A local equation for differential diagnosis of β-thalassemia trait and iron deficiency anemia by logistic regression analysis in Southeast Iran.

PubMed

Sargolzaie, Narjes; Miri-Moghaddam, Ebrahim

2014-01-01

The most common differential diagnosis of β-thalassemia (β-thal) trait is iron deficiency anemia. Several red blood cell equations were introduced during different studies for differential diagnosis between β-thal trait and iron deficiency anemia. Due to genetic variations in different regions, these equations cannot be useful in all population. The aim of this study was to determine a native equation with high accuracy for differential diagnosis of β-thal trait and iron deficiency anemia for the Sistan and Baluchestan population by logistic regression analysis. We selected 77 iron deficiency anemia and 100 β-thal trait cases. We used binary logistic regression analysis and determined best equations for probability prediction of β-thal trait against iron deficiency anemia in our population. We compared diagnostic values and receiver operative characteristic (ROC) curve related to this equation and another 10 published equations in discriminating β-thal trait and iron deficiency anemia. The binary logistic regression analysis determined the best equation for best probability prediction of β-thal trait against iron deficiency anemia with area under curve (AUC) 0.998. Based on ROC curves and AUC, Green & King, England & Frazer, and then Sirdah indices, respectively, had the most accuracy after our equation. We suggest that to get the best equation and cut-off in each region, one needs to evaluate specific information of each region, specifically in areas where populations are homogeneous, to provide a specific formula for differentiating between β-thal trait and iron deficiency anemia.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

Odds Ratio, Delta, ETS Classification, and Standardization Measures of DIF Magnitude for Binary Logistic Regression

ERIC Educational Resources Information Center

Monahan, Patrick O.; McHorney, Colleen A.; Stump, Timothy E.; Perkins, Anthony J.

2007-01-01

Previous methodological and applied studies that used binary logistic regression (LR) for detection of differential item functioning (DIF) in dichotomously scored items either did not report an effect size or did not employ several useful measures of DIF magnitude derived from the LR model. Equations are provided for these effect size indices.…

Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Alias, Siti Nor Shadila

2014-07-01

For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..

Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use among Students

ERIC Educational Resources Information Center

Merianos, Ashley L.; Rosen, Brittany L.; Montgomery, LaTrice; Barry, Adam E.; Smith, Matthew Lee

2017-01-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data (N=937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime…

Modelling Status Food Security Households Disease Sufferers Pulmonary Tuberculosis Uses the Method Regression Logistics Binary

NASA Astrophysics Data System (ADS)

Wulandari, S. P.; Salamah, M.; Rositawati, A. F. D.

2018-04-01

Food security is the condition where the food fulfilment is managed well for the country till the individual. Indonesia is one of the country which has the commitment to create the food security becomes main priority. However, the food necessity becomes common thing means that it doesn’t care about nutrient standard and the health condition of family member, so in the fulfilment of food necessity also has to consider the disease suffered by the family member, one of them is pulmonary tuberculosa. From that reasons, this research is conducted to know the factors which influence on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya by using binary logistic regression method. The analysis result by using binary logistic regression shows that the variables wife latest education, house density and spacious house ventilation significantly affect on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya, where the wife education level is University/equivalent, the house density is eligible or 8 m2/person and spacious house ventilation 10% of the floor area has the opportunity to become food secure households amounted to 0.911089. While the chance of becoming food insecure households amounted to 0.088911. The model household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya has been conformable, and the overall percentages of those classifications are at 71.8%.

Risk estimation using probability machines

PubMed Central

2014-01-01

Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306

Risk estimation using probability machines.

PubMed

Dasgupta, Abhijit; Szymczak, Silke; Moore, Jason H; Bailey-Wilson, Joan E; Malley, James D

2014-03-01

Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a "risk machine", will share properties from the statistical machine that it is derived from.

Are math readiness and personality predictive of first-year retention in engineering?

PubMed

Moses, Laurie; Hall, Cathy; Wuensch, Karl; De Urquidi, Karen; Kauffmann, Paul; Swart, William; Duncan, Steve; Dixon, Gene

2011-01-01

On the basis of J. G. Borkowski, L. K. Chan, and N. Muthukrishna's model of academic success (2000), the present authors hypothesized that freshman retention in an engineering program would be related to not only basic aptitude but also affective factors. Participants were 129 college freshmen with engineering as their stated major. Aptitude was measured by SAT verbal and math scores, high school grade-point average (GPA), and an assessment of calculus readiness. Affective factors were assessed by the NEO-Five Factor Inventory (FFI; P. I. Costa & R. R. McCrae, 2007), and the Nowicki-Duke Locus of Control (LOC) scale (S. Nowicki & M. Duke, 1974). A binary logistic regression analysis found that calculus readiness and high school GPA were predictive of retention. Scores on the Neuroticism and Openness subscales from the NEO-FFI and LOC were correlated with retention status, but Openness was the only affective factor with a significant unique effect in the binary logistic regression. Results of the study lend modest support to Borkowski's model.

Experiences That Predict Early Career Teacher Commitment to and Retention in High-Poverty Urban Schools

ERIC Educational Resources Information Center

Whipp, Joan L.; Geronime, Lara

2017-01-01

Correlation analysis was used to analyze what experiences before and during teacher preparation for 72 graduates of an urban teacher education program were associated with urban commitment, first job location, and retention in urban schools for 3 or more years. Binary logistic regression was then used to analyze whether urban K-12 schooling,…

Bayesian Analysis of Item Response Curves. Research Report 84-1. Mathematical Sciences Technical Report No. 132.

ERIC Educational Resources Information Center

Tsutakawa, Robert K.; Lin, Hsin Ying

Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. The procedure is illustrated by data…

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

Cerebrovascular risk factors for patients with cerebral watershed infarction: A case-control study based on computed tomography angiography in a population from Southwest China.

PubMed

Dong, Mei-Xue; Hu, Ling; Huang, Yuan-Jun; Xu, Xiao-Min; Liu, Yang; Wei, You-Dong

2017-07-01

To determine cerebrovascular risk factors for patients with cerebral watershed infarction (CWI) from Southwest China.Patients suffering from acute ischemic stroke were categorized into internal CWI (I-CWI), external CWI (E-CWI), or non-CWI (patients without CWI) groups. Clinical data were collected and degrees of steno-occlusion of all cerebral arteries were scored. Arteries associated with the circle of Willis were also assessed. Data were compared using Pearson chi-squared tests for categorical data and 1-way analysis of variance with Bonferroni post hoc tests for continuous data, as appropriate. Multivariate binary logistic regression analysis was performed to determine independent cerebrovascular risk factors for CWI.Compared with non-CWI, I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery, ipsilateral carotid artery, and contralateral middle cerebral artery. E-CWI showed no significant differences. All the 3 arteries were independent cerebrovascular risk factors for I-CWI confirmed by multivariate binary logistic regression analysis. I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery compared with E-CWI. No significant differences were found among arteries associated with the circle of Willis.The ipsilateral middle cerebral artery, carotid artery, and contralateral middle cerebral artery were independent cerebrovascular risk factors for I-CWI. No cerebrovascular risk factor was identified for E-CWI.

Binary Logistic Regression Analysis in Assessment and Identifying Factors That Influence Students' Academic Achievement: The Case of College of Natural and Computational Science, Wolaita Sodo University, Ethiopia

ERIC Educational Resources Information Center

Zewude, Bereket Tessema; Ashine, Kidus Meskele

2016-01-01

An attempt has been made to assess and identify the major variables that influence student academic achievement at college of natural and computational science of Wolaita Sodo University in Ethiopia. Study time, peer influence, securing first choice of department, arranging study time outside class, amount of money received from family, good life…

Social Impact of Stigma Regarding Tuberculosis Hindering Adherence to Treatment: A Cross Sectional Study Involving Tuberculosis Patients in Rajshahi City, Bangladesh.

PubMed

Chowdhury, Md Rocky Khan; Rahman, Md Shafiur; Mondal, Md Nazrul Islam; Sayem, Abu; Billah, Baki

2015-01-01

Stigma, considered a social disease, is more apparent in developing societies which are driven by various social affairs, and influences adherence to treatment. The aim of the present study was to examine levels of social stigma related to tuberculosis (TB) in sociodemographic context and identify the effects of sociodemographic factors on stigma. The study sample consisted of 372 TB patients. Data were collected using stratified sampling with simple random sampling techniques. T tests, chi-square tests, and binary logistic regression analysis were performed to examine correlations between stigma and sociodemographic variables. Approximately 85.9% of patients had experienced stigma. The most frequent indicator of the stigma experienced by patients involved problems taking part in social programs (79.5%). Mean levels of stigma were significantly higher in women (55.5%), illiterate individuals (60.8%), and villagers (60.8%) relative to those of other groups. Chi-square tests revealed that education, monthly family income, and type of patient (pulmonary and extrapulmonary) were significantly associated with stigma. Binary logistic regression analysis demonstrated that stigma was influenced by sex, education, and type of patient. Stigma is one of the most important barriers to treatment adherence. Therefore, in interventions that aim to reduce stigma, strong collaboration between various institutions is essential.

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

The crux of the method: assumptions in ordinary least squares and logistic regression.

PubMed

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

PubMed

Donath, Carolin; Graessel, Elmar; Baier, Dirk; Bleich, Stefan; Hillemacher, Thomas

2014-04-26

Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents' suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Three parental variables showed a relevant association with suicide attempts in adolescents - (all protective): mother's warmth and father's warmth in childhood and mother's control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p < .001) for suicidal attempts. Seven further variables were interpreted to be statistically significant and clinically relevant: ADHD, female sex, smoking, Binge Drinking, absenteeism/truancy, migration background, and parental separation events. Parenting style does matter. While children of Authoritative parents profit, children of Rejecting-Neglecting parents are put at risk - as we were able to show for suicide attempts in adolescence. Some of the identified risk factors contribute new knowledge and potential areas of intervention for special groups such as migrants or children diagnosed with ADHD.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging.

PubMed

Chen, Jin-Hua; Chen, Chun-Shu; Huang, Meng-Fan; Lin, Hung-Chih

2016-10-01

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback-Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed. © 2016 Society for Risk Analysis.

Socioeconomic and Demographic Disparities in Knowledge of Reproductive Healthcare among Female University Students in Bangladesh

PubMed Central

Islam Mondal, Md. Nazrul; Nasir Ullah, Md. Monzur Morshad; Khan, Md. Nuruzzaman; Islam, Mohammad Zamirul; Islam, Md. Nurul; Moni, Sabiha Yasmin; Hoque, Md. Nazrul; Rahman, Md. Mashiur

2015-01-01

Background: Reproductive health (RH) is a critical component of women’s health and overall well-being around the world, especially in developing countries. We examine the factors that determine knowledge of RH care among female university students in Bangladesh. Methods: Data on 300 female students were collected from Rajshahi University, Bangladesh through a structured questionnaire using purposive sampling technique. The data were used for univariate analysis, to carry out the description of the variables; bivariate analysis was used to examine the associations between the variables; and finally, multivariate analysis (binary logistic regression model) was used to examine and fit the model and interpret the parameter estimates, especially in terms of odds ratios. Results: The results revealed that more than one-third (34.3%) respondents do not have sufficient knowledge of RH care. The χ2-test identified the significant (p < 0.05) associations between respondents’ knowledge of RH care with respondents’ age, education, family type, watching television; and knowledge about pregnancy, family planning, and contraceptive use. Finally, the binary logistic regression model identified respondents’ age, education, family type; and knowledge about family planning, and contraceptive use as the significant (p < 0.05) predictors of RH care. Conclusions and Global Health Implications: Knowledge of RH care among female university students was found unsatisfactory. Government and concerned organizations should promote and strengthen various health education programs to focus on RH care especially for the female university students in Bangladesh. PMID:27622005

Factors associated with trait anger level of juvenile offenders in Hubei province: A binary logistic regression analysis.

PubMed

Tang, Li-Na; Ye, Xiao-Zhou; Yan, Qiu-Ge; Chang, Hong-Juan; Ma, Yu-Qiao; Liu, De-Bin; Li, Zhi-Gen; Yu, Yi-Zhen

2017-02-01

The risk factors of high trait anger of juvenile offenders were explored through questionnaire study in a youth correctional facility of Hubei province, China. A total of 1090 juvenile offenders in Hubei province were investigated by self-compiled social-demographic questionnaire, Childhood Trauma Questionnaire (CTQ), and State-Trait Anger Expression Inventory-II (STAXI-II). The risk factors were analyzed by chi-square tests, correlation analysis, and binary logistic regression analysis with SPSS 19.0. A total of 1082 copies of valid questionnaires were collected. High trait anger group (n=316) was defined as those who scored in the upper 27th percentile of STAXI-II trait anger scale (TAS), and the rest were defined as low trait anger group (n=766). The risk factors associated with high level of trait anger included: childhood emotional abuse, childhood sexual abuse, step family, frequent drug abuse, and frequent internet using (P<0.05 or P<0.01). Birth sequence, number of sibling, ranking in the family, identity of the main care-taker, the education level of care-taker, educational style of care-taker, family income, relationship between parents, social atmosphere of local area, frequent drinking, and frequent smoking did not predict to high level of trait anger (P>0.05). It was suggested that traumatic experience in childhood and unhealthy life style may significantly increase the level of trait anger in adulthood. The risk factors of high trait anger and their effects should be taken into consideration seriously.

Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

NASA Astrophysics Data System (ADS)

Ozdemir, Adnan

2011-07-01

SummaryThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km 2 (28.99%), 74.271 km 2 (19.906%), 101.203 km 2 (27.14%), and 90.05 km 2 (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model was found to be in strong agreement with the available groundwater spring test data. Hence, this method can be used routinely in groundwater exploration under favourable conditions.

A comparison of multiple imputation methods for incomplete longitudinal binary data.

PubMed

Yamaguchi, Yusuke; Misumi, Toshihiro; Maruo, Kazushi

2018-01-01

Longitudinal binary data are commonly encountered in clinical trials. Multiple imputation is an approach for getting a valid estimation of treatment effects under an assumption of missing at random mechanism. Although there are a variety of multiple imputation methods for the longitudinal binary data, a limited number of researches have reported on relative performances of the methods. Moreover, when focusing on the treatment effect throughout a period that has often been used in clinical evaluations of specific disease areas, no definite investigations comparing the methods have been available. We conducted an extensive simulation study to examine comparative performances of six multiple imputation methods available in the SAS MI procedure for longitudinal binary data, where two endpoints of responder rates at a specified time point and throughout a period were assessed. The simulation study suggested that results from naive approaches of a single imputation with non-responders and a complete case analysis could be very sensitive against missing data. The multiple imputation methods using a monotone method and a full conditional specification with a logistic regression imputation model were recommended for obtaining unbiased and robust estimations of the treatment effect. The methods were illustrated with data from a mental health research.

Risk Factors of Subacute Thrombosis After Intracranial Stenting for Symptomatic Intracranial Arterial Stenosis.

PubMed

Sun, Xuan; Tong, Xu; Lo, Wai Ting; Mo, Dapeng; Gao, Feng; Ma, Ning; Wang, Bo; Miao, Zhongrong

2017-03-01

We aimed to explore the risk factors of subacute thrombosis (SAT) after intracranial stenting for patients with symptomatic intracranial arterial stenosis. From January to December 2013, all symptomatic intracranial arterial stenosis patients who underwent intracranial stenting in Beijing Tiantan Hospital were prospectively registered into this study. Baseline clinical features and operative data were compared in patients who developed SAT with those who did not. Binary logistic regression model was used to determine the risk factors associated with SAT. Of the 221 patients enrolled, 9 (4.1%) cases had SAT 2 to 8 days after stenting. Binary logistic analysis showed that SAT was related with tandem stenting (odds ratio [OR], 11.278; 95% confidence interval [CI], 2.422-52.519) and antiplatelet resistance (aspirin resistance: OR, 6.267; 95% CI, 1.574-24.952; clopidogrel resistance: OR, 15.526; 95% CI, 3.105-77.626; aspirin and clopidogrel resistance: OR, 12.246; 95% CI, 2.932-51.147; and aspirin or clopidogrel resistance: OR, 11.340; 95% CI, 2.282-56.344). Tandem stenting and antiplatelet resistance might contribute to the development of SAT after intracranial stenting in patients with symptomatic intracranial arterial stenosis. © 2017 American Heart Association, Inc.

A simple measure of cognitive reserve is relevant for cognitive performance in MS patients.

PubMed

Della Corte, Marida; Santangelo, Gabriella; Bisecco, Alvino; Sacco, Rosaria; Siciliano, Mattia; d'Ambrosio, Alessandro; Docimo, Renato; Cuomo, Teresa; Lavorgna, Luigi; Bonavita, Simona; Tedeschi, Gioacchino; Gallo, Antonio

2018-05-04

Cognitive reserve (CR) contributes to preserve cognition despite brain damage. This theory has been applied to multiple sclerosis (MS) to explain the partial relationship between cognition and MRI markers of brain pathology. Our aim was to determine the relationship between two measures of CR and cognition in MS. One hundred and forty-seven MS patients were enrolled. Cognition was assessed using the Rao's Brief Repeatable Battery and the Stroop Test. CR was measured as the vocabulary subtest of the WAIS-R score (VOC) and the number of years of formal education (EDU). Regression analysis included raw score data on each neuropsychological (NP) test as dependent variables and demographic/clinical parameters, VOC, and EDU as independent predictors. A binary logistic regression analysis including clinical/CR parameters as covariates and absence/presence of cognitive deficits as dependent variables was performed too. VOC, but not EDU, was strongly correlated with performances at all ten NP tests. EDU was correlated with executive performances. The binary logistic regression showed that only the Expanded Disability Status Scale (EDSS) and VOC were independently correlated with the presence/absence of CD. The lower the VOC and/or the higher the EDSS, the higher the frequency of CD. In conclusion, our study supports the relevance of CR in subtending cognitive performances and the presence of CD in MS patients.

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

Electronic health record analysis via deep poisson factor models

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

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Analysis of Radiation Effects in Digital Subtraction Angiography of Intracranial Artery Stenosis.

PubMed

Guo, Chaoqun; Shi, Xiaolei; Ding, Xianhui; Zhou, Zhiming

2018-04-21

Intracranial artery stenosis (IAS) is the most common cause for acute cerebral accidents. Digital subtraction angiography (DSA) is the gold standard to detect IAS and usually brings excess radiation exposure to examinees and examiners. The artery pathology might influence the interventional procedure, causing prolonged radiation effects. However, no studies on the association between IAS pathology and operational parameters are available. A retrospective analysis was conducted on 93 patients with first-ever stroke/transient ischemic attack, who received DSA examination within 3 months from onset in this single center. Comparison of baseline characteristics was determined by 2-tailed Student's t-test or the chi-square test between subjects with and without IAS. A binary logistic regression analysis was performed to determine the association between IAS pathology and the items with a P value <0.05 in Student's t-test or chi-square test. There were 93 candidates (42 with IAS and 51 without IAS) in this study. The 2 groups shared no significance of the baseline characteristics (P > 0.05). We found a significantly higher total time, higher kerma area product, greater total dose, and greater DSA dose in the IAS group than in those without IAS (P < 0.05). A binary logistic regression analysis indicated the significant association between total time and IAS pathology (P < 0.05) but no significance in kerma area product, radiation dose, and DSA dose (P > 0.05). IAS pathology would indicate a prolonged total time of DSA procedure in clinical practice. However, the radiation effects would not change with pathologic changes. Copyright © 2018 Elsevier Inc. All rights reserved.

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

The Prevalence of Antenatal Depression and its Related Factors in Chinese Pregnant Women who Present with Obstetrical Complications.

PubMed

Zhao, Ying; Kane, Irene; Mao, Liping; Shi, Shenxun; Wang, Jing; Lin, Qiping; Luo, Jianfeng

2016-06-01

The psychological status of Chinese pregnant women who present with obstetrical complications is concerning to Chinese health professionals. This study aimed to investigate the prevalence of antenatal depression and analyzed related risk factors in a population of high-risk Chinese women. A large sample size, cross-sectional study. A total of 842 pregnant women with complications completed the Chinese version of the Postpartum Depression Screen Scale (PDSS) in this cross-sectional study. t-Test, ANOVA and Binary logistic regression tests were used in data analysis of antenatal depression and risk factors. The prevalence of major or minor depression in high-risk Chinese pregnant women during antenatal period was 8.3% and 28.9%, respectively. Independent-sample t-test and two-way analysis of variance (ANOVA) indicated significant differences in age, education, occupation and the number of complications (P<0.05). Binary logistic regression analysis indicated a significant negative association between depression and education (P<0.01) with lower educational level (OR: 0.590; 95% CI: 0.424-0.820) associated with a higher risk for depression. A significant positive association was observed between depression and age (P<0.05) with higher age (OR: 1.338; 95% CI: 1.008-1.774) correlated with a higher risk for depression. Women who experienced obstetric complications presented with higher PDSS depression scores. Screening for antenatal depression in high-risk pregnant women to promote early detection of depression and reduce health risks for universal health promotion is recommended. Copyright © 2015 Elsevier Inc. All rights reserved.

Nurses’ knowledge on phlebotomy in tertiary hospitals in China: a cross-sectional multicentric survey

PubMed Central

Cai, Qian; Zhou, Yunxian; Yang, Dangan

2017-01-01

Introduction In China, phlebotomy practice is mostly executed by nurses instead of phlebotomists. Our hypothesis was that these nurses may lack of knowledge on phlebotomy, especially factors influencing quality of blood samples. This study aims to assess the overall nurses’ knowledge on phlebotomy to provide reference for improving blood sampling practice in China. Materials and methods A survey was conducted involving nurses from 4 regions and 13 hospitals in China. A phlebotomy knowledge questionnaire was designed based on the Clinical and Laboratory Standards Institute H3-A6 guidelines, combining with the situations in China. Descriptive analysis and binary logistic regression analysis were used to analyze the knowledge level and its influencing factors. Results A total of 3400 questionnaires were distributed and 3077 valid questionnaires were returned, with an effective return rate of 90.5%. The correct rates of patient identification, hand sanitization, patient assessment, tube mixing time, needle disposing location and tube labelling were greater than 90%. However, the correct rates of order of draw (15.5%), definition of an inversion (22.5%), time to release tourniquet (18.5%) and time to change tube (28.5%) were relatively low. Binary logistic regression analysis showed that the correct rates of the aforementioned four questions were mainly related to the regional distribution of the hospitals (P < 0.001). Conclusions The knowledge level on phlebotomy among Chinese nurses was found unsatisfactory in some areas. An education program on phlebotomy should be developed for Chinese nurses to improve the consistency among different regions and to enhance nurse’s knowledge level on phlebotomy. PMID:29187796

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

PubMed

Smith, E M D; Jorgensen, A L; Beresford, M W

2017-10-01

Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged <16 years at diagnosis, were categorized as having active or inactive LN according to the renal domain of the British Isles Lupus Assessment Group score. Classic biomarkers: anti-dsDNA, C3, C4, ESR, CRP, haemoglobin, total white cells, neutrophils, lymphocytes, platelets and immunoglobulins were assessed for their ability to identify active LN using binary logistic regression modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

The rate of adherence to urate-lowering therapy and associated factors in Chinese gout patients: a cross-sectional study.

PubMed

Yin, Rulan; Cao, Haixia; Fu, Ting; Zhang, Qiuxiang; Zhang, Lijuan; Li, Liren; Gu, Zhifeng

2017-07-01

The aim of this study was to assess adherence rate and predictors of non-adherence with urate-lowering therapy (ULT) in Chinese gout patients. A cross-sectional study was administered to 125 gout patients using the Compliance Questionnaire on Rheumatology (CQR) for adherence to ULT. Patients were asked to complete the Treatment Satisfaction Questionnaire for Medication version II, Health Assessment Questionnaire, Confidence in Gout Treatment Questionnaire, Gout Knowledge Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and 36-Item Short Form Health Survey. Data were analyzed by independent sample t test, rank sum test, Chi-square analysis as well as binary stepwise logistic regression modeling. The data showed that the rate of adherence (CQR ≥80%) to ULT was 9.6% in our investigated gout patients. Adherence was associated with functional capacity, gout-related knowledge, satisfaction with medication, confidence in gout treatment and mental components summary. Multivariable analysis of binary stepwise logistic regression identified gout-related knowledge and satisfaction of effectiveness with medication was the independent risk factors of medication non-adherence. Patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication, were more likely not to adhere to ULT. Non-adherence to ULT among gout patients is exceedingly common, particularly in patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication. These findings could help medical personnel develop useful interventions to improve gout patients' medication adherence.

Financial performance monitoring of the technical efficiency of critical access hospitals: a data envelopment analysis and logistic regression modeling approach.

PubMed

Wilson, Asa B; Kerr, Bernard J; Bastian, Nathaniel D; Fulton, Lawrence V

2012-01-01

From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

PubMed Central

2014-01-01

Background Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents’ suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. Methods In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Results Three parental variables showed a relevant association with suicide attempts in adolescents – (all protective): mother’s warmth and father’s warmth in childhood and mother’s control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p < .001) for suicidal attempts. Seven further variables were interpreted to be statistically significant and clinically relevant: ADHD, female sex, smoking, Binge Drinking, absenteeism/truancy, migration background, and parental separation events. Conclusions Parenting style does matter. While children of Authoritative parents profit, children of Rejecting-Neglecting parents are put at risk – as we were able to show for suicide attempts in adolescence. Some of the identified risk factors contribute new knowledge and potential areas of intervention for special groups such as migrants or children diagnosed with ADHD. PMID:24766881

Prevalence and determinants of cardiovascular disease risk factors among the residents of urban community housing projects in Malaysia.

PubMed

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

2014-01-01

The objectives are to assess the prevalence and determinants of cardiovascular disease (CVD) risk factors among the residents of Community Housing Projects in metropolitan Kuala Lumpur, Malaysia. By using simple random sampling, we selected and surveyed 833 households which comprised of 3,722 individuals. Out of the 2,360 adults, 50.5% participated in blood sampling and anthropometric measurement sessions. Uni and bivariate data analysis and multivariate binary logistic regression were applied to identify demographic and socioeconomic determinants of the existence of having at least one CVD risk factor. As a Result, while obesity (54.8%), hypercholesterolemia (51.5%), and hypertension (39.3%) were the most common CVD risk factors among the low-income respondents, smoking (16.3%), diabetes mellitus (7.8%) and alcohol consumption (1.4%) were the least prevalent. Finally, the results from the multivariate binary logistic model illustrated that compared to the Malays, the Indians were 41% less likely to have at least one of the CVD risk factors (OR = 0.59; 95% CI: 0.37 - 0.93). In Conclusion, the low-income individuals were at higher risk of developing CVDs. Prospective policies addressing preventive actions and increased awareness focusing on low-income communities are highly recommended and to consider age, gender, ethnic backgrounds, and occupation classes.

London Measure of Unplanned Pregnancy: guidance for its use as an outcome measure

PubMed Central

Hall, Jennifer A; Barrett, Geraldine; Copas, Andrew; Stephenson, Judith

2017-01-01

Background The London Measure of Unplanned Pregnancy (LMUP) is a psychometrically validated measure of the degree of intention of a current or recent pregnancy. The LMUP is increasingly being used worldwide, and can be used to evaluate family planning or preconception care programs. However, beyond recommending the use of the full LMUP scale, there is no published guidance on how to use the LMUP as an outcome measure. Ordinal logistic regression has been recommended informally, but studies published to date have all used binary logistic regression and dichotomized the scale at different cut points. There is thus a need for evidence-based guidance to provide a standardized methodology for multivariate analysis and to enable comparison of results. This paper makes recommendations for the regression method for analysis of the LMUP as an outcome measure. Materials and methods Data collected from 4,244 pregnant women in Malawi were used to compare five regression methods: linear, logistic with two cut points, and ordinal logistic with either the full or grouped LMUP score. The recommendations were then tested on the original UK LMUP data. Results There were small but no important differences in the findings across the regression models. Logistic regression resulted in the largest loss of information, and assumptions were violated for the linear and ordinal logistic regression. Consequently, robust standard errors were used for linear regression and a partial proportional odds ordinal logistic regression model attempted. The latter could only be fitted for grouped LMUP score. Conclusion We recommend the linear regression model with robust standard errors to make full use of the LMUP score when analyzed as an outcome measure. Ordinal logistic regression could be considered, but a partial proportional odds model with grouped LMUP score may be required. Logistic regression is the least-favored option, due to the loss of information. For logistic regression, the cut point for un/planned pregnancy should be between nine and ten. These recommendations will standardize the analysis of LMUP data and enhance comparability of results across studies. PMID:28435343

An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

PubMed

Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

2014-09-01

Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

Analysis of factors influencing organic fruit and vegetable purchasing in Istanbul, Turkey.

PubMed

Oraman, Yasemin; Unakitan, Gökhan

2010-01-01

This article examines the influences on the purchasing decisions of fruit and vegetable consumers and presents findings from a survey conducted with 385 respondents living in urban areas in Istanbul, Turkey. It uses a binary logistic model to estimate factor effects in organic fruit and vegetable purchasing in Turkey. The results indicate that concern for human health and safety is a key factor that influences consumer preferences for organic food. Findings will help organic product suppliers understand the key factors influencing consumer purchasing and consumption behaviors.

Diagnostic accuracy of serum antibodies to human papillomavirus type 16 early antigens in the detection of human papillomavirus-related oropharyngeal cancer.

PubMed

Dahlstrom, Kristina R; Anderson, Karen S; Field, Matthew S; Chowell, Diego; Ning, Jing; Li, Nan; Wei, Qingyi; Li, Guojun; Sturgis, Erich M

2017-12-15

Because of the current epidemic of human papillomavirus (HPV)-related oropharyngeal cancer (OPC), a screening strategy is urgently needed. The presence of serum antibodies to HPV-16 early (E) antigens is associated with an increased risk for OPC. The purpose of this study was to evaluate the diagnostic accuracy of antibodies to a panel of HPV-16 E antigens in screening for OPC. This case-control study included 378 patients with OPC, 153 patients with nonoropharyngeal head and neck cancer (non-OPC), and 782 healthy control subjects. The tumor HPV status was determined with p16 immunohistochemistry and HPV in situ hybridization. HPV-16 E antibody levels in serum were identified with an enzyme-linked immunosorbent assay. A trained binary logistic regression model based on the combination of all E antigens was predefined and applied to the data set. The sensitivity and specificity of the assay for distinguishing HPV-related OPC from controls were calculated. Logistic regression analysis was used to calculate odds ratios with 95% confidence intervals for the association of head and neck cancer with the antibody status. Of the 378 patients with OPC, 348 had p16-positive OPC. HPV-16 E antibody levels were significantly higher among patients with p16-positive OPC but not among patients with non-OPC or among controls. Serology showed high sensitivity and specificity for HPV-related OPC (binary classifier: 83% sensitivity and 99% specificity for p16-positive OPC). A trained binary classification algorithm that incorporates information about multiple E antibodies has high sensitivity and specificity and may be advantageous for risk stratification in future screening trials. Cancer 2017;123:4886-94. © 2017 American Cancer Society. © 2017 American Cancer Society.

Clinical features and risk factor analysis for lower extremity deep venous thrombosis in Chinese neurosurgical patients

PubMed Central

Guo, Fuyou; Shashikiran, Tagilapalli; Chen, Xi; Yang, Lei; Liu, Xianzhi; Song, Laijun

2015-01-01

Background: Deep venous thrombosis (DVT) contributes significantly to the morbidity and mortality of neurosurgical patients; however, no data regarding lower extremity DVT in postoperative Chinese neurosurgical patients have been reported. Materials and Methods: From January 2012 to December 2013, 196 patients without preoperative DVT who underwent neurosurgical operations were evaluated by color Doppler ultrasonography and D-dimer level measurements on the 3rd, 7th, and 14th days after surgery. Follow-up clinical data were recorded to determine the incidence of lower extremity DVT in postoperative neurosurgical patients and to analyze related clinical features. First, a single factor analysis, Chi-square test, was used to select statistically significant factors. Then, a multivariate analysis, binary logistic regression analysis, was used to determine risk factors for lower extremity DVT in postoperative neurosurgical patients. Results: Lower extremity DVT occurred in 61 patients, and the incidence of DVT was 31.1% in the enrolled Chinese neurosurgical patients. The common symptoms of DVT were limb swelling and lower extremity pain as well as increased soft tissue tension. The common sites of venous involvement were the calf muscle and peroneal and posterior tibial veins. The single factor analysis showed statistically significant differences in DVT risk factors, including age, hypertension, smoking status, operation time, a bedridden or paralyzed state, the presence of a tumor, postoperative dehydration, and glucocorticoid treatment, between the two groups (P < 0.05). The binary logistic regression analysis showed that an age greater than 50 years, hypertension, a bedridden or paralyzed state, the presence of a tumor, and postoperative dehydration were risk factors for lower extremity DVT in postoperative neurosurgical patients. Conclusions: Lower extremity DVT was a common complication following craniotomy in the enrolled Chinese neurosurgical patients. Multiple factors were identified as predictive of DVT in neurosurgical patients, including the presence of a tumor, an age greater than 50 years, hypertension, and immobility. PMID:26752303

Gender differences in depressive symptom profiles and patterns of psychotropic drug usage in Asian patients with depression: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants study.

PubMed

Park, Seon-Cheol; Lee, Min-Soo; Shinfuku, Naotaka; Sartorius, Norman; Park, Yong Chon

2015-09-01

The purpose of this study was to investigate whether there were gender-specific depressive symptom profiles or gender-specific patterns of psychotropic agent usage in Asian patients with depression. Clinical data from the Research on Asian Psychotropic Prescription Patterns for Antidepressant study (1171 depressed patients) were used to determine gender differences by analysis of covariates for continuous variables and by logistic regression analysis for discrete variables. In addition, a binary logistic regression model was fitted to identify independent clinical correlates of the gender-specific pattern on psychotropic drug usage. Men were more likely than women to have loss of interest (adjusted odds ratio = 1.379, p = 0.009), fatigue (adjusted odds ratio = 1.298, p = 0.033) and concurrent substance abuse (adjusted odds ratio = 3.793, p = 0.008), but gender differences in other symptom profiles and clinical features were not significant. Men were also more likely than women to be prescribed adjunctive therapy with a second-generation antipsychotic (adjusted odds ratio = 1.320, p = 0.044). However, men were less likely than women to have suicidal thoughts/acts (adjusted odds ratio = 0.724, p = 0.028). Binary logistic regression models revealed that lower age (odds ratio = 0.986, p = 0.027) and current hospitalization (odds ratio = 3.348, p < 0.0001) were independent clinical correlates of use of second-generation antipsychotics as adjunctive therapy for treating depressed Asian men. Unique gender-specific symptom profiles and gender-specific patterns of psychotropic drug usage can be identified in Asian patients with depression. Hence, ethnic and cultural influences on the gender preponderance of depression should be considered in the clinical psychiatry of Asian patients. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Socio-Economic, Demographic and Lifestyle Determinants of Overweight and Obesity among Adults of Northeast India.

PubMed

Rengma, Melody Seb; Sen, Jaydip; Mondal, Nitish

2015-07-01

Overweight and obesity are the accumulation of high body adiposity, which can have detrimental health effects and contribute to the development of numerous preventable non-communicable diseases. This study aims to evaluate the effect of socio-economic, demographic and lifestyle factors on the prevalence of overweight and obesity among adults belonging to the Rengma-Naga population of North-east India. This cross-sectional study was conducted among 826 Rengma-Naga individuals (males: 422; females: 404) aged 20-49 years from the Karbi Anglong District of Assam, using a two-stage stratified random sampling. The socio-economic, demographic and lifestyle variables were recorded using structured schedules. Height and weight were recorded and the Body Mass Index (BMI) was calculated using standard procedures and equation. The WHO (2000) cut-off points were utilized to assess the prevalence of overweight (BMI ≥23.00-24.99 kg/m(2)) and obesity (BMI ≥25.00 kg/m(2)). The data were analysed using ANOVA, chi-square analysis and binary logistic regression analysis using SPSS (version 17.0). The prevalence of overweight and obesity were 32.57% (males: 39.34%; females: 25.50%) and 10.77% (males: 9.95%; females: 11.63%), respectively. The binary logistic regression analysis showed that age groups (e.g., 40-49 years), education (≥9(th) standard), part-time occupation and monthly income (≥Rs.10000) were significantly associated with overweight and obesity (p<0.05). Age, education occupation and income appear to have higher associations with overweight and obesity among adults. Suitable healthcare strategies and intervention programmes are needed for combating such prevalence in population.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

PubMed

Zheng, Wenjing; Balzer, Laura; van der Laan, Mark; Petersen, Maya

2018-01-30

Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency virus prevention program based on offering pre-exposure prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program. In this article, we consider a general class of constrained binary classification problems wherein the objective function and the constraint are both monotonic with respect to a threshold. These include the minimization of the rate of positive predictions subject to a minimum sensitivity, the maximization of sensitivity subject to a maximum rate of positive predictions, and the Neyman-Pearson paradigm, which minimizes the type II error subject to an upper bound on the type I error. We propose an ensemble approach to these binary classification problems based on the Super Learner methodology. This approach linearly combines a user-supplied library of scoring algorithms, with combination weights and a discriminating threshold chosen to minimize the constrained optimality criterion. We then illustrate the application of the proposed classifier to develop an individualized PrEP targeting strategy in a resource-limited setting, with the goal of minimizing the number of PrEP offerings while achieving a minimum required sensitivity. This proof of concept data analysis uses baseline data from the ongoing Sustainable East Africa Research in Community Health study. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Modelling the growth kinetics of Kocuria marina DAGII as a function of single and binary substrate during batch production of β-Cryptoxanthin.

PubMed

Mitra, Ruchira; Chaudhuri, Surabhi; Dutta, Debjani

2017-01-01

In the present investigation, growth kinetics of Kocuria marina DAGII during batch production of β-Cryptoxanthin (β-CRX) was studied by considering the effect of glucose and maltose as a single and binary substrate. The importance of mixed substrate over single substrate has been emphasised in the present study. Different mathematical models namely, the Logistic model for cell growth, the Logistic mass balance equation for substrate consumption and the Luedeking-Piret model for β-CRX production were successfully implemented. Model-based analyses for the single substrate experiments suggested that the concentrations of glucose and maltose higher than 7.5 and 10.0 g/L, respectively, inhibited the growth and β-CRX production by K. marina DAGII. The Han and Levenspiel model and the Luong product inhibition model accurately described the cell growth in glucose and maltose substrate systems with a R 2 value of 0.9989 and 0.9998, respectively. The effect of glucose and maltose as binary substrate was further investigated. The binary substrate kinetics was well described using the sum-kinetics with interaction parameters model. The results of production kinetics revealed that the presence of binary substrate in the cultivation medium increased the biomass and β-CRX yield significantly. This study is a first time detailed investigation on kinetic behaviours of K. marina DAGII during β-CRX production. The parameters obtained in the study might be helpful for developing strategies for commercial production of β-CRX by K. marina DAGII.

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results

ERIC Educational Resources Information Center

Osborne, Jason W.

2012-01-01

Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These…

Missing Data in Alcohol Clinical Trials with Binary Outcomes

PubMed Central

Hallgren, Kevin A.; Witkiewitz, Katie; Kranzler, Henry R.; Falk, Daniel E.; Litten, Raye Z.; O’Malley, Stephanie S.; Anton, Raymond F.

2017-01-01

Background Missing data are common in alcohol clinical trials for both continuous and binary endpoints. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). The present study compares approaches to modeling binary outcomes with missing data in the COMBINE study. Method We included participants in the COMBINE Study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N=1146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using four analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst-case scenario of missing equals any drinking or heavy drinking (WCS), and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. Results WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data, and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Conclusions Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. PMID:27254113

Missing Data in Alcohol Clinical Trials with Binary Outcomes.

PubMed

Hallgren, Kevin A; Witkiewitz, Katie; Kranzler, Henry R; Falk, Daniel E; Litten, Raye Z; O'Malley, Stephanie S; Anton, Raymond F

2016-07-01

Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study. We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. Copyright © 2016 by the Research Society on Alcoholism.

National health insurance subscription and maternal healthcare utilisation across mothers' wealth status in Ghana.

PubMed

Ameyaw, Edward Kwabena; Kofinti, Raymond Elikplim; Appiah, Francis

2017-12-01

This study is against the backdrop that despite the forty-nine percent decline in Maternal Mortality Rate in Ghana, the situation still remains high averaging 319 per 100,000 live births between 2011 and 2015. To examine the relationship between National Health Insurance and maternal healthcare utilisation across three main wealth quintiles (Poor, Middle and Rich). The study employed data from the 2014 Ghana Demographic and Health Survey. Both descriptive analysis and binary logistic regression were conducted. Descriptively, rich women had high antenatal attendance and health facility deliveries represented by 96.5% and 95.6% respectively. However, the binary logistic regression results revealed that poor women owning NHIS are 7% (CI = 1.76-2.87) more likely to make at least four antenatal care visits compared to women in the middle wealth quintile (5%, CI = 2.12-4.76) and rich women (2%, CI = 1.14-4.14). Similarly, poor women who owned the NHIS are 14% (CI = 1.42-2.13) likely to deliver in health facility than women in the middle and rich wealth quintile. The study has vindicated the claim that NHIS Scheme is pro-poor in Ghana. The Ministry of Health should target women in the rural area to be enrolled on the NHIS to improve maternal healthcare utilisation since poverty is principally a rural phenomenon in Ghana.

Prevalence and determinants of cardiovascular disease risk factors among the residents of urban community housing projects in Malaysia

PubMed Central

2014-01-01

Objectives The objectives are to assess the prevalence and determinants of cardiovascular disease (CVD) risk factors among the residents of Community Housing Projects in metropolitan Kuala Lumpur, Malaysia. Method By using simple random sampling, we selected and surveyed 833 households which comprised of 3,722 individuals. Out of the 2,360 adults, 50.5% participated in blood sampling and anthropometric measurement sessions. Uni and bivariate data analysis and multivariate binary logistic regression were applied to identify demographic and socioeconomic determinants of the existence of having at least one CVD risk factor. Results As a Result, while obesity (54.8%), hypercholesterolemia (51.5%), and hypertension (39.3%) were the most common CVD risk factors among the low-income respondents, smoking (16.3%), diabetes mellitus (7.8%) and alcohol consumption (1.4%) were the least prevalent. Finally, the results from the multivariate binary logistic model illustrated that compared to the Malays, the Indians were 41% less likely to have at least one of the CVD risk factors (OR = 0.59; 95% CI: 0.37 - 0.93). Conclusion In Conclusion, the low-income individuals were at higher risk of developing CVDs. Prospective policies addressing preventive actions and increased awareness focusing on low-income communities are highly recommended and to consider age, gender, ethnic backgrounds, and occupation classes. PMID:25436515

Portugal and Angola: similarities and differences in Toxoplasma gondii seroprevalence and risk factors in pregnant women.

