 Elsevier Inc. All rights reserved.

Flow and diffusion of high-stakes test scores.

PubMed

Marder, M; Bansal, D

2009-10-13

We apply visualization and modeling methods for convective and diffusive flows to public school mathematics test scores from Texas. We obtain plots that show the most likely future and past scores of students, the effects of random processes such as guessing, and the rate at which students appear in and disappear from schools. We show that student outcomes depend strongly upon economic class, and identify the grade levels where flows of different groups diverge most strongly. Changing the effectiveness of instruction in one grade naturally leads to strongly nonlinear effects on student outcomes in subsequent grades.

Prognostic capability of different liver disease scoring systems for prediction of early mortality after transjugular intrahepatic portosystemic shunt creation.

PubMed

Gaba, Ron C; Couture, Patrick M; Bui, James T; Knuttinen, M Grace; Walzer, Natasha M; Kallwitz, Eric R; Berkes, Jamie L; Cotler, Scott J

2013-03-01

To compare the performance of various liver disease scoring systems in predicting early mortality after transjugular intrahepatic portosystemic shunt (TIPS) creation. In this single-institution retrospective study, eight scoring systems were used to grade liver disease in 211 patients (male-to-female ratio = 131:80; mean age, 54 y) before TIPS creation from 1999-2011. Scoring systems included bilirubin level, Child-Pugh (CP) score, Model for End-Stage Liver Disease (MELD) and Model for End-Stage Liver Disease sodium (MELD-Na) score, Emory score, prognostic index (PI), Acute Physiology and Chronic Health Evaluation (APACHE) 2 score, and Bonn TIPS early mortality (BOTEM) score. Medical record review was used to identify 30-day and 90-day clinical outcomes. The relationship of scoring parameters with mortality outcomes was assessed with multivariate analysis, and the relative ability of systems to predict mortality after TIPS creation was evaluated by comparing area under receiver operating characteristic (AUROC) curves. TIPS were successfully created for variceal hemorrhage (n = 121), ascites (n = 72), hepatic hydrothorax (n = 15), and portal vein thrombosis (n = 3). All scoring systems had a significant association with 30-day and 90-day mortality (P<.050 in each case) on multivariate analysis. Based on 30-day and 90-day AUROC, MELD (0.878, 0.816) and MELD-Na (0.863, 0.823) scores had the best capability to predict early mortality compared with bilirubin (0.786, 0.749), CP (0.822, 0.771), Emory (0.786, 0.681), PI (0.854, 0.760), APACHE 2 (0.836, 0.735), and BOTEM (0.798, 0.698), with statistical superiority over bilirubin, Emory, and BOTEM scores. Several liver disease scoring systems have prognostic value for early mortality after TIPS creation. MELD and MELD-Na scores most effectively predict survival after TIPS creation. Copyright © 2013. Published by Elsevier Inc.

Relationship between candidate communication ability and oral certification examination scores.

PubMed

Lunz, Mary E; Bashook, Philip G

2008-12-01

Structured case-based oral examinations are widely used in medical certifying examinations in the USA. These orals assess the candidate's decision-making skills using real or realistic patient cases. Frequently mentioned but not empirically evaluated is the potential bias introduced by the candidate's communication ability. This study aimed to assess the relationship between candidate communication ability and medical certification oral examination scores. Non-doctor communication observers rated a random sample of 90 candidates on communication ability during a medical oral certification examination. The multi-facet Rasch model was used to analyse the communication survey and the oral examination data. The multi-facet model accounts for observer and examiner severity bias. anova was used to measure differences in communication ability between passing and failing candidates and candidates grouped by level of communication ability. Pearson's correlations were used to compare candidate communication ability and oral certification examination performance. Candidate separation reliability values for the communication survey and the oral examination were 0.85 and 0.97, respectively, suggesting accurate candidate measurement. The correlation between communication scores and oral examination scores was 0.10. No significant difference was found between passing and failing candidates for measured communication ability. When candidates were grouped by high, moderate and low communication ability, there was no significant difference in their oral certification examination performance. Candidates' communication ability has little relationship to candidate performance on high-stakes, case-based oral examinations. Examiners for this certifying examination focused on assessing candidate decision-making ability and were not influenced by candidate communication ability.

Evaluating Teach One Reach One-An STI/HIV Risk-Reduction Intervention to Enhance Adult-Youth Communication About Sex and Reduce the Burden of HIV/STI.

PubMed

Dave, Gaurav; Ritchwood, Tiarney; Young, Tiffany L; Isler, Malika Roman; Black, Adina; Akers, Aletha Y; Gizlice, Ziya; Blumenthal, Connie; Atley, Leslie; Wynn, Mysha; Stith, Doris; Cene, Crystal; Ellis, Danny; Corbie-Smith, Giselle

2017-11-01

Parents and caregivers play an important role in sexual socialization of youth, often serving as the primary source of information about sex. For African American rural youth who experience disparate rates of HIV/sexually transmitted infection, improving caregiver-youth communication about sexual topics may help to reduce risky behaviors. This study assessed the impact of an intervention to improve sexual topic communication. A Preintervention-postintervention, quasi-experimental, controlled, and community-based trial. Intervention was in 2 rural North Carolina counties with comparison group in 3 adjacent counties. Participants (n = 249) were parents, caregivers, or parental figures for African American youth aged 10 to 14. Twelve-session curriculum for participating dyads. Audio computer-assisted self-interview to assess changes at 9 months from baseline in communication about general and sensitive sex topics and overall communication about sex. Multivariable models were used to examine the differences between the changes in mean of scores for intervention and comparison groups. Statistically significant differences in changes in mean scores for communication about general sex topics ( P < .0001), communication about sensitive sex topics ( P < .0001), and overall communication about sex ( P < .0001) existed. Differences in change in mean scores remained significant after adjusting baseline scores and other variables in the multivariate models. In Teach One Reach One intervention, adult participants reported improved communication about sex, an important element to support risk reduction among youth in high-prevalence areas.

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

Hedeker, D; Gibbons, R D

1996-05-01

MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.

Projected 24-hour post-dose ocular itching scores post-treatment with olopatadine 0.7% versus 0.2.

PubMed

Fidler, Matthew L; Ogundele, Abayomi; Covert, David; Sarangapani, Ramesh

2018-04-21

Olopatadine is an antihistamine and mast cell stabilizer used for treating allergic conjunctivitis. Olopatadine 0.7% has been recently approved for daily dosing in the US, which supersedes the previously approved 0.2% strength. The objective of this analysis was to characterize patients who have better itching relief at 24 h when taking olopatadine 0.7% treatment instead of olopatadine 0.2% (in terms of proportions of responses) and relate this to the severity of baseline itching as an indirect metric of a patient's sensitivity to antihistamines. A differential odds model was developed using data from two conjunctival allergen challenge (CAC) studies to characterize individual-level and population-level response to ocular itching following olopatadine treatment and the data was analyzed retrospectively. This modeling analysis was designed to predict 24 h ocular itching scores and to quantify the differences in 24 h itching relief following treatment with olopatadine 0.2% versus 0.7% in patients with moderate-to-high baseline itching. A one-compartment kinetic-pharmacodynamic E max model was used to determine the effect of olopatadine. Impact of baseline itching severity, vehicle effect and the drug effect on the overall itching scores post-treatment were explicitly incorporated in the model. The model quantified trends observed in the clinical data with regards to both mean scores and the proportions of patients responding to olopatadine treatment. The model predicts a higher proportion of patients in the olopatadine 0.7% versus 0.2% group will experience relief within 24 h. This prediction was confirmed with retrospective clinical data analysis. The number of allergy patients relieved with olopatadine 0.7% increased with higher baseline itching severity scores, when compared to olopatadine 0.2%.

Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15.

PubMed

Mpundu-Kaambwa, Christine; Chen, Gang; Russo, Remo; Stevens, Katherine; Petersen, Karin Dam; Ratcliffe, Julie

2017-04-01

The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based. This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis. The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models. The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE. Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

Family-centred care delivery: comparing models of primary care service delivery in Ontario.

PubMed

Mayo-Bruinsma, Liesha; Hogg, William; Taljaard, Monica; Dahrouge, Simone

2013-11-01

To determine whether models of primary care service delivery differ in their provision of family-centred care (FCC) and to identify practice characteristics associated with FCC. Cross-sectional study. Primary care practices in Ontario (ie, 35 salaried community health centres, 35 fee-for-service practices, 32 capitation-based health service organizations, and 35 blended remuneration family health networks) that belong to 4 models of primary care service delivery. A total of 137 practices, 363 providers, and 5144 patients. Measures of FCC in patient and provider surveys were based on the Primary Care Assessment Tool. Statistical analyses were conducted using linear mixed regression models and generalized estimating equations. Patient-reported FCC scores were high and did not vary significantly by primary care model. Larger panel size in a practice was associated with lower odds of patients reporting FCC. Provider-reported FCC scores were significantly higher in community health centres than in family health networks (P = .035). A larger number of nurse practitioners and clinical services on-site were both associated with higher FCC scores, while scores decreased as the number of family physicians in a practice increased and if practices were more rural. Based on provider and patient reports, primary care reform strategies that encourage larger practices and more patients per family physician might compromise the provision of FCC, while strategies that encourage multidisciplinary practices and a range of services might increase FCC.

Modeling and simulation of sexual activity daily diary data of patients with female sexual arousal disorder treated with sildenafil citrate (Viagra).

PubMed

Claret, Laurent; Cox, Eugene H; McFadyen, Lynn; Pidgen, Alwyn; Johnson, Patrick J; Haughie, Scott; Boolell, Mitra; Bruno, Rene

2006-08-01

To develop a model to explore the dose-response of sildenafil citrate in patients with female sexual arousal disorder (FSAD) based on telephone sexual activity daily diary (TSADD) data obtained in double-blind, placebo controlled clinical studies. Data were available on 614 patients with FSAD. A parametric model (Weibull distribution) was developed to describe the probability density function of the time between sexual events. Orgasm satisfaction scores and overall sexual satisfaction scores were simultaneously modeled as ordered categorical variables. Simulations were performed to evaluate the expected clinical response in patients with FSAD. The expected time between sexual events was approximately 3.5 days. Satisfaction scores increased with time to achieve a plateau after 3 to 4 weeks on treatment. The expected probability of satisfying orgasm (score of 3 and higher) ranged from 34.7% for placebo to 41.6% for 100 mg sildenafil citrate. Treatment effect (difference from placebo) was 6.9% for 100 mg sildenafil citrate, ranging from 0.6 to 24.7% for testosterone levels of 0.1 to 4.0 pg/ml. The treatment effect in postmenopausal women was larger than in premenopausal women. A modeling and simulation framework to support drug development in FSAD was developed. Sildenafil citrate demonstrated a dose-dependent effect in patients with FSAD.

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

Li, B; Fujita, A; Buch, K

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIsmore » over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast, subtle texture changes in addition to human observers.« less

Color-Matching and Blending-Effect of Universal Shade Bulk-Fill-Resin-Composite in Resin-Composite-Models and Natural Teeth.

PubMed

Abdelraouf, Rasha M; Habib, Nour A

2016-01-01

Objectives . To assess visually color-matching and blending-effect (BE) of a universal shade bulk-fill-resin-composite placed in resin-composite-models with different shades and cavity sizes and in natural teeth (extracted and patients' teeth). Materials and Methods . Resin-composite-discs (10 mm × 1 mm) were prepared of universal shade composite and resin-composite of shades: A1, A2, A3, A3.5, and A4. Spectrophotometric-color-measurement was performed to calculate color-difference (Δ E ) between the universal shade and shaded-resin-composites discs and determine their translucency-parameter (TP). Visual assessment was performed by seven normal-color-vision-observers to determine the color-matching between the universal shade and each shade, under Illuminant D65. Color-matching visual scoring (VS) values were expressed numerically (1-5): 1: mismatch/totally unacceptable, 2: Poor-Match/hardly acceptable, 3: Good-Match/acceptable, 4: Close-Match/small-difference, and 5: Exact-Match/no-color-difference. Occlusal cavities of different sizes were prepared in teeth-like resin-composite-models with shades A1, A2, A3, A3.5, and A4. The cavities were filled by the universal shade composite. The same scale was used to score color-matching between the fillings and composite-models. BE was calculated as difference in mean-visual-scores in models and that of discs. Extracted teeth with two different class I-cavity sizes as well as ten patients' lower posterior molars with occlusal caries were prepared, filled by universal shade composite, and assessed similarly. Results . In models, the universal shade composite showed close matching in the different cavity sizes and surrounding shades (4 ≤ VS < 5) (BE = 0.6-2.9 in small cavities and 0.5-2.8 in large cavities). In extracted teeth, there was good-to-close color-matching (VS = 3.7-4.4 in small cavities, BE = 2.5-3.2) (VS = 3-3.5, BE = 1.8-2.3 in large cavities). In patients' molars, the universal shade composite showed good-matching (VS = 3-3.3, BE = -0.9-2.1). Conclusions . Color-matching of universal shade resin-composite was satisfactory rather than perfect in patients' teeth.