PubMed

Lobo, M L; Patrocinio, G; Sevivas, T; DE Sousa, B; Matos, O

2017-01-01

In this study we determined the presence of IgM/IgG antibodies to Toxoplasma gondii in sera of 155 and 300 pregnant women from Lisbon (Portugal) and Luanda (Angola), respectively, and evaluated the potential risk factors associated with this infection. DNA detection was performed by PCR assays targeting T. gondii regions (RE/B1). Overall, 21·9% (10·9% IgG, 10·9% IgG/IgM) of the Lisbon women and 27·3% (23·7%, IgG, 2% IgM, 1·7% IgG/IgM) of the Luanda women had antibodies to T. gondii. Single variable and binary logistic regression analyses were conducted. Based on the latter, contacts with cats (family/friends), and having more than two births were identified as risk factors for Toxoplasma infection in Lisbon women. In Luanda, the risk factors for T. gondii infection suggested by the single variable analysis (outdoor contact with cats and consumption of pasteurized milk/dairy products) were not confirmed by binary logistic regression. This study shows original data from Angola, and updated data from Portugal in the study of infection by T. gondii in pregnant women, indicating that the prevalence of anti-Toxoplasma antibodies is high enough to alert the government health authorities and implement appropriate measures to control this infection.

Depression and incident dementia. An 8-year population-based prospective study.

PubMed

Luppa, Melanie; Luck, Tobias; Ritschel, Franziska; Angermeyer, Matthias C; Villringer, Arno; Riedel-Heller, Steffi G

2013-01-01

The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45-51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01-1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03-1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.

Prevalence and Extrinsic Risk Factors for Dental Erosion in Adolescents.

PubMed

Mafla, Ana C; Cerón-Bastidas, Ximena A; Munoz-Ceballos, Maria E; Vallejo-Bravo, Diana C; Fajardo-Santacruz, Maria C

This manuscript examined the prevalence and extrinsic risk factors for dental erosion (DE) in early and middle adolescents in Pasto, Colombia. Dental erosion was evaluated in a random sample of 384 individuals aged 10-15 years attending three primary and high schools in this cross-sectional study. Clinical dental assessment for DE was done using O'Sullivan index. Data on general sociodemographic variables and extrinsic risks factors were obtained. Descriptive and univariate binary logistic regression analyses were performed. Dental erosion was observed in 57.3% of individuals. The univariate binary logistic regression analysis showed that frequency of drinking natural fruit juices (OR 2.670, 95% CI 1.346 - 5.295, P=0.004) and their pH (OR 2.303, 95% CI 1.292 - 4.107, P=0.004) were more associated with the odd of DE in early adolescence. However, a high SES (OR 10.360, 95% CI 3.700 - 29.010, P<0.001) and frequency of snacks with artificial lemon taste (OR 3.659, 95% CI 1.506 - 8.891, P=0.003) were highly associated with the risk of DE in middle adolescence. The results suggest that DE is a prevalent condition in adolescents living in a city in southern Colombia. The transition from early to middle adolescence implies new bio-psychosocial changes, which increase the risk for DE.

Psychological trauma symptoms and Type 2 diabetes prevalence, glucose control, and treatment modality among American Indians in the Strong Heart Family Study

PubMed Central

Jacob, Michelle M.; Gonzales, Kelly L.; Calhoun, Darren; Beals, Janette; Muller, Clemma Jacobsen; Goldberg, Jack; Nelson, Lonnie; Welty, Thomas K.; Howard, Barbara V.

2013-01-01

Aims The aims of this paper are to examine the relationship between psychological trauma symptoms and Type 2 diabetes prevalence, glucose control, and treatment modality among 3,776 American Indians in Phase V of the Strong Heart Family Study. Methods This cross-sectional analysis measured psychological trauma symptoms using the National Anxiety Disorder Screening Day instrument, diabetes by American Diabetes Association criteria, and treatment modality by four categories: no medication, oral medication only, insulin only, or both oral medication and insulin. We used binary logistic regression to evaluate the association between psychological trauma symptoms and diabetes prevalence. We used ordinary least squares regression to evaluate the association between psychological trauma symptoms and glucose control. We used binary logistic regression to model the association of psychological trauma symptoms with treatment modality. Results Neither diabetes prevalence (22-31%; p = 0.19) nor control (8.0-8.6; p = 0.25) varied significantly by psychological trauma symptoms categories. However, diabetes treatment modality was associated with psychological trauma symptoms categories, as people with greater burden used either no medication, or both oral and insulin medications (odds ratio = 3.1, p < 0.001). Conclusions The positive relationship between treatment modality and psychological trauma symptoms suggests future research investigate patient and provider treatment decision making. PMID:24051029

Use of antidementia drugs in frontotemporal lobar degeneration.

PubMed

López-Pousa, Secundino; Calvó-Perxas, Laia; Lejarreta, Saioa; Cullell, Marta; Meléndez, Rosa; Hernández, Erélido; Bisbe, Josep; Perkal, Héctor; Manzano, Anna; Roig, Anna Maria; Turró-Garriga, Oriol; Vilalta-Franch, Joan; Garre-Olmo, Josep

2012-06-01

Clinical evidence indicates that acetylcholinesterase inhibitors (AChEIs) are not efficacious to treat frontotemporal lobar degeneration (FTLD). The British Association for Psychopharmacology recommends avoiding the use of AChEI and memantine in patients with FTLD. Cross-sectional design using 1092 cases with Alzheimer's disease (AD) and 64 cases with FTLD registered by the Registry of Dementias of Girona. Bivariate analyses were performed, and binary logistic regressions were used to detect variables associated with antidementia drugs consumption. The AChEIs were consumed by 57.6% and 42.2% of the patients with AD and FTLD, respectively. Memantine was used by 17.2% and 10.9% of patients with AD and FTLD, respectively. Binary logistic regressions yielded no associations with antidementia drugs consumption. There is a discrepancy regarding clinical practice and the recommendations based upon clinical evidence. The increased central nervous system drug use detected in FTLD requires multicentric studies aiming at finding the best means to treat these patients.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Logistic regression for circular data

NASA Astrophysics Data System (ADS)

Al-Daffaie, Kadhem; Khan, Shahjahan

2017-05-01

This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

Comparison of support vector machine classification to partial least squares dimension reduction with logistic descrimination of hyperspectral data

NASA Astrophysics Data System (ADS)

Wilson, Machelle; Ustin, Susan L.; Rocke, David

2003-03-01

Remote sensing technologies with high spatial and spectral resolution show a great deal of promise in addressing critical environmental monitoring issues, but the ability to analyze and interpret the data lags behind the technology. Robust analytical methods are required before the wealth of data available through remote sensing can be applied to a wide range of environmental problems for which remote detection is the best method. In this study we compare the classification effectiveness of two relatively new techniques on data consisting of leaf-level reflectance from plants that have been exposed to varying levels of heavy metal toxicity. If these methodologies work well on leaf-level data, then there is some hope that they will also work well on data from airborne and space-borne platforms. The classification methods compared were support vector machine classification of exposed and non-exposed plants based on the reflectance data, and partial east squares compression of the reflectance data followed by classification using logistic discrimination (PLS/LD). PLS/LD was performed in two ways. We used the continuous concentration data as the response during compression, and then used the binary response required during logistic discrimination. We also used a binary response during compression followed by logistic discrimination. The statistics we used to compare the effectiveness of the methodologies was the leave-one-out cross validation estimate of the prediction error.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

Personality traits and coping styles explain anxiety in lung cancer patients to a greater extent than other factors.

PubMed

Shimizu, Ken; Nakaya, Naoki; Saito-Nakaya, Kumi; Akechi, Tatsuo; Ogawa, Asao; Fujisawa, Daisuke; Sone, Toshimasa; Yoshiuchi, Kazuhiro; Goto, Koichi; Iwasaki, Motoki; Tsugane, Shoichiro; Uchitomi, Yosuke

2015-05-01

Although various factors thought to be correlated with anxiety in cancer patients, relative importance of each factors were unknown. We tested our hypothesis that personality traits and coping styles explain anxiety in lung cancer patients to a greater extent than other factors. A total of 1334 consecutively recruited lung cancer patients were selected, and data on cancer-related variables, demographic characteristics, health behaviors, physical symptoms and psychological factors consisting of personality traits and coping styles were obtained. The participants were divided into groups with or without a significant anxiety using the Hospital Anxiety and Depression Scale-Anxiety, and a binary logistic regression analysis was used to identify factors correlated with significant anxiety using a multivariate model. Among the recruited patients, 440 (33.0%) had significant anxiety. The binary logistic regression analysis revealed a coefficient of determination (overall R(2)) of 39.0%, and the explanation for psychological factors was much higher (30.7%) than those for cancer-related variables (1.1%), demographic characteristics (2.1%), health behaviors (0.8%) and physical symptoms (4.3%). Four specific factors remained significant in a multivariate model. A neurotic personality trait, a coping style of helplessness/hopelessness, and a female sex were positively correlated with significant anxiety, while a coping style of fatalism was negatively correlated. Our hypothesis was supported, and anxiety was strongly linked with personality trait and coping style. As a clinical implication, the use of screening instruments to identify these factors and intervention for psychological crisis may be needed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The effect of migration on social capital and depression among older adults in China.

PubMed

Li, Qiuju; Zhou, Xudong; Ma, Sha; Jiang, Minmin; Li, Lu

2017-12-01

An estimated 9 million elderly people accompanied their adult children to urban areas in China, raising concerns about their social capital and mental health following re-location. The aim of this study was to examine the effect of migration on social capital and depression among this population. Multistage stratified cluster sampling was applied to recruit the migrant and urban elderly in Hangzhou from May to August, 2013. Data were collected from face-to-face interviews by trained college students using a standardized questionnaire. Social capital measurements included cognitive (generalized trust and reciprocity) and structure (support from individual and social contact) aspects. Depression was measured by Geriatric Depression Scale-30 (GDS-30). Chi-square tests and binary logistic regression models were used for analysis. A total of 1248 migrant elderly and 1322 urban elderly were eligible for analysis. After adjusting for a range of confounder factors, binary logistic regression models revealed that migrant elderly reported significantly lower levels of generalized trust [OR = 1.34, 95% CI (1.10-1.64)], reciprocity [OR = 1.55, 95% CI (1.29-1.87)], support from individual [OR = 1.96, 95% CI (1.61-2.38)] and social contact [OR = 3.27, 95% CI (2.70-3.97)]. In the full adjusted model, migrant elderly were more likely to be mentally unhealthy [OR = 1.85, 95% CI (1.44-2.36)] compared with urban elderly. Migrant elderly suffered from a lower mental health status and social capital than their urban counterparts in the emigrating city. Attention should focus on improving the social capital and mental health of this growing population.

In-hospital mortality after pre-treatment with antiplatelet agents or oral anticoagulants and hematoma evacuation of intracerebral hematomas.

PubMed

Stein, Marco; Misselwitz, Björn; Hamann, Gerhard F; Kolodziej, Malgorzata; Reinges, Marcus H T; Uhl, Eberhard

2016-04-01

Pre-treatment with antiplatelet agents is described to be a risk factor for mortality after spontaneous intracerebral hemorrhage (ICH). However, the impact of antithrombotic agents on mortality in patients who undergo hematoma evacuation compared to conservatively treated patients with ICH remains controversial. This analysis is based on a prospective registry for quality assurance in stroke care in the State of Hesse, Germany. Patients' data were collected between January 2008 and December 2012. Only patients with the diagnosis of spontaneous ICH were included (International Classification of Diseases 10th Revision codes I61.0-I61.9). Predictors of in-hospital mortality were determined by univariate analysis. Predictors with P<0.1 were included in a binary logistic regression model. The binary logistic regression model was adjusted for age, initial Glasgow Coma Score (GCS), the presence of intraventricular hemorrhage (IVH), and pre-ICH disability prior to ictus. In 8,421 patients with spontaneous ICH, pre-treatment with oral anticoagulants or antiplatelet agents was documented in 16.3% and 25.1%, respectively. Overall in-hospital mortality was 23.2%. In-hospital mortality was decreased in operatively treated patients compared to conservatively treated patients (11.6% versus 24.0%; P<0.001). Patients with antiplatelet pre-treatment had a significantly higher risk of death during the hospital stay after hematoma evacuation (odds ratio [OR]: 2.5; 95% confidence interval [CI]: 1.24-4.97; P=0.010) compared to patients without antiplatelet pre-treatment treatment (OR: 0.9; 95% CI: 0.79-1.09; P=0.376). In conclusion a higher rate of in-hospital mortality after pre-treatment with antiplatelet agents in combination with hematoma evacuation after spontaneous ICH was observed in the presented cohort. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant

PubMed Central

Fan, L; Liu, S-Y; Li, Q-C; Yu, H; Xiao, X-S

2012-01-01

Objective To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT). Methods 82 pathologically or clinically confirmed fGGOs were retrospectively analysed with regard to demographic data, lesion size and location, attenuation value and MDCT features including shape, margin, interface, internal characteristics and adjacent structure. Differences between benign and malignant fGGOs were analysed using a χ2 test, Fisher's exact test or Mann–Whitney U-test. Morphological characteristics were analysed by binary logistic regression analysis to estimate the likelihood of malignancy. Results There were 21 benign and 61 malignant lesions. No statistical differences were found between benign and malignant fGGOs in terms of demographic data, size, location and attenuation value. The frequency of lobulation (p=0.000), spiculation (p=0.008), spine-like process (p=0.004), well-defined but coarse interface (p=0.000), bronchus cut-off (p=0.003), other air-containing space (p=0.000), pleural indentation (p=0.000) and vascular convergence (p=0.006) was significantly higher in malignant fGGOs than that in benign fGGOs. Binary logistic regression analysis showed that lobulation, interface and pleural indentation were important indicators for malignant diagnosis of fGGO, with the corresponding odds ratios of 8.122, 3.139 and 9.076, respectively. In addition, a well-defined but coarse interface was the most important indicator of malignancy among all interface types. With all three important indicators considered, the diagnostic sensitivity, specificity and accuracy were 93.4%, 66.7% and 86.6%, respectively. Conclusion An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant. PMID:22128130

Prevalence of kidney stones in China: an ultrasonography based cross-sectional study.

PubMed

Zeng, Guohua; Mai, Zanlin; Xia, Shujie; Wang, Zhiping; Zhang, Keqin; Wang, Li; Long, Yongfu; Ma, Jinxiang; Li, Yi; Wan, Show P; Wu, Wenqi; Liu, Yongda; Cui, Zelin; Zhao, Zhijian; Qin, Jing; Zeng, Tao; Liu, Yang; Duan, Xiaolu; Mai, Xin; Yang, Zhou; Kong, Zhenzhen; Zhang, Tao; Cai, Chao; Shao, Yi; Yue, Zhongjin; Li, Shujing; Ding, Jiandong; Tang, Shan; Ye, Zhangqun

2017-07-01

To investigate the prevalence and associated factors of kidney stones among adults in China. A nationwide cross-sectional survey was conducted among individuals aged ≥18 years across China, from May 2013 to July 2014. Participants underwent urinary tract ultrasonographic examinations, completed pre-designed and standardised questionnaires, and provided blood and urine samples for analysis. Kidney stones were defined as particles of ≥4 mm. Prevalence was defined as the proportion of participants with kidney stones and binary logistic regression was used to estimate the associated factors. A total of 12 570 individuals (45.2% men) with a mean (sd, range) age of 48.8 (15.3, 18-96) years were selected and invited to participate in the study. In all, 9310 (40.7% men) participants completed the investigation, with a response rate of 74.1%. The prevalence of kidney stones was 6.4% [95% confidence interval (CI) 5.9, 6.9], and the age- and sex-adjusted prevalence was 5.8% (95% CI 5.3, 6.3; 6.5% in men and 5.1% in women). Binary logistic regression analysis showed that male gender, rural residency, age, family history of urinary stones, concurrent diabetes mellitus and hyperuricaemia, increased consumption of meat, and excessive sweating were all statistically significantly associated with a greater risk of kidney stones. By contrast, consumption of more tea, legumes, and fermented vinegar was statistically significantly associated with a lesser risk of kidney stone formation. Kidney stones are common among Chinese adults, with about one in 17 adults affected currently. Some Chinese dietary habits may lower the risk of kidney stone formation. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Assessment of renal function and electrolytes in patients with thyroid dysfunction in Addis Ababa, Ethiopia: a cross sectional study.

PubMed

Abebe, Nardos; Kebede, Tedla; Wolde, Mistire

2016-01-01

Studies demonstrated that abnormal thyroid functions may result in decreased or increased kidney size, kidney weight, and affect renal functions. In this regard, studies on the association of abnormal thyroid functions and renal function tests are scarcely found in Ethiopia. To assess renal function and electrolytes in patients with thyroid dysfunction, in Addis Ababa, Ethiopia. Cross sectional study was conducted from March 21/2015-May 27/2015 at Arsho Advanced Medical Laboratory. During the study period, 71 patients with thyroid dysfunction were eligible, and socio demographic data collected by structured questionnaire. Then blood sample was collected for thyroid function tests, renal function and blood electrolyte analysis. The collected data was analyzed by SPSS version 20. ANOVA and binary logistic regression were employed to evaluate the mean deference and associations of thyroid hormone with renal function and electrolyte balances. Among the renal function tests, serum uric acid, and creatinine mean values were significantly decreased in hyperthyroid patients; whereas, eGFR mean value was significantly increased in hyperthyroid study patients (P<0.05). Meanwhile, from the electrolyte measurements made, only the mean serum sodium value was significantly increased in hyperthyroid study participants. Binary logistic regression analysis on the association of thyroid dysfunction with electrolyte balance and renal function tests indicated that serum sodium, creatinine, eGFR values and hyperthyroidism have a statistical significant association at AOR 95% CI of 0.141(0.033-0.593, P=0.008); 16.236(3.481-75.739, P=0.001), and 13.797(3.261-58.67, P=0.001) respectively. The current study reveals, thyroid abnormalities may lead to renal function alterations and also may disturb electrolyte balance. Knowledge of this significant association has worthwhile value for clinicians, to manage their patients' optimally.

Clinical outcomes and predictors of response to photodynamic therapy in symptomatic circumscribed choroidal hemangioma: A retrospective case series

PubMed Central

Ho, Yeen-Fey; Chao, Anne; Chen, Kuan-Jen; Wang, Nan-Kai; Liu, Laura; Chen, Yen-Po; Hwang, Yih-Shiou; Wu, Wei-Chi; Lai, Chi-Chun; Chen, Tun-Lu

2018-01-01

Background To investigate the treatment outcomes and predictors of response to photodynamic therapy (PDT) in patients with symptomatic circumscribed hemangioma (CCH). Methods This retrospective case series examined 20 patients with symptomatic CCH (10 submacular CCHs and10 juxtapapillary CCHs) who underwent standard PDT (wavelength: 662 nm; light dose: 50J/cm2; exposure time: 83 sec) with verteporfin (6mg/m2), either as monotherapy (n = 9) or in association with other treatments (n = 11), of which 7 received intravitreal injections (IVI) of anti-vascular endothelial growth factor (anti-VEGF). A post-PDT improvement of at least two lines in best-corrected visual acuity (BCVA) was the primary outcome measure. Predictors of response were investigated with binary logistic regression analysis. Results Seventeen (85%) patients received one PDT session, and three patients (15%) underwent PDT at least twice. Ten patients (50%) achieved the primary outcome of a post-PDT BCVA improvement of at least two lines. Macular atrophy and recalcitrant cystoid macular edema in 2 patients. Binary logistic regression analysis revealed that younger age (< 50 years) (P = 0.033), pre-PDT BCVA of ≧20/200 (P = 0.013), exudative retinal detachment resolved within one month after PDT (P = 0.007), and a thinner post-PDT tumor thickness (P = 0.015) were associated with the achievement of a post-PDT BCVA improvement. Additional treatments to PDT including IVI anti-VEGF did not appear to improve visual and anatomical outcomes. Conclusions Symptomatic CCHs respond generally well to PDT. Patients with younger age (< 50 years), pretreatment BCVA≥ 20/200, and thinner foveal edema are most likely to benefit from this approach. PMID:29851977

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

PubMed

Chen, D G; Pounds, J G

1998-12-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium.

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

PubMed Central

Chen, D G; Pounds, J G

1998-01-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium. PMID:9860894

Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

USGS Publications Warehouse

Quist, M.C.; Rahel, F.J.; Hubert, W.A.

2005-01-01

Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

Predictors associated with the willingness to take human papilloma virus vaccination.

PubMed

Naing, Cho; Pereira, Joanne; Abe, Tatsuki; Eh Zhen Wei, Daniel; Rahman Bajera, Ibrizah Binti Abdul; Kavinda Perera, Undugodage Heshan

2012-04-01

Human papilloma virus vaccine is considered to be the primary form of cervical cancer prevention. The objectives were (1) to determine knowledge about, and perception of human papilloma virus infection in relation to cervical cancer, (2) to explore the intention of the community to be vaccinated with human papilloma virus vaccine, and (3) to identify variables that could predict the likelihood of uptake of the vaccine. A cross-sectional survey was carried out in a semi-urban Town of Malaysia, using a pre-tested structured questionnaire. Summary statistics, Pearson chi-square test and a binary logistic regression were used for data analysis. A total of 232 respondents were interviewed. Overall, only a few had good knowledge related to human papilloma virus (14%) or vaccination (8%). Many had misconceptions that it could be transmitted through blood transfusion (57%). Sixty percent had intention to take vaccination. In the binary logistic model, willingness to take vaccination was significant with 'trusts that vaccination would be effective for prevention of cervical cancer' (P = 0.001), 'worries for themselves' (P < 0.001) or 'their family members' (P = 0.003) and 'being Indian ethnicity' (P = 0.024). The model could fairly predict the likelihood of uptake of the vaccine (Cox & Snell R(2) = .415; Nagelkerke R(2) = 0.561). Results indicate that intensive health education dispelling misconception and risk perception towards human papilloma virus infection and cervical cancer would be helpful to increase the acceptability of vaccination program.

Three quantitative approaches to the diagnosis of abdominal pain in children: practical applications of decision theory.

PubMed

Klein, M D; Rabbani, A B; Rood, K D; Durham, T; Rosenberg, N M; Bahr, M J; Thomas, R L; Langenburg, S E; Kuhns, L R

2001-09-01

The authors compared 3 quantitative methods for assisting clinicians in the differential diagnosis of abdominal pain in children, where the most common important endpoint is whether the patient has appendicitis. Pretest probability in different age and sex groups were determined to perform Bayesian analysis, binary logistic regression was used to determine which variables were statistically significantly likely to contribute to a diagnosis, and recursive partitioning was used to build decision trees with quantitative endpoints. The records of all children (1,208) seen at a large urban emergency department (ED) with a chief complaint of abdominal pain were immediately reviewed retrospectively (24 to 72 hours after the encounter). Attempts were made to contact all the patients' families to determine an accurate final diagnosis. A total of 1,008 (83%) families were contacted. Data were analyzed by calculation of the posttest probability, recursive partitioning, and binary logistic regression. In all groups the most common diagnosis was abdominal pain (ICD-9 Code 789). After this, however, the order of the most common final diagnoses for abdominal pain varied significantly. The entire group had a pretest probability of appendicitis of 0.06. This varied with age and sex from 0.02 in boys 2 to 5 years old to 0.16 in boys older than 12 years. In boys age 5 to 12, recursive partitioning and binary logistic regression agreed on guarding and anorexia as important variables. Guarding and tenderness were important in girls age 5 to 12. In boys age greater than 12, both agreed on guarding and anorexia. Using sensitivities and specificities from the literature, computed tomography improved the posttest probability for the group from.06 to.33; ultrasound improved it from.06 to.48; and barium enema improved it from.06 to.58. Knowing the pretest probabilities in a specific population allows the physician to evaluate the likely diagnoses first. Other quantitative methods can help judge how much importance a certain criterion should have in the decision making and how much a particular test is likely to influence the probability of a correct diagnosis. It now should be possible to make these sophisticated quantitative methods readily available to clinicians via the computer. Copyright 2001 by W.B. Saunders Company.

Work related complaints of neck, shoulder and arm among computer office workers: a cross-sectional evaluation of prevalence and risk factors in a developing country.

PubMed

Ranasinghe, Priyanga; Perera, Yashasvi S; Lamabadusuriya, Dilusha A; Kulatunga, Supun; Jayawardana, Naveen; Rajapakse, Senaka; Katulanda, Prasad

2011-08-04

Complaints of arms, neck and shoulders (CANS) is common among computer office workers. We evaluated an aetiological model with physical/psychosocial risk-factors. We invited 2,500 computer office workers for the study. Data on prevalence and risk-factors of CANS were collected by validated Maastricht-Upper-extremity-Questionnaire. Workstations were evaluated by Occupational Safety and Health Administration (OSHA) Visual-Display-Terminal workstation-checklist. Participants' knowledge and awareness was evaluated by a set of expert-validated questions. A binary logistic regression analysis investigated relationships/correlations between risk-factors and symptoms. Sample size was 2,210. Mean age 30.8 ± 8.1 years, 50.8% were males. The 1-year prevalence of CANS was 56.9%, commonest region of complaint was forearm/hand (42.6%), followed by neck (36.7%) and shoulder/arm (32.0%). In those with CANS, 22.7% had taken treatment from a health care professional, only in 1.1% seeking medical advice an occupation-related injury had been suspected/diagnosed. In addition 9.3% reported CANS-related absenteeism from work, while 15.4% reported CANS causing disruption of normal activities. A majority of evaluated workstations in all participants (88.4%,) and in those with CANS (91.9%) had OSHA non-compliant workstations. In the binary logistic regression analyses female gender, daily computer usage, incorrect body posture, bad work-habits, work overload, poor social support and poor ergonomic knowledge were associated with CANS and its' severity In a multiple logistic regression analysis controlling for age, gender and duration of occupation, incorrect body posture, bad work-habits and daily computer usage were significant independent predictors of CANS. The prevalence of work-related CANS among computer office workers in Sri Lanka, a developing, South Asian country is high and comparable to prevalence in developed countries. Work-related physical factors, psychosocial factors and lack of awareness were all important associations of CANS and effective preventive strategies need to address all three areas.

Cerebrospinal fluid ferritin and albumin index: potential candidates for scoring system to differentiate between bacterial and viral meningitis in children.

PubMed

Jebamalar, Angelin A; Prabhat; Balakrishnapillai, Agiesh K; Parmeswaran, Narayanan; Dhiman, Pooja; Rajendiran, Soundravally

2016-07-01

To evaluate the diagnostic role of cerebrospinal fluid (CSF) ferritin and albumin index (AI = CSF albumin/serum albumin × 1000) in differentiating acute bacterial meningitis (ABM) from acute viral meningitis (AVM) in children. The study included 42 cases each of ABM and AVM in pediatric age group. Receiver operating characteristic (ROC) analysis was carried out for CSF ferritin and AI. Binary logistic regression was also done. CSF ferritin and AI were found significantly higher in ABM compared to AVM. Model obtained using AI and CSF ferritin along with conventional criteria is better than existing models.

Neuronal autoantibodies in mesial temporal lobe epilepsy with hippocampal sclerosis.

PubMed

Vanli-Yavuz, Ebru Nur; Erdag, Ece; Tuzun, Erdem; Ekizoglu, Esme; Baysal-Kirac, Leyla; Ulusoy, Canan; Peach, Sian; Gundogdu, Gokcen; Sencer, Serra; Sencer, Altay; Kucukali, Cem Ismail; Bebek, Nerses; Gurses, Candan; Gokyigit, Aysen; Baykan, Betul

2016-07-01

Our aim was to investigate the prevalence of neuronal autoantibodies (NAbs) in a large consecutive series with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) and to elucidate the clinical and laboratory clues for detection of NAbs in this prototype of frequent, drug-resistant epilepsy syndrome. Consecutive patients diagnosed with MTLE fulfilling the MRI criteria for HS were enrolled. The sera of patients and various control groups (80 subjects) were tested for eight NAbs after ethical approval and signed consents. Brain tissues obtained from surgical specimens were also investigated by immunohistochemical analysis for the presence of inflammatory infiltrates. The features of seropositive versus seronegative groups were compared and binary logistic regression analysis was performed to explore the differentiating variables. We found antibodies against antigens, contactin-associated protein-like 2 in 11 patients, uncharacterised voltage-gated potassium channel (VGKC)-complex antigens in four patients, glycine receptor (GLY-R) in 5 patients, N-methyl-d-aspartate receptor in 4 patients and γ-aminobutyric acid receptor A in 1 patient of 111 patients with MTLE-HS and none of the control subjects. The history of status epilepticus, diagnosis of psychosis and positron emission tomography or single-photon emission CT findings in temporal plus extratemporal regions were found significantly more frequently in the seropositive group. Binary logistic regression analysis disclosed that status epilepticus, psychosis and cognitive dysfunction were statistically significant variables to differentiate between the VGKC-complex subgroup versus seronegative group. This first systematic screening study of various NAbs showed 22.5% seropositivity belonging mostly to VGKC-complex antibodies in a large consecutive series of patients with MTLE-HS. Our results indicated a VGKC-complex autoimmunity-related subgroup in the syndrome of MTLE-HS. 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/

Automated particle identification through regression analysis of size, shape and colour

NASA Astrophysics Data System (ADS)

Rodriguez Luna, J. C.; Cooper, J. M.; Neale, S. L.

2016-04-01

Rapid point of care diagnostic tests and tests to provide therapeutic information are now available for a range of specific conditions from the measurement of blood glucose levels for diabetes to card agglutination tests for parasitic infections. Due to a lack of specificity these test are often then backed up by more conventional lab based diagnostic methods for example a card agglutination test may be carried out for a suspected parasitic infection in the field and if positive a blood sample can then be sent to a lab for confirmation. The eventual diagnosis is often achieved by microscopic examination of the sample. In this paper we propose a computerized vision system for aiding in the diagnostic process; this system used a novel particle recognition algorithm to improve specificity and speed during the diagnostic process. We will show the detection and classification of different types of cells in a diluted blood sample using regression analysis of their size, shape and colour. The first step is to define the objects to be tracked by a Gaussian Mixture Model for background subtraction and binary opening and closing for noise suppression. After subtracting the objects of interest from the background the next challenge is to predict if a given object belongs to a certain category or not. This is a classification problem, and the output of the algorithm is a Boolean value (true/false). As such the computer program should be able to "predict" with reasonable level of confidence if a given particle belongs to the kind we are looking for or not. We show the use of a binary logistic regression analysis with three continuous predictors: size, shape and color histogram. The results suggest this variables could be very useful in a logistic regression equation as they proved to have a relatively high predictive value on their own.

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Examining the Link Between Public Transit Use and Active Commuting

PubMed Central

Bopp, Melissa; Gayah, Vikash V.; Campbell, Matthew E.

2015-01-01

Background: An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. Methods: A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Results: Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. Conclusions: This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related. PMID:25898405

Examining the link between public transit use and active commuting.

PubMed

Bopp, Melissa; Gayah, Vikash V; Campbell, Matthew E

2015-04-17

An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related.

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

[Willingness of Patients with Obesity to Use New Media in Rehabilitation Aftercare].

PubMed

Dorow, M; Löbner, M; Stein, J; Kind, P; Markert, J; Keller, J; Weidauer, E; Riedel-Heller, S G

2017-06-01

Digital media offer new possibilities in rehabilitation aftercare. This study investigates the rehabilitants' willingness to use new media (sms, internet, social networks) in rehabilitation aftercare and factors that are associated with the willingness to use media-based aftercare. 92 rehabilitants (patients with obesity) filled in a questionnaire on the willingness to use new media in rehabilitation aftercare. In order to identify influencing factors, binary logistic regression models were calculated. 3 quarters of the rehabilitants (76.1%) reported that they would be willing to use new media in rehabilitation aftercare. The binary logistic regression model yielded two factors that were associated with the willingness to use media-based aftercare: the possession of a smartphone and the willingness to receive telephone counseling for aftercare. The majority of the rehabilitants was willing to use new media in rehabilitation aftercare. The reasons for refusal of media-based aftercare need to be examined more closely. © Georg Thieme Verlag KG Stuttgart · New York.

Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis.

PubMed

Vavougios, George D; George D, George; Pastaka, Chaido; Zarogiannis, Sotirios G; Gourgoulianis, Konstantinos I

2016-02-01

Phenotyping obstructive sleep apnea syndrome's comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data-driven approach. Data from 1472 consecutive patient records were recovered from our hospital's database. Categorical principal component analysis and two-step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one-way analysis of variance with Bonferroni correction and chi-square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, 'healthy, reporting sleeping related symptoms'; B, 'mild obstructive sleep apnea syndrome without significant comorbidities'; C1: 'moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities'; C2: 'moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke'; D1: 'severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension'; and D2: 'severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index'. Clusters differed significantly in apnea-hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one-way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at-risk groups. Finally, determining predictors of comorbidity for the moderate and severe strata of these phenotypes implies a need to take these factors into account when considering obstructive sleep apnea syndrome treatment options. © 2015 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

Image encryption with chaotic map and Arnold transform in the gyrator transform domains

NASA Astrophysics Data System (ADS)

Sang, Jun; Luo, Hongling; Zhao, Jun; Alam, Mohammad S.; Cai, Bin

2017-05-01

An image encryption method combing chaotic map and Arnold transform in the gyrator transform domains was proposed. Firstly, the original secret image is XOR-ed with a random binary sequence generated by a logistic map. Then, the gyrator transform is performed. Finally, the amplitude and phase of the gyrator transform are permutated by Arnold transform. The decryption procedure is the inverse operation of encryption. The secret keys used in the proposed method include the control parameter and the initial value of the logistic map, the rotation angle of the gyrator transform, and the transform number of the Arnold transform. Therefore, the key space is large, while the key data volume is small. The numerical simulation was conducted to demonstrate the effectiveness of the proposed method and the security analysis was performed in terms of the histogram of the encrypted image, the sensitiveness to the secret keys, decryption upon ciphertext loss, and resistance to the chosen-plaintext attack.

Efficient logistic regression designs under an imperfect population identifier.

PubMed

Albert, Paul S; Liu, Aiyi; Nansel, Tonja

2014-03-01

Motivated by actual study designs, this article considers efficient logistic regression designs where the population is identified with a binary test that is subject to diagnostic error. We consider the case where the imperfect test is obtained on all participants, while the gold standard test is measured on a small chosen subsample. Under maximum-likelihood estimation, we evaluate the optimal design in terms of sample selection as well as verification. We show that there may be substantial efficiency gains by choosing a small percentage of individuals who test negative on the imperfect test for inclusion in the sample (e.g., verifying 90% test-positive cases). We also show that a two-stage design may be a good practical alternative to a fixed design in some situations. Under optimal and nearly optimal designs, we compare maximum-likelihood and semi-parametric efficient estimators under correct and misspecified models with simulations. The methodology is illustrated with an analysis from a diabetes behavioral intervention trial. © 2013, The International Biometric Society.

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

PubMed

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

2017-03-01

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

The logistic model for predicting the non-gonoactive Aedes aegypti females.

PubMed

Reyes-Villanueva, Filiberto; Rodríguez-Pérez, Mario A

2004-01-01

To estimate, using logistic regression, the likelihood of occurrence of a non-gonoactive Aedes aegypti female, previously fed human blood, with relation to body size and collection method. This study was conducted in Monterrey, Mexico, between 1994 and 1996. Ten samplings of 60 mosquitoes of Ae. aegypti females were carried out in three dengue endemic areas: six of biting females, two of emerging mosquitoes, and two of indoor resting females. Gravid females, as well as those with blood in the gut were removed. Mosquitoes were taken to the laboratory and engorged on human blood. After 48 hours, ovaries were dissected to register whether they were gonoactive or non-gonoactive. Wing-length in mm was an indicator for body size. The logistic regression model was used to assess the likelihood of non-gonoactivity, as a binary variable, in relation to wing-length and collection method. Of the 600 females, 164 (27%) remained non-gonoactive, with a wing-length range of 1.9-3.2 mm, almost equal to that of all females (1.8-3.3 mm). The logistic regression model showed a significant likelihood of a female remaining non-gonoactive (Y=1). The collection method did not influence the binary response, but there was an inverse relationship between non-gonoactivity and wing-length. Dengue vector populations from Monterrey, Mexico display a wide-range body size. Logistic regression was a useful tool to estimate the likelihood for an engorged female to remain non-gonoactive. The necessity for a second blood meal is present in any female, but small mosquitoes are more likely to bite again within a 2-day interval, in order to attain egg maturation. The English version of this paper is available too at: http://www.insp.mx/salud/index.html.

The Mantel-Haenszel procedure revisited: models and generalizations.

PubMed

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.

The Mantel-Haenszel Procedure Revisited: Models and Generalizations

PubMed Central

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented. PMID:23516463

Body Image Satisfaction as a Physical Activity Indicator in University Students.

PubMed

Ramos-Jiménez, Arnulfo; Hernández-Torres, Rosa P; Urquidez-Romero, René; Wall-Medrano, Abraham; Villalobos-Molina, Rafael

2017-09-01

We examined the association of body image satisfaction (BIS) with physical activity (PA) in university athletes and non-athletes from northern Mexico. In a non-probability cross-sectional study, 294 participants (51% male, 41% athletes; 18-35 years old) completed 2 self-administered questionnaires to evaluate BIS and PA. We categorized somatotypes (endomorphy-mesomorphy-ectomorphy) by international standardized anthropometry. Data analysis included the Mann-Whitney U test, χ2test, Kendall's Tau-b correlation, binary logistic regression analysis, and receiver operating characteristic (ROC) curves. Self-perceived sports abilities and desirable body shape predicted 30% of sports participation in students, whereas an endomorphic shape (<5.4 units) and being male predicted 15.4% of sports participation. BIS was a reliable indicator of sports participation among these university students.

Statistical analysis of subjective preferences for video enhancement

NASA Astrophysics Data System (ADS)

Woods, Russell L.; Satgunam, PremNandhini; Bronstad, P. Matthew; Peli, Eli

2010-02-01

Measuring preferences for moving video quality is harder than for static images due to the fleeting and variable nature of moving video. Subjective preferences for image quality can be tested by observers indicating their preference for one image over another. Such pairwise comparisons can be analyzed using Thurstone scaling (Farrell, 1999). Thurstone (1927) scaling is widely used in applied psychology, marketing, food tasting and advertising research. Thurstone analysis constructs an arbitrary perceptual scale for the items that are compared (e.g. enhancement levels). However, Thurstone scaling does not determine the statistical significance of the differences between items on that perceptual scale. Recent papers have provided inferential statistical methods that produce an outcome similar to Thurstone scaling (Lipovetsky and Conklin, 2004). Here, we demonstrate that binary logistic regression can analyze preferences for enhanced video.

Adolescent sexual victimization: a prospective study on risk factors for first time sexual assault.

PubMed

Bramsen, Rikke Holm; Lasgaard, Mathias; Koss, Mary P; Elklit, Ask; Banner, Jytte

2012-09-01

The present study set out to investigate predictors of first time adolescent peer-on-peer sexual victimization (APSV) among 238 female Grade 9 students from 30 schools in Denmark. A prospective research design was utilized to examine the relationship among five potential predictors as measured at baseline and first time APSV during a 6-month period. Data analysis was a binary logistic regression analysis. Number of sexual partners and displaying sexual risk behaviors significantly predicted subsequent first time peer-on-peer sexual victimization, whereas a history of child sexual abuse, early sexual onset and failing to signal sexual boundaries did not. The present study identifies specific risk factors for first time sexual victimization that are potentially changeable. Thus, the results may inform prevention initiatives targeting initial experiences of APSV.

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

The special case of the 2 × 2 table: asymptotic unconditional McNemar test can be used to estimate sample size even for analysis based on GEE.

PubMed

Borkhoff, Cornelia M; Johnston, Patrick R; Stephens, Derek; Atenafu, Eshetu

2015-07-01

Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. The asymptotic unconditional McNemar test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar test can be used to estimate sample size. We do not recommend using an exact McNemar test. Copyright © 2015 Elsevier Inc. All rights reserved.

Factors associated with adult poisoning in northern Malaysia: a case-control study.

PubMed

Fathelrahman, A I; Ab Rahman, A F; Zain, Z Mohd; Tengku, M A

2006-04-01

Data on adult risk factors associated with drug or chemical poisonings in Malaysia are scarce. The objective of the study was to identify possible risk factors associated with adult admissions to the Penang General Hospital (PGH) due to chemical poisoning and/or drug overdose. The present study was a case-control study, conducted over 18 weeks. One hundred acutely poisoned adult patients admitted to PGH during the period from September 2003 to February 2004 were considered as cases. Two hundred patients admitted to the same medical wards for other illnesses, during the same period, were matched for age and gender with the poisoned cases and thus selected as controls. McNemar test and binary logistic were used for univariate analysis and logistic regression analysis for multivariate analyses. The odds ratio (OR) and its 95% confidence interval (95% CI) were calculated for each predictor variable. Positive histories of psychiatric illness and previous poisoning, problems in boy/girl friend relationships, family problems, marital problems, Indian ethnicity, Chinese ethnicity, living in rented houses and living in a household with less than five people were significant risk factors associated with adult admissions due to poisoning.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA.

PubMed

Wu, Zheyang; Zhao, Hongyu

2012-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA

PubMed Central

Wu, Zheyang; Zhao, Hongyu

2013-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies. PMID:23956610

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications

PubMed Central

Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram

2016-01-01

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks’ back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps’ detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies. PMID:26978523

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications.

PubMed

Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram

2016-01-01

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

Predictors of Employment Outcomes for State-Federal Vocational Rehabilitation Consumers with HIV/AIDS

ERIC Educational Resources Information Center

Jung, Youngoh; Schaller, James; Bellini, James

2010-01-01

In this study, the authors investigated the effects of demographic, medical, and vocational rehabilitation service variables on employment outcomes of persons living with HIV/AIDS. Binary logistic regression analyses were conducted to determine predictors of employment outcomes using two groups drawn from Rehabilitation Services Administration…

Who Benefits from Tuition Discounts at Public Universities?

ERIC Educational Resources Information Center

Hillman, Nicholas W.

2010-01-01

This article uses data from the 2004 National Postsecondary Student Aid Study to provide insight about the range of tuition discounting practices at public institutions. Specifically, it examines the characteristics of students who receive tuition discounts from public four-year colleges and universities. A binary logistic regression is applied to…

An Examination of Master's Student Retention & Completion

ERIC Educational Resources Information Center

Barry, Melissa; Mathies, Charles

2011-01-01

This study was conducted at a research-extensive public university in the southeastern United States. It examined the retention and completion of master's degree students across numerous disciplines. Results were derived from a series of descriptive statistics, T-tests, and a series of binary logistic regression models. The findings from binary…

Graduate Unemployment in South Africa: Social Inequality Reproduced

ERIC Educational Resources Information Center

Baldry, Kim

2016-01-01

In this study, I examine the influence of demographic and educational characteristics of South African graduates on their employment/unemployment status. A sample of 1175 respondents who graduated between 2006 and 2012 completed an online survey. Using binary logistic regression, the strongest determinants of unemployment were the graduates' race,…

Commitment of Licensed Social Workers to Aging Practice

ERIC Educational Resources Information Center

Simons, Kelsey; Bonifas, Robin; Gammonley, Denise

2011-01-01

This study sought to identify client, professional, and employment characteristics that enhance licensed social workers' commitment to aging practice. A series of binary logistic regressions were performed using data from 181 licensed, full-time social workers who reported aging as their primary specialty area as part of the 2004 NASW's national…

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

Quality management and job related factors predicting satisfaction of dental clinic staff in Estonia.

PubMed

Merisalu, Eda; Männik, Georg; Põlluste, Kaja

2014-01-01

The aim of the study was to explore the role of managerial style, work environment factors and burnout in determining job satisfaction during the implementation of quality improvement activities in a dental clinic. Quantitative research was carried out using a prestructured anonymous questionnaire to survey 302 respondents in Kaarli Dental Clinic, Estonia. Dental clinic staff assessed job satisfaction, managerial style, work stress and burnout levels through the implementation period of ISO 9000 quality management system in 2003 and annually during 2006-2009. Binary logistic regression was used to explain the impact of satisfaction with management and work organisation, knowledge about managerial activities, work environment and psychosocial stress and burnout on job satisfaction. The response rate limits were between 60% and 89.6%. Job satisfaction increased significantly from 2003 to 2006 and the percentage of very satisfied staff increased from 17 to 38 (p<0.01) over this period. In 2007, the proportion of very satisfied people dropped to 21% before increasing again in 2008-2009 (from 24% to 35%). Binary logistic regression analysis resulted in a model that included five groups of factors: managerial support, information about results achieved and progress to goals, work organisation and working environment, as well as factors related to career, security and planning. The average scores of emotional exhaustion showed significant decrease, correlating negatively with job satisfaction (p<0.05). The implementation of quality improvement activities in the Kaarli Dental Clinic has improved the work environment by decreasing burnout symptoms and increased job satisfaction in staff.

Relationship between postoperative lung atelectasis and position of the endotracheal tube in pediatric living-donor liver transplantation.

PubMed

Lee, H-Y; Lu, C-H; Lu, H-F; Chen, C-L; Wang, C-H; Cheng, K-W; Wu, S-C; Jawan, B; Huang, C-J

2012-05-01

The aims of current study were: 1) to evaluate the incidence of lung atelectasis; and 2) to investigate whether or not the position of the endotracheal (ET) tube is associated with this complication. The medical records and chest roentgenograms of 183 pediatric patients who underwent living-donor liver transplantation were retrospectively reviewed and analyzed. Patients without atelectasis were grouped in group I (GI) and those with atelectasis in group II (GII). The patients' characteristics and ET tube level between groups were compared with unpaired Student's t test. Multiple binary logistic regressions were also performed to identify the important risk factors associated with lung atelectasis. Right upper lung (RUL) atelectsis could be found in ET tube at any level from T1 to T5, with incidence rates of 12.7%, 15.2%, 26.3%, 6.7%, and 100% for T1, T2, T3, T4, and T5, respectively. The incidence of atelectasis is 16.6%, and all of the atelectasis occurred in the RUL. No significant difference between groups was observed in the patients' characteristics, except for the amount of preoperative ascites. The likelihood of this risk factor could not be confirmed by multivariate binary logistic regression analysis. The incidence of lung atelectasis in our study was 16.6%, which all occurred in the RUL. No predictive risk factor from the patients' characteristics could be found, and no correlation between the level of the ET tube and the occurrence of RUL atelectasis could be observed. Copyright © 2012 Elsevier Inc. All rights reserved.

Malnutrition risk predicts recovery of full oral intake among older adult stroke patients undergoing enteral nutrition: Secondary analysis of a multicentre survey (the APPLE study).

PubMed

Nishioka, Shinta; Okamoto, Takatsugu; Takayama, Masako; Urushihara, Maki; Watanabe, Misuzu; Kiriya, Yumiko; Shintani, Keiko; Nakagomi, Hiromi; Kageyama, Noriko

2017-08-01

Whether malnutrition risk correlates with recovery of swallowing function of convalescent stroke patients is unknown. This study was conducted to clarify whether malnutrition risks predict achievement of full oral intake in convalescent stroke patients undergoing enteral nutrition. We conducted a secondary analysis of 466 convalescent stroke patients, aged 65 years or over, who were undergoing enteral nutrition. Patients were extracted from the "Algorithm for Post-stroke Patients to improve oral intake Level; APPLE" study database compiled at the Kaifukuki (convalescent) rehabilitation wards. Malnutrition risk was determined by the Geriatric Nutritional Risk Index as follows: severe (<82), moderate (82 to <92), mild (92 to <98), and no malnutrition risks (≥98). Swallowing function was assessed by Fujishima's swallowing grade (FSG) on admission and discharge. The primary outcome was achievement of full oral intake, indicated by FSG ≥ 7. Binary logistic regression analysis was performed to identify predictive factors, including malnutrition risk, for achieving full oral intake. Estimated hazard risk was computed by Cox's hazard model. Of the 466 individuals, 264 were ultimately included in this study. Participants with severe malnutrition risk showed a significantly lower proportion of achievement of full oral intake than lower severity groups (P = 0.001). After adjusting for potential confounders, binary logistic regression analysis showed that patients with severe malnutrition risk were less likely to achieve full oral intake (adjusted odds ratio: 0.232, 95% confidence interval [95% CI]: 0.047-1.141). Cox's proportional hazard model revealed that severe malnutrition risk was an independent predictor of full oral intake (adjusted hazard ratio: 0.374, 95% CI: 0.166-0.842). Compared to patients who did not achieve full oral intake, patients who achieved full oral intake had significantly higher energy intake, but there was no difference in protein intake and weight change. Severe malnutrition risk independently predicts the achievement of full oral intake in convalescent stroke patients undergoing enteral nutrition. Copyright © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Exploring definitions of financial abuse in elderly Korean immigrants: the contribution of traditional cultural values.

PubMed

Lee, Hee Yun; Lee, Sang E; Eaton, Charissa K

2012-10-01

The purpose of this study is to explore the cultural definitions of financial abuse from the perspective of 124 elderly Korean immigrants and to examine the role of traditional cultural values in their definitions by using a mixed methods approach. The qualitative analysis generated four themes relevant to definition of financial abuse. A binary logistic regression indicated that those with stronger cultural adherence to traditional values had higher odds of providing culture-based definitions of financial abuse. Education is needed for health professionals, social service providers, and adult protective workers to increase their understanding of culture-specific experiences of financial abuse among ethnic minority elders.

Do Concomitant Cranium and Axis Injuries Predict Worse Outcome? A Trauma Database Quantitative Analysis

PubMed Central

Chittiboina, Prashant; Banerjee, Anirban Deep; Nanda, Anil

2011-01-01

We performed a trauma database analysis to identify the effect of concomitant cranial injuries on outcome in patients with fractures of the axis. We identified patients with axis fractures over a 14-year period. A binary outcome measure was used. Univariate and multiple logistic regression analysis were performed. There were 259 cases with axis fractures. Closed head injury was noted in 57% and skull base trauma in 14%. Death occurred in 17 cases (6%). Seventy-two percent had good outcome. Presence of abnormal computed tomography head findings, skull base fractures, and visceral injury was significantly associated with poor outcome. Skull base injury in association with fractures of the axis is a significant independent predictor of worse outcomes, irrespective of the severity of the head injury. We propose that presence of concomitant cranial and upper vertebral injuries require careful evaluation in view of the associated poor prognosis. PMID:22470268

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.

PubMed

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults' belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Sequence analysis to assess labour market participation following vocational rehabilitation: an observational study among patients sick-listed with low back pain from a randomised clinical trial in Denmark

PubMed Central

Lindholdt, Louise; Labriola, Merete; Nielsen, Claus Vinther; Horsbøl, Trine Allerslev; Lund, Thomas

2017-01-01

Introduction The return-to-work (RTW) process after long-term sickness absence is often complex and long and implies multiple shifts between different labour market states for the absentee. Standard methods for examining RTW research typically rely on the analysis of one outcome measure at a time, which will not capture the many possible states and transitions the absentee can go through. The purpose of this study was to explore the potential added value of sequence analysis in supplement to standard regression analysis of a multidisciplinary RTW intervention among patients with low back pain (LBP). Methods The study population consisted of 160 patients randomly allocated to either a hospital-based brief or a multidisciplinary intervention. Data on labour market participation following intervention were obtained from a national register and analysed in two ways: as a binary outcome expressed as active or passive relief at a 1-year follow-up and as four different categories for labour market participation. Logistic regression and sequence analysis were performed. Results The logistic regression analysis showed no difference in labour market participation for patients in the two groups after 1 year. Applying sequence analysis showed differences in subsequent labour market participation after 2 years after baseline in favour of the brief intervention group versus the multidisciplinary intervention group. Conclusion The study indicated that sequence analysis could provide added analytical value as a supplement to traditional regression analysis in prospective studies of RTW among patients with LBP. PMID:28729315

Bayesian inference for unidirectional misclassification of a binary response trait.

PubMed

Xia, Michelle; Gustafson, Paul

2018-03-15

When assessing association between a binary trait and some covariates, the binary response may be subject to unidirectional misclassification. Unidirectional misclassification can occur when revealing a particular level of the trait is associated with a type of cost, such as a social desirability or financial cost. The feasibility of addressing misclassification is commonly obscured by model identification issues. The current paper attempts to study the efficacy of inference when the binary response variable is subject to unidirectional misclassification. From a theoretical perspective, we demonstrate that the key model parameters possess identifiability, except for the case with a single binary covariate. From a practical standpoint, the logistic model with quantitative covariates can be weakly identified, in the sense that the Fisher information matrix may be near singular. This can make learning some parameters difficult under certain parameter settings, even with quite large samples. In other cases, the stronger identification enables the model to provide more effective adjustment for unidirectional misclassification. An extension to the Poisson approximation of the binomial model reveals the identifiability of the Poisson and zero-inflated Poisson models. For fully identified models, the proposed method adjusts for misclassification based on learning from data. For binary models where there is difficulty in identification, the method is useful for sensitivity analyses on the potential impact from unidirectional misclassification. Copyright © 2017 John Wiley & Sons, Ltd.

America's Democracy Colleges: The Civic Engagement of Community College Students

ERIC Educational Resources Information Center

Angeli Newell, Mallory

2014-01-01

This study explored the civic engagement of current two- and four-year students to explore whether differences exist between the groups and what may explain the differences. Using binary logistic regression and Ordinary Least Squares regression it was found that community-based engagement was lower for two- than four-year students, though…

Attitudes towards Participation in Business Development Programmes: An Ethnic Comparison in Sweden

ERIC Educational Resources Information Center

Abbasian, Saeid; Yazdanfar, Darush

2015-01-01

Purpose: The aim of the study is to investigate whether there are any differences between the attitudes towards participation in development programmes of entrepreneurs who are immigrants and those who are native-born. Design/methodology/approach: Several statistical methods, including a binary logistic regression model, were used to analyse a…

2004 Carolyn Sherif Award Address: Heart Disease and Gender Inequity

ERIC Educational Resources Information Center

Travis, Cheryl Brown

2005-01-01

Individual patient records from the National Hospital Discharge Survey for 1988 and 1998 comprising approximately 10 million cases were the basis for a binary logistic regression model to predict coronary artery bypass graft. Patterns in 1988 and in 1998 indicated a dramatic and pernicious gender discrepancy in medical decisions involving bypass…

Factors Affecting Code Status in a University Hospital Intensive Care Unit

ERIC Educational Resources Information Center

Van Scoy, Lauren Jodi; Sherman, Michael

2013-01-01

The authors collected data on diagnosis, hospital course, and end-of-life preparedness in patients who died in the intensive care unit (ICU) with "full code" status (defined as receiving cardiopulmonary resuscitation), compared with those who didn't. Differences were analyzed using binary and stepwise logistic regression. They found no…

Comparison between students and residents on determinants of willingness to separate waste and waste separation behaviour in Zhengzhou, China.

PubMed

Dai, Xiaoping; Han, Yuping; Zhang, Xiaohong; Hu, Wei; Huang, Liangji; Duan, Wenpei; Li, Siyi; Liu, Xiaolu; Wang, Qian

2017-09-01

A better understanding of willingness to separate waste and waste separation behaviour can aid the design and improvement of waste management policies. Based on the intercept questionnaire survey data of undergraduate students and residents in Zhengzhou City of China, this article compared factors affecting the willingness and behaviour of students and residents to participate in waste separation using two binary logistic regression models. Improvement opportunities for waste separation were also discussed. Binary logistic regression results indicate that knowledge of and attitude to waste separation and acceptance of waste education significantly affect the willingness of undergraduate students to separate waste, and demographic factors, such as gender, age, education level, and income, significantly affect the willingness of residents to do so. Presence of waste-specific bins and attitude to waste separation are drivers of waste separation behaviour for both students and residents. Improved education about waste separation and facilities are effective to stimulate waste separation, and charging on unsorted waste may be an effective way to improve it in Zhengzhou.

Multidimensional Ultrasound Imaging of the Wrist: Changes of Shape and Displacement of the Median Nerve and Tendons in Carpal Tunnel Syndrome

PubMed Central

Filius, Anika; Scheltens, Marjan; Bosch, Hans G.; van Doorn, Pieter A.; Stam, Henk J.; Hovius, Steven E.R.; Amadio, Peter C.; Selles, Ruud W.

2015-01-01

Dynamics of structures within the carpal tunnel may alter in carpal tunnel syndrome (CTS) due to fibrotic changes and increased carpal tunnel pressure. Ultrasound can visualize these potential changes, making ultrasound potentially an accurate diagnostic tool. To study this, we imaged the carpal tunnel of 113 patients and 42 controls. CTS severity was classified according to validated clinical and nerve conduction study (NCS) classifications. Transversal and longitudinal displacement and shape (changes) were calculated for the median nerve, tendons and surrounding tissue. To predict diagnostic value binary logistic regression modeling was applied. Reduced longitudinal nerve displacement (p≤0.019), increased nerve cross-sectional area (p≤0.006) and perimeter (p≤0.007), and a trend of relatively changed tendon displacements were seen in patients. Changes were more convincing when CTS was classified as more severe. Binary logistic modeling to diagnose CTS using ultrasound showed a sensitivity of 70-71% and specificity of 80-84%. In conclusion, CTS patients have altered dynamics of structures within the carpal tunnel. PMID:25865180

Non-specific low back pain: occupational or lifestyle consequences?

PubMed

Stričević, Jadranka; Papež, Breda Jesenšek

2015-12-01

Nursing occupation was identified as a risk occupation for the development of low back pain (LBP). The aim of our study was to find out how much occupational factors influence the development of LBP in hospital nursing personnel. Non-experimental approach with a cross-sectional survey and statistical analysis. Nine hundred questionnaires were distributed among nursing personnel, 663 were returned and 659 (73.2 %) were considered for the analysis. Univariate and multivariate statistics for LBP risk was calculated by the binary logistic regression. The χ(2), influence factor, 95 % confidence interval and P value were calculated. Multivariate binary logistic regression was calculated by the Wald method to omit insignificant variables. Not performing exercises represented the highest risk for the development of LBP (OR 2.8, 95 % CI 1.7-4.4; p < 0.001). The second and third ranked risk factors were frequent manual lifting > 10 kg (OR 2.4, 95 % CI 1.5-3.8; p < 0.001) and duration of employment ≥ 19 years (OR 2.4, 95 % CI 1.6-3.7; p < 0.001). The fourth ranked risk factor was better physical condition by frequent recreation and sports, which reduced the risk for the development of LBP (OR 0.4, 95 % CI 0.3-0.7; p = 0.001). Work with the computer ≥ 2 h per day as last significant risk factor also reduced the risk for the development of LBP (OR 0.6, 95 % CI 0.4-0.1; p = 0.049). Risk factors for LBP established in our study (exercises, duration of employment, frequent manual lifting, recreation and sports and work with the computer) are not specifically linked to the working environment of the nursing personnel. Rather than focusing on mechanical causes and direct workload in the development of non-specific LBP, the complex approach to LBP including genetics, psychosocial environment, lifestyle and quality of life is coming more to the fore.

Knowledge Attıtudes and Behavıors About Organ Donatıon Among Fırst- and Sıxth-class Medıcal Students: A Study From Turkey.

PubMed

Naçar, M; Çetinkaya, F; Baykan, Z; Elmalı, F

2015-01-01

The aim of this study is to determine the knowledge, attitude, and behaviors of Erciyes University School of Medicine students regarding organ donation. This descriptive study was conducted in 2014 on Erciyes University School of Medicine first- and sixth-grade students via questionnaire. It was to be conducted on all 490 students; in total, 464 students were enrolled-304 from first grade and 160 from sixth grade. Data were analyzed using descriptive statistics, χ(2) test, and binary logistic regression analysis. The mean age was 20.9 ± 2.8 years and it was found that 48.9% were male, 65.5% were in first grade; 50.0% of the students who participated in the study were considering donating their organs and this rate is 45.4% in the first grade and 58.8% at sixth grade. Those who donated their organs were 3.4% in the entire group and were 1.6% and 6.9% consequently in first and sixth grades. Those who are; at the sixth grade, female gender, those who feel themselves responsible for the donation of society, who think organ donation is appropriate in terms of religion and conversations within family about organ donations significantly want organ donation more statistically. However, grade and gender had no effect on wishing donating organs according to binary logistic regression analysis. The rate of feeling themselves responsible from the donation in society was 73.9% and finding organ donation appropriate in terms of religion was 75.6% and there wasn't significant difference between first and sixth grades. Although there are increases in many variables about this issue at sixth grade, students are unable to gain sufficient attitude and behavior about organ donation. Training can be planned during medical educations in terms of gaining attitudes and behaviors about the issue. Copyright © 2015 Elsevier Inc. All rights reserved.

Association of funding and conclusions in randomized drug trials: a reflection of treatment effect or adverse events?

PubMed

Als-Nielsen, Bodil; Chen, Wendong; Gluud, Christian; Kjaergard, Lise L

2003-08-20

Previous studies indicate that industry-sponsored trials tend to draw proindustry conclusions. To explore whether the association between funding and conclusions in randomized drug trials reflects treatment effects or adverse events. Observational study of 370 randomized drug trials included in meta-analyses from Cochrane reviews selected from the Cochrane Library, May 2001. From a random sample of 167 Cochrane reviews, 25 contained eligible meta-analyses (assessed a binary outcome; pooled at least 5 full-paper trials of which at least 1 reported adequate and 1 reported inadequate allocation concealment). The primary binary outcome from each meta-analysis was considered the primary outcome for all trials included in each meta-analysis. The association between funding and conclusions was analyzed by logistic regression with adjustment for treatment effect, adverse events, and additional confounding factors (methodological quality, control intervention, sample size, publication year, and place of publication). Conclusions in trials, classified into whether the experimental drug was recommended as the treatment of choice or not. The experimental drug was recommended as treatment of choice in 16% of trials funded by nonprofit organizations, 30% of trials not reporting funding, 35% of trials funded by both nonprofit and for-profit organizations, and 51% of trials funded by for-profit organizations (P<.001; chi2 test). Logistic regression analyses indicated that funding, treatment effect, and double blinding were the only significant predictors of conclusions. Adjusted analyses showed that trials funded by for-profit organizations were significantly more likely to recommend the experimental drug as treatment of choice (odds ratio, 5.3; 95% confidence interval, 2.0-14.4) compared with trials funded by nonprofit organizations. This association did not appear to reflect treatment effect or adverse events. Conclusions in trials funded by for-profit organizations may be more positive due to biased interpretation of trial results. Readers should carefully evaluate whether conclusions in randomized trials are supported by data.

Low uric acid level increases the risk of infectious mononucleosis and this effect is more pronounced in women

PubMed Central

Zhang, Li; Zhou, Pingping; Meng, Zhaowei; Gong, Lu; Pang, Chongjie; Li, Xue; Jia, Qiang; Tan, Jian; Liu, Na; Hu, Tianpeng; Zhang, Qing; Jia, Qiyu; Song, Kun

2017-01-01

Infectious mononucleosis (IM) due to Epstein-Barr virus infection is common. Uric acid (UA) is an important endogenous antioxidant. To the best of our knowledge, the association between UA and IM has not been comprehensively investigated to date. The aim of the present study was to investigate this association in Chinese patients. A total of 95 patients (47 men and 48 women) with IM were recruited, along with 95 healthy controls. Clinical data were classified by patient sex. Receiver operating characteristic (ROC) curve analysis was adopted to determine the cut-off values of UA for IM diagnosis and prediction. Crude and adjusted odds ratios (ORs) of UA for IM were analyzed by binary logistic regression. The UA levels were significantly lower in IM patients compared with those in controls. In addition, UA levels in men were significantly higher compared with those in women. The ROC curve demonstrated good diagnostic and predictive values of UA for IM in both sexes. The UA cut-off values were 326.00 and 243.50 µmol/l for diagnosing IM in men and women, respectively, with a diagnostic accuracy of 76.596 and 80.208%, respectively. Binary logistic regression analysis revealed a significant risk of IM in the low UA quartiles in both sexes. Following adjustments, the ORs even increased. Women with low UA levels appeared to be more susceptible to IM. For example, the crude ORs in quartile 1 were 24.000 and 52.500 for men and women, respectively, and the respective adjusted ORs were 31.437 and 301.746 (all P<0.01). To the best of our knowledge, the present study is the first to demonstrate the inverse association between UA and IM, suggesting a progressive decrease of antioxidant reserve in IM. Moreover, low UA was suggestive of IM, particularly in women. PMID:29285370

Knowledge, attitude, and practices related to cervical cancer among adult women: A hospital-based cross-sectional study.

PubMed

Bansal, Agam B; Pakhare, Abhijit P; Kapoor, Neelkamal; Mehrotra, Ragini; Kokane, Arun Mahadeo

2015-01-01

Cervical cancer is the most common cancer among Indian women of reproductive age. Unfortunately, despite the evidence of methods for prevention, most of the women remain unscreened. The reported barriers to screening include unawareness of risk factors, symptoms and prevention; stigma and misconceptions about gynecological diseases and lack of national cervical cancer screening guidelines and policies. This study attempts to assess the knowledge, attitude, and practices related to cervical cancer and its screening among women of reproductive age (15-45 years). A facility-based cross-sectional study was done on 400 females of reproductive age who presented to out-patient-department of All India Institute of Medical Sciences Bhopal. Structured questionnaire consisting 20 knowledge items and 7-items for attitude and history of pap smear for practices were administered by one of the investigators after informed consent. Data were entered and analyzed using Epi-Info version 7. Qualitative variables were summarized as counts and percentages while quantitative variables as mean and standard deviation. Predictors of better knowledge, attitude, and practices were identified by binary logistic regression analysis. A total of 442 women were approached for interview of which 400 responded of which two-third (65.5%) had heard of cervical cancer. At least one symptom and one risk factor were known to 35.25% and 39.75% participants. Only 34.5% participants had heard, and 9.5% actually underwent screening test, however, 76.25% of the participants expressed a favorable attitude for screening. Binary logistic regression analysis revealed that education age and income were independent predictors of better knowledge. Education level influences attitude toward screening and actual practice depends on age, income, and marital status. This study shows that despite the fact that women had suboptimal level of knowledge regarding cervical cancer, their attitude is favorable for screening. However, uptake is low in actual practice. Strategic communication targeting eligible women may increase the uptake of screening.

Progressive Occlusion of Small Saccular Aneurysms Incompletely Occluded After Stent-Assisted Coil Embolization : Analysis of Related Factors and Long-Term Outcomes.

PubMed

Lim, Jeong Wook; Lee, Jeongjun; Cho, Young Dae

2017-08-08

Incompletely occluded aneurysms after coil embolization are subject to recanalization but occasionally progress to a totally occluded state. Deployed stents may actually promote thrombosis of coiled aneurysms. We evaluated outcomes of small aneurysms (<10 mm) wherein saccular filling with contrast medium was evident after stent-assisted coiling, assessing factors implicated in subsequent progressive occlusion. Between September 2012 and June 2016, a total of 463 intracranial aneurysms were treated by stent-assisted coil embolization. Of these, 132 small saccular aneurysms displayed saccular filling with contrast medium in the immediate aftermath of coiling. Progressive thrombosis was defined as complete aneurysmal occlusion at the 6‑month follow-up point. Rates of progressive occlusion and factors predisposing to this were analyzed via binary logistic regression. In 101 (76.5%) of the 132 intracranial aneurysms, complete occlusion was observed in follow-up imaging studies at 6 months. Binary logistic regression analysis indicated that progressive occlusion was linked to smaller neck diameter (odds ratio [OR] = 1.533; p = 0.003), hyperlipidemia (OR = 3.329; p = 0.036) and stent type (p = 0.031). The LVIS stent is especially susceptible to progressive thrombosis, more so than Neuroform (OR = 0.098; p = 0.008) or Enterprise (OR = 0.317; p = 0.098) stents. In 57 instances of progressive thrombosis, followed for ≥12 months (mean 25.0 ± 10.7 months), 56 (98.2%) were stable, with minor recanalization noted once (1.8%) and no major recanalization. Aneurysms associated with smaller diameter necks, hyperlipidemic states and LVIS stent deployment may be inclined to possible thrombosis, if occlusion immediately after stent-assisted coil embolization is incomplete. In such instances, excellent long-term durability is anticipated.

Chronic obstructive pulmonary disease and coronary disease: COPDCoRi, a simple and effective algorithm for predicting the risk of coronary artery disease in COPD patients.

PubMed

Cazzola, Mario; Calzetta, Luigino; Matera, Maria Gabriella; Muscoli, Saverio; Rogliani, Paola; Romeo, Francesco

2015-08-01

Chronic obstructive pulmonary disease (COPD) is often associated with cardiovascular artery disease (CAD), representing a potential and independent risk factor for cardiovascular morbidity. Therefore, the aim of this study was to identify an algorithm for predicting the risk of CAD in COPD patients. We analyzed data of patients afferent to the Cardiology ward and the Respiratory Diseases outpatient clinic of Tor Vergata University (2010-2012, 1596 records). The study population was clustered as training population (COPD patients undergoing coronary arteriography), control population (non-COPD patients undergoing coronary arteriography), test population (COPD patients whose records reported information on the coronary status). The predicting model was built via causal relationship between variables, stepwise binary logistic regression and Hosmer-Lemeshow analysis. The algorithm was validated via split-sample validation method and receiver operating characteristics (ROC) curve analysis. The diagnostic accuracy was assessed. In training population the variables gender (men/women OR: 1.7, 95%CI: 1.237-2.5, P < 0.05), dyslipidemia (OR: 1.8, 95%CI: 1.2-2.5, P < 0.01) and smoking habit (OR: 1.5, 95%CI: 1.2-1.9, P < 0.001) were significantly associated with CAD in COPD patients, whereas in control population also age and diabetes were correlated. The stepwise binary logistic regressions permitted to build a well fitting predictive model for training population but not for control population. The predictive algorithm shown a diagnostic accuracy of 81.5% (95%CI: 77.78-84.71) and an AUC of 0.81 (95%CI: 0.78-0.85) for the validation set. The proposed algorithm is effective for predicting the risk of CAD in COPD patients via a rapid, inexpensive and non-invasive approach. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of statistical tests for association between rare variants and binary traits.

PubMed

Bacanu, Silviu-Alin; Nelson, Matthew R; Whittaker, John C

2012-01-01

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.

Association of the leptin-to-adiponectin ratio with metabolic syndrome in a sub-Saharan African population.

PubMed

Ayina, Clarisse Noël A; Endomba, Francky Teddy A; Mandengue, Samuel Honoré; Noubiap, Jean Jacques N; Ngoa, Laurent Serge Etoundi; Boudou, Philippe; Gautier, Jean-François; Mbanya, Jean Claude; Sobngwi, Eugene

2017-01-01

Worldwide there is an increased prevalence of metabolic syndrome mainly due to life-style modifications, and Africans are not saved of this situation. Many markers have been studied to predict the risk of this syndrome but the most used are leptin and adiponectin. Data on these metabolic markers are scare in Africa and this study aimed to assess the association between the leptin-to-adiponectin ratio (LAR) with metabolic syndrome in a Cameroonian population. This was a cross-sectional study that included 476 adults among a general population of Cameroon. Data collected concerned the body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose, plasma lipids, adiponectin, leptin, insulin and homeostasis model for assessment of insulin resistance (HOMA-IR). To assess correlations we used Spearman's analyses and association of the studied variables with metabolic syndrome were done using binary logistic regression analysis. The leptin to adiponectin ratio was significantly and positively correlated with the body mass index (r = 0.669, p < 0.0001), waist circumference (r = 0.595, p < 0.0001), triglycerides (r = 0.190, p = 0.001), insulin levels (r = 0.333, p < 0.0001) and HOMA-IR (r = 0.306, p < 0.0001). Binary logistic regression analysis revealed that leptin, adiponectin and LAR were significantly associated with metabolic syndrome with respective unadjusted OR of 1.429, 0.468 and 1.502. After adjustment, for age and sex, the associations remained significative; LAR was also found to be significantly associated with metabolic syndrome (OR = 1.573, p value =0.000) as well as lower levels of adiponectin (OR = 0.359, p value =0.000) and higher levels of leptin (OR = 1.469, p value =0.001). This study revealed that LAR is significantly associated with metabolic syndrome in sub-Saharan African population, independently to age and sex.

Childhood diarrheal morbidity and sanitation predictors in a nomadic community.

PubMed

Bitew, Bikes Destaw; Woldu, Wondwoson; Gizaw, Zemichael

2017-10-06

Diarrhea remains a leading killer of young children on the globe despite the availability of simple and effective solutions to prevent and control it. The disease is more prevalent among under - five children (U5C) in the developing world due to lack of sanitation. A child dies every 15 s from diarrheal disease caused largely by poor sanitation. Nearly 90% of diarrheal disease is attributed to inadequate sanitation. Even though, the health burden of diarrheal disease is widely recognized at global level, its prevalence and sanitation predictors among a nomadic population of Ethiopia are not researched. This study was therefore designed to assess the prevalence of childhood diarrheal disease and sanitation predictors among a nomadic people in Hadaleala district, Afar region, Northeast Ethiopia. A community based cross-sectional study design was carried out to investigate diarrheal disease among U5C. A total of 704 households who had U5C were included in this study and the study subjects were recruited by a multistage cluster sampling technique. Data were collected using a structured questionnaire and an observational checklist. All the mothers of U5C found in the selected clusters were interviewed. Furthermore, the living environment was observed. Univariable binary logistic regression analysis was used to choose variables for the multivariable binary logistic regression analysis on the basis of p- value less than 0.2. Finally, multivariable binary logistic regression analysis was used to identify variables associated with childhood diarrhea disease on the basis of adjusted odds ratio (AOR) with 95% confidence interval (CI) and p < 0.05. The two weeks period prevalence of diarrheal disease among U5C in Hadaleala district was 26.1% (95% CI: 22.9 - 29.3%). Childhood diarrheal disease was statistically associated with unprotected drinking water sources [AOR = 2.449, 95% CI = (1.264, 4.744)], inadequate drinking water service level [AOR = 1.535, 95% CI = (1.004, 2.346)], drinking water sources not protected from animal contact [AOR = 4.403, 95% CI = (2.424, 7.999)], un-availability of any type of latrine [AOR = 2.278, 95% CI = (1.045, 4.965)], presence of human excreta in the compound [AOR = 11.391, 95% CI = (2.100, 61.787)], not washing hand after visiting toilet [AOR = 16.511, 95% CI = (3.304, 82.509)], and live in one living room [AOR = 5.827, 95% CI = (3.208, 10.581)]. Childhood diarrheal disease was the common public health problem in Hadaleala district. Compared with the national and regional prevalence of childhood diarrhea, higher prevalence of diarrhea among U5C was reported. Types of drinking water sources, households whose water sources are shared with livestock, volume of daily water collected, availability of latrine, presence of faeces in the compound, hand washing after visiting the toilet and number of rooms were the sanitation predictors associated with childhood diarrhea. Therefore, enabling the community with safe and continuous supply of water and proper disposal of wastes including excreta is necessary with particular emphasis to the rural nomadic communities.

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Seroprevalence of human hydatidosis using ELISA method in qom province, central iran.

PubMed

Rakhshanpour, A; Harandi, M Fasihi; Moazezi, Ss; Rahimi, Mt; Mohebali, M; Mowlavi, Ghh; Babaei, Z; Ariaeipour, M; Heidari, Z; Rokni, Mb

2012-01-01

The objective of this study was to determine the prevalence of cystic echinococcosis (CE) in Qom Province, central Iran using ELISA test. Overall, 1564 serum samples (800 males and 764 females) were collected from selected subjects by randomized cluster sampling in 2011-2012. Sera were analyzed by ELISA test using AgB. Before sampling, a questionnaire was filled out for each case. Data were analyzed using Chi-square test and multivariate logistic regression for risk factors analysis. Seropositivity was 1.6% (25 cases). Males (2.2%) showed significantly more positivity than females (0.9%) (P= 0.03). There was no significant association between CE seropositivity and age group, occupation, and region. Age group of 30-60 years encompassed the highest rate of positivity. The seropositivity of CE was 2.1% and 1.2% for urban and rural cases respectively. Binary logistic regression showed that males were 2.5 times at higher risk for infection than females. Although seroprevalence of CE is relatively low in Qom Province, yet due to the importance of the disease, all preventive measures should be taken into consideration.

Evaluation of nature and extent of injuries during Dahihandi festival.

PubMed

Nemade, P; Wade, R; Patwardhan, A R; Kale, S

2012-01-01

Injuries related to the Hindu festival of Dahihandi where a human pyramid is formed and a pot of money kept at a height is broken, celebrated in the state of Maharashtra, have seen a significant rise in the past few years. The human pyramid formed is multi-layered and carries with it a high risk of injury including mortality. To evaluate the nature, extent and influencing factors of injuries related to Dahihandi festival. We present a retrospective analysis of patients who presented in a tertiary care center with injuries during the Dahihandi festival in the year 2010. 124 patients' records were evaluated for timing of injury, height of the Dahihandi pyramid, position of the patient in the multi-layered pyramid, mode of pyramid collapse and mechanism of an injury. A binary regression logistic analysis for risk factors was done at 5% significance level. Univariate and multi-variate binary logistic regression of the risk factors for occurrence of a major or minor injury was done using Minitab™ version 16.0 at 5% significance. Out of 139 patients presented to the center, 15 were not involved directly in the formation of pyramid, rest 124 were included in the analysis. A majority of the patients were above 15 years of age [110 (83.6%)]. 46 (37.1%) patients suffered major injuries. There were 39 fractures, 3 cases of chest wall trauma with 10 cases of head injuries and 1 death. More than half of the patients [78 (56.1%)] were injured after 1800 hours. 73 (58.9%) injured participants were part of the pyramid constructed to reach the Dahihandi placed at 30 feet or more above the ground. 72 (51.8%) participants were part of the middle layers of the pyramid. Fall of a participant from upstream layers on the body was the main mechanism of injury, and majority [101 (81.5%)] of the patients suffered injury during descent phase of the pyramid. There is a considerable risk of serious, life-threatening injuries inherent to human pyramid formation and descent in the Dahihandi festival. Safety guidelines are urgently needed to minimize risk and prevent loss of human life.

Pineal Gland Calcification in Kurdistan: A Cross-Sectional Study of 480 Roentgenograms.

PubMed

Mohammed, Kahee A; Adjei Boakye, Eric; Ismail, Honer A; Geneus, Christian J; Tobo, Betelihem B; Buchanan, Paula M; Zelicoff, Alan P

2016-01-01

The goal of this study was to compare the incidence of Pineal Gland Calcification (PGC) by age group and gender among the populations living in the Kurdistan Region-Iraq. This prospective study examined skull X-rays of 480 patients between the ages of 3 and 89 years who sought care at a large teaching public hospital in Duhok, Iraq from June 2014 to November 2014. Descriptive statistics and a binary logistic regression were used for analysis. The overall incidence rate of PGC among the study population was 26.9% with the 51-60 age group and males having the highest incidence. PGC incidence increased after the first decade and remained steady until the age of 60. Thereafter the incidence began to decrease. Logistic regression analysis revealed that both age and gender significantly affected the risk of PGC. After adjusting for age, males were 1.94 (95% CI, 1.26-2.99) times more likely to have PGC compared to females. In addition, a one year increase in age increases the odds of developing PGC by 1.02 (95% CI, 1.01-1.03) units after controlling for the effects of gender. Our analysis demonstrated a close relationship between PGC and age and gender, supporting a link between the development of PGC and these factors. This study provides a basis for future researchers to further investigate the nature and mechanisms underlying pineal gland calcification.

Construction of a pathological risk model of occult lymph node metastases for prognostication by semi-automated image analysis of tumor budding in early-stage oral squamous cell carcinoma

PubMed Central

Pedersen, Nicklas Juel; Jensen, David Hebbelstrup; Lelkaitis, Giedrius; Kiss, Katalin; Charabi, Birgitte; Specht, Lena; von Buchwald, Christian

2017-01-01

It is challenging to identify at diagnosis those patients with early oral squamous cell carcinoma (OSCC), who have a poor prognosis and those that have a high risk of harboring occult lymph node metastases. The aim of this study was to develop a standardized and objective digital scoring method to evaluate the predictive value of tumor budding. We developed a semi-automated image-analysis algorithm, Digital Tumor Bud Count (DTBC), to evaluate tumor budding. The algorithm was tested in 222 consecutive patients with early-stage OSCC and major endpoints were overall (OS) and progression free survival (PFS). We subsequently constructed and cross-validated a binary logistic regression model and evaluated its clinical utility by decision curve analysis. A high DTBC was an independent predictor of both poor OS and PFS in a multivariate Cox regression model. The logistic regression model was able to identify patients with occult lymph node metastases with an area under the curve (AUC) of 0.83 (95% CI: 0.78–0.89, P <0.001) and a 10-fold cross-validated AUC of 0.79. Compared to other known histopathological risk factors, the DTBC had a higher diagnostic accuracy. The proposed, novel risk model could be used as a guide to identify patients who would benefit from an up-front neck dissection. PMID:28212555

Association between Serum Cystatin C and Diabetic Foot Ulceration in Patients with Type 2 Diabetes: A Cross-Sectional Study

PubMed Central

Zhao, Jie; Deng, Wuquan; Zhang, Yuping; Zheng, Yanling; Zhou, Lina; Boey, Johnson; Armstrong, David G.; Yang, Gangyi

2016-01-01

Serum cystatin C (CysC) has been identified as a possible potential biomarker in a variety of diabetic complications, including diabetic peripheral neuropathy and peripheral artery disease. We aimed to examine the association between CysC and diabetic foot ulceration (DFU) in patients with type 2 diabetes (T2D). 411 patients with T2D were enrolled in this cross-sectional study at a university hospital. Clinical manifestations and biochemical parameters were compared between DFU group and non-DFU group. The association between serum CysC and DFU was explored by binary logistic regression analysis. The cut point of CysC for DFU was also evaluated by receiver operating characteristic (ROC) curve. The prevalence of coronary artery disease, diabetic nephropathy (DN), and DFU dramatically increased with CysC (P < 0.01) in CysC quartiles. Multivariate logistic regression analysis indicated that the significant risk factors for DFU were serum CysC, coronary artery disease, hypertension, insulin use, the differences between supine and sitting TcPO2, and hypertension. ROC curve analysis revealed that the cut point of CysC for DFU was 0.735 mg/L. Serum CysC levels correlated with DFU and severity of tissue loss. Our study results indicated that serum CysC was associated with a high prevalence of DFU in Chinese T2D subjects. PMID:27668262

Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

PubMed

Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

2016-05-01

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Sleep quality and motor vehicle crashes in adolescents.

PubMed

Pizza, Fabio; Contardi, Sara; Antognini, Alessandro Baldi; Zagoraiou, Maroussa; Borrotti, Matteo; Mostacci, Barbara; Mondini, Susanna; Cirignotta, Fabio

2010-02-15

Sleep-related complaints are common in adolescents, but their impact on the rate of motor vehicle crashes accidents is poorly known. We studied subjective sleep quality, driving habits, and self-reported car crashes in high-school adolescents. Self-administered questionnaires (with items exploring driving habits) were distributed to 339 students who had a driver's license and attended 1 of 7 high schools in Bologna, Italy. Statistical analysis were performed to describe lifestyle habits, sleep quality, sleepiness, and their relationship with the binary dependent variable (presence or absence of car crashes) to identify the factors significantly affecting the probability of car crashes in a multivariate binary logistic regression model. Nineteen percent of the sample reported bad sleep, 64% complained of daytime sleepiness, and 40% reported sleepiness while driving. Eighty students (24%), 76% of which were males, reported that they had already crashed at least once, and 15% considered sleepiness to have been the main cause of their crash. As compared with adolescents who had not had a crash, those who had at least 1 previous crash reported that they more frequently used to drive (79% vs 62%), drove at night (25% vs 9%), drove while sleepy (56% vs 35%), had bad sleep (29% vs 16%), and used stimulants such as caffeinated soft drinks (32% vs 19%), tobacco (54% vs 27%), and drugs (21% vs 7%). The logistic procedure established a significant predictive role of male sex (p < 0.0001; odds ratio = 3.3), tobacco use (p < 0.0001; odds ratio = 3.2), sleepiness while driving (p = 0.010; odds ratio = 2.1), and bad sleep (p = 0.047; odds ratio = 1.9) for the crash risk. Our results confirm the high prevalence of sleep-related complaints among adolescents and highlight their independent role on self-reported crash risk.