Global, broad, or specific cognitive differences? Using a MIMIC model to examine differences in CHC abilities in children with learning disabilities.

PubMed

Niileksela, Christopher R; Reynolds, Matthew R

2014-01-01

This study was designed to better understand the relations between learning disabilities and different levels of latent cognitive abilities, including general intelligence (g), broad cognitive abilities, and specific abilities based on the Cattell-Horn-Carroll theory of intelligence (CHC theory). Data from the Differential Ability Scales-Second Edition (DAS-II) were used to create a multiple-indicator multiple cause model to examine the latent mean differences in cognitive abilities between children with and without learning disabilities in reading (LD reading), math (LD math), and reading and writing(LD reading and writing). Statistically significant differences were found in the g factor between the norm group and the LD groups. After controlling for differences in g, the LD reading and LD reading and writing groups showed relatively lower latent processing speed, and the LD math group showed relatively higher latent comprehension-knowledge. There were also some differences in some specific cognitive abilities, including lower scores in spatial relations and numerical facility for the LD math group, and lower scores in visual memory for the LD reading and writing group. These specific mean differences were above and beyond any differences in the latent cognitive factor means.

Modeling Bivariate Change in Individual Differences: Prospective Associations Between Personality and Life Satisfaction.

PubMed

Hounkpatin, Hilda Osafo; Boyce, Christopher J; Dunn, Graham; Wood, Alex M

2017-09-18

A number of structural equation models have been developed to examine change in 1 variable or the longitudinal association between 2 variables. The most common of these are the latent growth model, the autoregressive cross-lagged model, the autoregressive latent trajectory model, and the latent change score model. The authors first overview each of these models through evaluating their different assumptions surrounding the nature of change and how these assumptions may result in different data interpretations. They then, to elucidate these issues in an empirical example, examine the longitudinal association between personality traits and life satisfaction. In a representative Dutch sample (N = 8,320), with participants providing data on both personality and life satisfaction measures every 2 years over an 8-year period, the authors reproduce findings from previous research. However, some of the structural equation models overviewed have not previously been applied to the personality-life satisfaction relation. The extended empirical examination suggests intraindividual changes in life satisfaction predict subsequent intraindividual changes in personality traits. The availability of data sets with 3 or more assessment waves allows the application of more advanced structural equation models such as the autoregressive latent trajectory or the extended latent change score model, which accounts for the complex dynamic nature of change processes and allows stronger inferences on the nature of the association between variables. However, the choice of model should be determined by theories of change processes in the variables being studied. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Individualized Physical 3-dimensional Kidney Tumor Models Constructed From 3-dimensional Printers Result in Improved Trainee Anatomic Understanding.

PubMed

Knoedler, Margaret; Feibus, Allison H; Lange, Andrew; Maddox, Michael M; Ledet, Elisa; Thomas, Raju; Silberstein, Jonathan L

2015-06-01

To evaluate the effect of 3-dimensionally (3D) printed physical renal models with enhancing masses on medical trainee characterization, localization, and understanding of renal malignancy. Proprietary software was used to import standard computed tomography (CT) cross-sectional imaging into 3D printers to create physical models of renal units with enhancing renal lesions in situ. Six different models were printed from a transparent plastic resin; the normal parenchyma was printed in a clear, translucent plastic, with a red hue delineating the suspicious renal lesion. Medical students, who had completed their first year of training, were given an overview and tasked with completion of RENAL nephrometry scores, separately using CT imaging and 3D models. Trainees were also asked to complete a questionnaire about their experience. Variability between trainees was assessed by intraclass correlation coefficients (ICCs), and kappa statistics were used to compare the trainee to experts. Overall trainee nephrometry score accuracy was significantly improved with the 3D model vs CT scan (P <.01). Furthermore, 3 of the 4 components of the nephrometry score (radius, nearness to collecting system, and location) showed significant improvement (P <.001) using the models. There was also more consistent agreement among trainees when using the 3D models compared with CT scans to assess the nephrometry score (intraclass correlation coefficient, 0.28 for CT scan vs 0.72 for 3D models). Qualitative evaluation with questionnaires filled out by the trainees further confirmed that the 3D models improved their ability to understand and conceptualize the renal mass. Physical 3D models using readily available printing techniques improve trainees' understanding and characterization of individual patients' enhancing renal lesions. Published by Elsevier Inc.

Dopamine Transporter Neuroimaging as an Enrichment Biomarker in Early Parkinson's Disease Clinical Trials: A Disease Progression Modeling Analysis

PubMed Central

Nicholas, Timothy; Tsai, Kuenhi; Macha, Sreeraj; Sinha, Vikram; Stone, Julie; Corrigan, Brian; Bani, Massimo; Muglia, Pierandrea; Watson, Ian A.; Kern, Volker D.; Sheveleva, Elena; Marek, Kenneth; Stephenson, Diane T.; Romero, Klaus

2017-01-01

Abstract Given the recognition that disease‐modifying therapies should focus on earlier Parkinson's disease stages, trial enrollment based purely on clinical criteria poses significant challenges. The goal herein was to determine the utility of dopamine transporter neuroimaging as an enrichment biomarker in early motor Parkinson's disease clinical trials. Patient‐level longitudinal data of 672 subjects with early‐stage Parkinson's disease in the Parkinson's Progression Markers Initiative (PPMI) observational study and the Parkinson Research Examination of CEP‐1347 Trial (PRECEPT) clinical trial were utilized in a linear mixed‐effects model analysis. The rate of worsening in the motor scores between subjects with or without a scan without evidence of dopamine transporter deficit was different both statistically and clinically. The average difference in the change from baseline of motor scores at 24 months between biomarker statuses was –3.16 (90% confidence interval [CI] = –0.96 to –5.42) points. Dopamine transporter imaging could identify subjects with a steeper worsening of the motor scores, allowing trial enrichment and 24% reduction of sample size. PMID:28749580

Locating, characterizing and minimizing sources of error for a paper case-based structured oral examination in a multi-campus clerkship.

PubMed

Kumar, A; Bridgham, R; Potts, M; Gushurst, C; Hamp, M; Passal, D

2001-01-01

To determine consistency of assessment in a new paper case-based structured oral examination in a multi-community pediatrics clerkship, and to identify correctable problems in the administration of examination and assessment process. Nine paper case-based oral examinations were audio-taped. From audio-tapes five community coordinators scored examiner behaviors and graded student performance. Correlations among examiner behaviors scores were examined. Graphs identified grading patterns of evaluators. The effect of exam-giving on evaluators was assessed by t-test. Reliability of grades was calculated and the effect of reducing assessment problems was modeled. Exam-givers differed most in their "teaching-guiding" behavior, and this negatively correlated with student grades. Exam reliability was lowered mainly by evaluator differences in leniency and grading pattern; less important was absence of standardization in cases. While grade reliability was low in early use of the paper case-based oral examination, modeling of plausible effects of training and monitoring for greater uniformity in administration of the examination and assigning scores suggests that more adequate reliabilities can be attained.

Assessing the Multidimensional Relationship Between Medication Beliefs and Adherence in Older Adults With Hypertension Using Polynomial Regression.

PubMed

Dillon, Paul; Phillips, L Alison; Gallagher, Paul; Smith, Susan M; Stewart, Derek; Cousins, Gráinne

2018-02-05

The Necessity-Concerns Framework (NCF) is a multidimensional theory describing the relationship between patients' positive and negative evaluations of their medication which interplay to influence adherence. Most studies evaluating the NCF have failed to account for the multidimensional nature of the theory, placing the separate dimensions of medication "necessity beliefs" and "concerns" onto a single dimension (e.g., the Beliefs about Medicines Questionnaire-difference score model). To assess the multidimensional effect of patient medication beliefs (concerns and necessity beliefs) on medication adherence using polynomial regression with response surface analysis. Community-dwelling older adults >65 years (n = 1,211) presenting their own prescription for antihypertensive medication to 106 community pharmacies in the Republic of Ireland rated their concerns and necessity beliefs to antihypertensive medications at baseline and their adherence to antihypertensive medication at 12 months via structured telephone interview. Confirmatory polynomial regression found the difference-score model to be inaccurate; subsequent exploratory analysis identified a quadratic model to be the best-fitting polynomial model. Adherence was lowest among those with strong medication concerns and weak necessity beliefs, and adherence was greatest for those with weak concerns and strong necessity beliefs (slope β = -0.77, p<.001; curvature β = -0.26, p = .004). However, novel nonreciprocal effects were also observed; patients with simultaneously high concerns and necessity beliefs had lower adherence than those with simultaneously low concerns and necessity beliefs (slope β = -0.36, p = .004; curvature β = -0.25, p = .003). The difference-score model fails to account for the potential nonreciprocal effects. Results extend evidence supporting the use of polynomial regression to assess the multidimensional effect of medication beliefs on adherence.

SEMIPARAMETRIC ZERO-INFLATED MODELING IN MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA)

PubMed Central

Liu, Hai; Ma, Shuangge; Kronmal, Richard; Chan, Kung-Sik

2013-01-01

We analyze the Agatston score of coronary artery calcium (CAC) from the Multi-Ethnic Study of Atherosclerosis (MESA) using semi-parametric zero-inflated modeling approach, where the observed CAC scores from this cohort consist of high frequency of zeroes and continuously distributed positive values. Both partially constrained and unconstrained models are considered to investigate the underlying biological processes of CAC development from zero to positive, and from small amount to large amount. Different from existing studies, a model selection procedure based on likelihood cross-validation is adopted to identify the optimal model, which is justified by comparative Monte Carlo studies. A shrinkaged version of cubic regression spline is used for model estimation and variable selection simultaneously. When applying the proposed methods to the MESA data analysis, we show that the two biological mechanisms influencing the initiation of CAC and the magnitude of CAC when it is positive are better characterized by an unconstrained zero-inflated normal model. Our results are significantly different from those in published studies, and may provide further insights into the biological mechanisms underlying CAC development in human. This highly flexible statistical framework can be applied to zero-inflated data analyses in other areas. PMID:23805172

Impact of Elevated Core Body Temperature on Attention Networks.

PubMed

Liu, Kai; Jiang, Qingjun; Li, Li; Li, Bo; Yang, Zhen; Qian, Shaowen; Li, Min; Sun, Gang

2015-12-01

Cognitive function can be impaired after passive heat exposure and with an elevation in core body temperature (Tcore). This study examined the dynamic correlation among passive heat exposure, Tcore, and cognition. We gave the Attention Network Test of alerting, orienting, and executive control to five groups of five young men who were being exposed to a hyperthermic condition (50°C, 40% relative humidity) for 0, 10, 20, 30, or 40 minutes. We used the participants' reaction time, accuracy (correct responses), efficiency (accuracy÷reaction time), and Tcore to estimate optimal curve models for best fit of data. We could not estimate an appropriate curve model for either alerting or orienting with Tcore, change in Tcore, or duration of passive heat exposure. We estimated quadratic models for Tcore and duration (adjusted R=0.752), change in Tcore and duration (0.906), executive control score and duration (0.509), and efficiency of executive control and duration (0.293). We estimated linear models for executive control score and Tcore (0.479), efficiency of executive control and Tcore (0.261), executive control score and change in Tcore (0.279), and efficiency of executive control and change in Tcore (0.262). Different attentional abilities had different sensitivities to thermal stress. Executive control of attention deteriorated linearly with a rise in Tcore within the normal physiologic range, but deteriorated nonlinearly with longer passive heat exposure.