Technical and physical analysis of the 2014 FIFA World Cup Brazil: winners vs. losers.

PubMed

Rumpf, Michael C; Silva, Joao R; Hertzog, Maxime; Farooq, Abdulaziz; Nassis, George

2017-10-01

The purpose of the present study was to investigate the technical and physical performance parameters that distinguish between teams winning and losing matches in the 2014 FIFA World Cup Brazil. Data were derived from the FIFA website and from live-statistics provided during each game of the world cup. Twelve physical (such as total distance covered in meters (TD), TD in distinct locomotor categories: low-intensity running (LIR; <11 km/h), moderate-intensity running (MIR; 11 to 14 km/h) and high-intensity-running (HIR; >14 km/h)) and 21 technical parameters (total passes, short-, medium- and long-distance passes, total pass completion rate, dangerous attacks, attacking attempts, delivery in penalty area, ball possession, goals, goals from set-pieces, goals per shot on goal, defending saves, shots, shots on goal, shot accuracy, set-pieces, crosses, corners, clearances, yellow cards) were analyzed. Forty-two games in which a winner and consequently a loser were presented after 90 minutes of game time were investigated with independent t-tests. A binary-logistic regression was utilized to investigate whether the significant variables predicted success of the winning teams. The winning teams scored significantly (P<0.05) greater amount of goals, goals per set-pieces, goals per shots on goals, shots on goal and shot accuracy and received significantly lower yellow cards. The binary-logistic regression utilized showed that shot accuracy was the best predictor for success. The physical parameters did not differ between teams winning and losing a match. Technical performance related to goal scoring parameters play a decisive role in World Cup games. Furthermore, scoring efficacy from open-play as well as from set-pieces are crucial to win matches in a World Cup tournament. At this level, physical performance was not the factor to discriminate between winners and losers.

Expression of p53 Breast Cancer in Kurdish Women in the West of Iran: a Reverse Correlation with Lymph Node Metastasis.

PubMed

Payandeh, Mehrdad; Sadeghi, Masoud; Sadeghi, Edris; Madani, Seyed-Hamid

2016-01-01

In breast cancer (BC), it has been suggested that nuclear overexpression of p53 protein might be an indicator of poor prognosis. The aim of the current study was to evaluate the expression of p53 BC in Kurdish women from the West of Iran and its correlation with other clinicopathology figures. In the present retrospective study, 231 patients were investigated for estrogen receptor (ER) and progesterone receptor (PR) positivity, defined as ≥10% positive tumor cells with nuclear staining. A binary logistic regression model was selected using Akaike Information Criteria (AIC) in stepwise selection for determination of important factors. ER, PR, the human epidermal growth factor receptor 2 (HER2) and p53 were positive in 58.4%, 55.4%, 59.7% and 45% of cases, respectively. Ki67 index was divided into two groups: 54.5% had Ki67<20% and 45.5% had Ki67 ≥20%. Of 214 patients, 137(64%) had lymph node metastasis and of 186 patients, 122(65.6%) had vascular invasion. Binary logistic regression analysis showed that there was inverse significant correlation between lymph node metastasis (P=0.008, OR 0.120 and 95%CI 0.025-0.574), ER status (P=0.006, OR 0.080, 95%CI 0.014-0.477) and a direct correlation between HER2 (P=005, OR 3.047, 95%CI 1.407-6.599) with the expression of p53. As in a number of studies, expression of p53 had a inverse correlation with lymph node metastasis and ER status and also a direct correlation with HER2 status. Also, p53-positivity is more likely in triple negative BC compared to other subtypes.

Acculturation and healthy lifestyle habits among Hispanics in United States-Mexico border communities.

PubMed

Ghaddar, Suad; Brown, Cynthia J; Pagán, José A; Díaz, Violeta

2010-09-01

To explore the relationship between acculturation and healthy lifestyle habits in the largely Hispanic populations living in underserved communities in the United States of America along the U.S.-Mexico border. A cross-sectional study was conducted from April 2006 to June 2008 using survey data from the Alliance for a Healthy Border, a program designed to reduce health disparities in the U.S.-Mexico border region by funding nutrition and physical activity education programs at 12 federally qualified community health centers in Arizona, California, New Mexico, and Texas. The survey included questions on acculturation, diet, exercise, and demographic factors and was completed by 2,381 Alliance program participants, of whom 95.3% were Hispanic and 45.4% were under the U.S. poverty level for 2007. Chi-square (χ2) and Student's t tests were used for bivariate comparisons between acculturation and dietary and physical activity measures. Linear regression and binary logistic regression were used to control for factors associated with nutrition and exercise. Based on univariate tests and confirmed by regression analysis controlling for sociodemographic and health variables, less acculturated survey respondents reported a significantly higher frequency of fruit and vegetable consumption and healthier dietary habits than those who were more acculturated. Adjusted binary logistic regression confirmed that individuals with low language acculturation were less likely to engage in physical activity than those with moderate to high acculturation (odds ratio 0.75, 95% confidence interval 0.59-0.95). Findings confirmed an association between acculturation and healthy lifestyle habits and supported the hypothesis that acculturation in border community populations tends to decrease the practice of some healthy dietary habits while increasing exposure to and awareness of the importance of other healthy behaviors.

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

PubMed

Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

2017-11-02

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

Correlates of anal sex roles among Malay and Chinese MSM in Kuala Lumpur, Malaysia.

PubMed

Dangerfield, Derek T; Gravitt, Patti; Rompalo, Anne M; Tai, Raymond; Lim, Sin How

2016-03-01

Identifying roles for anal sex is an important issue for populations of MSM. We describe the prevalence of identifying as being 'top', 'bottom', 'versatile', or 'don't know/not applicable' among Malay and Chinese MSM in Kuala Lumpur, Malaysia, and behavioural outcomes according to these labels for sexual role identity. Data analysis was conducted on a survey administered during weekly outreach throughout Kuala Lumpur in 2012. Pearson's Chi square tests were used to compare demographic and behavioural characteristics of MSM who reported roles for anal sex. Binary logistic regression was used to explore the odds of behavioural outcomes among MSM who identified as 'bottom', 'versatile,' and 'don't know' compared to MSM who reported that 'top' was their sexual role. Labels for anal sex roles were significantly associated with condom use for last anal sex. Among MSM who used labels for anal sex roles, MSM who identified as 'bottom' had highest level of not using condoms for last anal sex (24.1%, p = .045). In binary logistic regression model, identifying as 'top' was significantly associated with reporting using a condom during last anal sex and reported consistent condom use for anal sex in the past six months (p = .039 and .017, respectively). With regard to sexual role identity, some MSM may be a part of a special subgroup of at-risk men to be targeted. Future research should evaluate the origins, meanings, and perceptions of these labels, and the developmental process of how these MSM identify with any of these categories. Research should also uncover condom use decision making with regard to these labels for sexual positioning. © The Author(s) 2016.

Disposal of children's stools and its association with childhood diarrhea in India.

PubMed

Bawankule, Rahul; Singh, Abhishek; Kumar, Kaushalendra; Pedgaonkar, Sarang

2017-01-05

Children's stool disposal is often overlooked in sanitation programs of any country. Unsafe disposal of children's stool makes children susceptible to many diseases that transmit through faecal-oral route. Therefore, the study aims to examine the magnitude of unsafe disposal of children's stools in India, the factors associated with it and finally its association with childhood diarrhea. Data from the third round of the National Family Health Survey (NFHS-3) conducted in 2005-06 is used to carry out the analysis. The binary logistic regression model is used to examine the factors associated with unsafe disposal of children's stool. Binary logistic regression is also used to examine the association between unsafe disposal of children's stool and childhood diarrhea. Overall, stools of 79% of children in India were disposed of unsafely. The urban-rural gap in the unsafe disposal of children's stool was wide. Mother's illiteracy and lack of exposure to media, the age of the child, religion and caste/tribe of the household head, wealth index, access to toilet facility and urban-rural residence were statistically associated with unsafe disposal of stool. The odds of diarrhea in children whose stools were disposed of unsafely was estimated to be 11% higher (95% CI: 1.01-1.21) than that of children whose stools were disposed of safely. An increase in the unsafe disposal of children's stool in the community also increased the risk of diarrhea in children. We found significant statistical association between children's stool disposal and diarrhea. Therefore, gains in reduction of childhood diarrhea can be achieved in India through the complete elimination of unsafe disposal of children's stools. The sanitation programmes currently being run in India must also focus on safe disposal of children's stool.

Relationships between stressful life events and impaired fasting glucose among left-behind farmers in rural China.

PubMed

Liang, Han; Cheng, Jing; Shen, Xingrong; Chen, Penglai; Tong, Guixian; Chai, Jing; Li, Kaichun; Xie, Shaoyu; Shi, Yong; Wang, Debin; Sun, Yehuan

2015-02-01

This study aims at examining the effects of stressful life events on risk of impaired fasting glucose among left-behind farmers in rural China. The study collected data about stressful life events, family history of diabetes, lifestyle, demographics and minimum anthropometrics from left-behind famers aged 40-70 years. Calculated life event index was applied to assess the combined effects of stressful life events experienced by the left-behind farmers and its association with impaired fasting glucose was estimated using binary logistic regression models. The prevalence of abnormal fasting glucose was 61.4% by American Diabetes Association (ADA) standard and 32.4% by World Health Organization (WHO) standard. Binary logistic regression analysis revealed a coefficient of 0.033 (P<.001) by ADA standard or 0.028 (P<.001) by WHO standard between impaired fasting glucose and life event index. The overall odds ratios of impaired glucose for the second, third and fourth (highest) versus the first (lowest) quartile of life event index were 1.419 [95% CI=(1.173, 1.717)], 1.711 [95% CI=(1.413, 2.071)] and 1.957 [95% CI=(1.606, 2.385)] respectively by ADA standard. When more and more confounding factors were controlled for, these odds ratios remained statistically significant though decreased to a small extent. The left-behind farmers showed over two-fold prevalence rate of pre-diabetes than that of the nation's average and their risk of impaired fasting glucose was positively associated with stressful life events in a dose-dependent way. Both the population studied and their life events merit special attention. Copyright © 2014 Elsevier Inc. All rights reserved.

A three-level model for binary time-series data: the effects of air pollution on school absences in the Southern California Children's Health Study.

PubMed

Rondeau, Virginie; Berhane, Kiros; Thomas, Duncan C

2005-04-15

A three-level model is proposed to simultaneously examine the effects of daily exposure to air pollution and individual risk factors on health outcomes without aggregating over subjects or time. We used a logistic transition model with random effects to take into account heterogeneity and overdispersion of the observations. A distributed lag structure for pollution has been included, assuming that the event on day t for a subject depends on the levels of air pollution for several preceding days. We illustrate this proposed model via detailed analysis of the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

Merlo, Juan

2017-01-01

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517

Intermediate and advanced topics in multilevel logistic regression analysis.

PubMed

Austin, Peter C; Merlo, Juan

2017-09-10

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Predictors of Gender Inequalities in the Rank of Full Professor

ERIC Educational Resources Information Center

Heijstra, Thamar; Bjarnason, Thoroddur; Rafnsdóttir, Gudbjörg Linda

2015-01-01

This article examines whether age, work-related, and family-related predictors explain differences in the academic advancement of women and men in Iceland. Survey data were analyzed by binary logistic regression. The findings put that women climb the academic career ladder at a slower pace than men. This finding puts one of the widely known…

South Texas Mexican American Use of Traditional Folk and Mainstream Alternative Therapies

ERIC Educational Resources Information Center

Martinez, Leslie N.

2009-01-01

A telephone survey was conducted with a large sample of Mexican Americans from border (n = 1,001) and nonborder (n = 1,030) regions in Texas. Patterns of traditional folk and mainstream complementary and alternative medicine (CAM) use were analyzed with two binary logistic regressions, using gender, self-rated health, confidence in medical…

Propensity of University Students in the Region of Antofagasta, Chile to Create Enterprise

ERIC Educational Resources Information Center

Romani, Gianni; Didonet, Simone; Contuliano, Sue-Hellen; Portilla, Rodrigo

2013-01-01

The authors aim to discuss the propensity or intention to create enterprise among university students in the region of Antofagasta, Chile, and to analyze the factors that influence the step from desire to intention. 681 students were surveyed. The data were analyzed by binary logistical regression. The results show that curriculum is among the…

The CD4/CD8 ratio is associated with coronary artery disease (CAD) in elderly Chinese patients.

PubMed

Gao, Pan; Rong, Hong-Hui; Lu, Ting; Tang, Gang; Si, Liang-Yi; Lederer, James A; Xiong, Wei

2017-01-01

The aim of this study was to investigate the relationship between number of circulating T cells and coronary artery disease (CAD) in an elderly Chinese population. A total of 295 elderly inpatients (age≥60) were included in this cross-sectional study. Their clinical and biochemical characteristics were recorded. Patients were divided to two groups: control patients and CAD patients. The risk factors of CAD were explored by binary logistic regression analysis. Compared with control patients, the ratio of CD4 to CD8 T cells was significantly increased in CAD patients. There was no difference in the number of CD3, CD4, and CD8 T cells between the two groups. Multiple logistic regression analysis showed that CAD was independently associated with age, gender, body mass index (BMI), systolic blood pressure (SBP), chronic heart failure (CHF) and the CD4/CD8 ratio. In addition, after adjusting for different clinical parameters (including gender, age, CHF, hypertension, arrhythmia, SBP, and BMI), the risk of CAD was significantly increased in patients with a CD4/CD8 ratio>1.5. There was a strong and independent association between the ratio of CD4/CD8 and CAD in elderly Chinese population. Copyright © 2016. Published by Elsevier B.V.

Has there been a change in the knowledge of GP registrars between 2011 and 2016 as measured by performance on common items in the Applied Knowledge Test?

PubMed

Neden, Catherine A; Parkin, Claire; Blow, Carol; Siriwardena, Aloysius Niroshan

2018-05-08

The aim of this study was to assess whether the absolute standard of candidates sitting the MRCGP Applied Knowledge Test (AKT) between 2011 and 2016 had changed. It is a descriptive study comparing the performance on marker questions of a reference group of UK graduates taking the AKT for the first time between 2011 and 2016. Using aggregated examination data, the performance of individual 'marker' questions was compared using Pearson's chi-squared tests and trend-line analysis. Binary logistic regression was used to analyse changes in performance over the study period. Changes in performance of individual marker questions using Pearson's chi-squared test showed statistically significant differences in 32 of the 49 questions included in the study. Trend line analysis showed a positive trend in 29 questions and a negative trend in the remaining 23. The magnitude of change was small. Logistic regression did not demonstrate any evidence for a change in the performance of the question set over the study period. However, candidates were more likely to get items on administration wrong compared with clinical medicine or research. There was no evidence of a change in performance of the question set as a whole.

Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

PubMed

Nixon, R M; Thompson, S G

2003-09-15

Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.

Is the cluster environment quenching the Seyfert activity in elliptical and spiral galaxies?

NASA Astrophysics Data System (ADS)

de Souza, R. S.; Dantas, M. L. L.; Krone-Martins, A.; Cameron, E.; Coelho, P.; Hattab, M. W.; de Val-Borro, M.; Hilbe, J. M.; Elliott, J.; Hagen, A.; COIN Collaboration

2016-09-01

We developed a hierarchical Bayesian model (HBM) to investigate how the presence of Seyfert activity relates to their environment, herein represented by the galaxy cluster mass, M200, and the normalized cluster centric distance, r/r200. We achieved this by constructing an unbiased sample of galaxies from the Sloan Digital Sky Survey, with morphological classifications provided by the Galaxy Zoo Project. A propensity score matching approach is introduced to control the effects of confounding variables: stellar mass, galaxy colour, and star formation rate. The connection between Seyfert-activity and environmental properties in the de-biased sample is modelled within an HBM framework using the so-called logistic regression technique, suitable for the analysis of binary data (e.g. whether or not a galaxy hosts an AGN). Unlike standard ordinary least square fitting methods, our methodology naturally allows modelling the probability of Seyfert-AGN activity in galaxies on their natural scale, I.e. as a binary variable. Furthermore, we demonstrate how an HBM can incorporate information of each particular galaxy morphological type in an unified framework. In elliptical galaxies our analysis indicates a strong correlation of Seyfert-AGN activity with r/r200, and a weaker correlation with the mass of the host cluster. In spiral galaxies these trends do not appear, suggesting that the link between Seyfert activity and the properties of spiral galaxies are independent of the environment.

Prevalence of abortion and stillbirth in a beef cattle system in Southeastern Mexico.

PubMed

Segura-Correa, José C; Segura-Correa, Victor M

2009-12-01

Prenatal mortality is an important cause of production losses in the livestock industry. This study estimates the prevalences of abortion and stillbirth in a beef cattle system and determines the significance of some risk factors, in the tropics of Mexico. Data were obtained from a Zebu cattle herd and their crosses with Bos taurus breeds, in Yucatan, Mexico. The logit of the probability of an abortion or stillbirth was modeled using binary logistic regression. The risk factors tested were: year of abortion (or calving), season of abortion (or calving), parity number and dam breed group. The effect of twins on stillbirth was tested using Fisher exact test. Of the 4175 calvings studied 49 were abortions (1.17%). Significant factors in the logistic regression analysis for abortions were season of abortion and parity number. The risk of abortion was lower in the dry seasons compared to the rainy and windy seasons (P = 0.009). The risk of abortion was higher in second parity cows followed by the third and first parity cows, as compared to older cows (P = 0.015). Of the 4126 births, 87 were stillbirths (2.11%). Significant factors in the logistic regression analysis for stillbirth were year of calving (P = 0.0001) and parity number (P < 0.001). The risk of stillbirth in first parity cows was 2.6 times that of old cows. Of the total births, 15 were twins (0.36%) of which 7 were born dead calves. Herd owners must focus on the significant risk factors under their control to reduce the prevalence of prenatal mortality.

[Analysis on influential factors of Chinese medicinal herb growers' willingness to use green pesticides: evidence on Panax notoginseng production areas in Wenshan, Yunnan province].

PubMed

Qian, Yun-Xu; Yang, Yue; Zhao, Wei; Cui, Xiu-Ming; Bi, Kai-Shun

2013-10-01

The purpose of the article is to apply a binary logistic model to analyze the major factors, which influence Chinese medicinal herb growers' willingness to use green pesticides by using survey data collected in Wenshan, Yunnan Province. The results indicate that, output per capita, average pesticide cost per mu, cognition of pesticide residues, expectations on Panax notoginseng prices, cognition of pesticides' effect of pests control, cognition of P. notoginseng prices of low pesticide residues have a significant influence on growers' willingness to use green pesticides. According to the analysis above, some proposals for enhancing Chinese medicinal herb growers' willingness to use green pesticides are put forward, such as, moving toward the intensive planting systems, fetching down the pieces of green pesticides, emphasizing and propagating the advantages of green pesticides, keeping the prices of Chinese medicinal herb running at steady rates.

Characteristics of Illinois School Districts That Employ School Nurses.

PubMed

Searing, Lisabeth M; Guenette, Molly

2016-08-01

Research indicates that school nursing services are cost-effective, but the National Association of School Nurses estimates that 25% of schools do not have a school nurse (SN). The purpose of this study was to identify the characteristics of Illinois school districts that employed SNs. This was a secondary data analysis of Illinois School Report Card system data as well as data obtained from district websites regarding SNs. Employment of an SN was determined for 95% of the 862 existing districts. Binary logistic regression analysis found that district size was the largest significant predictor of employment of an SN. Other factors included the type of district and diversity of the teaching staff as well as the percentage of students receiving special education services or with limited English proficiency. These findings indicate where to focus advocacy and policy efforts to encourage employment of SNs. © The Author(s) 2015.

Statistical Analysis of Factors Affecting Child Mortality in Pakistan.

PubMed

Ahmed, Zoya; Kamal, Asifa; Kamal, Asma

2016-06-01

Child mortality is a composite indicator reflecting economic, social, environmental, healthcare services, and their delivery situation in a country. Globally, Pakistan has the third highest burden of fetal, maternal, and child mortality. Factors affecting child mortality in Pakistan are investigated by using Binary Logistic Regression Analysis. Region, education of mother, birth order, preceding birth interval (the period between the previous child birth and the index child birth), size of child at birth, and breastfeeding and family size were found to be significantly important with child mortality in Pakistan. Child mortality decreased as level of mother's education, preceding birth interval, size of child at birth, and family size increased. Child mortality was found to be significantly higher in Balochistan as compared to other regions. Child mortality was low for low birth orders. Child survival was significantly higher for children who were breastfed as compared to those who were not.

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking

PubMed Central

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults’ belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking. PMID:27853440

Detecting nonsense for Chinese comments based on logistic regression

NASA Astrophysics Data System (ADS)

Zhuolin, Ren; Guang, Chen; Shu, Chen

2016-07-01

To understand cyber citizens' opinion accurately from Chinese news comments, the clear definition on nonsense is present, and a detection model based on logistic regression (LR) is proposed. The detection of nonsense can be treated as a binary-classification problem. Besides of traditional lexical features, we propose three kinds of features in terms of emotion, structure and relevance. By these features, we train an LR model and demonstrate its effect in understanding Chinese news comments. We find that each of proposed features can significantly promote the result. In our experiments, we achieve a prediction accuracy of 84.3% which improves the baseline 77.3% by 7%.

Sequence analysis to assess labour market participation following vocational rehabilitation: an observational study among patients sick-listed with low back pain from a randomised clinical trial in Denmark.

PubMed

Lindholdt, Louise; Labriola, Merete; Nielsen, Claus Vinther; Horsbøl, Trine Allerslev; Lund, Thomas

2017-07-20

The return-to-work (RTW) process after long-term sickness absence is often complex and long and implies multiple shifts between different labour market states for the absentee. Standard methods for examining RTW research typically rely on the analysis of one outcome measure at a time, which will not capture the many possible states and transitions the absentee can go through. The purpose of this study was to explore the potential added value of sequence analysis in supplement to standard regression analysis of a multidisciplinary RTW intervention among patients with low back pain (LBP). The study population consisted of 160 patients randomly allocated to either a hospital-based brief or a multidisciplinary intervention. Data on labour market participation following intervention were obtained from a national register and analysed in two ways: as a binary outcome expressed as active or passive relief at a 1-year follow-up and as four different categories for labour market participation. Logistic regression and sequence analysis were performed. The logistic regression analysis showed no difference in labour market participation for patients in the two groups after 1 year. Applying sequence analysis showed differences in subsequent labour market participation after 2 years after baseline in favour of the brief intervention group versus the multidisciplinary intervention group. The study indicated that sequence analysis could provide added analytical value as a supplement to traditional regression analysis in prospective studies of RTW among patients with LBP. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Association of Brain-Derived Neurotrophic Factor and Vitamin D with Depression and Obesity: A Population-Based Study.

PubMed

Goltz, Annemarie; Janowitz, Deborah; Hannemann, Anke; Nauck, Matthias; Hoffmann, Johanna; Seyfart, Tom; Völzke, Henry; Terock, Jan; Grabe, Hans Jörgen

2018-06-19

Depression and obesity are widespread and closely linked. Brain-derived neurotrophic factor (BDNF) and vitamin D are both assumed to be associated with depression and obesity. Little is known about the interplay between vitamin D and BDNF. We explored the putative associations and interactions between serum BDNF and vitamin D levels with depressive symptoms and abdominal obesity in a large population-based cohort. Data were obtained from the population-based Study of Health in Pomerania (SHIP)-Trend (n = 3,926). The associations of serum BDNF and vitamin D levels with depressive symptoms (measured using the Patient Health Questionnaire) were assessed with binary and multinomial logistic regression models. The associations of serum BDNF and vitamin D levels with obesity (measured by the waist-to-hip ratio [WHR]) were assessed with binary logistic and linear regression models with restricted cubic splines. Logistic regression models revealed inverse associations of vitamin D with depression (OR = 0.966; 95% CI 0.951-0.981) and obesity (OR = 0.976; 95% CI 0.967-0.985). No linear association of serum BDNF with depression or obesity was found. However, linear regression models revealed a U-shaped association of BDNF with WHR (p < 0.001). Vitamin D was inversely associated with depression and obesity. BDNF was associated with abdominal obesity, but not with depression. At the population level, our results support the relevant roles of vitamin D and BDNF in mental and physical health-related outcomes. © 2018 S. Karger AG, Basel.

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impact of low vision on employment.

PubMed

Mojon-Azzi, Stefania M; Sousa-Poza, Alfonso; Mojon, Daniel S

2010-01-01

We investigated the influence of self-reported corrected eyesight on several variables describing the perception by employees and self-employed persons of their employment. Our study was based on data from the Survey of Health, Ageing and Retirement in Europe (SHARE). SHARE is a multidisciplinary, cross-national database of microdata on health, socioeconomic status, social and family networks, collected on 31,115 individuals in 11 European countries and in Israel. With the help of ordered logistic regressions and binary logistic regressions, we analyzed the influence of perceived visual impairment--corrected by 19 covariates capturing socioeconomic and health-related factors--on 10 variables describing the respondents' employment situation. Based on data covering 10,340 working individuals, the results of the logistic and ordered regressions indicate that respondents with lower levels of self-reported general eyesight were significantly less satisfied with their jobs, felt they had less freedom to decide, less opportunity to develop new skills, less support in difficult situations, less recognition for their work, and an inadequate salary. Respondents with a lower eyesight level more frequently reported that they feared their health might limit their ability to work before regular retirement age and more often indicated that they were seeking early retirement. Analysis of this dataset from 12 countries demonstrates the strong impact of self-reported visual impairment on individual employment, and therefore on job satisfaction, productivity, and well-being. Copyright © 2010 S. Karger AG, Basel.

Selenium in irrigated agricultural areas of the western United States

USGS Publications Warehouse

Nolan, B.T.; Clark, M.L.

1997-01-01

A logistic regression model was developed to predict the likelihood that Se exceeds the USEPA chronic criterion for aquatic life (5 ??g/L) in irrigated agricultural areas of the western USA. Preliminary analysis of explanatory variables used in the model indicated that surface-water Se concentration increased with increasing dissolved solids (DS) concentration and with the presence of Upper Cretaceous, mainly marine sediment. The presence or absence of Cretaceous sediment was the major variable affecting Se concentration in surface-water samples from the National Irrigation Water Quality Program. Median Se concentration was 14 ??g/L in samples from areas underlain by Cretaceous sediments and < 1 ??g/L in samples from areas underlain by non-Cretaceous sediments. Wilcoxon rank sum tests indicated that elevated Se concentrations in samples from areas with Cretaceous sediments, irrigated areas, and from closed lakes and ponds were statistically significant. Spearman correlations indicated that Se was positively correlated with a binary geology variable (0.64) and DS (0.45). Logistic regression models indicated that the concentration of Se in surface water was almost certain to exceed the Environmental Protection Agency aquatic-life chronic criterion of 5 ??g/L when DS was greater than 3000 mg/L in areas with Cretaceous sediments. The 'best' logistic regression model correctly predicted Se exceedances and nonexceedances 84.4% of the time, and model sensitivity was 80.7%. A regional map of Cretaceous sediment showed the location of potential problem areas. The map and logistic regression model are tools that can be used to determine the potential for Se contamination of irrigated agricultural areas in the western USA.

Predicting High School Students' Interest in Majoring in a STEM Field: Insight into High School Students' Postsecondary Plans

ERIC Educational Resources Information Center

Lichtenberger, Eric; George-Jackson, Casey

2013-01-01

This study examined how various individual, family, and school level contextual factors impact the likelihood of planning to major in one of the science, technology, engineering, or mathematics (STEM) fields for high school students. A binary logistic regression model was developed to determine the extent to which each of the covariates helped to…

Community-Based Juvenile Reentry Services: The Effects of Service Dosage on Juvenile and Adult Recidivism

ERIC Educational Resources Information Center

Abrams, Laura S.; Terry, Diane; Franke, Todd M.

2011-01-01

In this study the authors examined the influence of length of participation in a community-based reentry program on the odds of reconviction in the juvenile and adult criminal justice systems. A structured telephone survey of reentry program alumni was conducted with 75 transition-age (18-25 year-old) young men. Binary logistic regression analysis…

Predicators of Success for Undergraduate Students Reinstated after an Academic Dismissal at a Small Midwest Private University Campus

ERIC Educational Resources Information Center

Meador, Ryan E.

2012-01-01

This study examined students who successfully applied for reinstatement after being academically dismissed for the first time in order to discover indicators of future success. This study examined 666 students' appeals filed at the DeVry University Kansas City campus between 2004 and 2009. Binary logistic regression was used to discover if a…

Won't You Be My Neighbor? Using an Ecological Approach to Examine the Impact of Community on Revictimization

ERIC Educational Resources Information Center

Obasaju, Mayowa A.; Palin, Frances L.; Jacobs, Carli; Anderson, Page; Kaslow, Nadine J.

2009-01-01

An ecological model is used to explore the moderating effects of community-level variables on the relation between childhood sexual, physical, and emotional abuse and adult intimate partner violence (IPV) within a sample of 98 African American women from low incomes. Results from hierarchical, binary logistics regressions analyses show that…

The cost of acquiring public hunting access on family forests lands

Treesearch

Michael A. Kilgore; Stephanie A. Snyder; Joesph M. Schertz; Steven J. Taff

2008-01-01

To address the issue of declining access to private forest land in the United States for hunting, over 1,000 Minnesota family forest owners were surveyed to estimate the cost of acquiring non-exclusive public hunting access rights. The results indicate landowner interest in selling access rights is extremely modest. Using binary logistic regression, the mean annual...

Understanding the Gap between Cognitive Abilities and Daily Living Skills in Adolescents with Autism Spectrum Disorders with Average Intelligence

ERIC Educational Resources Information Center

Duncan, Amie W.; Bishop, Somer L.

2015-01-01

Daily living skills standard scores on the Vineland Adaptive Behavior Scales-2nd edition were examined in 417 adolescents from the Simons Simplex Collection. All participants had at least average intelligence and a diagnosis of autism spectrum disorder. Descriptive statistics and binary logistic regressions were used to examine the prevalence and…

Sociodemographic Barriers to Early Detection of Autism: Screening and Evaluation Using the M-CHAT, M-CHAT-R, and Follow-Up

ERIC Educational Resources Information Center

Khowaja, Meena K.; Hazzard, Ann P.; Robins, Diana L.

2015-01-01

Parents (n = 11,845) completed the Modified Checklist for Autism in Toddlers (or its latest revision) at pediatric visits. Using sociodemographic predictors of maternal education and race, binary logistic regressions were utilized to examine differences in autism screening, diagnostic evaluation participation rates and outcomes, and reasons for…

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

ERIC Educational Resources Information Center

Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.

2015-01-01

Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model

NASA Astrophysics Data System (ADS)

Shariff, S. Sarifah Radiah; Rodzi, Nur Atiqah Mohd; Rahman, Kahartini Abdul; Zahari, Siti Meriam; Deni, Sayang Mohd

2016-10-01

Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia's largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.

The likelihood of achieving quantified road safety targets: a binary logistic regression model for possible factors.

PubMed

Sze, N N; Wong, S C; Lee, C Y

2014-12-01

In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors - including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target - that contribute to a target's success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed. Copyright © 2014 Elsevier Ltd. All rights reserved.

A measurement of disorder in binary sequences

NASA Astrophysics Data System (ADS)

Gong, Longyan; Wang, Haihong; Cheng, Weiwen; Zhao, Shengmei

2015-03-01

We propose a complex quantity, AL, to characterize the degree of disorder of L-length binary symbolic sequences. As examples, we respectively apply it to typical random and deterministic sequences. One kind of random sequences is generated from a periodic binary sequence and the other is generated from the logistic map. The deterministic sequences are the Fibonacci and Thue-Morse sequences. In these analyzed sequences, we find that the modulus of AL, denoted by |AL | , is a (statistically) equivalent quantity to the Boltzmann entropy, the metric entropy, the conditional block entropy and/or other quantities, so it is a useful quantitative measure of disorder. It can be as a fruitful index to discern which sequence is more disordered. Moreover, there is one and only one value of |AL | for the overall disorder characteristics. It needs extremely low computational costs. It can be easily experimentally realized. From all these mentioned, we believe that the proposed measure of disorder is a valuable complement to existing ones in symbolic sequences.

Quantitative Analysis of Driving Factors of Grassland Degradation: A Case Study in Xilin River Basin, Inner Mongolia

PubMed Central

Xie, Yichun; Sha, Zongyao

2012-01-01

Current literature suggests that grassland degradation occurs in areas with poor soil conditions or noticeable environmental changes and is often a result of overgrazing or human disturbances. However, these views are questioned in our analyses. Based on the analysis of satellite vegetation maps from 1984, 1998, and 2004 for the Xilin River Basin, Inner Mongolia, China, and binary logistic regression (BLR) analysis, we observe the following: (1) grassland degradation is positively correlated with the growth density of climax communities; (2) our findings do not support a common notion that a decrease of biological productivity is a direct indicator of grassland degradation; (3) a causal relationship between grazing intensity and grassland degradation was not found; (4) degradation severity increased steadily towards roads but showed different trends near human settlements. This study found complex relationships between vegetation degradation and various microhabitat conditions, for example, elevation, slope, aspect, and proximity to water. PMID:22619613

[Correspondence analysis of association between types of unintentional injuries and influential factors among rural rear pupils].

PubMed

Dou, Dongmei; Wang, Peixi

2015-07-01

To explore the association between types of unintentional injuries and influential factors among rural rear pupils. The multistage stratified sampling method was used to select the study participant and thus 594 rural pupils were sampled, 292 rear pupils were confirmed and measured with unintentional injuries and influential factors of rural rear pupils scale. Binary logistic regression analysis indicate that the risk facts related to unintentional injury were left-behind status (OR = 2.68, 95% CI 1.06-6.79), gender (OR = 5.12, 95% C2.68-9.79) and surrounding environment (OR = 3.44, 95% CI 1.37-8.70). Correspondence analysis showed living with father, middle personality and low age were related possibly with traffic accident injury. Living with grandparents, extrovert personality and elder pupils were related possibly with unintentional falls injury. Living with mother, introvert personality and middle-age pupils were related possibly with animmal injury. The personality, ages and guardian types of rural rear pupils are correlated with types of unintentional injuries.

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

NASA Astrophysics Data System (ADS)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Exposure and impact of a mass media campaign targeting sexual health amongst Scottish men who have sex with men: an outcome evaluation

PubMed Central

2013-01-01

Background This paper explores the exposure and impact of a Scottish mass media campaign: Make Your Position Clear. It ran from October 2009 to July 2010, targeted gay men and other men who have sex with men (MSM), and had two key aims: to promote regular sexual health and HIV testing every 6 months, and to promote the use of appropriate condoms and water-based lubricant with each episode of anal intercourse. Methods A cross-sectional survey (anonymous and self-report) was conducted 10 months after the campaign was launched (July 2010). Men were recruited from commercial venues. Outcome measures included use of lubricant, testing for sexually transmitted infections and HIV, and intentions to seek HIV testing within the following six months. Linear-by-linear chi-square analysis and binary logistic regressions were conducted to explore the associations between the outcome measures and campaign exposure. Results The total sample was 822 men (62.6% response rate). Men self-identifying as HIV positive were excluded from the analysis (n = 38). Binary logistic analysis indicated that those with mid or high campaign exposure were more likely to have been tested for HIV in the previous six months when adjusted for age, area of residence and use of the “gay scene” (AOR = 1.96, 95% CI = 1.26 to 3.06, p = .003), but were not more likely to be tested for STIs (AOR = 1.37, 95% CI = 0.88 to 2.16, p = .167). When adjusted for previous HIV testing, those with mid or high campaign exposure were not more likely to indicate intention to be tested for HIV in the following six months (AOR = 1.30, 95% CI = 0.73 to 2.32, p = .367). Those with no campaign exposure were less likely than those with low exposure to have used appropriate lubricant with anal sex partners in the previous year (AOR = 0.42, 95% CI = 0.23 to 0.77, p = .005). Conclusions The campaign had demonstrable reach. The analysis showed partial support for the role of mass media campaigns in improving sexual health outcomes. This suggests that a role for mass media campaigns remains within combination HIV prevention. PMID:23923977

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

More caregiving, less working: caregiving roles and gender difference.

PubMed

Lee, Yeonjung; Tang, Fengyan

2015-06-01

This study examined the relationship of caregiving roles to labor force participation using the nationally representative data from the Health and Retirement Study. The sample was composed of men and women aged 50 to 61 years (N = 5,119). Caregiving roles included caregiving for spouse, parents, and grandchildren; a summary of three caregiving roles was used to indicate multiple caregiving roles. Bivariate analysis using chi-square and t tests and binary logistic regression models were applied. Results show that women caregivers for parents and/or grandchildren were less likely to be in the labor force than non-caregivers and that caregiving responsibility was not related to labor force participation for the sample of men. Findings have implication for supporting family caregivers, especially women, to balance work and caregiving commitments. © The Author(s) 2013.

Associations between national viral hepatitis policies/programmes and country-level socioeconomic factors: a sub-analysis of data from the 2013 WHO viral hepatitis policy report.

PubMed

Lazarus, Jeffrey V; Sperle, Ida; Safreed-Harmon, Kelly; Gore, Charles; Cebolla, Beatriz; Spina, Alexander

2017-07-26

As more countries worldwide develop national viral hepatitis strategies, it is important to ask whether context-specific factors affect their decision-making. This study aimed to determine whether country-level socioeconomic factors are associated with viral hepatitis programmes and policy responses across WHO Member States (MS). WHO MS focal points completed a questionnaire on national viral hepatitis policies. This secondary analysis of data reported in the 2013 Global Policy Report on the Prevention and Control of Viral Hepatitis in WHO Member States used logistic regression to examine associations between four survey questions and four socioeconomic factors: country income level, Human Development Index (HDI), health expenditure and physician density. This analysis included 119 MS. MS were more likely to have routine viral hepatitis surveillance and to have a national strategy and/or policy/guidelines for preventing infection in healthcare settings if they were in the higher binary categories for income level, HDI, health expenditure and physician density. In multivariable analyses, the only significant finding was a positive association between having routine surveillance and being in the higher binary HDI category (adjusted odds ratio 26; 95% confidence interval 2.0-340). Countries with differing socioeconomic status indicators did not appear to differ greatly regarding the existence of key national policies and programmes. A more nuanced understanding of the multifaceted interactions of socioeconomic factors, health policy, service delivery and health outcomes is needed to support country-level efforts to eliminate viral hepatitis.

Indicators of suboptimal performance embedded in the Wechsler Memory Scale-Fourth Edition (WMS-IV).

PubMed

Bouman, Zita; Hendriks, Marc P H; Schmand, Ben A; Kessels, Roy P C; Aldenkamp, Albert P

2016-01-01

Recognition and visual working memory tasks from the Wechsler Memory Scale-Fourth Edition (WMS-IV) have previously been documented as useful indicators for suboptimal performance. The present study examined the clinical utility of the Dutch version of the WMS-IV (WMS-IV-NL) for the identification of suboptimal performance using an analogue study design. The patient group consisted of 59 mixed-etiology patients; the experimental malingerers were 50 healthy individuals who were asked to simulate cognitive impairment as a result of a traumatic brain injury; the last group consisted of 50 healthy controls who were instructed to put forth full effort. Experimental malingerers performed significantly lower on all WMS-IV-NL tasks than did the patients and healthy controls. A binary logistic regression analysis was performed on the experimental malingerers and the patients. The first model contained the visual working memory subtests (Spatial Addition and Symbol Span) and the recognition tasks of the following subtests: Logical Memory, Verbal Paired Associates, Designs, Visual Reproduction. The results showed an overall classification rate of 78.4%, and only Spatial Addition explained a significant amount of variation (p < .001). Subsequent logistic regression analysis and receiver operating characteristic (ROC) analysis supported the discriminatory power of the subtest Spatial Addition. A scaled score cutoff of <4 produced 93% specificity and 52% sensitivity for detection of suboptimal performance. The WMS-IV-NL Spatial Addition subtest may provide clinically useful information for the detection of suboptimal performance.

Completing the Remedial Sequence and College-Level Credit-Bearing Math: Comparing Binary, Cumulative, and Continuation Ratio Logistic Regression Models

ERIC Educational Resources Information Center

Davidson, J. Cody

2016-01-01

Mathematics is the most common subject area of remedial need and the majority of remedial math students never pass a college-level credit-bearing math class. The majorities of studies that investigate this phenomenon are conducted at community colleges and use some type of regression model; however, none have used a continuation ratio model. The…

Modeling Student Performance in Mathematics Using Binary Logistic Regression at Selected Secondary Schools a Case Study of Mtwara Municipality and Ilemela District

ERIC Educational Resources Information Center

Mabula, Salyungu

2015-01-01

This study investigated the performance of secondary school students in Mathematics at the Selected Secondary Schools in Mtwara Municipality and Ilemela District by Absenteeism, Conduct, Type of School and Gender as explanatory Factors. The data used in the study was collected from documented records of 250 form three students with 1:1 gender…

User’s Guide to Southeast Asia Combat Data

DTIC Science & Technology

1976-06-01

North latitude Binary coded decimal Bomb damage assessment Battle Damage Assessment and Reporting Team Brigade Basic encyclopedia A University of...and movement routes Bomb wing CALCOMP CANDLESTICK CAP CAP CAS CAS CAVD CBU , CBS California Computer Products, Inc. Call sign...Special Studies Group (a high-level Washington committee) WAC WBLC WIA WOLF WSE3 WWDMS WWMCCS W X World Aeronautical Chart Waterborne logistic

Factors That Contributed to Gifted Students' Success on STEM Pathways: The Role of Race, Personal Interests, and Aspects of High School Experience

ERIC Educational Resources Information Center

Steenbergen-Hu, Saiying; Olszewski-Kubilius, Paula

2017-01-01

In this study, we conducted binary logistic regression on survey data collected from 244 past participants of a Talent Search program who attended regular high schools but supplemented their regular high school education with enriched or accelerated math and science learning activities. The participants completed an online survey 4 to 6 years…

Sample size calculations for case-control studies

Cancer.gov

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Association Between Socio-Demographic Background and Self-Esteem of University Students.

PubMed

Haq, Muhammad Ahsan Ul

2016-12-01

The purpose of this study was to scrutinize self-esteem of university students and explore association of self-esteem with academic achievement, gender and other factors. A sample of 346 students was selected from Punjab University, Lahore Pakistan. Rosenberg self-esteem scale with demographic variables was used for data collection. Besides descriptive statistics, binary logistic regression and t test were used for analysing the data. Significant gender difference was observed, self-esteem was significantly higher in males than females. Logistic regression indicates that age, medium of instruction, family income, student monthly expenditures, GPA and area of residence has direct effect on self-esteem; while number of siblings showed an inverse effect.

glmnetLRC f/k/a lrc package: Logistic Regression Classification

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

2016-06-09

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold formore » binary classification.« less

Risk stratification personalised model for prediction of life-threatening ventricular tachyarrhythmias in patients with chronic heart failure.

PubMed

Frolov, Alexander Vladimirovich; Vaikhanskaya, Tatjana Gennadjevna; Melnikova, Olga Petrovna; Vorobiev, Anatoly Pavlovich; Guel, Ludmila Michajlovna

2017-01-01

The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF). The study included 240 patients with CHF (mean-age of 50.5 ± 12.1 years; left ventricular ejection fraction 32.8 ± 10.9%; follow-up period 36.8 ± 5.7 months). The participants received basic therapy for heart failure. The elec-trocardiogram (ECG) markers of myocardial electrical instability were assessed including microvolt T-wave alternans, heart rate turbulence, heart rate deceleration, and QT dispersion. Additionally, echocardiography and Holter monitoring (HM) were performed. The cardiovascular events were considered as primary endpoints, including SCD, paroxysmal ventricular tachycardia/ventricular fibrillation (VT/VF) based on HM-ECG data, and data obtained from implantable device interrogation (CRT-D, ICD) as well as appropriated shocks. During the follow-up period, 66 (27.5%) subjects with CHF showed adverse arrhythmic events, including nine SCD events and 57 VTAs. Data from a stepwise discriminant analysis of cumulative ECG-markers of myocardial electrical instability were used to make a mathematical model of preliminary VTA risk stratification. Uni- and multivariate Cox logistic regression analysis were performed to define an individualised risk stratification model of SCD/VTA. A binary logistic regression model demonstrated a high prognostic significance of discriminant function with a classification sensitivity of 80.8% and specificity of 99.1% (F = 31.2; c2 = 143.2; p < 0.0001). The method of personalised risk stratification using Cox logistic regression allows correct classification of more than 93.9% of CHF cases. A robust body of evidence concerning logistic regression prognostic significance to define VTA risk allows inclusion of this method into the algorithm of subsequent control and selection of the optimal treatment modality to treat patients with CHF.

Seeing Double Old and New: Observations and Lightcurve Analysis at the Palmer Divide Observatory of Six Binary Asteroids

NASA Astrophysics Data System (ADS)

Warner, Brian D.

2013-04-01

Results of the analysis of lightcurves of six binary asteroids obtained at the Palmer Divide Observatory are reported. Of the six, three were previously known to be binary: 9069 Hovland, (26471) 2000 AS152, and 1994 XD. The remaining three are new confirmed or probable binary discoveries made at PDO: 2047 Smetana, (5646) 1990 TR, and (52316) 1992 BD.

Association among stress, personality traits, and sleep bruxism in children.

PubMed

Serra-Negra, Junia M; Paiva, Saul M; Flores-Mendoza, Carmen E; Ramos-Jorge, Maria L; Pordeus, Isabela A

2012-01-01

The purpose of this study was to determine the association among stress levels, personality traits, and sleep bruxism in children. A population-based case control study (proportion=1:2) was conducted involving 120 7- to 11-year-olds with sleep bruxism and 240 children without sleep bruxism. The sample was randomly selected from schools in Belo Horizonte, Minas Gerais, Brazil. The following instruments were used for data collection: questionnaire administered to parents; child stress scale; and neuroticism and responsibility scales of the big five questionnaire for children. Psychological tests were administered and evaluated by psychologists. Sleep bruxism was diagnosed from parents' reports. The chi-square test, as well as binary and multivariate logistic regression, was applied for statistical analysis. In the adjusted logistic model, children with a high level of stress, due to psychological reactions (odds ratio=1.8; confidence interval=1.1-2.9) and a high sense of responsibility (OR=1.6; CI=1.0-2.5) vs those with low levels of these psychological traits, presented a nearly 2-fold greater chance of exhibiting the habit of sleep bruxism. High levels of stress and responsibility are key factors in the development of sleep bruxism among children.

Propensity score matching of the gymnastics for diabetes mellitus using logistic regression

NASA Astrophysics Data System (ADS)

Otok, Bambang Widjanarko; Aisyah, Amalia; Purhadi, Andari, Shofi

2017-12-01

Diabetes Mellitus (DM) is a group of metabolic diseases with characteristics shows an abnormal blood glucose level occurring due to pancreatic insulin deficiency, decreased insulin effectiveness or both. The report from the ministry of health shows that DMs prevalence data of East Java province is 2.1%, while the DMs prevalence of Indonesia is only 1,5%. Given the high cases of DM in East Java, it needs the preventive action to control factors causing the complication of DM. This study aims to determine the combination factors causing the complication of DM to reduce the bias by confounding variables using Propensity Score Matching (PSM) with the method of propensity score estimation is binary logistic regression. The data used in this study is the medical record from As-Shafa clinic consisting of 6 covariates and health complication as response variable. The result of PSM analysis showed that there are 22 of 126 DMs patients attending gymnastics paired with patients who didnt attend to diabetes gymnastics. The Average Treatment of Treated (ATT) estimation results showed that the more patients who didnt attend to gymnastics, the more likely the risk for the patients having DMs complications.

Prediction of future falls in a community dwelling older adult population using instrumented balance and gait analysis.

PubMed

Bauer, C M; Gröger, I; Rupprecht, R; Marcar, V L; Gaßmann, K G

2016-04-01

The role of instrumented balance and gait assessment when screening for prospective fallers is currently a topic of controversial discussion. This study analyzed the association between variables derived from static posturography, instrumented gait analysis and clinical assessments with the occurrence of prospective falls in a sample of community dwelling older people. In this study 84 older people were analyzed. Based on a prospective occurrence of falls, participants were categorized into fallers and non-fallers. Variables derived from clinical assessments, static posturography and instrumented gait analysis were evaluated with respect to the association with the occurrence of prospective falls using a forward stepwise, binary, logistic regression procedure. Fallers displayed a significantly shorter single support time during walking while counting backwards, increased mediolateral to anteroposterior sway amplitude ratio, increased fast mediolateral oscillations and a larger coefficient (Coeff) of sway direction during various static posturography tests. Previous falls were insignificantly associated with the occurrence of prospective falls. Variables derived from posturography and instrumented gait analysis showed significant associations with the occurrence of prospective falls in a sample of community dwelling older adults.

Socio-economic Correlates of Malnutrition among Married Women in Bangladesh.

PubMed

Mostafa Kamal, S M; Md Aynul, Islam

2010-12-01

This paper examines the prevalence and socio-economic correlates of malnutrition among ever married non-pregnant women of reproductive age of Bangladesh using a nationally representative weighted sample of 10,145. Body mass index was used to measure nutritional status. Both bivariate and multivariate statistical analyses were employed to assess the relationship between socio-economic characteristics and women's nutritional status. Overall, 28.5% of the women were found to be underweight. The fixed effect multivariate binary logistic regression analysis yielded significantly increased risk of underweight for the young, currently working, non-Muslim, rural residents, widowed, divorced or separated women. Significant wide variations of malnourishment prevailed in the administrative regions of the country. Wealth index and women's education were the most important determinants of underweight. The multivariate logistic regression analysis revealed that the risk of being underweight was almost seven times higher (OR=6.76, 95% CI=5.20-8.80) among women with no formal education as compared to those with higher education and the likelihood of underweight was significantly (p<0.001) 5.2 times (OR=5.23, 95% CI=4.51-6.07) in the poorest as compared to their richest counterparts. Poverty alleviation programmes should be strengthened targeting the poor. Effective policies, information and health education programmes for women are required to ensure adequate access to health services and for them to understand the components of a healthy diet.

Association between maternal smoking, gender, and cleft lip and palate.

PubMed

Martelli, Daniella Reis Barbosa; Coletta, Ricardo D; Oliveira, Eduardo A; Swerts, Mário Sérgio Oliveira; Rodrigues, Laíse A Mendes; Oliveira, Maria Christina; Martelli Júnior, Hercílio

2015-01-01

Cleft lip and/or palate (CL/P) represent the most common congenital anomalies of the face. To assess the relationship between maternal smoking, gender and CL/P. This is an epidemiological cross-sectional study. We interviewed 1519 mothers divided into two groups: mothers of children with CL/P (n=843) and mothers of children without CL/P (n=676). All mothers were classified as smoker or non-smoker subjects during the first trimester of pregnancy. To determine an association among maternal smoking, gender, and CL/P, odds ratios were calculated and the adjustment was made by a logistic regression model. An association between maternal smoking and the presence of cleft was observed. There was also a strong association between male gender and the presence of cleft (OR=3.51; 95% CI 2.83-4.37). By binary logistic regression analysis, it was demonstrated that both variables were independently associated with clefts. In a multivariate analysis, male gender and maternal smoking had a 2.5- and a 1.5-time greater chance of having a cleft, respectively. Our findings are consistent with a positive association between maternal smoking during pregnancy and CL/P in male gender. The results support the importance of smoking prevention and introduction of cessation programs among women with childbearing potential. Copyright © 2015 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Association of salivary levels of the bone remodelling regulators sRANKL and OPG with periodontal clinical status.

PubMed

Tobón-Arroyave, Sergio I; Isaza-Guzmán, Diana M; Restrepo-Cadavid, Eliana M; Zapata-Molina, Sandra M; Martínez-Pabón, María C

2012-12-01

To determine the variations in salivary concentrations of sRANKL, osteoprotegerin (OPG) and its ratio, regarding the periodontal status. Ninety-seven chronic periodontitis (CP) subjects and 43 healthy controls were selected. Periodontal status was assessed based on full-mouth clinical periodontal measurements. sRANKL and OPG salivary levels were analysed by ELISA. The association between these analytes and its ratio with CP was analysed individually and adjusted for confounding using a binary logistic regression model. sRANKL and sRANKL/OPG ratio were increased, whereas OPG was decreased in CP compared with healthy controls subjects. Although univariate analysis revealed a positive association of sRANKL salivary levels ≥6 pg/ml, OPG salivary levels ≤131 pg/ml and sRANKL/OPG ratio ≥0.062 with CP, after logistic regression analysis only the latter parameter was strongly and independently associated with disease status. Confounding and interaction effects of ageing and smoking habit on sRANKL and OPG levels could be noted. Although salivary concentrations of sRANKL, OPG and its ratio may act as indicators of the amount/extent of periodontal breakdown, the mutual confounding and synergistic biological interactive effects related to ageing and smoking habit of the susceptible host may also promote the tissue destruction in CP. © 2012 John Wiley & Sons A/S.

Knowledge, awareness, and behaviors of endocrinologists and dentists for the relationship between diabetes and periodontitis.

PubMed

Lin, Hanxiao; Zhang, Hua; Yan, Yuxia; Liu, Duan; Zhang, Ruyi; Liu, Yeungyeung; Chen, Pei; Zhang, Jincai; Xuan, Dongying

2014-12-01

This study aimed to compare the opinions of dentists and endocrinologists regarding diabetes mellitus (DM) and periodontitis, and to investigate the possible effects on their practice. Cross-sectional data were collected from 297 endocrinologists and 134 dentists practicing in southern China using two separated questionnaires. Questions were close-ended or Likert-scaled. Statistical analyses were done by descriptive statistics, bivariate and binary logistic regression analysis. Compared with endocrinologists, dentists presented more favorable attitudes for the relationship of DM and periodontitis (P<0.001). 61.2% of dentists reported they would frequently refer patients with severe periodontitis for DM evaluation, while only 26.6% of endocrinologists reported they would frequently advise patients with DM to visit a dentist. Nearly all of the respondents (94.4%) agreed that the interdisciplinary collaboration should be strengthened. The logistic regression analysis exhibited that respondents with more favorable attitudes were more likely to advise a dental visit (P=0.003) or to screen for DM (P=0.006). Endocrinologists and dentists are not equally equipped with the knowledge about the relationship between DM and periodontitis, and there is a wide gap between their practice and the current evidence, especially for endocrinologists. It's urgent to take measures to develop the interdisciplinary education and collaboration among the health care providers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Is fetal-type posterior cerebral artery a risk factor for intracranial aneurysm as analyzed by multislice CT angiography?

PubMed

He, Zhen; Wan, Yeda

2018-01-01

Fetal-type posterior cerebral artery (FTP) is a common anatomic variation that is closely associated with intracranial aneurysm. In the present study, multislice computed tomography angiography (CTA) was performed to assess whether FTP is a risk factor for intracranial aneurysm. CTA data of 364 consecutive cases of patients who were suspected with cerebrovascular disease or intracranial aneurysm of intracranial artery from 2013 to 2016 were reviewed and the incidence rates of FTP, other variations of the circle of Willis, intracranial aneurysm and FTP with intracranial aneurysm were evaluated. The χ 2 test was used to assess the influence of FTP and gender on the incidence rates of other variations of the circle of Willis, intracranial aneurysm and internal carotid artery-posterior communicating artery (ICA-PComA) aneurysm. Binary logistic regression analysis was performed to assess the associations of FTP and gender with intracranial aneurysm and ICA-PComA aneurysm. Compared with non-FTP patients, FTP cases exhibited significantly higher rates of other variations of the circle of Willis (χ 2 =80.173, P<0.001) and ICA-PComA aneurysm (χ 2 =4.437, P=0.035). Among patients with FTP and bilateral FTP, more female than male patients with intracranial aneurysm were identified. However, among all patients with intracranial aneurysm, no statistically significant differences in the prevalence of FTP (χ 2 =2.577, P=0.108) and bilateral FTP (χ 2 =2.199, P=0.159) between males and females were identified. Binary logistic regression analysis revealed that FTP and gender were risk factors for intracranial aneurysm and ICA-PComA aneurysm. A moderate association between FTP and ICA-PComA aneurysm (OR=2.762) were identified, although there was a weak association between FTP and intracranial aneurysm [odds ratio (OR)=1.365]. Furthermore, a strong association was identified between gender and intracranial aneurysm (OR=0.328), and a moderate association existed between gender and ICA-PComA aneurysm (OR=0.357). In conclusion, female gender is an independent risk factor for intracranial aneurysm, and FTP and female gender are independent risk factors for ICA-PComA aneurysm.

Is fetal-type posterior cerebral artery a risk factor for intracranial aneurysm as analyzed by multislice CT angiography?

PubMed Central

He, Zhen; Wan, Yeda

2018-01-01

Fetal-type posterior cerebral artery (FTP) is a common anatomic variation that is closely associated with intracranial aneurysm. In the present study, multislice computed tomography angiography (CTA) was performed to assess whether FTP is a risk factor for intracranial aneurysm. CTA data of 364 consecutive cases of patients who were suspected with cerebrovascular disease or intracranial aneurysm of intracranial artery from 2013 to 2016 were reviewed and the incidence rates of FTP, other variations of the circle of Willis, intracranial aneurysm and FTP with intracranial aneurysm were evaluated. The χ2 test was used to assess the influence of FTP and gender on the incidence rates of other variations of the circle of Willis, intracranial aneurysm and internal carotid artery-posterior communicating artery (ICA-PComA) aneurysm. Binary logistic regression analysis was performed to assess the associations of FTP and gender with intracranial aneurysm and ICA-PComA aneurysm. Compared with non-FTP patients, FTP cases exhibited significantly higher rates of other variations of the circle of Willis (χ2=80.173, P<0.001) and ICA-PComA aneurysm (χ2=4.437, P=0.035). Among patients with FTP and bilateral FTP, more female than male patients with intracranial aneurysm were identified. However, among all patients with intracranial aneurysm, no statistically significant differences in the prevalence of FTP (χ2=2.577, P=0.108) and bilateral FTP (χ2=2.199, P=0.159) between males and females were identified. Binary logistic regression analysis revealed that FTP and gender were risk factors for intracranial aneurysm and ICA-PComA aneurysm. A moderate association between FTP and ICA-PComA aneurysm (OR=2.762) were identified, although there was a weak association between FTP and intracranial aneurysm [odds ratio (OR)=1.365]. Furthermore, a strong association was identified between gender and intracranial aneurysm (OR=0.328), and a moderate association existed between gender and ICA-PComA aneurysm (OR=0.357). In conclusion, female gender is an independent risk factor for intracranial aneurysm, and FTP and female gender are independent risk factors for ICA-PComA aneurysm. PMID:29434687

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

NASA Technical Reports Server (NTRS)

Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.

2013-01-01

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations.

Association of Genetic Polymorphisms of Renin–Angiotensin–Aldosterone System-Related Genes with Arterio-Venous Fistula Malfunction in Hemodialysis Patients

PubMed Central

Chen, Yu-Wei; Wu, Yu-Te; Lin, Jhin-Shyaun; Yang, Wu-Chang; Hsu, Yung-Ho; Lee, Kuo-Hua; Ou, Shou-Ming; Chen, Yung-Tai; Shih, Chia-Jen; Lee, Pui-Ching; Chan, Chia-Hao; Chung, Ming-Yi; Lin, Chih-Ching

2016-01-01

Hemodialysis (HD) is the most commonly-used renal replacement therapy for patients with end-stage renal disease worldwide. Arterio-venous fistula (AVF) is the vascular access of choice for HD patients with lowest risk of infection and thrombosis. In addition to environmental factors, genetic factors may also contribute to malfunction of AVF. Previous studies have demonstrated the effect of genotype polymorphisms of angiotensin converting enzyme on vascular access malfunction. We conducted a multicenter, cross-sectional study to evaluate the association between genetic polymorphisms of renin-angiotensin-aldosterone system and AVF malfunction. Totally, 577 patients were enrolled. Their mean age was 60 years old and 53% were male. HD patients with AVF malfunction had longer duration of HD (92.5 ± 68.1 vs. 61.2 ± 51.9 months, p < 0.001), lower prevalence of hypertension (44.8% vs. 55.3%, p = 0.025), right-sided (31.8% vs. 18.4%, p = 0.002) and upper arm AVF (26.6% vs. 9.7%, p < 0.001), and higher mean dynamic venous pressure (DVP) (147.8 ± 28.3 vs. 139.8 ± 30.0, p = 0.021). In subgroup analysis of different genders, location of AVF and DVP remained significant clinical risk factors of AVF malfunction in univariate and multivariate binary logistic regression in female HD patients. Among male HD patients, univariate binary logistic regression analysis revealed that right-side AVF and upper arm location are two important clinical risk factors. In addition, two single nucleotide polymorphisms (SNPs), rs275653 (Odds ratio 1.90, p = 0.038) and rs1492099 (Odds ratio 2.29, p = 0.017) of angiotensin II receptor 1 (AGTR1), were associated with increased risk of AVF malfunction. After adjustment for age and other clinical factors, minor allele-containing genotype polymorphisms (AA and CA) of rs1492099 still remained to be a significant risk factor of AVF malfunction (Odds ratio 3.63, p = 0.005). In conclusion, we demonstrated that rs1492099, a SNP of AGTR1 gene, could be a potential genetic risk factor of AVF malfunction in male HD patients. PMID:27240348

Waveform model for an eccentric binary black hole based on the effective-one-body-numerical-relativity formalism

NASA Astrophysics Data System (ADS)

Cao, Zhoujian; Han, Wen-Biao

2017-08-01

Binary black hole systems are among the most important sources for gravitational wave detection. They are also good objects for theoretical research for general relativity. A gravitational waveform template is important to data analysis. An effective-one-body-numerical-relativity (EOBNR) model has played an essential role in the LIGO data analysis. For future space-based gravitational wave detection, many binary systems will admit a somewhat orbit eccentricity. At the same time, the eccentric binary is also an interesting topic for theoretical study in general relativity. In this paper, we construct the first eccentric binary waveform model based on an effective-one-body-numerical-relativity framework. Our basic assumption in the model construction is that the involved eccentricity is small. We have compared our eccentric EOBNR model to the circular one used in the LIGO data analysis. We have also tested our eccentric EOBNR model against another recently proposed eccentric binary waveform model; against numerical relativity simulation results; and against perturbation approximation results for extreme mass ratio binary systems. Compared to numerical relativity simulations with an eccentricity as large as about 0.2, the overlap factor for our eccentric EOBNR model is better than 0.98 for all tested cases, including spinless binary and spinning binary, equal mass binary, and unequal mass binary. Hopefully, our eccentric model can be the starting point to develop a faithful template for future space-based gravitational wave detectors.

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local parameter estimates for all the variables and an important reduction of the autocorrelation in the residuals of the GW linear model. Despite the fitting improvement of local models, GW regression, more than an alternative to "global" or traditional regression modelling, seems to be a valuable complement to explore the non-stationary relationships between the response variable and the explanatory variables. The synergy of global and local modelling provides insights into fire management and policy and helps further our understanding of the fire problem over large areas while at the same time recognizing its local character.

Risk of Recurrence in Operated Parasagittal Meningiomas: A Logistic Binary Regression Model.

PubMed

Escribano Mesa, José Alberto; Alonso Morillejo, Enrique; Parrón Carreño, Tesifón; Huete Allut, Antonio; Narro Donate, José María; Méndez Román, Paddy; Contreras Jiménez, Ascensión; Pedrero García, Francisco; Masegosa González, José

2018-02-01

Parasagittal meningiomas arise from the arachnoid cells of the angle formed between the superior sagittal sinus (SSS) and the brain convexity. In this retrospective study, we focused on factors that predict early recurrence and recurrence times. We reviewed 125 patients with parasagittal meningiomas operated from 1985 to 2014. We studied the following variables: age, sex, location, laterality, histology, surgeons, invasion of the SSS, Simpson removal grade, follow-up time, angiography, embolization, radiotherapy, recurrence and recurrence time, reoperation, neurologic deficit, degree of dependency, and patient status at the end of follow-up. Patients ranged in age from 26 to 81 years (mean 57.86 years; median 60 years). There were 44 men (35.2%) and 81 women (64.8%). There were 57 patients with neurologic deficits (45.2%). The most common presenting symptom was motor deficit. World Health Organization grade I tumors were identified in 104 patients (84.6%), and the majority were the meningothelial type. Recurrence was detected in 34 cases. Time of recurrence was 9 to 336 months (mean: 84.4 months; median: 79.5 months). Male sex was identified as an independent risk for recurrence with relative risk 2.7 (95% confidence interval 1.21-6.15), P = 0.014. Kaplan-Meier curves for recurrence had statistically significant differences depending on sex, age, histologic type, and World Health Organization histologic grade. A binary logistic regression was made with the Hosmer-Lemeshow test with P > 0.05; sex, tumor size, and histologic type were used in this model. Male sex is an independent risk factor for recurrence that, associated with other factors such tumor size and histologic type, explains 74.5% of all cases in a binary regression model. Copyright © 2017 Elsevier Inc. All rights reserved.

Improvement of Binary Analysis Components in Automated Malware Analysis Framework

DTIC Science & Technology

2017-02-21

analyze malicious software (malware) with minimum human interaction. The system autonomously analyze malware samples by analyzing malware binary program...AFRL-AFOSR-JP-TR-2017-0018 Improvement of Binary Analysis Components in Automated Malware Analysis Framework Keiji Takeda KEIO UNIVERSITY Final...currently valid OMB control number . PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      21-02-2017 2. REPORT

Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China.

PubMed

Yuan, Quan; Lu, Meng; Theofilatos, Athanasios; Li, Yi-Bing

2017-02-01

Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle (FV). This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. Moreover, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers' age, weight difference between vehicles, visibility condition and lane number of road significantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers' age and drivers' original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beijing on weekdays. Copyright © 2016 Daping Hospital and the Research Institute of Surgery of the Third Military Medical University. Production and hosting by Elsevier B.V. All rights reserved.

Studies of Horst's Procedure for Binary Data Analysis.

ERIC Educational Resources Information Center

Gray, William M.; Hofmann, Richard J.

Most responses to educational and psychological test items may be represented in binary form. However, such dichotomously scored items present special problems when an analysis of correlational interrelationships among the items is attempted. Two general methods of analyzing binary data are proposed by Horst to partial out the effects of…

The Impact of Additional Weekdays of Active Commuting to School on Children Achieving a Criterion of 300+ Minutes of Moderate-to-Vigorous Physical Activity

ERIC Educational Resources Information Center

Daly-Smith, Andy J. W.; McKenna, Jim; Radley, Duncan; Long, Jonathan

2011-01-01

Objective: To investigate the value of additional days of active commuting for meeting a criterion of 300+ minutes of moderate-to-vigorous physical activity (MVPA; 60+ mins/day x 5) during the school week. Methods: Based on seven-day diaries supported by teachers, binary logistic regression analyses were used to predict achievement of MVPA…

Multiple logistic regression model of signalling practices of drivers on urban highways

NASA Astrophysics Data System (ADS)

Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

2015-05-01

Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

[Prevalence of smoking among Colombian adolescents].

PubMed

Martínez-Torres, Javier; Peñuela Epalza, Martha

2017-03-01

Cigarette smoking is considered the most important preventable public health problem in developed countries, especially among adolescents. To determine the prevalence of cigarette smoking and associated factors in high school adolescents, from a Colombian city. The self-administered global tobacco youth survey (GTYS) was answered by 831 teenagers aged 14 ± 2 years (54% females). For data analysis, proportions were calculated; for associations, binary and multivariable logistic regression was applied. Fourteen percent of respondents declared that they had consumed at least one cigarette during the last 30 days. The life-time prevalence of tobacco use was 27.1%. Being older than thirteen years old, father’s academic level and having a smoker mother were factors associated with smoking. The prevalence of smoking in these adolescents was high. Age over 13 years and a smoking mother were associated with the cigarette smoking.

Independent Life Skills among psychosocial care network users of Rio Grande do Sul, Brazil.

PubMed

Rodrigues, Cândida Garcia Sinott Silveira; Jardim, Vanda Maria da Rosa; Kantorski, Luciane Prado; Coimbra, Valeria Cristina Christello; Treichel, Carlos Alberto Dos Santos; Francchini, Beatriz; Bretanha, Andreia Ferreira; Neutzling, Aline Dos Santos

2016-08-01

This is a cross-sectional study that aims to identify the prevalence of lower independent living skills and their associations in 390 users of psychiatric community-based services in the state Rio Grande do Sul, Brazil. For tracing the outcome it was used the "scale Independent Living Skills Survey", adopting a cut-off value lower than 2. The crude and adjusted analyses were conducted on binary logistic regressions and they considered a hierarchical model developed through a systematic literature review. In adjusted analysis the level of the same variables were adjusted to each other and to previous levels. The statistical significance remained as a < 0.05 p-value. The prevalence of smaller independent living skills was 33% and their associations were: younger age; no partner; lower education; resident at SRT; diagnosis of schizophrenia and younger diagnosis.

The role of middle-class status in payday loan borrowing: a multivariate approach.

PubMed

Lim, Younghee; Bickham, Trey; Broussard, Julia; Dinecola, Cassie M; Gregory, Alethia; Weber, Brittany E

2014-10-01

Payday loans refer to small-dollar, high-interest, short-term loans usually extended to lower-income consumers. Despite much research to the contrary, the payday loan industry asserts that it primarily serves middle-class Americans. This article discusses the authors' investigation of the industry's claim, by analyzing data from a U.S. bankruptcy court serving a Southern district. Results of the multivariate binary logistic regression analysis showed that, controlling for various sociodemographic and economic variables, two middle-class indicators--home-ownership and annual income at or greater than the median income--are associated with a decreased likelihood of using payday loans. The article concludes with a discussion of the implications of the results for social work practice and advocacy in regard to financial capability, particularly asset development, income maintenance, and payday loan regulation.

Anisotropic composite human skull model and skull fracture validation against temporo-parietal skull fracture.

PubMed

Sahoo, Debasis; Deck, Caroline; Yoganandan, Narayan; Willinger, Rémy

2013-12-01

A composite material model for skull, taking into account damage is implemented in the Strasbourg University finite element head model (SUFEHM) in order to enhance the existing skull mechanical constitutive law. The skull behavior is validated in terms of fracture patterns and contact forces by reconstructing 15 experimental cases. The new SUFEHM skull model is capable of reproducing skull fracture precisely. The composite skull model is validated not only for maximum forces, but also for lateral impact against actual force time curves from PMHS for the first time. Skull strain energy is found to be a pertinent parameter to predict the skull fracture and based on statistical (binary logistical regression) analysis it is observed that 50% risk of skull fracture occurred at skull strain energy of 544.0mJ. © 2013 Elsevier Ltd. All rights reserved.

Operation Pied Piper: a geographical reappraisal of the impact of wartime evacuation on scarlet fever and diphtheria rates in England and Wales, 1939-1945.

PubMed

Smallman-Raynor, M R; Cliff, A D

2015-10-01

This paper examines the geographical impact of the British Government's wartime evacuation scheme on notified rates of two common acute childhood diseases (scarlet fever and diphtheria) in the 1470 local government districts of England and Wales, 1939-1945. Drawing on the notifications of communicable diseases collated by the General Register Office (GRO), we establish pre-war (baseline) disease rates for the 1470 districts. For the war years, techniques of binary logistic regression analysis are used to assess the associations between (a) above-baseline ('raised') disease rates in evacuation, neutral and reception districts and (b) the major phases of the evacuation scheme. The analysis demonstrates that the evacuation was temporally associated with distinct national and regional effects on notified levels of disease activity. These effects were most pronounced in the early years of the dispersal (1939-1941) and corresponded with initial levels of evacuation-related population change at the regional and district scales.

[Voluntary help in dementia - predictors for utilisation and expected quality from a family caregiver's point of view].

PubMed

Grässel, E; Luttenberger, K; Römer, H; Donath, C

2010-09-01

Although support services are considered cost-effective in the relief of care-giving family members of dementia patients, there has been little research to date on the predictors of use and quality expectations. These two questions are examined for the first time based on cross-sectional data of 404 care-giving family members, users and non-users of voluntary help services. Quantitative data are evaluated using binary logistical regression analysis, qualitative data using content analysis. The rating of how helpful the use of a voluntary help service is in the personal situation was found to be the only significant predictor of use. With respect to quality, it is most important that the persons giving support be punctual and well-trained. To increase the rate of use, care-giving family members must be convinced of the relevant benefits of using a voluntary help service. In addition, attention must be paid to the professional organization and training of voluntary helpers. Georg Thieme Verlag KG Stuttgart, New York.

Postsurgical complications in patients with renal tumours with venous thrombosis treated with surgery.

PubMed

Caño-Velasco, J; Herranz-Amo, F; Barbas-Bernardos, G; Mayor-de Castro, J; Aragón-Chamizo, J; Arnal-Chacón, G; Lledó García, E; Hernández-Fernández, C

2018-04-06

Surgery on renal tumours with venous thrombosis suffers a high rate of complications and non-negligible perioperative mortality. Our objective was to analyse the postoperative complications, their relationship with the level of the thrombus and its potential predisposing factors. A retrospective analysis was conducted of 101 patients with renal tumours with venous thrombosis operated on between 1988 and 2017. Two patients were excluded because of intraoperative pulmonary thromboembolism and exitus (2%). The postsurgical complications were classified according to Clavien-Dindo. To compare the qualitative variables, we employed the chi-squared test. We performed a multivariate analysis using binary logistic regression to identify the independent predictors. Some type of postsurgical complication occurred in 34 (34.3%) patients, 11 (11.1%) of which were severe (Clavien III-V). There were significant differences in the total complications (P=.003) and severe complications (Clavien≥III; P=.03) depending on the level of the tumour thrombus. Copyright © 2018 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Optimization of binary thermodynamic and phase diagram data

NASA Astrophysics Data System (ADS)

Bale, Christopher W.; Pelton, A. D.

1983-03-01

An optimization technique based upon least squares regression is presented to permit the simultaneous analysis of diverse experimental binary thermodynamic and phase diagram data. Coefficients of polynomial expansions for the enthalpy and excess entropy of binary solutions are obtained which can subsequently be used to calculate the thermodynamic properties or the phase diagram. In an interactive computer-assisted analysis employing this technique, one can critically analyze a large number of diverse data in a binary system rapidly, in a manner which is fully self-consistent thermodynamically. Examples of applications to the Bi-Zn, Cd-Pb, PbCl2-KCl, LiCl-FeCl2, and Au-Ni binary systems are given.

[Overload in the informal caregivers of patients with multiple comorbidities in an urban area].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Ortega-Calvo, Manuel; Ruiz-Arias, Esperanza

2012-01-01

The aim of the study was, to determine the profile of the family caregiver of patients with multiple pathologies, identify factors associated with overload, and construct predictive models using items from the Caregiver Strain Index (CSI). A cross-sectional study of caregivers of patients with multiple comorbidities who attended an urban health centre. Data were collected from health records and questionnaires (Barthel index, Pfeiffer index, and CSI). Statistical analysis was performed using measures of central tendency and dispersion, and by building multivariate models with binary logistic regression with the CSI items as predictors (program R version 2.14.0). The sample included 67 caregivers, with a mean age of 64.69 years (standard deviation=12.71, median 62 years), of whom 74.6% were women, 35.8% were wives, and 32.8% were daughters. The level of dependence of the patients cared for was total/severe in 77.6%, and moderate in 12% (Barthel), and 47.8% had some level of cognitive impairment (Pfeiffer). A CSI equal or greater than 7 was seen in 47.8% of caregivers, identifying life problems in more than 40% of them such as, restriction of social life, physical exertion, discomfort with change, bad behaviour, personal and family emotional changes, and sleep disturbances. Item 4 of the CSI, analysing the social restriction, was the one that showed a greater significance in the predictive multivariate model. Item 12 (economic burden) was the most significant with age in patients with cognitive impairment. Women tend to take the role of caregiver at an earlier age than men in the urban environment studied, and items from CSI showed that items 4 (social restrictions) and 12 (economic burden) have more significance in the predictive models constructed with Binary Logistic Regression. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Postoperative Delirium in Severely Burned Patients Undergoing Early Escharotomy: Incidence, Risk Factors, and Outcomes.

PubMed

Guo, Zhenggang; Liu, Jiabin; Li, Jia; Wang, Xiaoyan; Guo, Hui; Ma, Panpan; Su, Xiaojun; Li, Ping

The aim of this study is to investigate the incidence, related risk factors, and outcomes of postoperative delirium (POD) in severely burned patients undergoing early escharotomy. This study included 385 severely burned patients (injured <1 week; TBSA, 31-50% or 11-20%; American Society of Anesthesiologists physical status, II-IV) aged 18 to 65 years, who underwent early escharotomy between October 2014 and December 2015, and were selected by cluster sampling. The authors excluded patients with preoperative delirium or diagnosed dementia, depression, or cognitive dysfunction. Preoperative, perioperative, intraoperative, and postoperative information, such as demographic characteristics, vital signs, and health history were collected. The Confusion Assessment Method was used once daily for 5 days after surgery to identify POD. Stepwise binary logistic regression analysis was used to identify the risk factors for POD, t-tests, and χ tests were performed to compare the outcomes of patients with and without the condition. Fifty-six (14.55%) of the patients in the sample were diagnosed with POD. Stepwise binary logistic regression showed that the significant risk factors for POD in severely burned patients undergoing early escharotomy were advanced age (>50 years old), a history of alcohol consumption (>3/week), high American Society of Anesthesiologists classification (III or IV), time between injury and surgery (>2 days), number of previous escharotomies (>2), combined intravenous and inhalation anesthesia, no bispectral index applied, long duration surgery (>180 min), and intraoperative hypotension (mean arterial pressure < 55 mm Hg). On the basis of the different odds ratios, the authors established a weighted model. When the score of a patient's weighted odds ratios is more than 6, the incidence of POD increased significantly (P < .05). When the score of a patient's weighted odds ratios is more than 6, the incidence of POD increased significantly (P < .05). Further, POD was associated with more postoperative complications, including hepatic and renal function impairment and hypernatremia, as well as prolonged hospitalization, increased medical costs, and higher mortality.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

NASA Astrophysics Data System (ADS)

Greco, R.; Sorriso-Valvo, M.

2013-09-01

Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

On Bayesian Rules for Selecting 3PL Binary Items for Criterion-Referenced Interpretations and Creating Booklets for Bookmark Standard Setting.

ERIC Educational Resources Information Center

Huynh, Huynh

By noting that a Rasch or two parameter logistic (2PL) item belongs to the exponential family of random variables and that the probability density function (pdf) of the correct response (X=1) and the incorrect response (X=0) are symmetric with respect to the vertical line at the item location, it is shown that the conjugate prior for ability is…

A combination chaotic system and application in color image encryption

NASA Astrophysics Data System (ADS)

Parvaz, R.; Zarebnia, M.

2018-05-01

In this paper, by using Logistic, Sine and Tent systems we define a combination chaotic system. Some properties of the chaotic system are studied by using figures and numerical results. A color image encryption algorithm is introduced based on new chaotic system. Also this encryption algorithm can be used for gray scale or binary images. The experimental results of the encryption algorithm show that the encryption algorithm is secure and practical.

Management Options and Outcomes for Neonatal Hypoplastic Left Heart Syndrome in the Early Twenty-First Century.

PubMed

Kane, Jason M; Canar, Jeff; Kalinowski, Valerie; Johnson, Tricia J; Hoehn, K Sarah

2016-02-01

Without surgical treatment, neonatal hypoplastic left heart syndrome (HLHS) mortality in the first year of life exceeds 90 % and, in spite of improved surgical outcomes, many families still opt for non-surgical management. The purpose of this study was to investigate trends in neonatal HLHS management and to identify characteristics of patients who did not undergo surgical palliation. Neonates with HLHS were identified from a serial cross-sectional analysis using the Healthcare Cost and Utilization Project's Kids' Inpatient Database from 2000 to 2012. The primary analysis compared children undergoing surgical palliation to those discharged alive without surgery using a binary logistic regression model. Multivariate logistic regression was conducted to determine factors associated with treatment choice. A total of 1750 patients underwent analysis. Overall hospital mortality decreased from 35.3 % in 2000 to 22.9 % in 2012. The percentage of patients undergoing comfort care discharge without surgery also decreased from 21.2 to 14.8 %. After controlling for demographics and comorbidities, older patients at presentation were less likely to undergo surgery (OR 0.93, 0.91-0.96), and patients in 2012 were more likely to undergo surgery compared to those in prior years (OR 1.5, 1.1-2.1). Discharge without surgical intervention is decreasing with a 30 % reduction between 2000 and 2012. Given the improvement in surgical outcomes, further dialogue about ethical justification of non-operative comfort or palliative care is warranted. In the meantime, clinicians should present families with surgical outcome data and recommend intervention, while supporting their option to refuse.

Efficacy of pulsed dye laser treatment for common warts is not influenced by the causative HPV type: a prospective study.

PubMed

Fichman, Yoseph; Levi, Assi; Hodak, Emmilia; Halachmi, Shlomit; Mazor, Sigal; Wolf, Dana; Caplan, Orit; Lapidoth, Moshe

2018-05-01

Verruca vulgaris (VV) is a prevalent skin condition caused by various subtypes of human papilloma virus (HPV). The most common causes of non-genital lesions are HPV types 2 and 4, and to a lesser extent types 1, 3, 26, 29, and 57. Although numerous therapeutic modalities exist, none is universally effective or without adverse events (AE). Pulsed dye laser (PDL) is a favorable option due to its observed efficacy and relatively low AE rate. However, it is not known which verrucae are most likely to respond to PDL, or whether the causative viral subtype influences this response. The objective of this prospective blinded study was to assess whether the HPV subtype was predictive of response to PDL. For that matter, 26 verrucae from 26 immunocompetent patients were biopsied prior to treatment by PDL. HPV coding sequences were isolated and genotyped using PCR analysis. Patients were treated by PDL (595 nm wavelength, 5 mm spot size, 1.5 ms pulse duration, 12 J/cm 2 fluence) once a month for up to 6 months, and clinical response was assessed. Binary logistic regression analysis and linear logistic regression analysis were used in order to evaluate statistical significance. Different types of HPV were identified in 22 of 26 tissue samples. Response to treatment did not correlate with HPV type, age, or gender. As no association between HPV type and response to PDL therapy could be established, it is therefore equally effective for all HPV types and remains a favorable treatment option for all VV.

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

[Analysis of binary classification repeated measurement data with GEE and GLMMs using SPSS software].

PubMed

An, Shengli; Zhang, Yanhong; Chen, Zheng

2012-12-01

To analyze binary classification repeated measurement data with generalized estimating equations (GEE) and generalized linear mixed models (GLMMs) using SPSS19.0. GEE and GLMMs models were tested using binary classification repeated measurement data sample using SPSS19.0. Compared with SAS, SPSS19.0 allowed convenient analysis of categorical repeated measurement data using GEE and GLMMs.

An Experimental Realization of a Chaos-Based Secure Communication Using Arduino Microcontrollers.

PubMed

Zapateiro De la Hoz, Mauricio; Acho, Leonardo; Vidal, Yolanda

2015-01-01

Security and secrecy are some of the important concerns in the communications world. In the last years, several encryption techniques have been proposed in order to improve the secrecy of the information transmitted. Chaos-based encryption techniques are being widely studied as part of the problem because of the highly unpredictable and random-look nature of the chaotic signals. In this paper we propose a digital-based communication system that uses the logistic map which is a mathematically simple model that is chaotic under certain conditions. The input message signal is modulated using a simple Delta modulator and encrypted using a logistic map. The key signal is also encrypted using the same logistic map with different initial conditions. In the receiver side, the binary-coded message is decrypted using the encrypted key signal that is sent through one of the communication channels. The proposed scheme is experimentally tested using Arduino shields which are simple yet powerful development kits that allows for the implementation of the communication system for testing purposes.

Heterogeneous Suppression of Sequential Effects in Random Sequence Generation, but Not in Operant Learning.