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

PubMed

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

Critical Combinations of Radiation Dose and Volume Predict Intelligence Quotient and Academic Achievement Scores After Craniospinal Irradiation in Children With Medulloblastoma

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

Merchant, Thomas E., E-mail: thomas.merchant@stjude.org; Schreiber, Jane E.; Wu, Shengjie

Purpose: To prospectively follow children treated with craniospinal irradiation to determine critical combinations of radiation dose and volume that would predict for cognitive effects. Methods and Materials: Between 1996 and 2003, 58 patients (median age 8.14 years, range 3.99-20.11 years) with medulloblastoma received risk-adapted craniospinal irradiation followed by dose-intense chemotherapy and were followed longitudinally with multiple cognitive evaluations (through 5 years after treatment) that included intelligence quotient (estimated intelligence quotient, full-scale, verbal, and performance) and academic achievement (math, reading, spelling) tests. Craniospinal irradiation consisted of 23.4 Gy for average-risk patients (nonmetastatic) and 36-39.6 Gy for high-risk patients (metastatic or residual disease >1.5 cm{sup 2}). The primary sitemore » was treated using conformal or intensity modulated radiation therapy using a 2-cm clinical target volume margin. The effect of clinical variables and radiation dose to different brain volumes were modeled to estimate cognitive scores after treatment. Results: A decline with time for all test scores was observed for the entire cohort. Sex, race, and cerebrospinal fluid shunt status had a significant impact on baseline scores. Age and mean radiation dose to specific brain volumes, including the temporal lobes and hippocampi, had a significant impact on longitudinal scores. Dichotomized dose distributions at 25 Gy, 35 Gy, 45 Gy, and 55 Gy were modeled to show the impact of the high-dose volume on longitudinal test scores. The 50% risk of a below-normal cognitive test score was calculated according to mean dose and dose intervals between 25 Gy and 55 Gy at 10-Gy increments according to brain volume and age. Conclusions: The ability to predict cognitive outcomes in children with medulloblastoma using dose-effects models for different brain subvolumes will improve treatment planning, guide intervention, and help estimate the value of newer methods of irradiation.« less

Proceedings of the Annual U.S. Army Operations Research Symposium (12th) , 2-5 October 1973. Volume 1

DTIC Science & Technology

1973-01-01

of technical and data problems. In brief, some of the deficiencies are associated with (a) the use of the "firepower score" force ratio concept as the...ficantly different attrition of different weapon systems (which "" "leads to deficiencies in the dynamic modeling of campaigns of any duration, and to...performed during June and July. Although the BATTLE model will eliminate some of the deficiencies in existing models, it is important to recognize that

Interobserver Reliability of the Total Body Score System for Quantifying Human Decomposition.

PubMed

Dabbs, Gretchen R; Connor, Melissa; Bytheway, Joan A

2016-03-01

Several authors have tested the accuracy of the Total Body Score (TBS) method for quantifying decomposition, but none have examined the reliability of the method as a scoring system by testing interobserver error rates. Sixteen participants used the TBS system to score 59 observation packets including photographs and written descriptions of 13 human cadavers in different stages of decomposition (postmortem interval: 2-186 days). Data analysis used a two-way random model intraclass correlation in SPSS (v. 17.0). The TBS method showed "almost perfect" agreement between observers, with average absolute correlation coefficients of 0.990 and average consistency correlation coefficients of 0.991. While the TBS method may have sources of error, scoring reliability is not one of them. Individual component scores were examined, and the influences of education and experience levels were investigated. Overall, the trunk component scores were the least concordant. Suggestions are made to improve the reliability of the TBS method. © 2016 American Academy of Forensic Sciences.

M-AMST: an automatic 3D neuron tracing method based on mean shift and adapted minimum spanning tree.

PubMed

Wan, Zhijiang; He, Yishan; Hao, Ming; Yang, Jian; Zhong, Ning

2017-03-29

Understanding the working mechanism of the brain is one of the grandest challenges for modern science. Toward this end, the BigNeuron project was launched to gather a worldwide community to establish a big data resource and a set of the state-of-the-art of single neuron reconstruction algorithms. Many groups contributed their own algorithms for the project, including our mean shift and minimum spanning tree (M-MST). Although M-MST is intuitive and easy to implement, the MST just considers spatial information of single neuron and ignores the shape information, which might lead to less precise connections between some neuron segments. In this paper, we propose an improved algorithm, namely M-AMST, in which a rotating sphere model based on coordinate transformation is used to improve the weight calculation method in M-MST. Two experiments are designed to illustrate the effect of adapted minimum spanning tree algorithm and the adoptability of M-AMST in reconstructing variety of neuron image datasets respectively. In the experiment 1, taking the reconstruction of APP2 as reference, we produce the four difference scores (entire structure average (ESA), different structure average (DSA), percentage of different structure (PDS) and max distance of neurons' nodes (MDNN)) by comparing the neuron reconstruction of the APP2 and the other 5 competing algorithm. The result shows that M-AMST gets lower difference scores than M-MST in ESA, PDS and MDNN. Meanwhile, M-AMST is better than N-MST in ESA and MDNN. It indicates that utilizing the adapted minimum spanning tree algorithm which took the shape information of neuron into account can achieve better neuron reconstructions. In the experiment 2, 7 neuron image datasets are reconstructed and the four difference scores are calculated by comparing the gold standard reconstruction and the reconstructions produced by 6 competing algorithms. Comparing the four difference scores of M-AMST and the other 5 algorithm, we can conclude that M-AMST is able to achieve the best difference score in 3 datasets and get the second-best difference score in the other 2 datasets. We develop a pathway extraction method using a rotating sphere model based on coordinate transformation to improve the weight calculation approach in MST. The experimental results show that M-AMST utilizes the adapted minimum spanning tree algorithm which takes the shape information of neuron into account can achieve better neuron reconstructions. Moreover, M-AMST is able to get good neuron reconstruction in variety of image datasets.

Relationships between host body condition and immunocompetence, not host sex, best predict parasite burden in a bat-helminth system.

PubMed

Warburton, Elizabeth M; Pearl, Christopher A; Vonhof, Maarten J

2016-06-01

Sex-biased parasitism highlights potentially divergent approaches to parasite resistance resulting in differing energetic trade-offs for males and females; however, trade-offs between immunity and self-maintenance could also depend on host body condition. We investigated these relationships in the big brown bat, Eptesicus fuscus, to determine if host sex or body condition better predicted parasite resistance, if testosterone levels predicted male parasite burdens, and if immune parameters could predict male testosterone levels. We found that male and female hosts had similar parasite burdens and female bats scored higher than males in only one immunological measure. Top models of helminth burden revealed interactions between body condition index and agglutination score as well as between agglutination score and host sex. Additionally, the strength of the relationships between sex, agglutination, and helminth burden is affected by body condition. Models of male parasite burden provided no support for testosterone predicting helminthiasis. Models that best predicted testosterone levels did not include parasite burden but instead consistently included month of capture and agglutination score. Thus, in our system, body condition was a more important predictor of immunity and worm burden than host sex.

Performance and Cognitive Assessment in 3-D Modeling

ERIC Educational Resources Information Center

Fahrer, Nolan E.; Ernst, Jeremy V.; Branoff, Theodore J.; Clark, Aaron C.

2011-01-01

The purpose of this study was to investigate identifiable differences between performance and cognitive assessment scores in a 3-D modeling unit of an engineering drafting course curriculum. The study aimed to provide further investigation of the need of skill-based assessments in engineering/technical graphics courses to potentially increase…

Syntax and reading comprehension: a meta-analysis of different spoken-syntax assessments.

PubMed

Brimo, Danielle; Lund, Emily; Sapp, Alysha

2018-05-01

Syntax is a language skill purported to support children's reading comprehension. However, researchers who have examined whether children with average and below-average reading comprehension score significantly different on spoken-syntax assessments report inconsistent results. To determine if differences in how syntax is measured affect whether children with average and below-average reading comprehension score significantly different on spoken-syntax assessments. Studies that included a group comparison design, children with average and below-average reading comprehension, and a spoken-syntax assessment were selected for review. Fourteen articles from a total of 1281 reviewed met the inclusionary criteria. The 14 articles were coded for the age of the children, score on the reading comprehension assessment, type of spoken-syntax assessment, type of syntax construct measured and score on the spoken-syntax assessment. A random-effects model was used to analyze the difference between the effect sizes of the types of spoken-syntax assessments and the difference between the effect sizes of the syntax construct measured. There was a significant difference between children with average and below-average reading comprehension on spoken-syntax assessments. Those with average and below-average reading comprehension scored significantly different on spoken-syntax assessments when norm-referenced and researcher-created assessments were compared. However, when the type of construct was compared, children with average and below-average reading comprehension scored significantly different on assessments that measured knowledge of spoken syntax, but not on assessments that measured awareness of spoken syntax. The results of this meta-analysis confirmed that the type of spoken-syntax assessment, whether norm-referenced or researcher-created, did not explain why some researchers reported that there were no significant differences between children with average and below-average reading comprehension, but the syntax construct, awareness or knowledge, did. Thus, when selecting how to measure syntax among school-age children, researchers and practitioners should evaluate whether they are measuring children's awareness of spoken syntax or knowledge of spoken syntax. Other differences, such as participant diagnosis and the format of items on the spoken-syntax assessments, also were discussed as possible explanations for why researchers found that children with average and below-average reading comprehension did not score significantly differently on spoken-syntax assessments. © 2017 Royal College of Speech and Language Therapists.

Teaching ear reconstruction using an alloplastic carving model.

PubMed

Murabit, Amera; Anzarut, Alexander; Kasrai, Laila; Fisher, David; Wilkes, Gordon

2010-11-01

Ear reconstruction is challenging surgery, often with poor outcomes. Our purpose was to develop a surgical training model for auricular reconstruction. Silicone costal cartilage models were incorporated in a workshop-based instructional program. Trainees were randomly divided. Workshop group (WG) participated in an interactive session, carving frameworks under supervision. Nonworkshop group (NWG) did not participate. Standard Nagata templates were used. Two further frameworks were created, first with supervision then without. Groups were combined after the first carving because of frustration in the NWG. Assessment was completed by 3 microtia surgeons from 2 different centers, blinded to framework origin. Frameworks were rated out of 10 using Likert and visual analog scales. Results were examined using SPSS (version 14), with t test, ANOVA, and Bonferroni post hoc analyses. Cartilaginous frameworks from the WG scored better for the first carving (WG 5.5 vs NWG 4.4), the NWG improved for the second carving (WG 6.6 vs NWG 6.5), and both groups scored lower with the third unsupervised carving (WG 5.9 vs NWG 5.6). Combined scores after 3 frameworks were not statistically significantly different between original groups. A statistically significant improvement was demonstrated for all carvers between sessions 1 and 2 (P ≤ 0.09), between sessions 1 and 3 (P ≤ 0.05), but not between sessions 2 and 3, thus suggesting the necessity of in vitro practice until high scores are achieved and maintained without supervision before embarking on in vivo carvings. Quality of carvings was not related to level of training. An appropriate and applicable surgical training model and training method can aid in attaining skills necessary for successful auricular reconstruction.

The brief negative symptom scale (BNSS): Sensitivity to treatment effects.

PubMed

Kirkpatrick, Brian; Saoud, Jay B; Strauss, Gregory P; Ahmed, Anthony O; Tatsumi, Kazunori; Opler, Mark; Luthringer, Remy; Davidson, Michael

2017-12-21

The Brief Negative Symptom Scale (BNSS) grew out of a recommendation by the NIMH-sponsored Consensus Development Conference on Negative Symptoms that a scale based on contemporary concepts be developed. We assessed sensitivity to change of the BNSS in a trial of MIN-101, which showed efficacy for negative symptoms (PANSS pentagonal model) at daily doses of 32 and 64mg/day. Using mixed-effects model for repeated measures, we examined change in BNSS total score and in the BNSS factors of anhedonia/avolition/asociality (AAA), and expressivity (EXP). Compared to placebo, the 64mg group (N=83) showed a significant decrease in BNSS total score (effect size d [ES] 0.56, p<0.01) and both factor scores (AAA ES=0.48, EXP ES=0.46, p<0.02 for both). Patients in the trial had minimal depression and positive symptom scores; covarying for disorganization, positive symptoms, or anxiety/depression did not cause a meaningful change in the significance of the BNSS total or factor scores in this group. The 32mg group (N=78) did not differ significantly from placebo (N=83) on BNSS total score (ES=0.33, p<0.09), AAA (ES=0.25, p<0.20) or EXP (ES=0.30, p<0.12) scores. These results demonstrate the BNSS is sensitive to change. Copyright © 2017. Published by Elsevier B.V.

[Study on the infectious risk model of AIDS among men who have sex with men in Guangzhou].

PubMed

Hu, Pei; Zhong, Fei; Cheng, Wei-Bin; Xu, Hui-Fang; Ling, Li

2012-07-01

To develop a human immune deficiency virus (HIV) infection risk appraisal model suitable for men who has sex with men (MSM) in Guangzhou, and to provide tools for follow-up the outcomes on health education and behavior intervention. A cros-sectional study was conducted in Guangzhou from 2008 to 2010. Based on the HIV surveillance data, the main risk factors of HIV infection among MSM were screened by means of logistic regression. Degree on relative risk was transformed into risk scores by adopting the statistics models. Individual risk scores, group risk scores and individual infection risk in comparison with usual MSM groups could then be calculated according to the rate of exposure on those risk factors appeared in data from the surveillance programs. Risk factors related to HIV infection among MSM and the quantitative assessment standard (risk scores and risk scores table of population groups) for those factors were set up by multiple logistic regression, including age, location of registered residence, monthly income, major location for finding their sexual partners, HIV testing in the past year, age when having the first sexual intercourse, rate of condom use in the past six months, symptoms related to sexually transmitted diseases (STDs) and syphilis in particular. The average risk score of population was 6.06, with risk scores for HIV positive and negative as 3.10 and 18.08 respectively (P < 0.001). The rates of HIV infection for different score groups were 0.9%, 2.0%, 7.0%, 14.4% and 33.3%, respectively. The sensitivity and specificity on the prediction of scores were 54.4% and 75.4% respectively, with the accuracy rate as 74.2%. HIV infection risk model could be used to quantify and classify the individual's infectious status and related factors among MSM more directly and effectively, so as to help the individuals to identify their high-risk behaviors as well as lifestyles. We felt that it could also serve as an important tool used for personalized HIV health education and behavior intervention programs.

MCAT Verbal Reasoning score: less predictive of medical school performance for English language learners.

PubMed

Winegarden, Babbi; Glaser, Dale; Schwartz, Alan; Kelly, Carolyn

2012-09-01

Medical College Admission Test (MCAT) scores are widely used as part of the decision-making process for selecting candidates for admission to medical school. Applicants who learned English as a second language may be at a disadvantage when taking tests in their non-native language. Preliminary research found significant differences between English language learners (ELLs), applicants who learned English after the age of 11 years, and non-ELL examinees on the Verbal Reasoning (VR) sub-test of the MCAT. The purpose of this study was to determine if relationships between VR sub-test scores and measures of medical school performance differed between ELL and non-ELL students. Scores on the MCAT VR sub-test and student performance outcomes (grades, examination scores, and markers of distinction and difficulty) were extracted from University of California San Diego School of Medicine admissions files and the Association of American Medical Colleges database for 924 students who matriculated in 1998-2005 (graduation years 2002-2009). Regression models were fitted to determine whether MCAT VR sub-test scores predicted medical school performance similarly for ELLs and non-ELLs. For several outcomes, including pre-clerkship grades, academic distinction, US Medical Licensing Examination Step 2 Clinical Knowledge scores and two clerkship shelf examinations, ELL status significantly affects the ability of the VR score to predict performance. Higher correlations between VR score and medical school performance emerged for non-ELL students than for ELL students for each of these outcomes. The MCAT VR score should be used with discretion when assessing ELL applicants for admission to medical school. © Blackwell Publishing Ltd 2012.

The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer.

PubMed

Reeh, Matthias; Metze, Johannes; Uzunoglu, Faik G; Nentwich, Michael; Ghadban, Tarik; Wellner, Ullrich; Bockhorn, Maximilian; Kluge, Stefan; Izbicki, Jakob R; Vashist, Yogesh K

2016-02-01

Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P < 0.001) and OS (P < 0.001). The PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P < 0.001) and OS (HR 2.2; P < 0.001). The PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score.

Construct validity of the ovine model in endoscopic sinus surgery training.

PubMed

Awad, Zaid; Taghi, Ali; Sethukumar, Priya; Tolley, Neil S

2015-03-01

To demonstrate construct validity of the ovine model as a tool for training in endoscopic sinus surgery (ESS). Prospective, cross-sectional evaluation study. Over 18 consecutive months, trainees and experts were evaluated in their ability to perform a range of tasks (based on previous face validation and descriptive studies conducted by the same group) relating to ESS on the sheep-head model. Anonymized randomized video recordings of the above were assessed by two independent and blinded assessors. A validated assessment tool utilizing a five-point Likert scale was employed. Construct validity was calculated by comparing scores across training levels and experts using mean and interquartile range of global and task-specific scores. Subgroup analysis of the intermediate group ascertained previous experience. Nonparametric descriptive statistics were used, and analysis was carried out using SPSS version 21 (IBM, Armonk, NY). Reliability of the assessment tool was confirmed. The model discriminated well between different levels of expertise in global and task-specific scores. A positive correlation was noted between year in training and both global and task-specific scores (P < .001). Experience of the intermediate group was variable, and the number of ESS procedures performed under supervision had the highest impact on performance. This study describes an alternative model for ESS training and assessment. It is also the first to demonstrate construct validity of the sheep-head model for ESS training. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

An Analysis of Cross Racial Identity Scale Scores Using Classical Test Theory and Rasch Item Response Models

ERIC Educational Resources Information Center

Sussman, Joshua; Beaujean, A. Alexander; Worrell, Frank C.; Watson, Stevie

2013-01-01

Item response models (IRMs) were used to analyze Cross Racial Identity Scale (CRIS) scores. Rasch analysis scores were compared with classical test theory (CTT) scores. The partial credit model demonstrated a high goodness of fit and correlations between Rasch and CTT scores ranged from 0.91 to 0.99. CRIS scores are supported by both methods.…

Technical note: Combining quantile forecasts and predictive distributions of streamflows

NASA Astrophysics Data System (ADS)

Bogner, Konrad; Liechti, Katharina; Zappa, Massimiliano

2017-11-01

The enhanced availability of many different hydro-meteorological modelling and forecasting systems raises the issue of how to optimally combine this great deal of information. Especially the usage of deterministic and probabilistic forecasts with sometimes widely divergent predicted future streamflow values makes it even more complicated for decision makers to sift out the relevant information. In this study multiple streamflow forecast information will be aggregated based on several different predictive distributions, and quantile forecasts. For this combination the Bayesian model averaging (BMA) approach, the non-homogeneous Gaussian regression (NGR), also known as the ensemble model output statistic (EMOS) techniques, and a novel method called Beta-transformed linear pooling (BLP) will be applied. By the help of the quantile score (QS) and the continuous ranked probability score (CRPS), the combination results for the Sihl River in Switzerland with about 5 years of forecast data will be compared and the differences between the raw and optimally combined forecasts will be highlighted. The results demonstrate the importance of applying proper forecast combination methods for decision makers in the field of flood and water resource management.

Response to depression treatment in the Aging Brain Care Medical Home model.

PubMed

LaMantia, Michael A; Perkins, Anthony J; Gao, Sujuan; Austrom, Mary G; Alder, Cathy A; French, Dustin D; Litzelman, Debra K; Cottingham, Ann H; Boustani, Malaz A

2016-01-01

To evaluate the effect of the Aging Brain Care (ABC) Medical Home program's depression module on patients' depression severity measurement over time. Retrospective chart review. Public hospital system. Patients enrolled in the ABC Medical Home program between October 1, 2012 and March 31, 2014. The response of 773 enrolled patients who had multiple patient health questionnaire-9 (PHQ-9) scores recorded in the ABC Medical Home program's depression care protocol was evaluated. Repeatedly measured PHQ-9 change scores were the dependent variables in the mixed effects models, and demographic and comorbid medical conditions were tested as potential independent variables while including random effects for time and intercept. Among those patients with baseline PHQ-9 scores >10, there was a significant decrease in PHQ-9 scores over time ( P <0.001); however, the effect differed by gender ( P =0.015). On average, women's scores (4.5 point drop at 1 month) improved faster than men's scores (1 point drop at 1 month). Moreover, both men and women had a predicted drop of 7 points (>50% decline from baseline) on the PHQ-9 at 6 months. These analyses demonstrate evidence for the sustained effectiveness of the ABC Medical Home program at inducing depression remission outcomes while employing clinical staff who required less formal training than earlier clinical trials.

Better prognostic marker in ICU - APACHE II, SOFA or SAP II!

PubMed

Naqvi, Iftikhar Haider; Mahmood, Khalid; Ziaullaha, Syed; Kashif, Syed Mohammad; Sharif, Asim

2016-01-01

This study was designed to determine the comparative efficacy of different scoring system in assessing the prognosis of critically ill patients. This was a retrospective study conducted in medical intensive care unit (MICU) and high dependency unit (HDU) Medical Unit III, Civil Hospital, from April 2012 to August 2012. All patients over age 16 years old who have fulfilled the criteria for MICU admission were included. Predictive mortality of APACHE II, SAP II and SOFA were calculated. Calibration and discrimination were used for validity of each scoring model. A total of 96 patients with equal gender distribution were enrolled. The average APACHE II score in non-survivors (27.97+8.53) was higher than survivors (15.82+8.79) with statistically significant p value (<0.001). The average SOFA score in non-survivors (9.68+4.88) was higher than survivors (5.63+3.63) with statistically significant p value (<0.001). SAP II average score in non-survivors (53.71+19.05) was higher than survivors (30.18+16.24) with statistically significant p value (<0.001). All three tested scoring models (APACHE II, SAP II and SOFA) would be accurate enough for a general description of our ICU patients. APACHE II has showed better calibration and discrimination power than SAP II and SOFA.

Health Care Providers’ Support of Patients’ Autonomy, Phosphate Medication Adherence, Race and Gender in End Stage Renal Disease

PubMed Central

Umeukeje, Ebele; Merighi, J. R.; Browne, T.; Wild, M.; Alsmaan, H.; Umanath, K.; Lewis, J.; Wallston, K; Cavanaugh, K. L.

2016-01-01

This study was designed to assess dialysis subjects’ perceived autonomy support association with phosphate binder medication adherence, race and gender. A multi-site cross-sectional study was conducted among 377 dialysis subjects. The Health Care Climate (HCC) Questionnaire assessed subjects’ perception of their providers’ autonomy support for phosphate binder use, and adherence was assessed by the self-reported Morisky Medication Adherence Scale (MMAS). Serum phosphorus was obtained from the medical record. Regression models were used to examine independent factors of medication adherence, serum phosphorus, and differences by race and gender. Non-white HCC scores were consistently lower compared with white subjects’ scores. No differences were observed by gender. Reported phosphate binder adherence was associated with HCC score, and also with phosphorus control. No significant association was found between HCC score and serum phosphorus. Autonomy support, especially in non-white end stage renal disease subjects, may be an appropriate target for culturally informed strategies to optimize mineral bone health. PMID:27167227

Effects of Didactic Instruction and Test-Enhanced Learning in a Nursing Review Course.

PubMed

Tu, Yu-Ching; Lin, Yi-Jung; Lee, Jonathan W; Fan, Lir-Wan

2017-11-01

Determining the most effective approach for students' successful academic performance and achievement on the national licensure examination for RNs is important to nursing education and practice. A quasi-experimental design was used to compare didactic instruction and test-enhanced learning among nursing students divided into two fundamental nursing review courses in their final semester. Students in each course were subdivided into low-, intermediate-, and high-score groups based on their first examination scores. Mixed model of repeated measure and two-way analysis of variance were applied to evaluate students' academic results and both teaching approaches. Intermediate-scoring students' performances improved more through didactic instruction, whereas low-scoring students' performances improved more through test-enhanced learning. Each method had differing effects on individual subgroups within the different performance level groups of their classes, which points to the importance of considering both the didactic and test-enhanced learning approaches. [J Nurs Educ. 2017;56(11):683-687.]. Copyright 2017, SLACK Incorporated.

Formulary evaluation of third-generation cephalosporins using decision analysis.

PubMed

Cano, S B; Fujita, N K

1988-03-01

A structured, objective approach to formulary review of third-generation cephalosporins using the decision-analysis model is described. The pharmacy and therapeutics (P&T) committee approved the evaluation criteria for this drug class and assigned priority weights (as percentages of 100) to those drug characteristics deemed most important. Clinical data (spectrum of activity, pharmacokinetics, adverse effects, and stability) and financial data (cost of acquisition and cost of therapy per day) were used to determine ranking scores for each drug. Total scores were determined by multiplying ranking scores by the assigned priority weights for the criteria. The two highest-scoring drugs were selected for inclusion in the formulary. By this decision-analysis process, the P&T committee recommended that all current third-generation cephalosporins (cefotaxime, cefoperazone, and moxalactam) be removed from the institutions's formulary and be replaced with ceftazidime and ceftriaxone. P&T committees at other institutions may structure their criteria differently, and different recommendations may result. Using decision analysis for formulary review may promote rational drug therapy and achieve cost savings.