PubMed

Shteingart, Hanan; Loewenstein, Yonatan

2016-01-01

There is a long history of experiments in which participants are instructed to generate a long sequence of binary random numbers. The scope of this line of research has shifted over the years from identifying the basic psychological principles and/or the heuristics that lead to deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of participants' choices. Surprisingly, a population analysis indicated that the contribution of the most recent trial has only a weak effect on behavior, compared to more preceding trials, a result that seems irreconcilable with standard sequential effects that decay monotonously with the delay. However, when considering each participant separately, we found that the magnitudes of the sequential effect are a monotonous decreasing function of the delay, yet these individual sequential effects are largely averaged out in a population analysis because of heterogeneity. The substantial behavioral heterogeneity in this task is further demonstrated quantitatively by considering the predictive power of the model. We show that a heterogeneous model of sequential dependencies captures the structure available in random sequence generation. Finally, we show that the results of the logistic regression analysis can be interpreted in the framework of reinforcement learning, allowing us to compare the sequential effects in the random sequence generation task to those in an operant learning task. We show that in contrast to the random sequence generation task, sequential effects in operant learning are far more homogenous across the population. These results suggest that in the random sequence generation task, different participants adopt different cognitive strategies to suppress sequential dependencies when generating the "random" sequences.

Research on the Orbital Period of Massive Binaries

NASA Astrophysics Data System (ADS)

Zhao, E.; Qain, S.

2011-12-01

Massive binary is the kind of binary, whose spectral type is earlier than B5. Research on massive binary plays an important role in the mass and angular momentum transfer or loss between the components, and the evolution of binary. Some massive binaries are observed and analyzed, including O-type binary LY Aur, B-type contact binary RZ Pyx and B-type semi-detached binary AI Cru. It is found that all of their periods have a long-term increasing, which indicates that the system is undergoing a Case A slow mass transfer stage on the nuclear time-scale of the secondary. Moreover, analysis show a cyclic change of orbital period, which can be explained by the light-travel effect time of the third body.

Prevalence and predictors of thyroid functional abnormalities in newly diagnosed AL amyloidosis.

PubMed

Muchtar, E; Dean, D S; Dispenzieri, A; Dingli, D; Buadi, F K; Lacy, M Q; Hayman, S R; Kapoor, P; Leung, N; Russell, S; Lust, J A; Lin, Yi; Warsame, R; Gonsalves, W; Kourelis, T V; Go, R S; Chakraborty, R; Zeldenrust, S; Kyle, R A; Rajkumar, S Vincent; Kumar, S K; Gertz, M A

2017-06-01

Data on the effect of systemic immunoglobulin light chain amyloidosis (AL amyloidosis) on thyroid function are limited. To assess the prevalence of hypothyroidism in AL amyloidosis patients and determine its predictors. 1142 newly diagnosed AL amyloidosis patients were grouped based on the thyroid-stimulating hormone (TSH) measurement at diagnosis: hypothyroid group (TSH above upper normal reference; >5 mIU L -1 ; n = 217, 19% of study participants) and euthyroid group (n = 925, 81%). Predictors for hypothyroidism were assessed in a binary multivariate model. Survival between groups was compared using the log-rank test and a multivariate analysis. Patients with hypothyroidism were older, more likely to present with renal and hepatic involvement and had a higher light chain burden compared to patients in the euthyroid group. Higher proteinuria in patients with renal involvement and lower albumin in patients with hepatic involvement were associated with hypothyroidism. In a binary logistic regression model, age ≥65 years, female sex, renal involvement, hepatic involvement, kappa light chain restriction and amiodarone use were independently associated with hypothyroidism. Ninety-three per cent of patients in the hypothyroid group with free thyroxine measurement had normal values, consistent with subclinical hypothyroidism. Patients in the hypothyroid group had a shorter survival compared to patients in the euthyroid group (4-year survival 36% vs 43%; P = 0.008), a difference that was maintained in a multivariate analysis. A significant proportion of patients with AL amyloidosis present with hypothyroidism, predominantly subclinical, which carries a survival disadvantage. Routine assessment of TSH in these patients is warranted. © 2017 The Association for the Publication of the Journal of Internal Medicine.

MARVELS Radial Velocity Solutions to Seven Kepler Eclipsing Binaries

NASA Astrophysics Data System (ADS)

Heslar, Michael Francis; Thomas, Neil B.; Ge, Jian; Ma, Bo; Herczeg, Alec; Reyes, Alan; SDSS-III MARVELS Team

2016-01-01

Eclipsing binaries serve momentous purposes to improve the basis of understanding aspects of stellar astrophysics, such as the accurate calculation of the physical parameters of stars and the enigmatic mass-radius relationship of M and K dwarfs. We report the investigation results of 7 eclipsing binary candidates, initially identified by the Kepler mission, overlapped with the radial velocity observations from the SDSS-III Multi-Object APO Radial-Velocity Exoplanet Large-Area Survey (MARVELS). The RV extractions and spectroscopic solutions of these eclipsing binaries were generated by the University of Florida's 1D data pipeline with a median RV precision of ~60-100 m/s, which was utilized for the DR12 data release. We performed the cross-reference fitting of the MARVELS RV data and the Kepler photometric fluxes obtained from the Kepler Eclipsing Binary Catalog (V2) and modelled the 7 eclipsing binaries in the BinaryMaker3 and PHOEBE programs. This analysis accurately determined the absolute physical and orbital parameters of each binary. Most of the companion stars were determined to have masses of K and M dwarf stars (0.3-0.8 M⊙), and allowed for an investigation into the mass-radius relationship of M and K dwarfs. Among the cases are KIC 9163796, a 122.2 day period "heartbeat star", a recently-discovered class of eccentric binaries known for tidal distortions and pulsations, with a high eccentricity (e~0.75) and KIC 11244501, a 0.29 day period, contact binary with a double-lined spectrum and mass ratio (q~0.45). We also report on the possible reclassification of 2 Kepler eclipsing binary candidates as background eclipsing binaries based on the analysis of the flux measurements, flux ratios of the spectroscopic and photometric solutions, the differences in the FOVs, the image processing of Kepler, and RV and spectral analysis of MARVELS.

Childhood growth and development associated with need for full-time special education at school age.

PubMed

Mannerkoski, Minna; Aberg, Laura; Hoikkala, Marianne; Sarna, Seppo; Kaski, Markus; Autti, Taina; Heiskala, Hannu

2009-01-01

To explore how growth measurements and attainment of developmental milestones in early childhood reflect the need for full-time special education (SE). After stratification in this population-based study, 900 pupils in full-time SE groups (age-range 7-16 years, mean 12 years 8 months) at three levels and 301 pupils in mainstream education (age-range 7-16, mean 12 years 9 months) provided data on height and weight from birth to age 7 years and head circumference to age 1 year. Developmental screening was evaluated from age 1 month to 48 months. Statistical methods included a general linear model (growth measurements), binary logistic regression analysis (odds ratios for growth), and multinomial logistic regression analysis (odds ratios for developmental milestones). At 1 year, a 1 standard deviation score (SDS) decrease in height raised the probability of SE placement by 40%, and a 1 SDS decrease in head size by 28%. In developmental screening, during the first months of life the gross motor milestones, especially head support, differentiated the children at levels 0-3. Thereafter, the fine motor milestones and those related to speech and social skills became more important. Children whose growth is mildly impaired, though in the normal range, and who fail to attain certain developmental milestones have an increased probability for SE and thus a need for special attention when toddlers age. Similar to the growth curves, these children seem to have consistent developmental curves (patterns).

Child sex tourism - prevalence of and risk factors for its use in a German community sample.

PubMed

Koops, Thula; Turner, Daniel; Neutze, Janina; Briken, Peer

2017-04-20

To investigate the prevalence of child sex tourism (CST) in a large German community sample, and to compare those who made use of CST with other child sexual abusers regarding established characteristics and risk factors for child sexual abuse. Adult German men were recruited through a German market research panel and questioned by means of an anonymous online survey. Group assignment was accomplished based on information on previous sexual contacts with children and previous use of CST. Characteristics and risk factors were compared between the groups using t- and Chi-square tests. Binary logistic regression analysis was performed to predict CST. Data collection was conducted in 2013, data analysis in January 2015. Out of 8718 men, 36 (0.4%) reported CST use. The CST group differed from the nonCST group (n = 96; 1.1%) with regard to pedophilic sexual and antisocial behaviors as well as own experiences of sexual abuse. Social difficulties, pedophilic sexual interests, and hypersexuality were not distinct features in the CST group. Own experiences of sexual abuse, child prostitution use, and previous conviction for a violent offense predicted CST in a logistic regression model. This study is a first step to gain insight into the prevalence and characteristics of men using CST. Findings could help to augment prevention strategies against commercial forms of sexual abuse in developed as well as in developing countries by fostering the knowledge about the characteristics of perpetrators.

Age at onset of major depressive disorder in Han Chinese women: Relationship with clinical features and family history☆

PubMed Central

Yang, Fuzhong; Li, Yihan; Xie, Dong; Shao, Chunhong; Ren, Jianer; Wu, Wenyuan; Zhang, Ning; Zhang, Zhen; Zou, Ying; Zhang, Jiulong; Qiao, Dongdong; Gao, Chengge; Li, Youhui; Hu, Jian; Deng, Hong; Wang, Gang; Du, Bo; Wang, Xumei; Liu, Tiebang; Gan, Zhaoyu; Peng, Juyi; Wei, Bo; Pan, Jiyang; Chen, Honghui; Sun, Shufan; Jia, Hong; Liu, Ying; Chen, Qiaoling; Wang, Xueyi; Cao, Juling; Lv, Luxian; Chen, Yunchun; Ha, Baowei; Ning, Yuping; Chen, YiPing; Kendler, Kenneth S.; Flint, Jonathan; Shi, Shenxun

2011-01-01

Background Individuals with early-onset depression may be a clinically distinct group with particular symptom patterns, illness course, comorbidity and family history. This question has not been previously investigated in a Han Chinese population. Methods We examined the clinical features of 1970 Han Chinese women with DSM-IV major depressive disorder (MDD) between 30 and 60 years of age across China. Analysis of linear, logistic and multiple logistic regression models was used to determine the association between age at onset (AAO) with continuous, binary and discrete characteristic clinical features of MDD. Results Earlier AAO was associated with more suicidal ideation and attempts and higher neuroticism, but fewer sleep, appetite and weight changes. Patients with an earlier AAO were more likely to suffer a chronic course (longer illness duration, more MDD episodes and longer index episode), increased rates of MDD in their parents and a lower likelihood of marriage. They tend to have higher comorbidity with anxiety disorders (general anxiety disorder, social phobia and agoraphobia) and dysthymia. Conclusions Early AAO in MDD may be an index of a more severe, highly comorbid and familial disorder. Our findings indicate that the features of MDD in China are similar to those reported elsewhere in the world. PMID:21782247

Age at onset of major depressive disorder in Han Chinese women: relationship with clinical features and family history.

PubMed

Yang, Fuzhong; Li, Yihan; Xie, Dong; Shao, Chunhong; Ren, Jianer; Wu, Wenyuan; Zhang, Ning; Zhang, Zhen; Zou, Ying; Zhang, Jiulong; Qiao, Dongdong; Gao, Chengge; Li, Youhui; Hu, Jian; Deng, Hong; Wang, Gang; Du, Bo; Wang, Xumei; Liu, Tiebang; Gan, Zhaoyu; Peng, Juyi; Wei, Bo; Pan, Jiyang; Chen, Honghui; Sun, Shufan; Jia, Hong; Liu, Ying; Chen, Qiaoling; Wang, Xueyi; Cao, Juling; Lv, Luxian; Chen, Yunchun; Ha, Baowei; Ning, Yuping; Chen, Yiping; Kendler, Kenneth S; Flint, Jonathan; Shi, Shenxun

2011-12-01

Individuals with early-onset depression may be a clinically distinct group with particular symptom patterns, illness course, comorbidity and family history. This question has not been previously investigated in a Han Chinese population. We examined the clinical features of 1970 Han Chinese women with DSM-IV major depressive disorder (MDD) between 30 and 60 years of age across China. Analysis of linear, logistic and multiple logistic regression models was used to determine the association between age at onset (AAO) with continuous, binary and discrete characteristic clinical features of MDD. Earlier AAO was associated with more suicidal ideation and attempts and higher neuroticism, but fewer sleep, appetite and weight changes. Patients with an earlier AAO were more likely to suffer a chronic course (longer illness duration, more MDD episodes and longer index episode), increased rates of MDD in their parents and a lower likelihood of marriage. They tend to have higher comorbidity with anxiety disorders (general anxiety disorder, social phobia and agoraphobia) and dysthymia. Early AAO in MDD may be an index of a more severe, highly comorbid and familial disorder. Our findings indicate that the features of MDD in China are similar to those reported elsewhere in the world. Copyright © 2011 Elsevier B.V. All rights reserved.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Malware detection and analysis

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

Chiang, Ken; Lloyd, Levi; Crussell, Jonathan

Embodiments of the invention describe systems and methods for malicious software detection and analysis. A binary executable comprising obfuscated malware on a host device may be received, and incident data indicating a time when the binary executable was received and identifying processes operating on the host device may be recorded. The binary executable is analyzed via a scalable plurality of execution environments, including one or more non-virtual execution environments and one or more virtual execution environments, to generate runtime data and deobfuscation data attributable to the binary executable. At least some of the runtime data and deobfuscation data attributable tomore » the binary executable is stored in a shared database, while at least some of the incident data is stored in a private, non-shared database.« less

Beyond the Binary: Differences in Eating Disorder Prevalence by Gender Identity in a Transgender Sample.

PubMed

Diemer, Elizabeth W; White Hughto, Jaclyn M; Gordon, Allegra R; Guss, Carly; Austin, S Bryn; Reisner, Sari L

2018-01-01

Purpose: To investigate whether the prevalence of eating disorders (EDs) differs across diverse gender identity groups in a transgender sample. Methods: Secondary analysis of data from Project VOICE, a cross-sectional study of stress and health among 452 transgender adults (ages 18-75 years) residing in Massachusetts. Age-adjusted logistic regression models were fit to compare the prevalence of self-reported lifetime EDs in female-to-male (FTM), male-to-female (MTF), and gender-nonconforming participants assigned male at birth (MBGNC) to gender-nonconforming participants assigned female at birth (FBGNC; referent). Results: The age-adjusted odds of self-reported ED in MTF participants were 0.14 times the odds of self-reported ED in FBGNC participants ( p =0.022). In FTM participants, the age-adjusted odds of self-reported ED were 0.46 times the odds of self-reported ED in FBGNC participants, a marginally significant finding ( p =0.068). No statistically significant differences in ED prevalence were found for MBGNC individuals. Conclusions: Gender nonconforming individuals assigned a female sex at birth appear to have heightened lifetime risk of EDs relative to MTF participants. Further research into specific biologic and psychosocial ED risk factors and gender-responsive intervention strategies are urgently needed. Training clinical providers and ensuring competency of treatment services beyond the gender binary will be vital to addressing this disparity.

Beyond the Binary: Differences in Eating Disorder Prevalence by Gender Identity in a Transgender Sample

PubMed Central

Diemer, Elizabeth W.; White Hughto, Jaclyn M.; Gordon, Allegra R.; Guss, Carly; Austin, S. Bryn; Reisner, Sari L.

2018-01-01

Abstract Purpose: To investigate whether the prevalence of eating disorders (EDs) differs across diverse gender identity groups in a transgender sample. Methods: Secondary analysis of data from Project VOICE, a cross-sectional study of stress and health among 452 transgender adults (ages 18–75 years) residing in Massachusetts. Age-adjusted logistic regression models were fit to compare the prevalence of self-reported lifetime EDs in female-to-male (FTM), male-to-female (MTF), and gender-nonconforming participants assigned male at birth (MBGNC) to gender-nonconforming participants assigned female at birth (FBGNC; referent). Results: The age-adjusted odds of self-reported ED in MTF participants were 0.14 times the odds of self-reported ED in FBGNC participants (p=0.022). In FTM participants, the age-adjusted odds of self-reported ED were 0.46 times the odds of self-reported ED in FBGNC participants, a marginally significant finding (p=0.068). No statistically significant differences in ED prevalence were found for MBGNC individuals. Conclusions: Gender nonconforming individuals assigned a female sex at birth appear to have heightened lifetime risk of EDs relative to MTF participants. Further research into specific biologic and psychosocial ED risk factors and gender-responsive intervention strategies are urgently needed. Training clinical providers and ensuring competency of treatment services beyond the gender binary will be vital to addressing this disparity. PMID:29359198

Human Epidermal Growth Factor Receptor 2 Expression in Unresectable Gastric Cancers: Relationship with CT Characteristics.

PubMed

Lee, Jeong Sub; Kim, Se Hyung; Im, Seock-Ah; Kim, Min A; Han, Joon Koo

2017-01-01

To retrospectively analyze the qualitative CT features that correlate with human epidermal growth factor receptor 2 (HER2)-expression in pathologically-proven gastric cancers. A total of 181 patients with pathologically-proven unresectable gastric cancers with HER2-expression (HER2-positive [n = 32] and negative [n = 149]) were included. CT features of primary gastric and metastatic tumors were reviewed. The prevalence of each CT finding was compared in both groups. Thereafter, binary logistic regression determined the most significant differential CT features. Clinical outcomes were compared using Kaplan-Meier method. HER2-postive cancers showed lower clinical T stage (21.9% vs. 8.1%; p = 0.015), hyperattenuation on portal phase (62.5% vs. 30.9%; p = 0.003), and was more frequently metastasized to the liver (62.5% vs. 32.2%; p = 0.001), than HER2-negative cancers. On binary regression analysis, hyperattenuation of the tumor (odds ratio [OR], 4.68; p < 0.001) and hepatic metastasis (OR, 4.43; p = 0.001) were significant independent factors that predict HER2-positive cancers. Median survival of HER2-positive cancers (13.7 months) was significantly longer than HER2-negative cancers (9.6 months) ( p = 0.035). HER2-positive gastric cancers show less-advanced T stage, hyperattenuation on the portal phase, and frequently metastasize to the liver, as compared to HER2-negative cancers.

Predictors of depressive symptoms in older Japanese primiparas at 1 month post-partum: A risk-stratified analysis.

PubMed

Iwata, Hiroko; Mori, Emi; Tsuchiya, Miyako; Sakajo, Akiko; Maehara, Kunie; Ozawa, Harumi; Morita, Akiko; Maekawa, Tomoko; Aoki, Kyoko; Tamakoshi, Koji

2016-01-01

Older maternal age has become more common in Japan. Studies suggest that older maternal age and primiparity are associated with post-partum depression. The present study aimed to identify predictors of post-partum depression in older Japanese primiparas at 1 month post-partum. Participants were 479 primiparas aged 35 years and over, drawn from a prospective cohort study. Data were collected using self-report questionnaires. Depression was measured with the Japanese version of the Edinburgh Postnatal Depression Scale. Stepwise logistic regression analysis was conducted on binary outcome variables of depression at 1 month post-partum, along with a stratified analysis based on the risk status of depression. Five predictors were identified: (i) the depression score during hospital stay; (ii) financial burden; (iii) dissatisfaction with appraisal support; (iv) physical burden in daily life; and (v) concerns about infant caretaking. Stratified analysis identified dissatisfaction with instrumental support in the low-risk group, and the Child-care Value Scale score as unique predictors in the high-risk group. These results highlight the importance of early assessment of depressive symptoms and the provision of continuous care. © 2015 Japan Academy of Nursing Science.

Milk consumption and lactose intolerance in adults.

PubMed

Qiao, Rong; Huang, ChengYu; Du, HuiZhang; Zeng, Guo; Li, Ling; Ye, Sheng

2011-10-01

To investigate relations between milk consumption and lactose intolerance (LI) in adults and to explore the effect of milk consumption on lactase activity. Total of 182 subjects aged 20-70 years were recruited and interviewed by questionnaires, and their accumulative cow's milk intake (AMI) was calculated. LI was evaluated by hydrogen breath test (HBT). A negative correlation was found between AMI and severity of observed LI symptom (r=-0.2884; P<0.05). Binary logistic regression analysis showed a negative correlation between LI and duration and frequency of milk consumption (OR, 0.317 and 0.465, respectively; both P<0.05) and a positive correlation between LI and amount of milk consumed per sitting (OR, 6.337; P<0.05). LI is related to various milk consumption behaviors. Most Chinese adults with LI may tolerate moderate milk consumption <160 mL. Copyright © 2011 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

Spectral analysis of white ash response to emerald ash borer infestations

NASA Astrophysics Data System (ADS)

Calandra, Laura

The emerald ash borer (EAB) (Agrilus planipennis Fairmaire) is an invasive insect that has killed over 50 million ash trees in the US. The goal of this research was to establish a method to identify ash trees infested with EAB using remote sensing techniques at the leaf-level and tree crown level. First, a field-based study at the leaf-level used the range of spectral bands from the WorldView-2 sensor to determine if there was a significant difference between EAB-infested white ash (Fraxinus americana) and healthy leaves. Binary logistic regression models were developed using individual and combinations of wavelengths; the most successful model included 545 and 950 nm bands. The second half of this research employed imagery to identify healthy and EAB-infested trees, comparing pixel- and object-based methods by applying an unsupervised classification approach and a tree crown delineation algorithm, respectively. The pixel-based models attained the highest overall accuracies.

[Characteristics present in secondary school students who do not smoke and who have no intention to smoke].

PubMed

Lima-Serrano, Marta; Martínez-Montilla, José Manuel; Vargas-Martínez, Ana Magdalena; Zafra-Agea, José Antonio; Lima-Rodríguez, Joaquín Salvador

2018-02-27

To know the variables present in primary and secondary school students who do not smoke or intend to smoke from a positive health model. Cross-sectional study with 482 students from Andalusia and Catalonia using a validated questionnaire (ESFA and PASE project). Binary logistic regression analysis was performed. Those who did not intend to smoke viewed smoking unfavourably and had high self-efficacy (p <0.001). In non-consumers, the most associated variables were attitude, social model (p <0.001), and self-efficacy (p =0.005). The results show motivational factors present in students who do not smoke and do not intend to do so. Attitude and self-efficacy are strongly associated with intention and behaviour. This information might be useful for developing positive health promotion strategies from a salutogenesis approach. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Central nervous system drug consumption depending on the time between symptom onset and the diagnosis of Alzheimer's disease: an analysis by the Registry of Dementias of Girona.

PubMed

Calvó-Perxas, Laia; López-Pousa, Secundino; Vilalta-Franch, Joan; Turró-Garriga, Oriol; Blankenburg, Michael; Febrer, Laia; Flaqué, Margarida; Vallmajó, Natàlia; Aguirregomozcorta, Maria; Genís, David; Casas, Isabel; Perkal, Héctor; Coromina, Joan; Garre-Olmo, Josep

2012-01-01

To describe central nervous system (CNS) drug consumption patterns depending on the time to diagnosis of Alzheimer's disease (AD), and to check whether the cases diagnosed later are associated with greater severity and consuming more CNS drugs. Cross-sectional study using 952 cases of the Registry of Dementias of Girona. A binary logistic regression was used to detect variables associated with the use of CNS drugs depending on the time to diagnosis. CNS drugs were consumed by 95.8% of the AD patients. Only antipsychotics presented a statistically significant increase in the frequency of prescription to patients with longer time elapsed from symptom onset to AD diagnosis. Longer time elapsed from the onset of symptoms to the diagnosis resulted in increased probability of antipsychotic consumption. Copyright © 2012 S. Karger AG, Basel.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Family violence exposure and associated risk factors for child PTSD in a Mexican sample.

PubMed

Erolin, Kara S; Wieling, Elizabeth; Parra, R Elizabeth Aguilar

2014-06-01

This study was undertaken in an effort to help illuminate the deleterious effects of traumatic stress on children and families in Mexico. Rates of exposure to traumatic events, family and community violence, and posttraumatic stress disorder (PTSD) were investigated in 87 school-age children and their mothers. Binary logistic regression analysis was performed to examine potential family and ecological risk factors for the presence of child PTSD. A total of 51 children (58.6%) reported an event that met the DSM-IV A criteria, and 36 children (41.4%; 20 boys and 16 girls) met criteria for full PTSD. Traumatic exposure in this sample was considerable, particularly intense, and chronic as a result of interpersonal violence in the home and community. Results support the need for preventive systemic interventions targeting the individual level, parent-child dyadic level, and the larger cultural and community context. Published by Elsevier Ltd.

[Analysis of population survey for determining the factors associated with the control diabetes mellitus in Mexico].

PubMed

Hernández-Romieu, Alfonso Claudio; Elnecavé-Olaiz, Alejandro; Huerta-Uribe, Nidia; Reynoso-Noverón, Nancy

2011-01-01

Determine the influence of nutritional counseling, exercise, access to social healthcare and drugs, and the quality of medical care on the control of diabetics. The information and blood samples were obtained in 2005. Glycemic control was defined as good if HbA1c was ≤7.0%, poor from 7.01%-9.50% and very poor if HbA1c >9.5%. Binary logistic regression models were used to determine the association of these factors with HbA1c>9.5%. Thirty percent of the patients with a medical diagnosis of diabetes had adequate metabolic control. Nutritional guidance was associated with an increase in the degree of control. A majority of diabetics have poor or very poor glycemic control. Strengthening the quality of and access to medical care for these patients is urgently needed.

Catastrophic Health Expenditure Among Colorectal Cancer Patients and Families: A Case of Malaysia.

PubMed

Azzani, Meram; Yahya, Abqariyah; Roslani, April Camilla; Su, Tin Tin

2017-09-01

This study aimed to estimate the cost of colorectal cancer (CRC) management and to explore the prevalence and determinants of catastrophic health expenditure (CHE) among CRC patients and their families arising from the costs of CRC management. Data were collected prospectively from 138 CRC patients. Patients were interviewed by using a structured questionnaire at the time of the diagnosis, then at 6 months and 12 months following diagnosis. Simple descriptive methods and multivariate binary logistic regression were used in the analysis. The mean cost of managing CRC was RM8306.9 (US$2595.9), and 47.8% of patients' families experienced CHE. The main determinants of CHE were the economic status of the family and the likelihood of the patient undergoing surgery. The results of this study strongly suggest that stakeholders and policy makers should provide individuals with financial protection against the consequences of cancer, a costly illness that often requires prolonged treatment.

Global Patterns in the Implementation of Payments for Environmental Services

PubMed Central

Ezzine-de-Blas, Driss; Wunder, Sven; Ruiz-Pérez, Manuel; Moreno-Sanchez, Rocio del Pilar

2016-01-01

Assessing global tendencies and impacts of conditional payments for environmental services (PES) programs is challenging because of their heterogeneity, and scarcity of comparative studies. This meta-study systematizes 55 PES schemes worldwide in a quantitative database. Using categorical principal component analysis to highlight clustering patterns, we reconfirm frequently hypothesized differences between public and private PES schemes, but also identify diverging patterns between commercial and non-commercial private PES vis-à-vis their service focus, area size, and market orientation. When do these PES schemes likely achieve significant environmental additionality? Using binary logistical regression, we find additionality to be positively influenced by three theoretically recommended PES ‘best design’ features: spatial targeting, payment differentiation, and strong conditionality, alongside some contextual controls (activity paid for and implementation time elapsed). Our results thus stress the preeminence of customized design over operational characteristics when assessing what determines the outcomes of PES implementation. PMID:26938065

First trimester vaginal bleeding and adverse pregnancy outcomes among Chinese women: from a large cohort study in China.

PubMed

Sun, Lu; Tao, Fangbiao; Hao, Jiahu; Su, Puyu; Liu, Fang; Xu, Rong

2012-08-01

To examine the effect of first trimester vaginal bleeding on adverse pregnancy outcomes including preterm delivery, low birth weight and small for gestational age. This is a prospective population-based cohort study. A questionnaire survey was conducted on 4342 singleton pregnancies by trained doctors. Binary logistic regression was used to estimate risk ratios (RRs) and 95% confidence intervals (95% CI). Vaginal bleeding occurred among 1050 pregnant women, the incidence of vaginal bleeding was 24.2%, 37.4% of whom didn't see a doctor, 62.6% of whom saw a doctor for vaginal bleeding. Binary logistic regression demonstrated that bleeding with seeing a doctor was significantly associated with preterm birth (RR 1.84, 95% CI 1.25-2.69) and bleeding without seeing a doctor was related to increased of low birth weight (RR 2.52, 95% CI 1.34-4.75) and was 1.97-fold increased of small for gestational age (RR 1.97, 95% CI 1.19-3.25). These results suggest that first trimester vaginal bleeding is an increased risk of low birth weight, preterm delivery and small for gestational age. Find ways to reduce the risk of vaginal bleeding and lower vaginal bleeding rate may be helpful to reduce the incidence of preterm birth, low birth weight and small for gestational age.

Exploring stop-go decision zones at rural high-speed intersections with flashing green signal and insufficient yellow time in China.

PubMed

Tang, Keshuang; Xu, Yanqing; Wang, Fen; Oguchi, Takashi

2016-10-01

The objective of this study is to empirically analyze and model the stop-go decision behavior of drivers at rural high-speed intersections in China, where a flashing green signal of 3s followed by a yellow signal of 3s is commonly applied to end a green phase. 1, 186 high-resolution vehicle trajectories were collected at four typical high-speed intersection approaches in Shanghai and used for the identification of actual stop-go decision zones and the modeling of stop-go decision behavior. Results indicate that the presence of flashing green significantly changed the theoretical decision zones based on the conventional Dilemma Zone theory. The actual stop-go decision zones at the study intersections were thus formulated and identified based on the empirical data. Binary Logistic model and Fuzzy Logic model were then developed to further explore the impacts of flashing green on the stop-go behavior of drivers. It was found that the Fuzzy Logic model could produce comparably good estimation results as compared to the traditional Binary Logistic models. The findings of this study could contribute the development of effective dilemma zone protection strategies, the improvement of stop-go decision model embedded in the microscopic traffic simulation software and the proper design of signal change and clearance intervals at high-speed intersections in China. Copyright © 2016 Elsevier Ltd. All rights reserved.

A binary logistic regression model with complex sampling design of unmet need for family planning among all women aged (15-49) in Ethiopia.

PubMed

Workie, Demeke Lakew; Zike, Dereje Tesfaye; Fenta, Haile Mekonnen; Mekonnen, Mulusew Admasu

2017-09-01

Unintended pregnancy related to unmet need is a worldwide problem that affects societies. The main objective of this study was to identify the prevalence and determinants of unmet need for family planning among women aged (15-49) in Ethiopia. The Performance Monitoring and Accountability2020/Ethiopia was conducted in April 2016 at round-4 from 7494 women with two-stage-stratified sampling. Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. The prevalence of unmet-need for family planning was 16.2% in Ethiopia. Women between the age range of 15-24 years were 2.266 times more likely to have unmet need family planning compared to above 35 years. Women who were currently married were about 8 times more likely to have unmet need family planning compared to never married women. Women who had no under-five child were 0.125 times less likely to have unmet need family planning compared to those who had more than two-under-5. The key determinants of unmet need family planning in Ethiopia were residence, age, marital-status, education, household members, birth-events and number of under-5 children. Thus the Government of Ethiopia would take immediate steps to address the causes of high unmet need for family planning among women.

Spectroscopy of hot subdwarf binaries

NASA Astrophysics Data System (ADS)

Kreuzer, Simon; Irrgang, Andreas; Heber, Ulrich

2018-06-01

We present a status report of our spectroscopic analysis of subdwarf binaries consisting of a subdwarf and a F/G/K-type main-sequence companion. These systems selected from SDSS photometry show significant excess in the (infra-)red which can not be explained by interstellar reddening. Inspection of SDSS spectra revealed that most of them are composite spectrum sdB binaries. Once their spectra are disentangled, a detailed spectral analysis can be carried out. It reveals Teff, log g and the metal abundance of each individual star. The cool companion is of particular interest, because its spectrum reveals the original chemical composition of the binary.

Comparison of two gas chromatograph models and analysis of binary data

NASA Technical Reports Server (NTRS)

Keba, P. S.; Woodrow, P. T.

1972-01-01

The overall objective of the gas chromatograph system studies is to generate fundamental design criteria and techniques to be used in the optimum design of the system. The particular tasks currently being undertaken are the comparison of two mathematical models of the chromatograph and the analysis of binary system data. The predictions of two mathematical models, an equilibrium absorption model and a non-equilibrium absorption model exhibit the same weaknesses in their inability to predict chromatogram spreading for certain systems. The analysis of binary data using the equilibrium absorption model confirms that, for the systems considered, superposition of predicted single component behaviors is a first order representation of actual binary data. Composition effects produce non-idealities which limit the rigorous validity of superposition.

High statistical heterogeneity is more frequent in meta-analysis of continuous than binary outcomes.

PubMed

Alba, Ana C; Alexander, Paul E; Chang, Joanne; MacIsaac, John; DeFry, Samantha; Guyatt, Gordon H

2016-02-01

We compared the distribution of heterogeneity in meta-analyses of binary and continuous outcomes. We searched citations in MEDLINE and Cochrane databases for meta-analyses of randomized trials published in 2012 that reported a measure of heterogeneity of either binary or continuous outcomes. Two reviewers independently performed eligibility screening and data abstraction. We evaluated the distribution of I(2) in meta-analyses of binary and continuous outcomes and explored hypotheses explaining the difference in distributions. After full-text screening, we selected 671 meta-analyses evaluating 557 binary and 352 continuous outcomes. Heterogeneity as assessed by I(2) proved higher in continuous than in binary outcomes: the proportion of continuous and binary outcomes reporting an I(2) of 0% was 34% vs. 52%, respectively, and reporting an I(2) of 60-100% was 39% vs. 14%. In continuous but not binary outcomes, I(2) increased with larger number of studies included in a meta-analysis. Increased precision and sample size do not explain the larger I(2) found in meta-analyses of continuous outcomes with a larger number of studies. Meta-analyses evaluating continuous outcomes showed substantially higher I(2) than meta-analyses of binary outcomes. Results suggest differing standards for interpreting I(2) in continuous vs. binary outcomes may be appropriate. Copyright © 2016 Elsevier Inc. All rights reserved.

All Source Sensor Analysis

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

- PNNL, Harold Trease

2012-10-10

ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.

Applications Of Binary Image Analysis Techniques

NASA Astrophysics Data System (ADS)

Tropf, H.; Enderle, E.; Kammerer, H. P.

1983-10-01

After discussing the conditions where binary image analysis techniques can be used, three new applications of the fast binary image analysis system S.A.M. (Sensorsystem for Automation and Measurement) are reported: (1) The human view direction is measured at TV frame rate while the subject's head is free movable. (2) Industrial parts hanging on a moving conveyor are classified prior to spray painting by robot. (3) In automotive wheel assembly, the eccentricity of the wheel is minimized by turning the tyre relative to the rim in order to balance the eccentricity of the components.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Relationship between serum bilirubin concentrations and diabetic nephropathy in Shanghai Han's patients with type 1 diabetes mellitus.

PubMed

Li, Xu; Zhang, Lei; Chen, Haibing; Guo, Kaifeng; Yu, Haoyong; Zhou, Jian; Li, Ming; Li, Qing; Li, Lianxi; Yin, Jun; Liu, Fang; Bao, Yuqian; Han, Junfeng; Jia, Weiping

2017-03-31

Recent studies highlight a negative association between total bilirubin concentrations and albuminuria in patients with type 2 diabetes mellitus. Our study evaluated the relationship between bilirubin concentrations and the prevalence of diabetic nephropathy (DN) in Chinese patients with type 1 diabetes mellitus (T1DM). A total of 258 patients with T1DM were recruited and bilirubin concentrations were compared between patients with or without diabetic nephropathy. Multiple stepwise regression analysis was used to examine the relationship between bilirubin concentrations and 24 h urinary microalbumin. Binary logistic regression analysis was performed to assess independent risk factors for diabetic nephropathy. Participants were divided into four groups according to the quartile of total bilirubin concentrations (Q1, 0.20-0.60; Q2, 0.60-0.80; Q3, 0.80-1.00; Q4, 1.00-1.90 mg/dL) and the chi-square test was used to compare the prevalence of DN in patients with T1DM. The median bilirubin level was 0.56 (interquartile: 0.43-0.68 mg/dL) in the DN group, significantly lower than in the non-DN group (0.70 [interquartile: 0.58-0.89 mg/dL], P < 0.001). Spearman's correlational analysis showed bilirubin concentrations were inversely correlated with 24 h urinary microalbumin (r = -0.13, P < 0.05) and multiple stepwise regression analysis showed bilirubin concentrations were independently associated with 24 h urinary microalbumin. In logistic regression analysis, bilirubin concentrations were significantly inversely associated with nephropathy. In addition, in stratified analysis, from the first to the fourth quartile group, increased bilirubin concentrations were associated with decreased prevalence of DN from 21.90% to 2.00%. High bilirubin concentrations are independently and negatively associated with albuminuria and the prevalence of DN in patients with T1DM.

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

Preoperative Radiographic and CT Findings Predicting Syndesmotic Injuries in Supination-External Rotation-Type Ankle Fractures.

PubMed

Choi, Young; Kwon, Soon-Sun; Chung, Chin Youb; Park, Moon Seok; Lee, Seung Yeol; Lee, Kyoung Min

2014-07-16

The Lauge-Hansen classification system does not provide sufficient data related to syndesmotic injuries in supination-external rotation (SER)-type ankle fractures. The aim of the present study was to investigate factors helpful for the preoperative detection of syndesmotic injuries in SER-type ankle fractures using radiographs and computed tomography (CT). A cohort of 191 consecutive patients (104 male and eighty-seven female patients with a mean age [and standard deviation] of 50.7 ± 16.4 years) with SER-type ankle fractures who had undergone operative treatment were included. Preoperative ankle radiographs and CT imaging scans were made for all patients, and clinical data, including age, sex, and mechanism of injury (high or low-energy trauma), were collected. Patients were divided into two groups: the stable syndesmotic group and the unstable syndesmotic group, with a positive intraoperative lateral stress test leading to syndesmotic screw fixation. Fracture height, fracture length, medial joint space, extent of fracture, and bone attenuation were measured on radiographs and CT images and were compared between the groups. Binary logistic regression analysis was performed to identify the factors that significantly contributed to unstable syndesmotic injuries. Receiver operating characteristic curves were calculated, and cutoff values were suggested to predict unstable syndesmotic injuries on preoperative imaging measurements. Of the 191 patents with a SER-type ankle fracture, thirty-eight (19.9%) had a concurrent unstable syndesmotic injury. Age, sex, mechanism of injury, fracture height, medial joint space, and bone attenuation were significantly different between the two groups. In the binary logistic analysis, fracture height, medial joint space, and bone attenuation were found to be significant factors contributing to unstable syndesmotic injuries. The cutoff values for predicting unstable syndesmotic injuries were a fracture height of >3 mm and a medial joint space of >4.9 mm on CT scans, and a fracture height of >7 mm and medial joint space of >4.5 mm on radiographs. Fracture height, medial joint space, and bone attenuation were useful factors for the preoperative detection of unstable syndesmotic injuries in SER-type ankle fractures. Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence. Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.

Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors.

PubMed

Ranasinghe, P; Wathurapatha, W S; Perera, Y S; Lamabadusuriya, D A; Kulatunga, S; Jayawardana, N; Katulanda, P

2016-03-09

Computer vision syndrome (CVS) is a group of visual symptoms experienced in relation to the use of computers. Nearly 60 million people suffer from CVS globally, resulting in reduced productivity at work and reduced quality of life of the computer worker. The present study aims to describe the prevalence of CVS and its associated factors among a nationally-representative sample of Sri Lankan computer workers. Two thousand five hundred computer office workers were invited for the study from all nine provinces of Sri Lanka between May and December 2009. A self-administered questionnaire was used to collect socio-demographic data, symptoms of CVS and its associated factors. A binary logistic regression analysis was performed in all patients with 'presence of CVS' as the dichotomous dependent variable and age, gender, duration of occupation, daily computer usage, pre-existing eye disease, not using a visual display terminal (VDT) filter, adjusting brightness of screen, use of contact lenses, angle of gaze and ergonomic practices knowledge as the continuous/dichotomous independent variables. A similar binary logistic regression analysis was performed in all patients with 'severity of CVS' as the dichotomous dependent variable and other continuous/dichotomous independent variables. Sample size was 2210 (response rate-88.4%). Mean age was 30.8 ± 8.1 years and 50.8% of the sample were males. The 1-year prevalence of CVS in the study population was 67.4%. Female gender (OR: 1.28), duration of occupation (OR: 1.07), daily computer usage (1.10), pre-existing eye disease (OR: 4.49), not using a VDT filter (OR: 1.02), use of contact lenses (OR: 3.21) and ergonomics practices knowledge (OR: 1.24) all were associated with significantly presence of CVS. The duration of occupation (OR: 1.04) and presence of pre-existing eye disease (OR: 1.54) were significantly associated with the presence of 'severe CVS'. Sri Lankan computer workers had a high prevalence of CVS. Female gender, longer duration of occupation, higher daily computer usage, pre-existing eye disease, not using a VDT filter, use of contact lenses and higher ergonomics practices knowledge all were associated with significantly with the presence of CVS. The factors associated with the severity of CVS were the duration of occupation and presence of pre-existing eye disease.

Predictive Factors for Differentiating Between Septic Arthritis and Lyme Disease of the Knee in Children.

PubMed

Baldwin, Keith D; Brusalis, Christopher M; Nduaguba, Afamefuna M; Sankar, Wudbhav N

2016-05-04

Differentiating between septic arthritis and Lyme disease of the knee in endemic areas can be challenging and has major implications for patient management. The purpose of this study was to identify a prediction rule to differentiate septic arthritis from Lyme disease in children presenting with knee pain and effusion. We retrospectively reviewed the records of patients younger than 18 years of age with knee effusions who underwent arthrocentesis at our institution from 2005 to 2013. Patients with either septic arthritis (positive joint fluid culture or synovial white blood-cell count of >60,000 white blood cells/mm(3) with negative Lyme titer) or Lyme disease (positive Lyme immunoglobulin G on Western blot analysis) were included. To avoid misclassification bias, undiagnosed knee effusions and joints with both a positive culture and positive Lyme titers were excluded. Historical, clinical, and laboratory data were compared between groups to identify variables for comparison. Binary logistic regression analysis was used to identify independent predictive variables. One hundred and eighty-nine patients were studied: 23 with culture-positive septic arthritis, 26 with culture-negative septic arthritis, and 140 with Lyme disease. Multivariate binary logistic regression identified pain with short arc motion, history of fever reported by the patient or a family member, C-reactive protein of >4 mg/L, and age younger than 2 years as independent predictive factors for septic arthritis. A simpler model was developed that showed that the risk of septic arthritis with none of these factors was 2%, with 1 of these factors was 18%, with 2 of these factors was 45%, with 3 of these factors was 84%, or with all 4 of these factors was 100%. Although septic arthritis of the knee and Lyme monoarthritis share common features that can make them difficult to distinguish clinically, the presence of pain with short arc motion, C-reactive protein of >4.0 mg/L, patient-reported history of fever, and age younger than 2 years were independent predictive factors of septic arthritis in pediatric patients. The more factors that are present, the higher the risk of having septic arthritis. Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

Does migration 'pay off' for foreign-born migrant health workers? An exploratory analysis using the global WageIndicator dataset.