Self-affirmation model for football goal distributions

NASA Astrophysics Data System (ADS)

Bittner, E.; Nußbaumer, A.; Janke, W.; Weigel, M.

2007-06-01

Analyzing football score data with statistical techniques, we investigate how the highly co-operative nature of the game is reflected in averaged properties such as the distributions of scored goals for the home and away teams. It turns out that in particular the tails of the distributions are not well described by independent Bernoulli trials, but rather well modeled by negative binomial or generalized extreme value distributions. To understand this behavior from first principles, we suggest to modify the Bernoulli random process to include a simple component of self-affirmation which seems to describe the data surprisingly well and allows to interpret the observed deviation from Gaussian statistics. The phenomenological distributions used before can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments and found the proposed models to be applicable rather universally. In particular, here we compare men's and women's leagues and the separate German leagues during the cold war times and find some remarkable differences.

Measuring and Benchmarking Technical Efficiency of Public Hospitals in Tianjin, China

PubMed Central

Li, Hao; Dong, Siping

2015-01-01

China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application of this method for benchmarking and inter-organizational learning. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional Banker, Charnes, and Cooper (BCC) model, which means that Chinese researchers need to update their DEA models for more scientific calculation of hospital efficiency scores. Our research has helped shorten the gap between China and the international world in relative efficiency measurement and improvement of hospitals. It is suggested that Bootstrap-DEA be widely applied into afterward research to measure relative efficiency and productivity of Chinese hospitals so as to better serve for efficiency improvement and related decision making. PMID:26396090

Tests for detecting overdispersion in models with measurement error in covariates.

PubMed

Yang, Yingsi; Wong, Man Yu

2015-11-30

Measurement error in covariates can affect the accuracy in count data modeling and analysis. In overdispersion identification, the true mean-variance relationship can be obscured under the influence of measurement error in covariates. In this paper, we propose three tests for detecting overdispersion when covariates are measured with error: a modified score test and two score tests based on the proposed approximate likelihood and quasi-likelihood, respectively. The proposed approximate likelihood is derived under the classical measurement error model, and the resulting approximate maximum likelihood estimator is shown to have superior efficiency. Simulation results also show that the score test based on approximate likelihood outperforms the test based on quasi-likelihood and other alternatives in terms of empirical power. By analyzing a real dataset containing the health-related quality-of-life measurements of a particular group of patients, we demonstrate the importance of the proposed methods by showing that the analyses with and without measurement error correction yield significantly different results. Copyright © 2015 John Wiley & Sons, Ltd.

No-Reference Image Quality Assessment by Wide-Perceptual-Domain Scorer Ensemble Method.

PubMed

Liu, Tsung-Jung; Liu, Kuan-Hsien

2018-03-01

A no-reference (NR) learning-based approach to assess image quality is presented in this paper. The devised features are extracted from wide perceptual domains, including brightness, contrast, color, distortion, and texture. These features are used to train a model (scorer) which can predict scores. The scorer selection algorithms are utilized to help simplify the proposed system. In the final stage, the ensemble method is used to combine the prediction results from selected scorers. Two multiple-scale versions of the proposed approach are also presented along with the single-scale one. They turn out to have better performances than the original single-scale method. Because of having features from five different domains at multiple image scales and using the outputs (scores) from selected score prediction models as features for multi-scale or cross-scale fusion (i.e., ensemble), the proposed NR image quality assessment models are robust with respect to more than 24 image distortion types. They also can be used on the evaluation of images with authentic distortions. The extensive experiments on three well-known and representative databases confirm the performance robustness of our proposed model.

Self-Perceived Quality of Life Among Patients with Alzheimer's Disease: Two Longitudinal Models of Analysis.

PubMed

Conde-Sala, Josep L; Turró-Garriga, Oriol; Portellano-Ortiz, Cristina; Viñas-Diez, Vanesa; Gascón-Bayarri, Jordi; Reñé-Ramírez, Ramón

2016-04-12

The objective was to analyze the factors that influence self-perceived quality of life (QoL) in patients with Alzheimer's disease (AD), contrasting two different longitudinal models. A total of 127 patients were followed up over 24 months. The instruments applied were: Quality of Life in Alzheimer's Disease scale (QoL-AD), Geriatric Depression Scale-15, Anosognosia Questionnaire-Dementia, Disability Assessment in Dementia, Neuropsychiatric Inventory, and the Mini-Mental State Examination. Two models for grouping patients were tested: 1) Baseline score on the QoL-AD (QoL-Baseline), and 2) Difference in QoL-AD score between baseline and follow-up (QoL-Change). Generalized estimating equations were used to analyze longitudinal data, and multinomial regression analyses were performed. Over the follow-up period the QoL-Baseline model showed greater variability between groups (Wald χ2 = 172.3, p < 0.001) than did the QoL-Change model (Wald χ2  = 1.7, p = 0.427). In the QoL-Baseline model the predictive factors were greater depression (odds ratio [OR] = 1.20; 95% CI: 1.00- 1.45) and lower functional ability (OR = 0.92; 95% CI: 0.85- 0.99) for the Low QoL group (< 33 QoL-AD), and less depression (OR = 0.68; 95% CI: 0.52- 0.88), more anosognosia (OR = 1.07; 95% CI: 1.01- 1.13), and fewer neuropsychiatric symptoms (OR = 0.95; 95% CI: 0.91- 0.99) for the High-QoL group (>37 QoL-AD). The model based on baseline scores (QoL-Baseline) was better than the QoL-Change model in terms of identifying trajectories and predictors of QoL in AD.

The variability of software scoring of the CDMAM phantom associated with a limited number of images

NASA Astrophysics Data System (ADS)

Yang, Chang-Ying J.; Van Metter, Richard

2007-03-01

Software scoring approaches provide an attractive alternative to human evaluation of CDMAM images from digital mammography systems, particularly for annual quality control testing as recommended by the European Protocol for the Quality Control of the Physical and Technical Aspects of Mammography Screening (EPQCM). Methods for correlating CDCOM-based results with human observer performance have been proposed. A common feature of all methods is the use of a small number (at most eight) of CDMAM images to evaluate the system. This study focuses on the potential variability in the estimated system performance that is associated with these methods. Sets of 36 CDMAM images were acquired under carefully controlled conditions from three different digital mammography systems. The threshold visibility thickness (TVT) for each disk diameter was determined using previously reported post-analysis methods from the CDCOM scorings for a randomly selected group of eight images for one measurement trial. This random selection process was repeated 3000 times to estimate the variability in the resulting TVT values for each disk diameter. The results from using different post-analysis methods, different random selection strategies and different digital systems were compared. Additional variability of the 0.1 mm disk diameter was explored by comparing the results from two different image data sets acquired under the same conditions from the same system. The magnitude and the type of error estimated for experimental data was explained through modeling. The modeled results also suggest a limitation in the current phantom design for the 0.1 mm diameter disks. Through modeling, it was also found that, because of the binomial statistic nature of the CDMAM test, the true variability of the test could be underestimated by the commonly used method of random re-sampling.

Validation of the Lupus Nephritis Clinical Indices in Childhood-Onset Systemic Lupus Erythematosus

PubMed Central

Mina, Rina; Abulaban, Khalid; Klein-Gitelman, Marisa; Eberhard, Anne; Ardoin, Stacy; Singer, Nora; Onel, Karen; Tucker, Lori; O’Neil, Kathleen; Wright, Tracey; Brooks, Elizabeth; Rouster-Stevens, Kelly; Jung, Lawrence; Imundo, Lisa; Rovin, Brad; Witte, David; Ying, Jun; Brunner, Hermine I.

2015-01-01

Objective To validate clinical indices of lupus nephritis (LN) activity and damage when used in children against the criterion standard of kidney biopsy findings. Methods In 83 children requiring kidney biopsy the SLE Disease Activity Index Renal Domain (SLEDAI-R); British Isles Lupus Assessment Group index Renal Domain (BILAG-R), Systemic Lupus International Collaborating Clinics Renal Activity (SLICC-RAS) and Damage Index Renal Domain (SDI-R) were measured. Fixed effect and logistic models were done to predict International Society of Nephrology/Renal Pathology Society (ISN/RPS) class; low/moderate vs. high LN-activity [NIH Activity Index (NIH-AI) score: ≤ 10 vs. > 10; Tubulointerstitial Activity Index (TIAI) score: ≤ 5 vs. > 5) or the absence vs. presence of LN chronicity [NIH Chronicity Index (NIH-CI) score: 0 vs. ≥ 1]. Results There were 10, 50 and 23 patients with class I/II, III/IV and V, respectively. Scores of the clinical indices did not differentiate among patients by ISN/RPS class. The SLEDAI-R and SLICC-RAS but not the BILAG-R differed with LN-activity status defined by NIH-AI scores, while only the SLEDAI-R scores differed between LN-activity status based on TIAI scores. The sensitivity and specificity of the SDI-R to capture LN chronicity was 23.5% and 91.7%, respectively. Despite designed to measure LN-activity, SLICC-RAS and SLEDAI-R scores significantly differed with LN chronicity status. Conclusion Current clinical indices of LN fail to discriminate ISN/RPS Class in children. Despite its shortcomings, the SLEDAI-R appears to best for measuring LN activity in a clinical setting. The SDI-R is a poor correlate of LN chronicity. PMID:26213987

Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles.

PubMed

Bonny, S P F; Gardner, G E; Pethick, D W; Legrand, I; Polkinghorne, R J; Hocquette, J F

2015-01-01

The ability of the biochemical measurements, haem iron, intramuscular fat (IMF%), moisture content, and total, soluble and insoluble collagen contents, to predict untrained consumer sensory scores both across different muscles and within the same muscle from different carcasses were investigated. Sensory scores from 540 untrained French consumers (tenderness, flavour liking, juiciness and overall liking) were obtained for six muscles; outside (m. biceps femoris), topside (m. semimembranosus), striploin (m. longissimus thoracis), rump (m. gluteus medius), oyster blade (m. infraspinatus) and tenderloin (m. psoas major) from each of 18 French and 18 Australian cattle. The four sensory scores were weighted and combined into a single score termed MQ4, which was also analysed. All sensory scores were highly correlated with each other and with MQ4. This in part reflects the fact that MQ4 is derived from the consumer scores for tenderness, juiciness, flavour and overall liking and also reflects an interrelationship between the sensory scores themselves and in turn validates the use of the MQ4 term to reflect the scope of the consumer eating experience. When evaluated across the six different muscles, all biochemical measurements, except soluble collagen, had a significant effect on all of the sensory scores and MQ4. The average magnitude of impact of IMF%, haem iron, moisture content, total and insoluble collagen contents across the four different sensory scores are 34.9, 5.1, 7.2, 36.3 and 41.3, respectively. When evaluated within the same muscle, only IMF% and moisture content had a significant effect on overall liking (5.9 and 6.2, respectively) and flavour liking (6.1 and 6.4, respectively). These results indicate that in a commercial eating quality prediction model including muscle type, only IMF% or moisture content has the capacity to add any precision. However, all tested biochemical measurements, particularly IMF% and insoluble collagen contents, are strong predictors of eating quality when muscle type is not known. This demonstrates their potential usefulness in extrapolating the sensory data derived from these six muscles to other muscles with no sensory data, but with similar biochemical parameters, and therefore reducing the amount of future sensory testing required.

An approach to holistically assess (dairy) farm eco-efficiency by combining Life Cycle Analysis with Data Envelopment Analysis models and methodologies.