PubMed

de Vries, Daniel H; Steinmetz, Stephanie; Tijdens, Kea G

2016-06-24

This study used the global WageIndicator web survey to answer the following research questions: (RQ1) What are the migration patterns of health workers? (RQ2) What are the personal and occupational drivers of migration? (RQ3) Are foreign-born migrant health workers discriminated against in their destination countries? Of the unweighted data collected in 2006-2014 from health workers aged 15-64 in paid employment, 7.9 % were on migrants (N = 44,394; 36 countries). To answer RQ1, binary logistic regression models were applied to the full sample. To answer RQ2, binary logistic regression was used to compare data on migrants with that on native respondents from the same source countries, a condition met by only four African countries (N = 890) and five Latin American countries (N = 6356). To answer RQ3, a multilevel analysis was applied to the full sample to take into account the nested structure of the data (N = 33,765 individual observations nested within 31 countries). RQ1: 57 % migrated to a country where the same language is spoken, 33 % migrated to neighbouring countries and 21 % migrated to former colonizing countries. Women and nurses migrated to neighbouring countries, nurses and older and highly educated workers to former colonizing countries and highly educated health workers and medical doctors to countries that have a language match. RQ2: In the African countries, nurses more often out-migrated compared to other health workers; in the Latin American countries, this is the case for doctors. Out-migrated health workers earn more and work fewer hours than comparable workers in source countries, but only Latin American health workers reported a higher level of life satisfaction. RQ3: We did not detect discrimination against migrants with respect to wages and occupational status. However, there seems to be a small wage premium for the group of migrants in other healthcare occupations. Except doctors, migrant health workers reported a lower level of life satisfaction. Migration generally seems to 'pay off' in terms of work and labour conditions, although accrued benefits are not equal for all cadres, regions and routes. Because the WageIndicator survey is a voluntary survey, these findings are exploratory rather than representative.

Multireader multicase reader studies with binary agreement data: simulation, analysis, validation, and sizing.

PubMed

Chen, Weijie; Wunderlich, Adam; Petrick, Nicholas; Gallas, Brandon D

2014-10-01

We treat multireader multicase (MRMC) reader studies for which a reader's diagnostic assessment is converted to binary agreement (1: agree with the truth state, 0: disagree with the truth state). We present a mathematical model for simulating binary MRMC data with a desired correlation structure across readers, cases, and two modalities, assuming the expected probability of agreement is equal for the two modalities ([Formula: see text]). This model can be used to validate the coverage probabilities of 95% confidence intervals (of [Formula: see text], [Formula: see text], or [Formula: see text] when [Formula: see text]), validate the type I error of a superiority hypothesis test, and size a noninferiority hypothesis test (which assumes [Formula: see text]). To illustrate the utility of our simulation model, we adapt the Obuchowski-Rockette-Hillis (ORH) method for the analysis of MRMC binary agreement data. Moreover, we use our simulation model to validate the ORH method for binary data and to illustrate sizing in a noninferiority setting. Our software package is publicly available on the Google code project hosting site for use in simulation, analysis, validation, and sizing of MRMC reader studies with binary agreement data.

Multireader multicase reader studies with binary agreement data: simulation, analysis, validation, and sizing

PubMed Central

Chen, Weijie; Wunderlich, Adam; Petrick, Nicholas; Gallas, Brandon D.

2014-01-01

Abstract. We treat multireader multicase (MRMC) reader studies for which a reader’s diagnostic assessment is converted to binary agreement (1: agree with the truth state, 0: disagree with the truth state). We present a mathematical model for simulating binary MRMC data with a desired correlation structure across readers, cases, and two modalities, assuming the expected probability of agreement is equal for the two modalities (P1=P2). This model can be used to validate the coverage probabilities of 95% confidence intervals (of P1, P2, or P1−P2 when P1−P2=0), validate the type I error of a superiority hypothesis test, and size a noninferiority hypothesis test (which assumes P1=P2). To illustrate the utility of our simulation model, we adapt the Obuchowski–Rockette–Hillis (ORH) method for the analysis of MRMC binary agreement data. Moreover, we use our simulation model to validate the ORH method for binary data and to illustrate sizing in a noninferiority setting. Our software package is publicly available on the Google code project hosting site for use in simulation, analysis, validation, and sizing of MRMC reader studies with binary agreement data. PMID:26158051

Binary Trees and Parallel Scheduling Algorithms.

DTIC Science & Technology

1980-09-01

been pro- cessed for p. time units. If a job does not complete by its due time, it is tardy. In a nonpreemptive schedule, job i is scheduled to process...the preemptive schedule obtained by the algorithm of section 2.1.2 also minimizes 5Ti, this problem is easily solved in parallel. When lci is to e...August 1978, pp. 657-661. 14. Horn, W. A., "Some simple scheduling algorithms," Naval Res. Logist . Qur., Vol. 21, pp. 177-185, 1974. i5. Hforowitz, E

Sexual Dysfunction in Women Undergoing Fertility Treatment in Iran: Prevalence and Associated Risk Factors

PubMed Central

Bakhtiari, Afsaneh; Basirat, Zahra; Nasiri-Amiri, Fatemeh

2016-01-01

Background: Sexual dysfunctions are one of the most fundamental difficulties for infertile women, which can be as the cause of infertility. This study investigated the prevalence of this disorder and associated factors in order to improve infertility treatment process and the quality of life of women referring to infertility center. Methods: A cross sectional study was performed on 236 women who referred to Fatima Zahra infertility center of Babol, Iran. Data collection tool was a questionnaire contained two parts; demographic characteristics and infertility information. Also, data for sexual dysfunction was obtained through diagnostic interview based on the international classification DSM-IV. For data analysis, logistic and linear regression analysis were used. The p<0.05 was considered significant. Results: Most of women (84.9%) suffered from primary infertility and the mean duration of infertility was 60.2±8.4 months. The prevalence of sexual dysfunction was 55.5% (n=131); including dyspareunia in 28% (n=66), impaired sexual desire and lack of orgasm in 26.3% (n=62 patients), vaginismus in 15.2% (n=36) and lack of sexual stimulation in 13.6% (n=32). Binary logistic regression analysis showed that age, sexual satisfaction and history of mental illness had a significant effect on the probability of experiencing the sexual dysfunction. Conclusion: There is a high prevalence of sexual dysfunction among infertile women. Considering the interaction between sexual dysfunction and infertility, professional health care centers should be sensitive to this effect. Also, more attention must be paid on marital relationships, economic and social situation and infertility characteristics in order to prevent sexual dysfunction development through early screening and psychological interference. PMID:26962480

KEPLER ECLIPSING BINARIES WITH STELLAR COMPANIONS

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

Gies, D. R.; Matson, R. A.; Guo, Z.

2015-12-15

Many short-period binary stars have distant orbiting companions that have played a role in driving the binary components into close separation. Indirect detection of a tertiary star is possible by measuring apparent changes in eclipse times of eclipsing binaries as the binary orbits the common center of mass. Here we present an analysis of the eclipse timings of 41 eclipsing binaries observed throughout the NASA Kepler mission of long duration and precise photometry. This subset of binaries is characterized by relatively deep and frequent eclipses of both stellar components. We present preliminary orbital elements for seven probable triple stars amongmore » this sample, and we discuss apparent period changes in seven additional eclipsing binaries that may be related to motion about a tertiary in a long period orbit. The results will be used in ongoing investigations of the spectra and light curves of these binaries for further evidence of the presence of third stars.« less

Factors affecting medication adherence in community-managed patients with hypertension based on the principal component analysis: evidence from Xinjiang, China.

PubMed

Zhang, Yuji; Li, Xiaoju; Mao, Lu; Zhang, Mei; Li, Ke; Zheng, Yinxia; Cui, Wangfei; Yin, Hongpo; He, Yanli; Jing, Mingxia

2018-01-01

The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis. A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ 2 -test and a binary logistic regression model. This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications. Community management plays an important role in improving the patients' medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers.

Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients.

PubMed

Guo, Qi; Lu, Xiaoni; Gao, Ya; Zhang, Jingjing; Yan, Bin; Su, Dan; Song, Anqi; Zhao, Xi; Wang, Gang

2017-03-07

Grading of essential hypertension according to blood pressure (BP) level may not adequately reflect clinical heterogeneity of hypertensive patients. This study was carried out to explore clinical phenotypes in essential hypertensive patients using cluster analysis. This study recruited 513 hypertensive patients and evaluated BP variations with ambulatory blood pressure monitoring. Four distinct hypertension groups were identified using cluster analysis: (1) younger male smokers with relatively high BP had the most severe carotid plaque thickness but no coronary artery disease (CAD); (2) older women with relatively low diastolic BP had more diabetes; (3) non-smokers with a low systolic BP level had neither diabetes nor CAD; (4) hypertensive patients with BP reverse dipping were most likely to have CAD but had least severe carotid plaque thickness. In binary logistic analysis, reverse dipping was significantly associated with prevalence of CAD. Cluster analysis was shown to be a feasible approach for investigating the heterogeneity of essential hypertension in clinical studies. BP reverse dipping might be valuable for prediction of CAD in hypertensive patients when compared with carotid plaque thickness. However, large-scale prospective trials with more information of plaque morphology are necessary to further compare the predicative power between BP dipping pattern and carotid plaque.

Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients

PubMed Central

Guo, Qi; Lu, Xiaoni; Gao, Ya; Zhang, Jingjing; Yan, Bin; Su, Dan; Song, Anqi; Zhao, Xi; Wang, Gang

2017-01-01

Grading of essential hypertension according to blood pressure (BP) level may not adequately reflect clinical heterogeneity of hypertensive patients. This study was carried out to explore clinical phenotypes in essential hypertensive patients using cluster analysis. This study recruited 513 hypertensive patients and evaluated BP variations with ambulatory blood pressure monitoring. Four distinct hypertension groups were identified using cluster analysis: (1) younger male smokers with relatively high BP had the most severe carotid plaque thickness but no coronary artery disease (CAD); (2) older women with relatively low diastolic BP had more diabetes; (3) non-smokers with a low systolic BP level had neither diabetes nor CAD; (4) hypertensive patients with BP reverse dipping were most likely to have CAD but had least severe carotid plaque thickness. In binary logistic analysis, reverse dipping was significantly associated with prevalence of CAD. Cluster analysis was shown to be a feasible approach for investigating the heterogeneity of essential hypertension in clinical studies. BP reverse dipping might be valuable for prediction of CAD in hypertensive patients when compared with carotid plaque thickness. However, large-scale prospective trials with more information of plaque morphology are necessary to further compare the predicative power between BP dipping pattern and carotid plaque. PMID:28266630

Effects of spatial location and household wealth on health insurance subscription among women in Ghana.

PubMed

Kumi-Kyereme, Akwasi; Amo-Adjei, Joshua

2013-06-17

This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana

PubMed Central

2013-01-01

Background This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. Methods The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. Results By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. Conclusions The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable. PMID:23768255

Factors influencing women's utilization of public health care services during childbirth in Malawi Public health facility utilization.

PubMed

Machira, Kennedy; Palamuleni, Martin

2017-06-01

Maternal mortality remains a public health challenge claiming many lives at the time of giving birth lives. However, there have been scanty studies investigating factors influencing women's use of public health facilities during childbirth. The aim of the study was to explore the factors associated with women choice of public health facility during childbirth. The study used 2010 Malawi Demographic Health Survey dataset and a binary logistics regression analysis to estimate the determinants influencing women's use of public health facilities at the time they give birth. Of 23020 women respondents, 8454(36.7%) chose to give birth in public health facilities. Multivariate analysis reported that frequency of antenatal care (ANC), birth order, women's education, wealth status and quality of care were the major predictors increasing women's choice to use public health facilities at childbirth. There is need to use multimedia approach to engage women on significance of utilizing public health facilities during childbirth and promote quality of care in facilities if their health outcome is to improve in Malawi.

Lymphatic vessel invasion and lymph node metastasis in patients with clinical stage I non-small cell lung cancer.

PubMed

Kang, Du-Young; Lee, Sungsoo

2014-09-01

The aim of this study was to investigate the association between the presence of lymphatic vessel invasion (LVI) in primary tumors and lymph node (LN) metastasis in clinical stage I non-small cell lung cancer (NSCLC) patients. A total of 76 patients who underwent complete resection for clinical stage I adenocarcinoma and squamous cell carcinoma were retrospectively examined. Tumors consisted of 51 cases of adenocarcinoma and 25 cases of squamous cell carcinoma as determined by histology. LN metastasis was detected in 24.4% (19/76) of patients. Factors associated with LN metastasis on univariate analysis included LVI (p < 0.001) and increased tumor dimensions (p < 0.05). Binary logistic regression analysis showed that the presence of LVI (p < 0.001) was the only predictor of LN metastasis. LVI is significantly associated with LN metastasis in patients with clinical stage I NSCLC. These findings may be helpful in determining the most appropriate operative strategy for patients if preoperative detection of LVI becomes feasible. Georg Thieme Verlag KG Stuttgart · New York.

Somatic symptoms and holistic thinking as major dimensions behind modern health worries.

PubMed

Köteles, Ferenc; Simor, Péter

2014-01-01

Modern health worries (MHWs) were related to somatic symptoms and to preference of holistic healing methods in previous studies. The study aimed to investigate the contribution of symptom-related and holism-related factors to MHWs. Participants (visitors of an Internet news portal; N = 16152; 64.1 % males) completed a questionnaire assessing MHWs, somatosensory amplification, somatic symptoms, positive and negative affect, spirituality, holistic health beliefs, and various aspects of health care utilization (both conventional and alternative). Exploratory factor analysis with oblique rotation revealed two independent dimensions ("Somatic symptom distress" and "Holism") MHWs were involved with factor loadings of 0.294 and 0.417, respectively. The existence of two factors was supported by the results of confirmatory factor analysis. No practically significant interaction between the two factors was found in binary logistic regression analysis. Positive and negative affect, somatosensory amplification, spirituality, and holistic health beliefs were positively connected, while self-rated health status was negatively connected to MHWs even after controlling for socio-demographic and treatment-related variables. Holistic thinking and symptom-related behavioral and psychological factors are independently associated with MHWs. Modern health worries can be conceptualized as symptom-related by-products of a holistic-spiritual worldview.

Determinant factors of tobacco use among ever-married men in Bangladesh

PubMed Central

Rahman, Md Shafiur; Mondal, Md Nazrul Islam; Islam, Md Rafiqul; Rahman, Md Mizanur; Hoque, M Nazrul; Alam, Md Shamsher

2015-01-01

Background The burden of tobacco use is shifting from developed to developing countries. This study aimed to explore the different types of tobacco use, and to identify the determinant factors associated with the tobacco use among ever-married men in Bangladesh. Data and methods Data of 3,771 ever-married men, 15–54 years of age were extracted from the Bangladesh Demographic and Health Survey 2007. Prevalence rate, chi-square (χ2) test, and binary logistic regression analysis were used as the statistical tools to analyze the data. Results Tobacco use through smoking (58.68%) was found to be higher than that of chewing (21.63%) among men, which was significantly more prevalent among the poorest, less educated, and businessmen. In bivariate analysis, all the socioeconomic factors were found significantly associated with tobacco use; while in multivariate analysis, age, education, wealth index, and occupation were identified as the significant predictors. Conclusion Tobacco use was found to be remarkably common among males in Bangladesh. The high prevalence of tobacco use suggests that there is an urgent need for developing intervention plans to address this major public health problem in Bangladesh. PMID:25999762

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

Bersabé, Rosa; Rivas, Teresa

2010-05-01

The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

An Experimental Realization of a Chaos-Based Secure Communication Using Arduino Microcontrollers

PubMed Central

Zapateiro De la Hoz, Mauricio; Vidal, Yolanda

2015-01-01

Security and secrecy are some of the important concerns in the communications world. In the last years, several encryption techniques have been proposed in order to improve the secrecy of the information transmitted. Chaos-based encryption techniques are being widely studied as part of the problem because of the highly unpredictable and random-look nature of the chaotic signals. In this paper we propose a digital-based communication system that uses the logistic map which is a mathematically simple model that is chaotic under certain conditions. The input message signal is modulated using a simple Delta modulator and encrypted using a logistic map. The key signal is also encrypted using the same logistic map with different initial conditions. In the receiver side, the binary-coded message is decrypted using the encrypted key signal that is sent through one of the communication channels. The proposed scheme is experimentally tested using Arduino shields which are simple yet powerful development kits that allows for the implementation of the communication system for testing purposes. PMID:26413563

[Relationship between family functioning and lifestyle in school-age adolescents].

PubMed

Lima-Serrano, Marta; Guerra-Martín, María Dolores; Lima-Rodríguez, Joaquín Salvador

Risk behaviors in adolescents can lead to serious disorders, therefore the objectives of this work are to characterize the lifestyles of teenagers about substance use, sex, and road safety, and to meet socio-demographic factors associated with these. A cross-sectional, descriptive and correlational study was conducted with 204 school-age-children from 12 to 17 years, in 2013. They were given a validated questionnaire about sociodemographic, family functioning, and lifestyles such as substance abuse, sexual intercourse and road safety. A descriptive and multivariate analysis was performed by using multiple linear regression in the case of quantitative dependent variables, and binary logistic regression models in the case of binary categories. Data analysis was based on SPSS 20.0, with a significance level of p<0.05. 32.4% of students had smoked, and 61.3% had drunk alcohol. 26% of adolescent between 14-17 years had sexual intercourse; the average age of the first sexual intercourse was 14.9 years. 85.2% used condoms. 94.6% respected traffic signs, 77.5% used to wear a seat belt and 81.9% a helmet. Family functioning, as protective factor, was the variable more frequently associated to risk behaviour: smoking (OR=7.06, p=.000), alcohol drinking (OR=3.97, p=.008), sexual intercourse (OR=3.67, p=.041), and road safety (β=1.82, p=.000). According the results, age, gender and family functioning are the main factors associated with the adoption of risk behaviors. This information is important for the development of public health policies, for instance health promotion at schools. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Photometric study of the eclipsing binary GR Bootis

NASA Astrophysics Data System (ADS)

Zhang, Z. L.; Zhang, Y. P.; Fu, J. N.; Xue, H. F.

2016-07-01

We present CCD photometry and low-resolution spectra of the eclipsing binary GR Boo. A new ephemeris is determined based on all the available times of the minimum light. The period analysis reveals that the orbital period is decreasing with a rate of dP / dt = - 2.05 ×10-10 d yr-1 . A photometric analysis for the obtained light curves is performed with the Wilson-Devinney Differential Correction program for the first time. The photometric solutions confirm the W UMa-type nature of the binary system. The mass ratio turns out to be q = 0.985 ± 0.001 . The evolutionary status and physical nature of the binary system are briefly discussed.

The impact of IUE on binary star studies

NASA Technical Reports Server (NTRS)

Plavec, M. J.

1981-01-01

The use of IUE observations in the investigation of binary stars is discussed. The results of data analysis of several classes of binary systems are briefly reviewed including zeta Aurigae and VV Cephei stars, mu Sagittarii, epsilon Aurigae, beta Lyrae and the W Serpentis stars, symbiotic stars, and the Algols.

Multilevel Models for Binary Data

ERIC Educational Resources Information Center

Powers, Daniel A.

2012-01-01

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

Anxiety and Depression among Breast Cancer Patients in an Urban Setting in Malaysia.

PubMed

Hassan, Mohd Rohaizat; Shah, Shamsul Azhar; Ghazi, Hasanain Faisal; Mohd Mujar, Noor Mastura; Samsuri, Mohd Fadhli; Baharom, Nizam

2015-01-01

Breast cancer is one of the most feared diseases among women and it could induce the development of psychological disorders like anxiety and depression. An assessment was here performed of the status and to determine contributory factors. A cross-sectional study was conducted among breast cancer patients at University Kebangsaan Malaysia Medical Center (UKMMC), Kuala Lumpur. A total of 205 patients who were diagnosed between 2007 until 2010 were interviewed using the questionnaires of Hospital Anxiety and Depression (HADS). The associated factors investigated concerned socio-demographics, socio economic background and the cancer status. Descriptive analysis, chi-squared tests and logistic regression were used for the statistical test analysis. The prevalence of anxiety was 31.7% (n=65 ) and of depression was 22.0% (n=45) among the breast cancer patients. Age group (p= 0.032), monthly income (p=0.015) and number of visits per month (p=0.007) were significantly associated with anxiety. For depression, marital status (p=0.012), accompanying person (p=0.041), financial support (p-0.007) and felt burden (p=0.038) were significantly associated. In binary logistic regression, those in the younger age group were low monthly income were 2 times more likely to be associated with anxiety. Having less financial support and being single were 3 and 4 times more likely to be associated with depression. In management of breast cancer patients, more care or support should be given to the young and low socio economic status as they are at high risk of anxiety and depression.

An All-Sky Search for Wide Binaries in the SUPERBLINK Proper Motion Catalog

NASA Astrophysics Data System (ADS)

Hartman, Zachary; Lepine, Sebastien

2017-01-01

We present initial results from an all-sky search for Common Proper Motion (CPM) binaries in the SUPERBLINK all-sky proper motion catalog of 2.8 million stars with proper motions greater than 40 mas/yr, which has been recently enhanced with data from the GAIA mission. We initially search the SUPERBLINK catalog for pairs of stars with angular separations up to 1 degree and proper motion difference less than 40 mas/yr. In order to determine which of these pairs are real binaries, we develop a Bayesian analysis to calculate probabilities of true companionship based on a combination of proper motion magnitude, angular separation, and proper motion differences. The analysis reveals that the SUPERBLINK catalog most likely contains ~40,000 genuine common proper motion binaries. We provide initial estimates of the distances and projected physical separations of these wide binaries.

Racial residential segregation and preterm birth: built environment as a mediator.

PubMed

Anthopolos, Rebecca; Kaufman, Jay S; Messer, Lynne C; Miranda, Marie Lynn

2014-05-01

Racial residential segregation has been associated with preterm birth. Few studies have examined mediating pathways, in part because, with binary outcomes, indirect effects estimated from multiplicative models generally lack causal interpretation. We develop a method to estimate additive-scale natural direct and indirect effects from logistic regression. We then evaluate whether segregation operates through poor-quality built environment to affect preterm birth. To estimate natural direct and indirect effects, we derive risk differences from logistic regression coefficients. Birth records (2000-2008) for Durham, North Carolina, were linked to neighborhood-level measures of racial isolation and a composite construct of poor-quality built environment. We decomposed the total effect of racial isolation on preterm birth into direct and indirect effects. The adjusted total effect of an interquartile increase in racial isolation on preterm birth was an extra 27 preterm events per 1000 births (risk difference = 0.027 [95% confidence interval = 0.007 to 0.047]). With poor-quality built environment held at the level it would take under isolation at the 25th percentile, the direct effect of an interquartile increase in isolation was 0.022 (-0.001 to 0.042). Poor-quality built environment accounted for 35% (11% to 65%) of the total effect. Our methodology facilitates the estimation of additive-scale natural effects with binary outcomes. In this study, the total effect of racial segregation on preterm birth was partially mediated by poor-quality built environment.

Depression and associated variables in people over 50 years in Spain.

PubMed

Portellano-Ortiz, Cristina; Garre-Olmo, Josep; Calvó-Perxas, Laia; Conde-Sala, Josep Lluís

2016-12-06

Depression is a common and disabling psychiatric disorder in adulthood and is associated with higher mortality and functional disability. To determine the association between clinical and sociodemographic variables with depression in a sample of people over 50 years old living in Spain, and compare the prevalence of depression with the other Survey of Health, Ageing and Retirement (SHARE) countries. There were 5,830 participants in the Spanish sample of the Wave 5, 2013, of SHARE. Tools used: EURO-D (Depression) and CASP-12 (Quality of Life). Bivariate, and binary logistic. The variables associated with depression in the binary logistic regression (EURO-D ≥4) were poor self-perceived physical health (OR=13.34; 95% CI: 9.74-18.27), having more than 2 difficulties in Activities of Daily Living (ADL) (OR=4.46; 95% CI: 3.13-6.34) and female gender (OR=2.16; 95% CI: 1.83-2.56). Depression was more common among participants with Alzheimer (76.4%), emotional disorders (73.9%), Parkinson (57.4%), hip fracture (55.4%), and rheumatism (50.9%). Compared with other European countries, Spain had a percentage of people with depression (29.3%) that was higher than the European average (27.9%). The most important variables associated with depression were poor perceived physical health, presence of difficulties in ADL, and female gender. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Application of wavelet analysis to estimation of parameters of the gravitational-wave signal from a coalescing binary

NASA Astrophysics Data System (ADS)

Królak, Andrzej; Trzaskoma, Pawel

1996-05-01

Application of wavelet analysis to the estimation of parameters of the broad-band gravitational-wave signal emitted by a binary system is investigated. A method of instantaneous frequency extraction first proposed in this context by Innocent and Vinet is used. The gravitational-wave signal from a binary is investigated from the point of view of signal analysis theory and it is shown that such a signal is characterized by a large time - bandwidth product. This property enables the extraction of frequency modulation from the wavelet transform of the signal. The wavelet transform of the chirp signal from a binary is calculated analytically. Numerical simulations with the noisy chirp signal are performed. The gravitational-wave signal from a binary is taken in the quadrupole approximation and it is buried in noise corresponding to three different values of the signal-to-noise ratio and the wavelet method to extract the frequency modulation of the signal is applied. Then, from the frequency modulation, the chirp mass parameter of the binary is estimated. It is found that the chirp mass can be estimated to a good accuracy, typically of the order of (20/0264-9381/13/5/006/img5% where 0264-9381/13/5/006/img6 is the optimal signal-to-noise ratio. It is also shown that the post-Newtonian effects in the gravitational wave signal from a binary can be discriminated to a satisfactory accuracy.

United States Air Force Computer-Aided Acquisition and Logistics Support (CALS). Logistics Support Analysis Current Environment. Volume 2

DOT National Transportation Integrated Search

1988-10-01

An analysis of the current environment within the Acquisition stage of the Weapon System Life Cycle Pertaining to the Logistics Support Analysis (LSA) process, the Logistics Support Analysis Record (LSAR), and other Logistics Support data was underta...

United States Air Force Computer-Aided Acquisition and Logistics Support (CALS). Logistics Support Analysis Current Environment. Volume 1

DOT National Transportation Integrated Search

1988-10-01

An analysis of the current environment within the Acquisition stage of the Weapon System Life Cycle Pertaining to the Logistics Support Analysis (LSA) process, the Logistics Support Analysis Record (LSAR), and other Logistics Support data was underta...

Binary tree eigen solver in finite element analysis

NASA Technical Reports Server (NTRS)

Akl, F. A.; Janetzke, D. C.; Kiraly, L. J.

1993-01-01

This paper presents a transputer-based binary tree eigensolver for the solution of the generalized eigenproblem in linear elastic finite element analysis. The algorithm is based on the method of recursive doubling, which parallel implementation of a number of associative operations on an arbitrary set having N elements is of the order of o(log2N), compared to (N-1) steps if implemented sequentially. The hardware used in the implementation of the binary tree consists of 32 transputers. The algorithm is written in OCCAM which is a high-level language developed with the transputers to address parallel programming constructs and to provide the communications between processors. The algorithm can be replicated to match the size of the binary tree transputer network. Parallel and sequential finite element analysis programs have been developed to solve for the set of the least-order eigenpairs using the modified subspace method. The speed-up obtained for a typical analysis problem indicates close agreement with the theoretical prediction given by the method of recursive doubling.

Successful treatment algorithm for evaluation of early pregnancy after in vitro fertilization.

PubMed

Cookingham, Lisa Marii; Goossen, Rachel P; Sparks, Amy E T; Van Voorhis, Bradley J; Duran, Eyup Hakan

2015-10-01

To evaluate a prospectively implemented clinical algorithm for early identification of ectopic pregnancy (EP) and heterotopic pregnancy (HP) after assisted reproductive technology (ART). Analysis of prospectively collected data. Academic medical center. All ART-conceived pregnancies between January 1995 and June 2013. Early pregnancy monitoring via clinical algorithm with all pregnancies screened using human chorionic gonadotropin (hCG) levels and reported symptoms, with subsequent early ultrasound evaluation if hCG levels were abnormal or if the patient reported pain or vaginal bleeding. Algorithmic efficiency for diagnosis of EP and HP and their subsequent clinical outcomes using a binary forward stepwise logistic regression model built to determine predictors of early pregnancy failure. Of the 3,904 pregnancies included, the incidence of EP and HP was 0.77% and 0.46%, respectively. The algorithm selected 96.7% and 83.3% of pregnancies diagnosed with EP and HP, respectively, for early ultrasound evaluation, leading to earlier treatment and resolution. Logistic regression revealed that first hCG, second hCG, hCG slope, age, pain, and vaginal bleeding were all independent predictors of early pregnancy failure after ART. Our clinical algorithm for early pregnancy evaluation after ART is effective for identification and prompt intervention of EP and HP without significant over- or misdiagnosis, and avoids the potential catastrophic morbidity associated with delayed diagnosis. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Farmers' Market Manager's Level of Communication and Influence on Electronic Benefits Transfer (EBT) Adoption at Midwest Farmers' Markets.

PubMed

Hasin, Afroza; Smith, Sylvia

2018-01-01

To understand market managers' level of communication and use of technology that might influence decision to adopt Electronic Benefits Transfer (EBT) at farmers' markets. Cross-sectional study using the Theory of Diffusion of Innovation. Electronic survey administered in midwest states of Illinois, Michigan, and Wisconsin. Farmers' market managers in Illinois, Michigan, and Wisconsin. Information on EBT adoption, market managers' communication, and technology use. Binary logistic regression analysis with EBT adoption as the dependent variable and frequency of technology use, partnership with organizations, farmers' market association (FMA) membership, Facebook page and Web site for the market, and primary source of information as independent variables. Chi-square tests and ANOVA were used to compare states and adopter categories. Logistic regression results showed that the odds of adopting EBT was 7.5 times higher for markets that had partnership with other organizations. Compared with non-adopters, a significantly greater number of early adopters had partnership, FMA membership, and a Facebook page and Web site for market, and reported to a board of directors. Markets that had partnership, FMA membership, a Facebook page and Web site, and mandatory reporting to a board of directors were important factors that influenced EBT adoption at midwest farmers' markets. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Dentists' perspectives on caries-related treatment decisions.

PubMed

Gomez, J; Ellwood, R P; Martignon, S; Pretty, I A

2014-06-01

To assess the impact of patient risk status on Colombian dentists' caries related treatment decisions for early to intermediate caries lesions (ICDAS code 2 to 4). A web-based questionnaire assessed dentists' views on the management of early/intermediate lesions. The questionnaire included questions on demographic characteristics, five clinical scenarios with randomised levels of caries risk, and two questions on different clinical and radiographic sets of images with different thresholds of caries. Questionnaires were completed by 439 dentists. For the two scenarios describing occlusal lesions ICDAS code 2, dentists chose to provide a preventive option in 63% and 60% of the cases. For the approximal lesion ICDAS code 2, 81% of the dentists chose to restore. The main findings of the binary logistic regression analysis for the clinical scenarios suggest that for the ICDAS code 2 occlusal lesions, the odds of a high caries risk patient having restorations is higher than for a low caries risk patient. For the questions describing different clinical thresholds of caries, most dentists would restore at ICDAS code 2 (55%) and for the question showing different radiographic thresholds images, 65% of dentists would intervene operatively at the inner half of enamel. No significant differences with respect to risk were found for these questions with the logistic regression. The results of this study indicate that Colombian dentists have not yet fully adopted non-invasive treatment for early caries lesions.

Human papillomavirus vaccination in Auckland: reducing ethnic and socioeconomic inequities.

PubMed

Poole, Tracey; Goodyear-Smith, Felicity; Petousis-Harris, Helen; Desmond, Natalie; Exeter, Daniel; Pointon, Leah; Jayasinha, Ranmalie

2012-12-17

The New Zealand HPV publicly funded immunisation programme commenced in September 2008. Delivery through a school based programme was anticipated to result in higher coverage rates and reduced inequalities compared to vaccination delivered through other settings. The programme provided for on-going vaccination of girls in year 8 with an initial catch-up programme through general practices for young women born after 1 January 1990 until the end of 2010. To assess the uptake of the funded HPV vaccine through school based vaccination programmes in secondary schools and general practices in 2009, and the factors associated with coverage by database matching. Retrospective quantitative analysis of secondary anonymised data School-Based Vaccination Service and National Immunisation Register databases of female students from secondary schools in Auckland District Health Board catchment area. Data included student and school demographic and other variables. Binary logistic regression was used to estimate odds ratios and significance for univariables. Multivariable logistic regression estimated strength of association between individual factors and initiation and completion, adjusted for all other factors. The programme achieved overall coverage of 71.5%, with Pacific girls highest at 88% and Maori at 78%. Girls higher socioeconomic status were more likely be vaccinated in general practice. School-based vaccination service targeted at ethic sub-populations provided equity for the Maori and Pacific student who achieved high levels of vaccination. Copyright © 2012 Elsevier Ltd. All rights reserved.

The relationship between problem gambling and mental and physical health correlates among a nationally representative sample of Canadian women.

PubMed

Afifi, Tracie O; Cox, Brian J; Martens, Patricia J; Sareen, Jitender; Enns, Murray W

2010-01-01

Gambling has become an increasingly common activity among women since the widespread growth of the gambling industry. Currently, our knowledge of the relationship between problem gambling among women and mental and physical correlates is limited. Therefore, important relationships between problem gambling and health and functioning, mental disorders, physical health conditions, and help-seeking behaviours among women were examined using a nationally representative Canadian sample. Data were from the nationally representative Canadian Community Health Survey Cycle 1.2 (CCHS 1.2; n = 10,056 women aged 15 years and older; data collected in 2002). The statistical analysis included binary logistic regression, multinomial logistic regression, and linear regression models. Past 12-month problem gambling was associated with a significantly higher probability of current lower general health, suicidal ideation and attempts, decreased psychological well-being, increased distress, depression, mania, panic attacks, social phobia, agoraphobia, alcohol dependence, any mental disorder, comorbidity of mental disorders, chronic bronchitis, fibromyalgia, migraine headaches, help-seeking from a professional, attending a self-help group, and calling a telephone help line (odds ratios ranged from 1.5 to 8.2). Problem gambling was associated with a broad range of negative health correlates among women. Problem gambling is an important public health concern. These findings can be used to inform healthy public policies on gambling.

Family Medicine or Primary Care Residency Selection: Effects of Family Medicine Interest Groups, MD/MPH Dual Degrees, and Rural Medical Education.

PubMed

Wei McIntosh, Elizabeth; Morley, Christopher P

2016-05-01

If medical schools are to produce primary care physicians (family medicine, pediatrics, or general internal medicine), they must provide educational experiences that enable medical students to maintain existing or form new interests in such careers. This study examined three mechanisms for doing so, at one medical school: participation as an officer in a family medicine interest group (FMIG), completion of a dual medical/public health (MD/MPH) degree program, and participation in a rural medical education (RMED) clinical track. Specialty Match data for students who graduated from the study institution between 2006 and 2015 were included as dependent variables in bivariate analysis (c2) and logistic regression models, examining FMIG, MD/MPH, and RMED participation as independent predictors of specialty choice (family medicine yes/no, or any primary care (PC) yes/no), controlling for student demographic data. In bivariate c2 analyses, FMIG officership did not significantly predict matching with family medicine or any PC; RMED and MD/MPH education were significant predictors of both family medicine and PC. Binary logistic regression analyses replicated the bivariate findings, controlling for student demographics. Dual MD/MPH and rural medical education had stronger effects in producing primary care physicians than participation in a FMIG as an officer, at one institution. Further study at multiple institutions is warranted.

Dental Care in an Equal Access System Valuing Equity: Are There Racial Disparities?

PubMed

Boehmer, Ulrike; Glickman, Mark; Jones, Judith A; Orner, Michelle B; Wheler, Carolyn; Berlowitz, Dan R; Kressin, Nancy R

2016-11-01

Racial disparities in dental care have previously been shown in the Veterans Health Administration (VA)-a controlled access setting valuing equitable, high-quality care. The aim of this study is to examine current disparities in dental care by focusing on the receipt of root canal therapy (RCT) versus tooth extraction. This is a retrospective analysis of data contained in the VA's electronic health records. We performed logistic regressions on the independent measures along with a facility-specific random effect, using dependent binary variables that distinguished RCT from tooth extraction procedures. VA outpatients who had at least 1 tooth extraction or RCT visit in the VA in fiscal year 2011. A dependent binary measure of tooth extraction or RCT. Other measures are medical record data on medical comorbidities, dental morbidity, prior dental utilization, and demographic characteristics. The overall rate of preferred tooth-preserving RCT was 18.1% during the study period. Black and Asian patients were most dissimilar with respect to dental morbidity, medical and psychological disorders, and black patients had the least amount of eligibility for comprehensive dental care. After adjustment for known confounding factors of RCT, black patients had the lowest RCT rates, whereas Asians had the highest. Current quality improvement efforts and a value to improve the equity of care are not sufficient to address racial/ethnic disparities in VA dental care; rather more targeted efforts will be needed to achieve equity for all.

The influence of endometriosis-related symptoms on work life and work ability: a study of Danish endometriosis patients in employment.

PubMed

Hansen, Karina E; Kesmodel, Ulrik S; Baldursson, Einar B; Schultz, Rikke; Forman, Axel

2013-07-01

Little is known about the implications of endometriosis on women's work life. This study aimed at examining the relation between endometriosis-related symptoms and work ability in employed women with endometriosis. In a cohort study, 610 patients with diagnosed endometriosis and 751 reference women completed an electronic survey based on the Endometriosis Health Profile 30-questionnaire and the Work Ability Index (short form). Percentages were reported for all data. Binary and multivariate logistic regression analyses were used to assess risk factors for low work ability. The level of statistical significance was set at p<0.025 in all analyses. In binary analyses a diagnosis of endometriosis was associated with more sick days, work disturbances due to symptoms, lower work ability and a wide number of other implications on work life in employed women. Moreover, a higher pain level and degree of symptoms were associated with low work ability. Full regression analysis indicated that tiredness, frequent pain, a higher daily pain level, a higher number of sick days and feeling depressed at work were associated with low work ability. A long delay from symptom onset to diagnosis was associated with low work ability. These data indicate a severe impact of endometriosis on the work ability of employed women with endometriosis and add to the evidence that this disease represents a significant socio-economic burden. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Phasor Analysis of Binary Diffraction Gratings with Different Fill Factors

ERIC Educational Resources Information Center

Martinez, Antonio; Sanchez-Lopez, Ma del Mar; Moreno, Ignacio

2007-01-01

In this work, we present a simple analysis of binary diffraction gratings with different slit widths relative to the grating period. The analysis is based on a simple phasor technique directly derived from the Huygens principle. By introducing a slit phasor and a grating phasor, the intensity of the diffracted orders and the grating's resolving…

Sleep Quality and Motor Vehicle Crashes in Adolescents

PubMed Central

Pizza, Fabio; Contardi, Sara; Antognini, Alessandro Baldi; Zagoraiou, Maroussa; Borrotti, Matteo; Mostacci, Barbara; Mondini, Susanna; Cirignotta, Fabio

2010-01-01

Study Objectives: Sleep-related complaints are common in adolescents, but their impact on the rate of motor vehicle crashes accidents is poorly known. We studied subjective sleep quality, driving habits, and self-reported car crashes in high-school adolescents. Methods: Self-administered questionnaires (with items exploring driving habits) were distributed to 339 students who had a driver's license and attended 1 of 7 high schools in Bologna, Italy. Statistical analysis were performed to describe lifestyle habits, sleep quality, sleepiness, and their relationship with the binary dependent variable (presence or absence of car crashes) to identify the factors significantly affecting the probability of car crashes in a multivariate binary logistic regression model. Results: Nineteen percent of the sample reported bad sleep, 64% complained of daytime sleepiness, and 40% reported sleepiness while driving. Eighty students (24%), 76% of which were males, reported that they had already crashed at least once, and 15% considered sleepiness to have been the main cause of their crash. As compared with adolescents who had not had a crash, those who had at least 1 previous crash reported that they more frequently used to drive (79% vs 62%), drove at night (25% vs 9%), drove while sleepy (56% vs 35%), had bad sleep (29% vs 16%), and used stimulants such as caffeinated soft drinks (32% vs 19%), tobacco (54% vs 27%), and drugs (21% vs 7%). The logistic procedure established a significant predictive role of male sex (p < 0.0001; odds ratio = 3.3), tobacco use (p < 0.0001; odds ratio = 3.2), sleepiness while driving (p = 0.010; odds ratio = 2.1), and bad sleep (p = 0.047; odds ratio = 1.9) for the crash risk. Conclusions: Our results confirm the high prevalence of sleep-related complaints among adolescents and highlight their independent role on self-reported crash risk. Citation: Pizza F; Contardi S; Baldi Antognini A; Zagoraiou M; Borrotti M; Mostacci B; Mondini S; Cirignotta F. Sleep quality and motor vehicle crashes in adolescents. J Clin Sleep Med 2010;6(1):41-45. PMID:20191936

Single nucleotide polymorphisms in the CD40 gene associate with the disease susceptibility and severity in knee osteoarthritis in the Chinese Han population: a case-control study.