PubMed

Soteriades, A D; Faverdin, P; Moreau, S; Charroin, T; Blanchard, M; Stott, A W

2016-11-01

Eco-efficiency is a useful guide to dairy farm sustainability analysis aimed at increasing output (physical or value added) and minimizing environmental impacts (EIs). Widely used partial eco-efficiency ratios (EIs per some functional unit, e.g. kg milk) can be problematic because (i) substitution possibilities between EIs are ignored, (ii) multiple ratios can complicate decision making and (iii) EIs are not usually associated with just the functional unit in the ratio's denominator. The objective of this study was to demonstrate a 'global' eco-efficiency modelling framework dealing with issues (i) to (iii) by combining Life Cycle Analysis (LCA) data and the multiple-input, multiple-output production efficiency method Data Envelopment Analysis (DEA). With DEA each dairy farm's outputs and LCA-derived EIs are aggregated into a single, relative, bounded, dimensionless eco-efficiency score, thus overcoming issues (i) to (iii). A novelty of this study is that a model providing a number of additional desirable properties was employed, known as the Range Adjusted Measure (RAM) of inefficiency. These properties altogether make RAM advantageous over other DEA models and are as follows. First, RAM is able to simultaneously minimize EIs and maximize outputs. Second, it indicates which EIs and/or outputs contribute the most to a farm's eco-inefficiency. Third it can be used to rank farms in terms of eco-efficiency scores. Thus, non-parametric rank tests can be employed to test for significant differences in terms of eco-efficiency score ranks between different farm groups. An additional DEA methodology was employed to 'correct' the farms' eco-efficiency scores for inefficiencies attributed to managerial factors. By removing managerial inefficiencies it was possible to detect differences in eco-efficiency between farms solely attributed to uncontrollable factors such as region. Such analysis is lacking in previous dairy studies combining LCA with DEA. RAM and the 'corrective' methodology were demonstrated with LCA data from French specialized dairy farms grouped by region (West France, Continental France) and feeding strategy (regardless of region). Mean eco-efficiency score ranks were significantly higher for farms with 30% maize in the total forage area before correcting for managerial inefficiencies. Mean eco-efficiency score ranks were higher for West than Continental farms, but significantly higher only after correcting for managerial inefficiencies. These results helped identify the eco-efficiency potential of each region and feeding strategy and could therefore aid advisors and policy makers at farm or region/sector level. The proposed framework helped better measure and understand (dairy) farm eco-efficiency, both within and between different farm groups.

Rasch analysis of the Edmonton Symptom Assessment System and research implications

PubMed Central

Cheifetz, O.; Packham, T.L.; MacDermid, J.C.

2014-01-01

Background Reliable and valid assessment of the disease burden across all forms of cancer is critical to the evaluation of treatment effectiveness and patient progress. The Edmonton Symptom Assessment System (esas) is used for routine evaluation of people attending for cancer care. In the present study, we used Rasch analysis to explore the measurement properties of the esas and to determine the effect of using Rasch-proposed interval-level esas scoring compared with traditional scoring when evaluating the effects of an exercise program for cancer survivors. Methods Polytomous Rasch analysis (Andrich’s rating-scale model) was applied to data from 26,645 esas questionnaires completed at the Juravinski Cancer Centre. The fit of the esas to the polytomous Rasch model was investigated, including evaluations of differential item functioning for sex, age, and disease group. The research implication was investigated by comparing the results of an observational research study previously analysed using a traditional approach with the results obtained by Rasch-proposed interval-level esas scoring. Results The Rasch reliability index was 0.73, falling short of the desired 0.80–0.90 level. However, the esas was found to fit the Rasch model, including the criteria for uni-dimensional data. The analysis suggests that the current esas scoring system of 0–10 could be collapsed to a 6-point scale. Use of the Rasch-proposed interval-level scoring yielded results that were different from those calculated using summarized ordinal-level esas scores. Differential item functioning was not found for sex, age, or diagnosis groups. Conclusions The esas is a moderately reliable uni-dimensional measure of cancer disease burden and can provide interval-level scaling with Rasch-based scoring. Further, our study indicates that, compared with the traditional scoring metric, Rasch-based scoring could result in substantive changes to conclusions. PMID:24764703

A Milestone-Based Evaluation System-The Cure for Grade Inflation?

PubMed

Kuo, Lindsay E; Hoffman, Rebecca L; Morris, Jon B; Williams, Noel N; Malachesky, Mark; Huth, Laura E; Kelz, Rachel R

2015-01-01

Controversy exists over the optimal use of the Milestones in the process of resident evaluation and feedback. We sought to evaluate the performance of a Milestones-based feedback system in comparison to a traditional model. The traditional evaluation system (TES) consisted of a generic 16-item survey using a 5-point Likert scale ranging from 1 to 5, and a free-text comments section. The Milestones-based evaluation system (MBES) was launched in July 2014, ranging from 0 to 4. Individual milestones were mapped to rotations based on resident educational goals by postgraduate year (PGY). The MBES consisted of a survey with a maximum of 7 items, followed by a free-text comment section. Within each evaluation system, an overall composite score was calculated for each categorical general surgical resident. To scale the 2 systems for comparison, TES scores were adjusted downward by 1 point. Descriptive statistics were performed. Univariate analysis was performed with the Wilcoxon signed-rank test. A test for trend across PGY was used for the MBES only. In the traditional system, the median score was 3.66 (range: 3.2-4.0). There was no meaningful difference in the median score by PGY. In the new system, the median score was 2.69 (range: 1.5-3.7, p < 0.01). The median score differed across PGY and increased by PGY of training (p < 0.01). There was an increase in differences between median scores by PGY. On using the milestones to facilitate faculty evaluation of resident knowledge and skill, there was a trend in increasing score by PGY of training. In the MBES, scores could be used to better discriminate resident skill and knowledge levels and resulted in improved differentiation in scoring by PGY. The use of the milestones as a basis for evaluation enabled the program to provide more meaningful feedback to residents and represents an improvement in surgical education. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Evaluation of a health promoting schools program in a school board in Nova Scotia, Canada.

PubMed

McIsaac, Jessie-Lee D; Penney, Tarra L; Ata, Nicole; Munro-Sigfridson, Lori; Cunningham, Jane; Veugelers, Paul J; Storey, Kate; Ohinmaa, Arto; Kirk, Sara F L; Kuhle, Stefan

2017-03-01

A Health promoting schools (HPS) approach aims to make schools a healthy place through a holistic approach that promotes a supportive 'school ethos' and emphasizes improvements in physical, social, and emotional well-being and educational outcomes. A HPS initiative in rural Nova Scotia (Canada) provided an opportunity for a population-level natural experiment. This study investigated student well-being and health behaviours between schools with and without HPS implementation and schools with high and low school ethos scores. Student well-being, nutrition, and physical activity were examined in a cross-sectional survey of elementary students in Nova Scotia, Canada in 2014. Multiple regression was used to assess the relationship with student well-being using the Quality of Life in School (QoLS) instrument and health behaviours. The main exposure was attending one of the 10 HPS schools; secondary exposure was the school ethos score. The overall QoLS score and its subdomain scores in the adjusted models were higher in students attending HPS schools compared to those in non-HPS schools, but the differences were not statistically significant and the effect sizes were small. Students in schools that scored high on school ethos score had higher scores for the QoLS and its subdomains, but the difference was only significant for the teacher-student relationship domain. Although this study did not find significant differences between HPS and non-HPS schools, our results highlight the complexity of evaluating HPS effects in the real world. The findings suggest a potential role of a supportive school ethos for student well-being in school.

Students' perception of the psycho-social clinical learning environment: an evaluation of placement models.

PubMed

Henderson, Amanda; Twentyman, Michelle; Heel, Alison; Lloyd, Belinda

2006-10-01

Nursing is a practice based discipline. A supportive environment has been identified as important for the transfer of learning in the clinical context. The aim of the paper was to assess undergraduate nurses' perceptions of the psychosocial characteristics of clinical learning environments within three different clinical placement models. Three hundred and eight-nine undergraduate nursing students rated their perceptions of the psycho-social learning environment using a Clinical Learning Environment Inventory. There were 16 respondents in the Preceptor model category, 269 respondents in the Facilitation model category and 114 respondents in the clinical education unit model across 25 different clinical areas in one tertiary facility. The most positive social climate was associated with the preceptor model. On all subscales the median score was rated higher than the two other models. When clinical education units were compared with the standard facilitation model the median score was rated higher in all of the subscales in the Clinical Learning Environment Inventory. These results suggest that while preceptoring is an effective clinical placement strategy that provides psycho-social support for students, clinical education units that are more sustainable through their placement of greater numbers of students, can provide greater psycho-social support for students than traditional models.

[Effect of Electroacupuncture at "Neiguan" (PC 6) and "Tianshu" (ST 25) for Colonic Motility and D 2 Receptor in Irritable Bowel Syndrome Rats].

PubMed

Wang, Shan; Guo, Meng-Wei; Gao, Yu-Shan; Ren, Xiao-Xuan; Lan, Ying; Ji, Mao-Xian; Wu, Yan-Ying; Li, Kai-Ge; Tan, Li-Hua; Sui, Ming-He

2018-01-25

To observe and compare the effects of electroacupuncture (EA) at "Tianshu" (ST 25) and "Neiguan" (PC 6) for colonic motility and the expression of colon dopamine D 2 in irritable bowel syndrome (IBS) rats, and to explore the specificity of different meridians and different acupoints. Forty Wistar newborn rats were randomly divided into blank, model, Tianshu and Neiguan groups. Separation of mother and child and acetic acid coloclyster combined with colorectal distension were used to establish IBS model in the model, Tianshu and Neiguan groups. At the age of 9 weeks, EA at bilateral ST 25 and PC 6 were applied in the corresponding groups 5 times, once every other day. After the intervention, the Bristol fecal score, the latent period of abdominal retraction reflex and the number of contraction waves were recorded. The expression of dopamine D 2 receptor was detected by immunohistochemistry. Compared with the blank group, the Bristol fecal score of the model group was higher ( P <0.01), the 1 st contraction wave latent period was shorter ( P <0.01), the number of contraction waves in 90 s increased ( P <0.01), the immunoreactive expression of D 2 receptor in colon decreased ( P <0.01). Compared with the model group, the Bristol fecal scores of the Tianshu and Neiguan groups decreased ( P <0.01), the 1 st contraction wave latent periods were longer ( P <0.01), the numbers of contraction waves in 90 s decreased ( P <0.01), the positive expressions of D 2 receptor in colon increased ( P <0.01, P <0.05). Compared with the Tianshu group, the immunoreactive expression of D 2 receptor in the Neiguan group decreased ( P <0.01). EA at ST 25 and PC 6 can improve the symptoms of colonic motility in IBS rats. The effect of EA at ST 25 is better, which indicates that different meridians and different acupoints play specific effects.

Methods for Constructing and Assessing Propensity Scores

PubMed Central

Garrido, Melissa M; Kelley, Amy S; Paris, Julia; Roza, Katherine; Meier, Diane E; Morrison, R Sean; Aldridge, Melissa D

2014-01-01

Objectives To model the steps involved in preparing for and carrying out propensity score analyses by providing step-by-step guidance and Stata code applied to an empirical dataset. Study Design Guidance, Stata code, and empirical examples are given to illustrate (1) the process of choosing variables to include in the propensity score; (2) balance of propensity score across treatment and comparison groups; (3) balance of covariates across treatment and comparison groups within blocks of the propensity score; (4) choice of matching and weighting strategies; (5) balance of covariates after matching or weighting the sample; and (6) interpretation of treatment effect estimates. Empirical Application We use data from the Palliative Care for Cancer Patients (PC4C) study, a multisite observational study of the effect of inpatient palliative care on patient health outcomes and health services use, to illustrate the development and use of a propensity score. Conclusions Propensity scores are one useful tool for accounting for observed differences between treated and comparison groups. Careful testing of propensity scores is required before using them to estimate treatment effects. PMID:24779867

An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma.

PubMed

Burden, Anne; Roche, Nicolas; Miglio, Cristiana; Hillyer, Elizabeth V; Postma, Dirkje S; Herings, Ron Mc; Overbeek, Jetty A; Khalid, Javaria Mona; van Eickels, Daniela; Price, David B

2017-01-01

Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment. We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of <10% between cohorts. Of 4064 eligible patients, 1382 (34%) were prescribed ciclesonide and 2682 (66%) fine-particle ICS. The IPTW and propensity score-based methods retained more patients (96%-100%) than exact matching (90%); exact matching selected less severe patients. Standardized differences were >10% for four variables in the exact-matched dataset and <10% for both PSM algorithms and the weighted pseudo-dataset used in the IPTW method. With all methods, ciclesonide was associated with better 1-year asthma-related outcomes, at one-third the prescribed dose, than fine-particle ICS; results varied slightly by method, but direction and statistical significance remained the same. We found that each method has its particular strengths, and we recommend at least two methods be applied for each matched cohort study to evaluate the robustness of the findings. Balance diagnostics should be applied with all methods to check the balance of confounders between treatment cohorts. If exact matching is used, the calculation of a propensity score could be useful to identify variables that require balancing, thereby informing the choice of matching criteria together with clinical considerations.

An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma

PubMed Central

Burden, Anne; Roche, Nicolas; Miglio, Cristiana; Hillyer, Elizabeth V; Postma, Dirkje S; Herings, Ron MC; Overbeek, Jetty A; Khalid, Javaria Mona; van Eickels, Daniela; Price, David B

2017-01-01

Background Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre–post historical database study to investigate asthma-related outcomes by treatment. Methods We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of <10% between cohorts. Results Of 4064 eligible patients, 1382 (34%) were prescribed ciclesonide and 2682 (66%) fine-particle ICS. The IPTW and propensity score-based methods retained more patients (96%–100%) than exact matching (90%); exact matching selected less severe patients. Standardized differences were >10% for four variables in the exact-matched dataset and <10% for both PSM algorithms and the weighted pseudo-dataset used in the IPTW method. With all methods, ciclesonide was associated with better 1-year asthma-related outcomes, at one-third the prescribed dose, than fine-particle ICS; results varied slightly by method, but direction and statistical significance remained the same. Conclusion We found that each method has its particular strengths, and we recommend at least two methods be applied for each matched cohort study to evaluate the robustness of the findings. Balance diagnostics should be applied with all methods to check the balance of confounders between treatment cohorts. If exact matching is used, the calculation of a propensity score could be useful to identify variables that require balancing, thereby informing the choice of matching criteria together with clinical considerations. PMID:28356782

Macroscopic cartilage repair scoring of defect fill, integration and total points correlate with corresponding items in histological scoring systems - a study in adult sheep.

PubMed

Goebel, L; Orth, P; Cucchiarini, M; Pape, D; Madry, H

2017-04-01

To correlate osteochondral repair assessed by validated macroscopic scoring systems with established semiquantitative histological analyses in an ovine model and to test the hypothesis that important macroscopic individual categories correlate with their corresponding histological counterparts. In the weight-bearing portion of medial femoral condyles (n = 38) of 19 female adult Merino sheep (age 2-4 years; weight 70 ± 20 kg) full-thickness chondral defects were created (size 4 × 8 mm; International Cartilage Repair Society (ICRS) grade 3C) and treated with Pridie drilling. After sacrifice, 1520 blinded macroscopic observations from three observers at 2-3 time points including five different macroscopic scoring systems demonstrating all grades of cartilage repair where correlated with corresponding categories from 418 blinded histological sections. Categories "defect fill" and "total points" of different macroscopic scoring systems correlated well with their histological counterparts from the Wakitani and Sellers scores (all P ≤ 0.001). "Integration" was assessed in both histological scoring systems and in the macroscopic ICRS, Oswestry and Jung scores. Here, a significant relationship always existed (0.020 ≤ P ≤ 0.049), except for Wakitani and Oswestry (P = 0.054). No relationship was observed for the "surface" between histology and macroscopy (all P > 0.05). Major individual morphological categories "defect fill" and "integration", and "total points" of macroscopic scoring systems correlate with their corresponding categories in elementary and complex histological scoring systems. Thus, macroscopy allows to precisely predict key histological aspects of articular cartilage repair, underlining the specific value of macroscopic scoring for examining cartilage repair. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Poster — Thur Eve — 45: Comparison of different Monte Carlo methods of scoring linear energy transfer in modulated proton therapy beams

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

Granville, DA; Sawakuchi, GO

2014-08-15

In this work, we demonstrate inconsistencies in commonly used Monte Carlo methods of scoring linear energy transfer (LET) in proton therapy beams. In particle therapy beams, the LET is an important parameter because the relative biological effectiveness (RBE) depends on it. LET is often determined using Monte Carlo techniques. We used a realistic Monte Carlo model of a proton therapy nozzle to score proton LET in spread-out Bragg peak (SOBP) depth-dose distributions. We used three different scoring and calculation techniques to determine average LET at varying depths within a 140 MeV beam with a 4 cm SOBP and a 250more » MeV beam with a 10 cm SOBP. These techniques included fluence-weighted (Φ-LET) and dose-weighted average (D-LET) LET calculations from: 1) scored energy spectra converted to LET spectra through a lookup table, 2) directly scored LET spectra and 3) accumulated LET scored ‘on-the-fly’ during simulations. All protons (primary and secondary) were included in the scoring. Φ-LET was found to be less sensitive to changes in scoring technique than D-LET. In addition, the spectral scoring methods were sensitive to low-energy (high-LET) cutoff values in the averaging. Using cutoff parameters chosen carefully for consistency between techniques, we found variations in Φ-LET values of up to 1.6% and variations in D-LET values of up to 11.2% for the same irradiation conditions, depending on the method used to score LET. Variations were largest near the end of the SOBP, where the LET and energy spectra are broader.« less

Role of a computer-generated three-dimensional laryngeal model in anatomy teaching for advanced learners.

PubMed

Tan, S; Hu, A; Wilson, T; Ladak, H; Haase, P; Fung, K

2012-04-01

(1) To investigate the efficacy of a computer-generated three-dimensional laryngeal model for laryngeal anatomy teaching; (2) to explore the relationship between students' spatial ability and acquisition of anatomical knowledge; and (3) to assess participants' opinion of the computerised model. Forty junior doctors were randomised to undertake laryngeal anatomy study supplemented by either a three-dimensional computer model or two-dimensional images. Outcome measurements comprised a laryngeal anatomy test, the modified Vandenberg and Kuse mental rotation test, and an opinion survey. Mean scores ± standard deviations for the anatomy test were 15.7 ± 2.0 for the 'three dimensions' group and 15.5 ± 2.3 for the 'standard' group (p = 0.7222). Pearson's correlation between the rotation test scores and the scores for the spatial ability questions in the anatomy test was 0.4791 (p = 0.086, n = 29). Opinion survey answers revealed significant differences in respondents' perceptions of the clarity and 'user friendliness' of, and their preferences for, the three-dimensional model as regards anatomical study. The three-dimensional computer model was equivalent to standard two-dimensional images, for the purpose of laryngeal anatomy teaching. There was no association between students' spatial ability and functional anatomy learning. However, students preferred to use the three-dimensional model.

A comparison of MRI and CT imaging clarity of titanium alloy and titanium alloy with cobalt-chromium-alloy pedicle screw and rod implants in the lumbar spine.

PubMed

Trammell, Terry R; Flint, Kathy; Ramsey, Curtis J

2012-08-15

Magnetic resonance imaging (MRI) and computed tomography (CT) imaging are important postoperative diagnostic and evaluation tools, particularly in patients who have undergone spinal fusions. Advancements in materials and imaging techniques have lessened artifact and improved overall imaging results. Systems that combine titanium alloy and cobalt-chromium components have been introduced to reduce implant profile while maintaining strength. The objective of this study was to determine if there were any differences in the clarity of imaging between two types of implant materials in a lumbar spine construct model. One of two lumbar spine stabilization implant systems, titanium alloy (titanium) or titanium alloy with cobalt-chromium alloy (titanium-cobalt), was placed to simulate a four-level fusion construct in two human cadaveric spine segments, followed by MRI and CT imaging. The implant systems were then removed from each cadaver and implanted in the other cadaver. Nine physician graders from three subspecialties scored the images using a 5-point scale, with higher imaging scores indicating greater clarity of the region of interest. Physician-rated scores were compared across systems and between physician groups. There were no significant differences in the overall mean total scores on the basis of construct material. Overall mean scores were 18.16 for titanium and 17.45 for titanium-cobalt (p = 0.275). Among images of the titanium-cobalt constructs, no significant differences in mean scores were found between specimens with use of MRI (p = 0.883) or with use of CT only (p = 0.274). Among images of the titanium system, a slightly significant difference was found between specimens with use of MRI (p = 0.044) but not with CT imaging (p = 0.837). Overall image clarity scores were not significantly different between titanium and titanium-cobalt implant systems in the lumbar spine. Observation of pertinent anatomy in the regions of interest was not degraded by the presence of either system.

A comprehensive subaxial cervical spine injury severity assessment model using numeric scores and its predictive value for surgical intervention.

PubMed

Tsou, Paul M; Daffner, Scott D; Holly, Langston T; Shamie, A Nick; Wang, Jeffrey C

2012-02-10

Multiple factors contribute to the determination for surgical intervention in the setting of cervical spinal injury, yet to date no unified classification system exists that predicts this need. The goals of this study were twofold: to create a comprehensive subaxial cervical spine injury severity numeric scoring model, and to determine the predictive value of this model for the probability of surgical intervention. In a retrospective cohort study of 333 patients, neural impairment, patho-morphology, and available spinal canal sagittal diameter post-injury were selected as injury severity determinants. A common numeric scoring trend was created; smaller values indicated less favorable clinical conditions. Neural impairment was graded from 2-10, patho-morphology scoring ranged from 2-15, and post-injury available canal sagittal diameter (SD) was measured in millimeters at the narrowest point of injury. Logistic regression analysis was performed using the numeric scores to predict the probability for surgical intervention. Complete neurologic deficit was found in 39 patients, partial deficits in 108, root injuries in 19, and 167 were neurologically intact. The pre-injury mean canal SD was 14.6 mm; the post-injury measurement mean was 12.3 mm. The mean patho-morphology score for all patients was 10.9 and the mean neurologic function score was 7.6. There was a statistically significant difference in mean scores for neural impairment, canal SD, and patho-morphology for surgical compared to nonsurgical patients. At the lowest clinical score for each determinant, the probability for surgery was 0.949 for neural impairment, 0.989 for post-injury available canal SD, and 0.971 for patho-morphology. The unit odds ratio for each determinant was 1.73, 1.61, and 1.45, for neural impairment, patho-morphology, and canal SD scores, respectively. The subaxial cervical spine injury severity determinants of neural impairment, patho-morphology, and post-injury available canal SD have well defined probability for surgical intervention when scored separately. Our data showed that each determinant alone could act as a primary predictor for surgical intervention.

Border Bicultural Personality Traits: Surprising Gender Findings among Mexican American Undergraduates

ERIC Educational Resources Information Center

Chavez, Mary R.; Rudolph, Bonnie A.

2007-01-01

Personality traits of 178 Mexican American college students were surveyed to test applicability of the Five Factor Model of personality and to investigate gender differences within this bicultural group. Results revealed atypical gender differences on neuroticism. Men scored significantly higher than did women, which is opposite cross-cultural…

The Case of Public Schools in Argentina

ERIC Educational Resources Information Center

Adrogue, Cecilia; Orlicki, Maria Eugenia

2013-01-01

As Argentina presents problems of malnutrition, the federal in-school feeding program has become a key policy because it provides an important nutritional intervention during a relevant growth period. This paper estimates the effect of the program on academic performance--measured by standardized test scores--with a difference in difference model,…

High Stakes Tests with Self-Selected Essay Questions: Addressing Issues of Fairness

ERIC Educational Resources Information Center

Lamprianou, Iasonas

2008-01-01

This study investigates the effect of reporting the unadjusted raw scores in a high-stakes language exam when raters differ significantly in severity and self-selected questions differ significantly in difficulty. More sophisticated models, introducing meaningful facets and parameters, are successively used to investigate the characteristics of…

Differences in BMI z-Scores between Offspring of Smoking and Nonsmoking Mothers: A Longitudinal Study of German Children from Birth through 14 Years of Age

PubMed Central

Fenske, Nora; Müller, Manfred J.; Plachta-Danielzik, Sandra; Keil, Thomas; Grabenhenrich, Linus; von Kries, Rüdiger

2014-01-01

Background: Children of mothers who smoked during pregnancy have a lower birth weight but have a higher chance to become overweight during childhood. Objectives: We followed children longitudinally to assess the age when higher body mass index (BMI) z-scores became evident in the children of mothers who smoked during pregnancy, and to evaluate the trajectory of changes until adolescence. Methods: We pooled data from two German cohort studies that included repeated anthropometric measurements until 14 years of age and information on smoking during pregnancy and other risk factors for overweight. We used longitudinal quantile regression to estimate age- and sex-specific associations between maternal smoking and the 10th, 25th, 50th, 75th, and 90th quantiles of the BMI z-score distribution in study participants from birth through 14 years of age, adjusted for potential confounders. We used additive mixed models to estimate associations with mean BMI z-scores. Results: Mean and median (50th quantile) BMI z-scores at birth were smaller in the children of mothers who smoked during pregnancy compared with children of nonsmoking mothers, but BMI z-scores were significantly associated with maternal smoking beginning at the age of 4–5 years, and differences increased over time. For example, the difference in the median BMI z-score between the daughters of smokers versus nonsmokers was 0.12 (95% CI: 0.01, 0.21) at 5 years, and 0.30 (95% CI: 0.08, 0.39) at 14 years of age. For lower BMI z-score quantiles, the association with smoking was more pronounced in girls, whereas in boys the association was more pronounced for higher BMI z-score quantiles. Conclusions: A clear difference in BMI z-score (mean and median) between children of smoking and nonsmoking mothers emerged at 4–5 years of age. The shape and size of age-specific effect estimates for maternal smoking during pregnancy varied by age and sex across the BMI z-score distribution. Citation: Riedel C, Fenske N, Müller MJ, Plachta-Danielzik S, Keil T, Grabenhenrich L, von Kries R. 2014. Differences in BMI z-scores between offspring of smoking and nonsmoking mothers: a longitudinal study of German children from birth through 14 years of age. Environ Health Perspect 122:761–767; http://dx.doi.org/10.1289/ehp.1307139 PMID:24695368

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

PubMed Central

Eddy, Sean R.

2008-01-01

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments. PMID:18516236

General Models for Automated Essay Scoring: Exploring an Alternative to the Status Quo

ERIC Educational Resources Information Center

Kelly, P. Adam

2005-01-01

Powers, Burstein, Chodorow, Fowles, and Kukich (2002) suggested that automated essay scoring (AES) may benefit from the use of "general" scoring models designed to score essays irrespective of the prompt for which an essay was written. They reasoned that such models may enhance score credibility by signifying that an AES system measures the same…

Computerized measurement of facial expression of emotions in schizophrenia.

PubMed

Alvino, Christopher; Kohler, Christian; Barrett, Frederick; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

2007-07-30

Deficits in the ability to express emotions characterize several neuropsychiatric disorders and are a hallmark of schizophrenia, and there is need for a method of quantifying expression, which is currently done by clinical ratings. This paper presents the development and validation of a computational framework for quantifying emotional expression differences between patients with schizophrenia and healthy controls. Each face is modeled as a combination of elastic regions, and expression changes are modeled as a deformation between a neutral face and an expressive face. Functions of these deformations, known as the regional volumetric difference (RVD) functions, form distinctive quantitative profiles of expressions. Employing pattern classification techniques, we have designed expression classifiers for the four universal emotions of happiness, sadness, anger and fear by training on RVD functions of expression changes. The classifiers were cross-validated and then applied to facial expression images of patients with schizophrenia and healthy controls. The classification score for each image reflects the extent to which the expressed emotion matches the intended emotion. Group-wise statistical analysis revealed this score to be significantly different between healthy controls and patients, especially in the case of anger. This score correlated with clinical severity of flat affect. These results encourage the use of such deformation based expression quantification measures for research in clinical applications that require the automated measurement of facial affect.

Case-mix adjustment of consumer reports about managed behavioral health care and health plans.

PubMed

Eselius, Laura L; Cleary, Paul D; Zaslavsky, Alan M; Huskamp, Haiden A; Busch, Susan H

2008-12-01

To develop a model for adjusting patients' reports of behavioral health care experiences on the Experience of Care and Health Outcomes (ECHO) survey to allow for fair comparisons across health plans. Survey responses from 4,068 individuals enrolled in 21 managed behavioral health plans who received behavioral health care within the previous year (response rate = 48 percent). Potential case-mix adjustors were evaluated by combining information about their predictive power and the amount of within- and between-plan variability. Changes in plan scores and rankings due to case-mix adjustment were quantified. The final case-mix adjustment model included self-reported mental health status, self-reported general health status, alcohol/drug treatment, age, education, and race/ethnicity. The impact of adjustment on plan report scores was modest, but large enough to change some plan rankings. Adjusting plan report scores on the ECHO survey for differences in patient characteristics had modest effects, but still may be important to maintain the credibility of patient reports as a quality metric. Differences between those with self-reported fair/poor health compared with those in excellent/very good health varied by plan, suggesting quality differences associated with health status and underscoring the importance of collecting quality information.

Age versus schooling effects on intelligence development.

PubMed

Cahan, S; Cohen, N

1989-10-01

The effect of formal education, as opposed to chronological age, on intelligence development has suffered from inadequate empirical investigation. Most studies of this issue have relied on natural variation in exposure to school among children of the same age, thus confounding differences in schooling with differences in other intelligence-related variables. This difficulty can be overcome by a quasi-experimental paradigm involving comparison between children who differ in both chronological age and schooling. The present study applies this paradigm to the estimation of the independent effects of age and schooling in grades 5 and 6 on raw scores obtained on a variety of general ability tests. The sample included all students in Jerusalem's Hebrew-language, state-controlled elementary schools. The results unambiguously point to schooling as the major factor underlying the increase of intelligence test scores as a function of age and to the larger effect schooling has on verbal than nonverbal tests. These results contribute to our understanding of the causal model underlying intelligence development and call for reconsideration of the conceptual basis underlying the definition of deviation-IQ scores. Some implications of these results concerning the distinction between intelligence and scholastic achievement, the causal model underlying the development of "crystallized" and "fluid" abilities, and the notion of "culture-fair" tests are discussed.

Admission glucose does not improve GRACE score at 6 months and 5 years after myocardial infarction.

PubMed

de Mulder, Maarten; van der Ploeg, Tjeerd; de Waard, Guus A; Boersma, Eric; Umans, Victor A

2011-01-01

Admission plasma glucose (APG) is a biomarker that predicts mortality in myocardial infarction (MI) patients. Therefore, APG may improve risk stratification based on the GRACE risk score. We collected data on baseline characteristics and long-term (median 55 months) outcome of 550 MI patients who entered our hospital in 2003 and 2006. We determined the GRACE risk score at admission for each patient, which was entered in a logistic regression model, together with APG, to evaluate their prognostic value for 6-month and 5-year mortality. Patients with APG ≥7.8 mmol/l had a higher mortality than those with APG levels <7.8 mmol/l; 6 months: 13.7 versus 3.6%, p value <0.001; 5 years: 20.4 versus 11.1%, p value 0.003. After adjustment for the GRACE risk score variables, APG appeared a significant predictor of 6-month and 5-year mortality, adjusted OR 1.17 (1.06-1.29) and 1.12 (1.03-1.22). The combination of the GRACE risk score and APG increased the model's performance (discrimination C-index 0.87 vs. 0.85), although the difference was not significant (p = 0.095). Combining the GRACE risk score and APG reclassified 12.9% of the patients, but the net reclassification improvement was nonsignificant (p = 0.146). APG is a predictor of 6-month and 5-year mortality, each mmol/l increase in APG being associated with a mortality increase of 17 and 12%, respectively, independent of the GRACE risk score. However, adding APG to the GRACE model did not result in significantly improved clinical risk stratification. Copyright © 2012 S. Karger AG, Basel.

Ideal cardiovascular health score at the ELSA-Brasil baseline and its association with sociodemographic characteristics.

PubMed

Machado, Lucas B M; Silva, Bianca L S; Garcia, Ana P; Oliveira, Renata A M; Barreto, Sandhi M; Fonseca, Maria de Jesus M; Lotufo, Paulo A; Bensenor, Isabela M; Santos, Itamar S

2018-03-01

The American Heart Association's ideal cardiovascular health (ICH) define criteria for seven metrics, four classified as lifestyle factors (diet, physical activity, smoking and body-mass index) and four classified as health factors (smoking, blood pressure, fasting plasma glucose and total cholesterol). We aimed to analyze ICH scores at the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline assessment and the associations with sociodemographic characteristics (age, sex, race, educational level, and family income). We analyzed 13,356 ELSA-Brasil participants without cardiovascular disease using quasi-Poisson regression models to study the association between the ICH score and sociodemographic characteristics. Mean ICH scores were 2.5±1.3. Only 1047 (7.8%) participants had 5 or more ICH metrics. In adjusted models, age 65-74years was associated with lower ICH scores (-35.4%; 95% confidence interval [CI]: -37.6% to -33.1%) compared to age 35-44years. Women had higher ICH scores compared to men (+13.8%; 95%CI: +11.8% to +15.7%), mainly due to differences in the health factor ICH metrics. Participants of Black race had lower ICH scores compared to those of White race (-9.4%; 95%CI: -11.8% to -7.0%). Individuals with less than high school education had lower ICH scores than college-educated individuals (-17.2%; 95%CI: -20.0% to -14.2%). Low (<1245 USD) family income was also associated with lower ICH scores compared to those with high (≥3320 USD) family income (-4.4%, 95%CI: -7.2% to -1.6%). We found a low proportion of individuals with 5 or more ICH metrics. Age, sex, race, educational level and income were associated with ICH scores. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Cognition in patients with burn injury in the inpatient rehabilitation population.

PubMed

Purohit, Maulik; Goldstein, Richard; Nadler, Deborah; Mathews, Katie; Slocum, Chloe; Gerrard, Paul; DiVita, Margaret A; Ryan, Colleen M; Zafonte, Ross; Kowalske, Karen; Schneider, Jeffrey C

2014-07-01

To analyze potential cognitive impairment in patients with burn injury in the inpatient rehabilitation population. Rehabilitation patients with burn injury were compared with the following impairment groups: spinal cord injury, amputation, polytrauma and multiple fractures, and hip replacement. Differences between the groups were calculated for each cognitive subscale item and total cognitive FIM. Patients with burn injury were compared with the other groups using a bivariate linear regression model. A multivariable linear regression model was used to determine whether differences in cognition existed after adjusting for covariates (eg, sociodemographic factors, facility factors, medical complications) based on previous studies. Inpatient rehabilitation facilities. Data from Uniform Data System for Medical Rehabilitation from 2002 to 2011 for adults with burn injury (N=5347) were compared with other rehabilitation populations (N=668,816). Not applicable. Comparison of total cognitive FIM scores and subscales (memory, verbal comprehension, verbal expression, social interaction, problem solving) for patients with burn injury versus other rehabilitation populations. Adults with burn injuries had an average total cognitive FIM score ± SD of 26.8±7.0 compared with an average FIM score ± SD of 28.7±6.0 for the other groups combined (P<.001). The subscale with the greatest difference between those with burn injury and the other groups was memory (5.1±1.7 compared with 5.6±1.5, P<.001). These differences persisted after adjustment for covariates. Adults with burn injury have worse cognitive FIM scores than other rehabilitation populations. Future research is needed to determine the impact of this comorbidity on patient outcomes and potential interventions for these deficits. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Assessment of prognostic performance of Albumin-Bilirubin, Child-Pugh, and Model for End-stage Liver Disease scores in patients with liver cirrhosis complicated with acute upper gastrointestinal bleeding.

PubMed

Xavier, Sofia A; Vilas-Boas, Ricardo; Boal Carvalho, Pedro; Magalhães, Joana T; Marinho, Carla M; Cotter, José B

2018-06-01

The Albumin-Bilirubin (ALBI) score was developed recently to assess the severity of liver dysfunction. We aimed to assess its prognostic performance in patients with liver cirrhosis complicated with upper gastrointestinal bleeding (UGIB) while comparing it with Child-Pugh (CP) and Model for End-stage Liver Disease (MELD) scores. This was a retrospective unicentric study, including consecutive adult patients with cirrhosis admitted for UGIB between January 2011 and November 2015. Clinical, analytical, and endoscopic variables were assessed and ALBI, CP, and MELD scores at admission were calculated. This study included 111 patients. During the first 30 days of follow-up, 12 (10.8%) patients died, and during the first year of follow-up, another 10 patients died (first-year mortality of 19.8%).On comparing the three scores, for in-stay and 30-day mortality, only the ALBI score showed statistically significant results, with an area under the curve (AUC) of 0.80 (P<0.01) for both outcomes. For first-year mortality, AUC for ALBI, CP, and MELD scores were 0.71 (P<0.01), 0.64 (P<0.05), and 0.66 (P=0.02), respectively, whereas for global mortality, AUC were 0.75 (P<0.01), 0.72 (P<0.01), and 0.72 (P<0.01), respectively. On comparing the AUC of the three scores, no significant differences were found in first-year mortality and global mortality. In our series, the ALBI score accurately predicted both in-stay and 30-day mortality, whereas CP and MELD scores could not predict these outcomes. All scores showed a fair prognostic prediction performance for first-year and global mortality. These results suggest that the ALBI score is particularly useful in the assessment of short-term outcomes, with a better performance than the most commonly used scores.