PubMed

Deng, Zhen-Han; Sun, Ming-Hua; Li, Yu-Sheng; Luo, Wei; Zhang, Fang-Jie; Tian, Jian; Wu, Ping; Xiao, Wen-Feng

2017-03-21

This study explored the association between single nucleotide polymorphisms (SNPs) in the CD40 gene, rs4810485 G > T and rs1883832 C > T, as well as disease susceptibility and severity in knee osteoarthritis (KOA) in the Chinese Han population. Peripheral venous blood was collected from 133 KOA patients (KOA group) and 143 healthy people (control group) from December 2012 to November 2013. The patients in the KOA group were classified into mild, moderate and severe groups according to disease severity. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to test the genotypes of all subjects. Binary logistic regression analyses were performed to analyze the risk factors for KOA. The KOA group was significantly different from the control group in living environment (P < 0.05). The KOA group had a lower frequency of TT genotype and T allele distribution of rs4810485 G > T compared with the control group, and rs4810485 G > T TT genotype and T allele may associate with low incidence of KOA (all P < 0.05). Besides, T allele and mutant homozygous TT genotype of rs1883832 C > T increased the susceptibility to KOA. Genotype and allele distribution of rs4810485 G > T and rs1883832 C > T were significantly different among the mild, moderate and severe groups (P < 0.05). There were more patients with rs4810485 G > T GG genotype and rs1883832 C > T TT genotype in the severe group than other genotypes of these two SNPs. According to binary logistic regression analysis, rs4810485 G > T TT genotype could alleviate disease severity in KOA, rs1883832 C > T TT genotype increase the severity of KOA and living environment is an important external factor that affects KOA severity. These data provide evidences that rs4810485 G > T and rs1883832 C > T in the CD40 gene may be associated with disease susceptibility and severity in KOA.

Association of Ghrelin Gene Polymorphisms and Serum Ghrelin Levels with the Risk of Hepatitis B Virus-Related Liver Diseases in a Chinese Population.

PubMed

Zhang, Xiaolian; Zhai, Limin; Rong, Chengzhi; Qin, Xue; Li, Shan

2015-01-01

The functions of ghrelin (GHRL) include anti-inflammatory effects, reduction of the fibrogenic response, protection of liver tissue, and regulation of cell proliferation. Genetic variations in the GHRL gene may play an important role in the development of chronic hepatitis B (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Therefore, we investigated whether GHRL gene polymorphisms and its serum levels are associated with hepatitis B virus (HBV)-related diseases risk in a Chinese population. 176 patients with CHB, 106 patients with HBV-related LC, 151 patients with HBV-related HCC, and 167 healthy controls were recruited in the study. Genotyping of GHRL rs26311, rs27647, rs696217, and rs34911341 polymorphisms were determined with the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and DNA sequencing. The serum GHRL concentrations were determined using enzyme-linked immunosorbent assay (ELISA). Binary logistic regression analyses adjusting for gender and age revealed that a significant increased risk of LC was found in the GHRL rs26311 GC genotype and combined GC+CC genotypes when compared with the GG genotype (GC vs. GG: OR = 1.671, 95% CI = 1.013-2.757, P = 0.044; GC+CC vs. GG: OR = 1.674, 95% CI = 1.040-2.696, P = 0.034). In subgroup analysis by gender, binary logistic regression analyses adjusting for age showed that the GHRL rs26311 C allele and combined GC+CC genotypes were associated with a significantly increased risk to LC in males (C vs. G OR = 1.416, 95% CI = 1.017-1.972, P = 0.040; GC+CC vs. GG: OR = 1.729, 95% CI = 1.019-2.933, P = 0.042). In addition, we found significant decreased serum GHRL levels in LC patients compared with the healthy controls. However, there was no significant association of the GHRL rs26311 polymorphism with serum GHRL levels in LC patients. These observations suggest that the GHRL rs26311 polymorphism is associated with an increased risk to HBV-related LC, especially in men. We also found an inverse association of serum GHRL levels with LC.

Analysis of 45-years of Eclipse Timings of the Hyades (K2 V+ DA) Eclipsing Binary V471 Tauri

NASA Astrophysics Data System (ADS)

Marchioni, Lucas; Guinan, Edward; Engle, Scott

2018-01-01

V471 Tau is an important detached 0.521-day eclipsing binary composed of a K2 V and a hot DA white dwarf star. This system resides in the Hyades star cluster located approximately 153 Ly from us. V471 Tau is considered to be the end-product of common-envelope binary star evolution and is currently a pre-CV system. V471 Tau serves as a valuable astrophysical laboratory for studying stellar evolution, white dwarfs, stellar magnetic dynamos, and possible detection of low mass companions using the Light Travel Time (LTT) Effects. Since its discovery as an eclipsing binary in 1970, photometry has been carried out and many eclipse timings have been determined. We have performed an analysis of the available photometric data available on V471 Tauri. The binary system has been the subject of analyses regarding the orbital period. From this analysis several have postulated the existence of a third body in the form of a brown dwarf that is causing periodic variations in the system’s apparent period. In this study we combine ground based data with photometry secured recently from the Kepler K2 mission. After detrending and phasing the available data, we are able to compare the changing period of the eclipsing binary system against predictions on the existence of this third body. The results of the analysis will be presented. This research is sponsored by grants from NASA and NSF for which we are very grateful.

Application of Pulsed-Field Gel Electrophoresis and Binary Typing as Tools in Veterinary Clinical Microbiology and Molecular Epidemiologic Analysis of Bovine and Human Staphylococcus aureus Isolates

PubMed Central

Zadoks, Ruth; van Leeuwen, Willem; Barkema, Herman; Sampimon, Otlis; Verbrugh, Henri; Schukken, Ynte Hein; van Belkum, Alex

2000-01-01

Thirty-eight bovine mammary Staphylococcus aureus isolates from diverse clinical, temporal, and geographical origins were genotyped by pulsed-field gel electrophoresis (PFGE) after SmaI digestion of prokaryotic DNA and by means of binary typing using 15 strain-specific DNA probes. Seven pulsed-field types and four subtypes were identified, as were 16 binary types. Concordant delineation of genetic relatedness was documented by both techniques, yet based on practical and epidemiological considerations, binary typing was the preferable method. Genotypes of bovine isolates were compared to 55 previously characterized human S. aureus isolates through cluster analysis of binary types. Genetic clusters containing strains of both human and bovine origin were found, but bacterial genotypes were predominantly associated with a single host species. Binary typing proved an excellent tool for comparison of S. aureus strains, including methicillin-resistant S. aureus, derived from different host species and from different databases. For 28 bovine S. aureus isolates, detailed clinical observations in vivo were compared to strain typing results in vitro. Associations were found between distinct genotypes and severity of disease, suggesting strain-specific bacterial virulence. Circumstantial evidence furthermore supports strain-specific routes of bacterial dissemination. We conclude that PFGE and binary typing can be successfully applied for genetic analysis of S. aureus isolates from bovine mammary secretions. Binary typing in particular is a robust and simple method and promises to become a powerful tool for strain characterization, for resolution of clonal relationships of bacteria within and between host species, and for identification of sources and transmission routes of bovine S. aureus. PMID:10790124

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

NASA Astrophysics Data System (ADS)

Hinder, Ian; Buonanno, Alessandra; Boyle, Michael; Etienne, Zachariah B.; Healy, James; Johnson-McDaniel, Nathan K.; Nagar, Alessandro; Nakano, Hiroyuki; Pan, Yi; Pfeiffer, Harald P.; Pürrer, Michael; Reisswig, Christian; Scheel, Mark A.; Schnetter, Erik; Sperhake, Ulrich; Szilágyi, Bela; Tichy, Wolfgang; Wardell, Barry; Zenginoğlu, Anıl; Alic, Daniela; Bernuzzi, Sebastiano; Bode, Tanja; Brügmann, Bernd; Buchman, Luisa T.; Campanelli, Manuela; Chu, Tony; Damour, Thibault; Grigsby, Jason D.; Hannam, Mark; Haas, Roland; Hemberger, Daniel A.; Husa, Sascha; Kidder, Lawrence E.; Laguna, Pablo; London, Lionel; Lovelace, Geoffrey; Lousto, Carlos O.; Marronetti, Pedro; Matzner, Richard A.; Mösta, Philipp; Mroué, Abdul; Müller, Doreen; Mundim, Bruno C.; Nerozzi, Andrea; Paschalidis, Vasileios; Pollney, Denis; Reifenberger, George; Rezzolla, Luciano; Shapiro, Stuart L.; Shoemaker, Deirdre; Taracchini, Andrea; Taylor, Nicholas W.; Teukolsky, Saul A.; Thierfelder, Marcus; Witek, Helvi; Zlochower, Yosef

2013-01-01

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ˜100-200M⊙, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios ⩽4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.

Characteristics of foodborne outbreaks in which use of analytical epidemiological studies contributed to identification of suspected vehicles, European Union, 2007 to 2011.

PubMed

Schlinkmann, K M; Razum, O; Werber, D

2017-04-01

Foodborne disease outbreaks (FBDOs) occur frequently in Europe. Employing analytical epidemiological study designs increases the likelihood of identifying the suspected vehicle(s), but these studies are rarely applied in FBDO investigations. We used multivariable binary logistic regression analysis to identify characteristics of investigated FBDOs reported to the European Food Safety Authority (2007-2011) that were associated with analytical epidemiological evidence (compared to evidence from microbiological investigations/descriptive epidemiology only). The analysis was restricted to FBDO investigations, where the evidence for the suspected vehicle was considered 'strong', i.e. convincing. The presence of analytical epidemiological evidence was reported in 2012 (50%) of these 4038 outbreaks. In multivariable analysis, increasing outbreak size, number of hospitalizations, causative (i.e. aetiological) agent (whether identified and, if so, which one), and the setting in which these outbreaks occurred (e.g. geographically dispersed outbreaks) were independently associated with presence of analytical evidence. The number of investigations with reported analytical epidemiological evidence was unexpectedly high, likely indicating the need for quality assurance within the European Union foodborne outbreak reporting system, and warranting cautious interpretation of our findings. This first analysis of evidence implicating a food vehicle in FBDOs may help to inform public health authorities on when to use analytical epidemiological study designs.

Micro-Logistics Analysis for Human Space Exploration

NASA Technical Reports Server (NTRS)

Cirillo, William; Stromgren, Chel; Galan, Ricardo

2008-01-01

Traditionally, logistics analysis for space missions has focused on the delivery of elements and goods to a destination. This type of logistics analysis can be referred to as "macro-logistics". While the delivery of goods is a critical component of mission analysis, it captures only a portion of the constraints that logistics planning may impose on a mission scenario. The other component of logistics analysis concerns the local handling of goods at the destination, including storage, usage, and disposal. This type of logistics analysis, referred to as "micro-logistics", may also be a primary driver in the viability of a human lunar exploration scenario. With the rigorous constraints that will be placed upon a human lunar outpost, it is necessary to accurately evaluate micro-logistics operations in order to develop exploration scenarios that will result in an acceptable level of system performance.

Accounting for informatively missing data in logistic regression by means of reassessment sampling.

PubMed

Lin, Ji; Lyles, Robert H

2015-05-20

We explore the 'reassessment' design in a logistic regression setting, where a second wave of sampling is applied to recover a portion of the missing data on a binary exposure and/or outcome variable. We construct a joint likelihood function based on the original model of interest and a model for the missing data mechanism, with emphasis on non-ignorable missingness. The estimation is carried out by numerical maximization of the joint likelihood function with close approximation of the accompanying Hessian matrix, using sharable programs that take advantage of general optimization routines in standard software. We show how likelihood ratio tests can be used for model selection and how they facilitate direct hypothesis testing for whether missingness is at random. Examples and simulations are presented to demonstrate the performance of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.

Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix models

NASA Astrophysics Data System (ADS)

Almog, Assaf; Garlaschelli, Diego

2014-09-01

The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons, respectively. While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relations between binary and non-binary properties of financial time series. These relations are a novel quantification of the fact that extreme price increments occur more often when most stocks move in the same direction. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices and their mapping to spin models in statistical physics, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to accurately replicate, and mathematically characterize, the observed binary/non-binary relations. We also obtain a phase diagram allowing us to identify, based only on the instantaneous aggregate return of a set of multiple time series, a regime where the so-called ‘market mode’ has an optimal interpretation in terms of collective (endogenous) effects, a regime where it is parsimoniously explained by pure noise, and a regime where it can be regarded as a combination of endogenous and exogenous factors. Our approach allows us to connect spin models, simple stochastic processes, and ensembles of time series inferred from partial information.

Error analysis of numerical gravitational waveforms from coalescing binary black holes

NASA Astrophysics Data System (ADS)

Fong, Heather; Chu, Tony; Kumar, Prayush; Pfeiffer, Harald; Boyle, Michael; Hemberger, Daniel; Kidder, Lawrence; Scheel, Mark; Szilagyi, Bela; SXS Collaboration

2016-03-01

The Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO) has finished a successful first observation run and will commence its second run this summer. Detection of compact object binaries utilizes matched-filtering, which requires a vast collection of highly accurate gravitational waveforms. This talk will present a set of about 100 new aligned-spin binary black hole simulations. I will discuss their properties, including a detailed error analysis, which demonstrates that the numerical waveforms are sufficiently accurate for gravitational wave detection purposes, as well as for parameter estimation purposes.

Spectral properties of binary asteroids

NASA Astrophysics Data System (ADS)

Pajuelo, Myriam; Birlan, Mirel; Carry, Benoît; DeMeo, Francesca E.; Binzel, Richard P.; Berthier, Jérôme

2018-04-01

We present the first attempt to characterize the distribution of taxonomic class among the population of binary asteroids (15% of all small asteroids). For that, an analysis of 0.8-2.5{μ m} near-infrared spectra obtained with the SpeX instrument on the NASA/IRTF is presented. Taxonomic class and meteorite analog is determined for each target, increasing the sample of binary asteroids with known taxonomy by 21%. Most binary systems are bound in the S-, X-, and C- classes, followed by Q and V-types. The rate of binary systems in each taxonomic class agrees within uncertainty with the background population of small near-Earth objects and inner main belt asteroids, but for the C-types which are under-represented among binaries.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

ERIC Educational Resources Information Center

Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…

Elevated Fasting Blood Glucose Is Predictive of Poor Outcome in Non-Diabetic Stroke Patients: A Sub-Group Analysis of SMART.

PubMed

Yao, Ming; Ni, Jun; Zhou, Lixin; Peng, Bin; Zhu, Yicheng; Cui, Liying

2016-01-01

Although increasing evidence suggests that hyperglycemia following acute stroke adversely affects clinical outcome, whether the association between glycaemia and functional outcome varies between stroke patients with\\without pre-diagnosed diabetes remains controversial. We aimed to investigate the relationship between the fasting blood glucose (FBG) and the 6-month functional outcome in a subgroup of SMART cohort and further to assess whether this association varied based on the status of pre-diagnosed diabetes. Data of 2862 patients with acute ischemic stroke (629 with pre-diagnosed diabetics) enrolled from SMART cohort were analyzed. Functional outcome at 6-month post-stroke was measured by modified Rankin Scale (mRS) and categorized as favorable (mRS:0-2) or poor (mRS:3-5). Binary logistic regression model, adjusting for age, gender, educational level, history of hypertension and stroke, baseline NIHSS and treatment group, was used in the whole cohort to evaluate the association between admission FBG and functional outcome. Stratified logistic regression analyses were further performed based on the presence/absence of pre-diabetes history. In the whole cohort, multivariable logistical regression showed that poor functional outcome was associated with elevated FBG (OR1.21 (95%CI 1.07-1.37), p = 0.002), older age (OR1.64 (95% CI1.38-1.94), p<0.001), higher NIHSS (OR2.90 (95%CI 2.52-3.33), p<0.001) and hypertension (OR1.42 (95%CI 1.13-1.98), p = 0.04). Stratified logistical regression analysis showed that the association between FBG and functional outcome remained significant only in patients without pre-diagnosed diabetes (OR1.26 (95%CI 1.03-1.55), p = 0.023), but not in those with premorbid diagnosis of diabetes (p = 0.885). The present results demonstrate a significant association between elevated FBG after stroke and poor functional outcome in patients without pre-diagnosed diabetes, but not in diabetics. This finding confirms the importance of glycemic control during acute phase of ischemic stroke especially in patients without pre-diagnosed diabetes. Further investigation for developing optimal strategies to control blood glucose level in hyperglycemic setting is therefore of great importance. ClinicalTrials.gov NCT00664846.

The association between insured male expatriates' knowledge of health insurance benefits and lack of access to health care in Saudi Arabia.

PubMed

Alkhamis, Abdulwahab A

2018-03-15

Insufficient knowledge of health insurance benefits could be associated with lack of access to health care, particularly for minority populations. This study aims to assess the association between expatriates' knowledge of health insurance benefits and lack of access to health care. A cross-sectional study design was conducted from March 2015 to February 2016 among 3398 insured male expatriates in Riyadh, Saudi Arabia. The dependent variable was binary and expresses access or lack of access to health care. Independent variables included perceived and validated knowledge of health insurance benefits and other variables. Data were summarized by computing frequencies and percentage of all quantities of variables. To evaluate variations in knowledge, personal and job characteristics with lack of access to health care, the Chi square test was used. Odds ratio (OR) and 95% confidence interval (CI) were recorded for each independent variable. Multiple logistic regression and stepwise logistic regression were performed and adjusted ORs were extracted. Descriptive analysis showed that 15% of participants lacked access to health care. The majority of these were unskilled laborers, usually with no education (17.5%), who had been working for less than 3 years (28.1%) in Saudi Arabia. A total of 23.3% worked for companies with less than 50 employees and 16.5% earned less than 4500 Saudi Riyals monthly ($1200). Many (20.3%) were young (< 30 years old) or older (17.9% ≥ 56 years old) and had no formal education (24.7%). Nearly half had fair or poor health status (49.5%), were uncomfortable conversing in Arabic (29.7%) or English (16.7%) and lacked previous knowledge of health insurance (18%). For perceived knowledge of health insurance, 55.2% scored 1 or 0 from total of 3. For validated knowledge, 16.9% scored 1 or 0 from total score of 4. Multiple logistic regression analysis showed that only perceived knowledge of health insurance had significant associations with lack of access to health care ((OR) = 0.393, (CI) = 0.335-0.461), but the result was insignificant for validated knowledge. Stepwise logistic regression gave similar findings. Our results confirmed that low perceived knowledge of health insurance in expatriates was associated with less access to health care.

Finding an appropriate equation to measure similarity between binary vectors: case studies on Indonesian and Japanese herbal medicines.

PubMed

Wijaya, Sony Hartono; Afendi, Farit Mochamad; Batubara, Irmanida; Darusman, Latifah K; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2016-12-07

The binary similarity and dissimilarity measures have critical roles in the processing of data consisting of binary vectors in various fields including bioinformatics and chemometrics. These metrics express the similarity and dissimilarity values between two binary vectors in terms of the positive matches, absence mismatches or negative matches. To our knowledge, there is no published work presenting a systematic way of finding an appropriate equation to measure binary similarity that performs well for certain data type or application. A proper method to select a suitable binary similarity or dissimilarity measure is needed to obtain better classification results. In this study, we proposed a novel approach to select binary similarity and dissimilarity measures. We collected 79 binary similarity and dissimilarity equations by extensive literature search and implemented those equations as an R package called bmeasures. We applied these metrics to quantify the similarity and dissimilarity between herbal medicine formulas belonging to the Indonesian Jamu and Japanese Kampo separately. We assessed the capability of binary equations to classify herbal medicine pairs into match and mismatch efficacies based on their similarity or dissimilarity coefficients using the Receiver Operating Characteristic (ROC) curve analysis. According to the area under the ROC curve results, we found Indonesian Jamu and Japanese Kampo datasets obtained different ranking of binary similarity and dissimilarity measures. Out of all the equations, the Forbes-2 similarity and the Variant of Correlation similarity measures are recommended for studying the relationship between Jamu formulas and Kampo formulas, respectively. The selection of binary similarity and dissimilarity measures for multivariate analysis is data dependent. The proposed method can be used to find the most suitable binary similarity and dissimilarity equation wisely for a particular data. Our finding suggests that all four types of matching quantities in the Operational Taxonomic Unit (OTU) table are important to calculate the similarity and dissimilarity coefficients between herbal medicine formulas. Also, the binary similarity and dissimilarity measures that include the negative match quantity d achieve better capability to separate herbal medicine pairs compared to equations that exclude d.

Life satisfaction, coping, self-esteem and suicide ideation in Chinese adolescents: a school-based study.

PubMed

Yao, Y-S; Chang, W-W; Jin, Y-L; Chen, Y; He, L-P; Zhang, L

2014-09-01

To determine the prevalence and associated risk factors of suicidal ideation (SI) among junior, senior high and college school students. A total of 5249 students in Anhui Province of China participated in a self-administered anonymous survey. Females were more likely to report SI than males (32.1% vs. 20.6%). Using binary logistic regression analysis, we found that being female, passive coping, lower family satisfaction, lower school satisfaction, lower living environment satisfaction and higher self-esteem were associated with an increased risk of SI. This study suggested that SI was common among Chinese adolescents. Being female, high score of passive coping, lower family satisfaction, lower school satisfaction, lower living environment satisfaction and higher self-esteem were significantly associated with an increased risk of SI. There is an urgent need to take effective measures reducing the rate of SI among adolescents through collaboration among families, schools and society. © 2014 John Wiley & Sons Ltd.

Nutritional status of under-five children in Bangladesh: a multilevel analysis.

PubMed

Alom, Jahangir; Quddus, Md Abdul; Islam, Mohammad Amirul

2012-09-01

The nutritional status of under-five children is a sensitive sign of a country's health status as well as economic condition. This study investigated the differential impact of some demographic, socioeconomic, environmental and health-related factors on the nutritional status among under-five children in Bangladesh using Bangladesh Demographic and Health Survey 2007 data. Two-level random intercept binary logistic regression models were used to identify the determinants of under-five malnutrition. The analyses revealed that 16% of the children were severely stunted and 25% were moderately stunted. Among the children under five years of age 3% were severely wasted and 14% were moderately wasted. Furthermore, 11% of the children were severely underweight and 28% were moderately underweight. The main contributing factors for under-five malnutrition were found to be child's age, mother's education, father's education, father's occupation, family wealth index, currently breast-feeding, place of delivery and division. Significant community-level variations were found in the analyses.

Examining the Effects of Transphobic Discrimination and Race on HIV Risk Among Transwomen in San Francisco.

PubMed

Arayasirikul, Sean; Wilson, Erin C; Raymond, Henry F

2017-09-01

Transwomen, in particular transwomen of color (TWOC), are among the most vulnerable populations at risk for HIV. This secondary analysis is organized using a gender minority stress framework to examine the effects of transphobic discrimination and race on HIV risk factors. We describe the sample of 149 HIV- adult transwomen in San Francisco and use binary logistic regression to examine the relationship between levels of transphobic discrimination and TWOC status on binge drinking and condomless receptive anal intercourse (CRAI), controlling for potential confounders. Those with high levels of transphobic discrimination had 3.59 fold greater odds of engaging in binge drinking compared to those who reported a low level of transphobic discrimination (95% CI 1.284-10.034; P = 0.015). TWOC had nearly threefold greater odds of CRAI compared to white transwomen (95% CI 1.048-8.464; P = 0.040). We discuss implications for gender minority stress research and future interventions for this population.

Public university entry in Ghana: Is it equitable?

NASA Astrophysics Data System (ADS)

Yusif, Hadrat; Yussof, Ishak; Osman, Zulkifly

2013-06-01

Public universities in Ghana are highly subsidised by the central government and account for about 80 per cent of university students in the country. Yet issues of fairness in terms of entry into the public university system have so far hardly been addressed. To find out whether participation in public university education is equitable, the authors of this paper carried out a binary logistic regression analysis. Individual data were collected from 1,129 (614 male and 515 female) final year senior high school (SHS) students for the 2009 cohort. The authors measured student, father and mother characteristics likely to influence admission to a public university. The results show that the major predictors of public university entry are students' academic ability, quality of SHS attended and number of siblings. This seems to suggest that there is a significant bias in the selection of students from different socio-economic groups for admission to highly subsidised public universities. The implication is that public financing of university education in Ghana may not be equitable.

The influence of intrinsic and extrinsic job values on turnover intention among continuing care assistants in Nova Scotia.

PubMed

Dill, Donna M; Keefe, Janice M; McGrath, Daniel S

2012-01-01

This article examines the influence that intrinsic and extrinsic job values have on the turnover intention of continuing care assistants (CCAs) who work either in home care or facility-based care in Nova Scotia (n = 188). Factor analysis of job values identified three latent job values structures: "compensation and commitment," "flexibility and opportunity," and "positive work relationships." Using binary logistic regression, we examined the predictive utility of these factors on two indices of turnover intention. Regression results indicate that, in general, job values constructs did not significantly predict turnover intention when controlling for demographics and job characteristics. However, a trend was found for the "positive work relationships" factor in predicting consideration of changing employers. In addition, CCAs who work in facility-based care were significantly more likely to have considered leaving their current employer. With projected increases in the demand for these workers in both home and continuing care, more attention is needed to identify and address factors to reduce turnover intention.

Polynomial Size Formulations for the Distance and Capacity Constrained Vehicle Routing Problem

NASA Astrophysics Data System (ADS)

Kara, Imdat; Derya, Tusan

2011-09-01

The Distance and Capacity Constrained Vehicle Routing Problem (DCVRP) is an extension of the well known Traveling Salesman Problem (TSP). DCVRP arises in distribution and logistics problems. It would be beneficial to construct new formulations, which is the main motivation and contribution of this paper. We focused on two indexed integer programming formulations for DCVRP. One node based and one arc (flow) based formulation for DCVRP are presented. Both formulations have O(n2) binary variables and O(n2) constraints, i.e., the number of the decision variables and constraints grows with a polynomial function of the nodes of the underlying graph. It is shown that proposed arc based formulation produces better lower bound than the existing one (this refers to the Water's formulation in the paper). Finally, various problems from literature are solved with the node based and arc based formulations by using CPLEX 8.0. Preliminary computational analysis shows that, arc based formulation outperforms the node based formulation in terms of linear programming relaxation.

Population Pharmacokinetics, Pharmacodynamics, and Exploratory Exposure–Response Analyses of Apixaban in Subjects Treated for Venous Thromboembolism

PubMed Central

Sweeney, K; Frost, C; Boyd, RA

2017-01-01

Apixaban is approved for treatment of venous thromboembolism (VTE) and prevention of recurrence. Population pharmacokinetics, pharmacokinetics–pharmacodynamics (anti‐FXa activity), and exposure–response (binary bleeding and thromboembolic endpoints) of apixaban in VTE treatment subjects were characterized using data from phase I–III studies. Apixaban pharmacokinetics were adequately characterized by a two‐compartment model with first‐order absorption and elimination. Age, sex, and Asian race had less than 25% impact on exposure, while subjects with severe renal impairment were predicted to have 56% higher exposure than the reference subject (60‐year‐old non‐Asian male weighing 85 kg with creatinine clearance of 100 mL/min). The relationship between apixaban concentration and anti‐FXa activity was described by a linear model with a slope estimate of 0.0159 IU/ng. The number of subjects with either a bleeding or thromboembolic event was small, and no statistically significant relationship between apixaban exposure and clinical endpoints could be discerned with a logistic regression analysis. PMID:28547774

Access to a Car and the Self-Reported Health and Mental Health of People Aged 65 and Older in Northern Ireland.

PubMed

Doebler, Stefanie

2016-05-01

This article examines relationships between access to a car and the self-reported health and mental health of older people. The analysis is based on a sample of N = 65,601 individuals aged 65 years and older from the Northern Ireland Longitudinal Study linked to 2001 and 2011 census returns. The findings from hierarchical linear and binary logistic multilevel path models indicate that having no access to a car is related to a considerable health and mental health disadvantage particularly for older people who live alone. Rural-urban health and mental health differences are mediated by access to a car. The findings support approaches that emphasize the importance of autonomy and independence for the well-being of older people and indicate that not having access to a car can be a problem for older people not only in rural but also in intermediate and urban areas, if no sufficient alternative forms of mobility are provided. © The Author(s) 2015.

Correlates of Worry About Health Care Costs Among Older Adults.

PubMed

Choi, Namkee G; DiNitto, Diana M

2018-06-01

Although older adults in the United States incur more health care expenses than younger adults, little research has been done on their worry about health care costs. Using data from the 2013 National Health Interview Survey ( n = 7,253 for those 65+ years), we examined factors associated with older adults' health care cost worries, defined as at least a moderate level of worry, about ability to pay for normal health care and/or for health care due to a serious illness or accident. Bivariate analyses were used to compare worriers and nonworriers. Binary logistic regression analysis was used to examine the association of income, health status, health care service use, and insurance type with worry status. Older age and having Medicaid and Veterans Affairs (VA)/military health benefits were associated with lower odds of worry, while low income, chronic pain, functional limitations, psychological distress, and emergency department visits were associated with higher odds. Practice and policy implications for the findings are discussed.

The level of consumer information about health insurance in Nanjing, China.

PubMed

Xu, Weiwei; Van de Ven, Wynand P M M

2014-01-01

The Chinese government is considering a (regulated) competitive healthcare system. Sufficient consumer information is a crucial pre-condition to benefit from such a change. We conducted a survey on the level of consumer information regarding health insurance among the insured population in Nanjing, China in 2009. The results from descriptive analysis and binary logistic regression demonstrate that the current level of consumer information about health insurance is low. The level of consumer information is positively correlated with the subscribers' motivation to obtain the information and its availability. The level of searching for health insurance information is also low; moreover, even upon searching, the chance of finding relevant information is less than 25%. We conclude that the level of consumer information is currently insufficient in China. If the Chinese government is determined to adopt market mechanisms in the healthcare sector, it should take the lead in making valid and reliable information publicly available and easily accessible. Copyright © 2012 John Wiley & Sons, Ltd.

Epidemiological, clinical and laboratory profile of scrub typhus cases detected by serology and RT-PCR in Kumaon, Uttarakhand: a hospital-based study.

PubMed

Rawat, Vinita; Singh, Rajesh Kumar; Kumar, Ashok; Saxena, Sandip R; Varshney, Umesh; Kumar, Mukesh

2018-04-01

We analysed the epidemiology, clinical and laboratory data of the 168 scrub typhus cases confirmed by a combination of any one of the following: real time polymerase chain reaction (RT-PCR) and/or immunofluorescence assay (IFA) (IgM and/or IgG). The peak season for scrub typhus was from July to October. By multivariate binary logistic regression analysis, the risk of scrub typhus was about four times in those working in occupation related to forest work. Major clinical manifestations were fever (100%), myalgia (65%), cough (51%) and vomiting (46%); major complications were meningitis/meningoencephatilitis (12.5%) and multi-organ failure (MOF) and pneumonia (5.3% each). Laboratory investigations revealed raised aminotranferase levels and thrombocytopenia in most confirmed cases. We conclude that scrub typhus is an important cause of febrile illness in the Kumaon hills of Uttarakhand where this disease had not previously been considered to exist.

Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use Among Students.

PubMed

Merianos, Ashley L; Rosen, Brittany L; Montgomery, LaTrice; Barry, Adam E; Smith, Matthew Lee

2017-12-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data ( N = 937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime alcohol use-compared to students who had never used alcohol or marijuana-perceived lower alcohol risk ( p < .001), higher friend drinking approval ( p < .001), and greater friend drinking ( p = .003). Using both alcohol and marijuana in one's life was associated with being in public schools ( p = .010), higher grade levels ( p = .001), lower perceived alcohol ( p = .011) and marijuana use risk ( p = .003), higher friend approval of alcohol ( p < .001) and marijuana use ( p < .001), and believed more friends used alcohol ( p < .001). Compared to lifetime alcohol only, perceived friend academic performance decreased the risk of lifetime alcohol and marijuana use ( p = .043). Findings are beneficial to school nurses with students experiencing effects associated with substance use.

Auditory processing and phonological awareness skills of five-year-old children with and without musical experience.

PubMed

Escalda, Júlia; Lemos, Stela Maris Aguiar; França, Cecília Cavalieri

2011-09-01

To investigate the relations between musical experience, auditory processing and phonological awareness of groups of 5-year-old children with and without musical experience. Participants were 56 5-year-old subjects of both genders, 26 in the Study Group, consisting of children with musical experience, and 30 in the Control Group, consisting of children without musical experience. All participants were assessed with the Simplified Auditory Processing Assessment and Phonological Awareness Test and the data was statistically analyzed. There was a statistically significant difference between the results of the sequential memory test for verbal and non-verbal sounds with four stimuli, phonological awareness tasks of rhyme recognition, phonemic synthesis and phonemic deletion. Analysis of multiple binary logistic regression showed that, with exception of the sequential verbal memory with four syllables, the observed difference in subjects' performance was associated with their musical experience. Musical experience improves auditory and metalinguistic abilities of 5-year-old children.

The impact of HIV antiretroviral treatment perception on risky sexual behaviour in Botswana: a short report.

PubMed

Letamo, Gobopamang; Keetile, Mpho; Navaneetham, Kannan

2017-12-01

The aim of this article is to investigate the impact of ART perception on risky sexual behaviours in Botswana. Using binary logistic regression analysis controlling for individual characteristics, the results tend to support the hypothesis that ART misconceptions do not necessarily increase risky sexual behaviours. In particular, the study findings suggest the belief that ARVs cure HIV and AIDS and that people on ARVs should not always use condoms do not necessarily lead to increased risky sexual behaviours, particularly among women. Gender differentials exist in the perceived sexual risk resulting from the use of ART. Risky sexual behaviours increase for women who, wrongly, believed that ARVs cure HIV and AIDS and people on ARVs should not always use condoms. Although there is evidence to suggest ART perceptions do not necessarily lead to increased risky sexual behaviours, HIV and AIDS prevention programmes are needed to strengthen their information, education and communication intervention component that can address misconceptions about ART treatment and provide correct information that is gender-appropriate.

Preferences for the sex-composition of children in Europe: a multilevel examination of its effect on progression to a third child.

PubMed

Mills, Melinda; Begall, Katia

2010-03-01

Comparative research on the preferred sex of children in Western societies has generally focused on women only and ignored the role of gender equity and the need for children's economic support in old age. A multilevel analysis extends existing research by examining, for both men and women and across 24 European countries, the effect of the preferred sex-composition of offspring on whether parents have or intend to have a third child. Using the European Social Survey (2004/5), a multilevel (random coefficient) ordered logit regression of that intention (N = 3,323) and a binary logistic multilevel model of the transition to a third child (N = 6,502) demonstrate the presence of a mixed-sex preference. In countries with a high risk of poverty in old age, a preference for sons is found, particularly for men. In societies where there is lower gender equity, both men and women have a significant preference for boys.

Prevalence and Correlates of Self-Reported ADHD Symptoms in Children Attending School in India.

PubMed

Jaisoorya, T S; Beena, K V; Beena, M; Ellangovan, K; George, Sanju; Thennarasu, K; Srinath, Shoba

2016-09-02

To study the prevalence and correlates of self-reported ADHD symptoms among school-going adolescents from Kerala, India. Seven thousand five hundred sixty students from Classes 8, 10, and 12, aged 12 to 19 years, across 73 schools selected by cluster random sampling, were invited to participate, but only 7,150 successfully completed the questionnaire incorporating standardized instruments. Three hundred five (4.3%) self-reported symptoms for ADHD combined type, 131 (1.8%) for ADHD hyperactive-impulsive type, and 102 (1.4%) for ADHD inattentive type with a male predominance. Binary logistic regression analysis showed that those with symptoms of ADHD (combined type) compared with the non-ADHD group had poorer academic performance, significantly higher substance use, psychological distress, suicidality, and sexual abuse. The high prevalence of self-reported ADHD symptoms and its association with negative correlates previously reported in literature in those with a diagnosis of ADHD suggests that clinically significant self-reported ADHD symptoms could be as disabling as ADHD. © The Author(s) 2016.

Stability of binaries. Part II: Rubble-pile binaries

NASA Astrophysics Data System (ADS)

Sharma, Ishan

2016-10-01

We consider the stability of the binary asteroids whose members are granular aggregates held together by self-gravity alone. A binary is said to be stable whenever both its members are orbitally and structurally stable to both orbital and structural perturbations. To this end, we extend the stability analysis of Sharma (Sharma [2015] Icarus, 258, 438-453), that is applicable to binaries with rigid members, to the case of binary systems with rubble members. We employ volume averaging (Sharma et al. [2009] Icarus, 200, 304-322), which was inspired by past work on elastic/fluid, rotating and gravitating ellipsoids. This technique has shown promise when applied to rubble-pile ellipsoids, but requires further work to settle some of its underlying assumptions. The stability test is finally applied to some suspected binary systems, viz., 216 Kleopatra, 624 Hektor and 90 Antiope. We also see that equilibrated binaries that are close to mobilizing their maximum friction can sustain only a narrow range of shapes and, generally, congruent shapes are preferred.

Eclipsing Binaries From the CSTAR Project at Dome A, Antarctica

NASA Astrophysics Data System (ADS)

Yang, Ming; Zhang, Hui; Wang, Songhu; Zhou, Ji-Lin; Zhou, Xu; Wang, Lingzhi; Wang, Lifan; Wittenmyer, R. A.; Liu, Hui-Gen; Meng, Zeyang; Ashley, M. C. B.; Storey, J. W. V.; Bayliss, D.; Tinney, Chris; Wang, Ying; Wu, Donghong; Liang, Ensi; Yu, Zhouyi; Fan, Zhou; Feng, Long-Long; Gong, Xuefei; Lawrence, J. S.; Liu, Qiang; Luong-Van, D. M.; Ma, Jun; Wu, Zhenyu; Yan, Jun; Yang, Huigen; Yang, Ji; Yuan, Xiangyan; Zhang, Tianmeng; Zhu, Zhenxi; Zou, Hu

2015-04-01

The Chinese Small Telescope ARray (CSTAR) has observed an area around the Celestial South Pole at Dome A since 2008. About 20,000 light curves in the i band were obtained during the observation season lasting from 2008 March to July. The photometric precision achieves about 4 mmag at i = 7.5 and 20 mmag at i = 12 within a 30 s exposure time. These light curves are analyzed using Lomb-Scargle, Phase Dispersion Minimization, and Box Least Squares methods to search for periodic signals. False positives may appear as a variable signature caused by contaminating stars and the observation mode of CSTAR. Therefore, the period and position of each variable candidate are checked to eliminate false positives. Eclipsing binaries are removed by visual inspection, frequency spectrum analysis, and a locally linear embedding technique. We identify 53 eclipsing binaries in the field of view of CSTAR, containing 24 detached binaries, 8 semi-detached binaries, 18 contact binaries, and 3 ellipsoidal variables. To derive the parameters of these binaries, we use the Eclipsing Binaries via Artificial Intelligence method. The primary and secondary eclipse timing variations (ETVs) for semi-detached and contact systems are analyzed. Correlated primary and secondary ETVs confirmed by false alarm tests may indicate an unseen perturbing companion. Through ETV analysis, we identify two triple systems (CSTAR J084612.64-883342.9 and CSTAR J220502.55-895206.7). The orbital parameters of the third body in CSTAR J220502.55-895206.7 are derived using a simple dynamical model.

Spectral properties of binary asteroids

NASA Astrophysics Data System (ADS)

Pajuelo, Myriam; Birlan, Mirel; Carry, Benoît; DeMeo, Francesca E.; Binzel, Richard P.; Berthier, Jérôme

2018-07-01

We present the first attempt to characterize the distribution of taxonomic class among the population of binary asteroids (15 per cent of all small asteroids). For that, an analysis of 0.8-2.5 µm near-infrared spectra obtained with the SpeX instrument on the NASA/IRTF (Infrared Telescope Facility) is presented. Taxonomic class and meteorite analogue is determined for each target, increasing the sample of binary asteroids with known taxonomy by 21 per cent. Most binary systems are bound in the S, X, and C classes, followed by Q and V types. The rate of binary systems in each taxonomic class agrees within uncertainty with the background population of small near-Earth objects and inner main belt asteroids, but for the C types which are under-represented among binaries.

A photometric analysis of the neglected EW-type binary V336 TrA

NASA Astrophysics Data System (ADS)

Kriwattanawong, W.; Sarotsakulchai, T.; Maungkorn, S.; Reichart, D. E.; Haislip, J. B.; Kouprianov, V. V.; LaCluyze, A. P.; Moore, J. P.

2018-05-01

This study presents an analysis of photometric light curves and absolute parameters for the EW-type binary V336 TrA. VRI imaging observations were taken in 2013 by using the robotic telescopes PROMPT 4 and PROMPT 5 at Cerro Tololo Inter-American Observatory (CTIO), Chile. The observed light curves were fitted by using the Wilson-Devinney method. The results showed that V336 TrA is a W-type contact binary with a mass ratio of q = 1.396. The binary is a weak contact system with a fill-out factor of f = 15.69%. The system contains components with masses of 0.653 M⊙ and 0.912 M⊙ for the hotter and the cooler, respectively. The location of the secondary (less massive) component on the log M - log L diagram was found to be near the TAMS. The component has evolved to be oversize and overluminous. The orbital angular momentum of the binary was found to be log Jo = 51.61 cgs, less than all detached systems for same mass. The system has undergone angular momentum and/or mass loss, during the binary evolution from the detached to contact system.

Formation and Evolution of X-ray Binaries

NASA Astrophysics Data System (ADS)

Fragkos, Anastasios

X-ray binaries - mass-transferring binary stellar systems with compact object accretors - are unique astrophysical laboratories. They carry information about many complex physical processes such as star formation, compact object formation, and evolution of interacting binaries. My thesis work involves the study of the formation and evolution of Galactic and extra-galacticX-ray binaries using both detailed and realistic simulation tools, and population synthesis techniques. I applied an innovative analysis method that allows the reconstruction of the full evolutionary history of known black hole X-ray binaries back to the time of compact object formation. This analysis takes into account all the available observationally determined properties of a system, and models in detail four of its evolutionary evolutionary phases: mass transfer through the ongoing X-ray phase, tidal evolution before the onset of Roche-lobe overflow, motion through the Galactic potential after the formation of the black hole, and binary orbital dynamics at the time of core collapse. Motivated by deep extra-galactic Chandra survey observations, I worked on population synthesis models of low-mass X-ray binaries in the two elliptical galaxies NGC3379 and NGC4278. These simulations were targeted at understanding the origin of the shape and normalization of the observed X-ray luminosity functions. In a follow up study, I proposed a physically motivated prescription for the modeling of transient neutron star low-mass X-ray binary properties, such as duty cycle, outburst duration and recurrence time. This prescription enabled the direct comparison of transient low-mass X-ray binary population synthesis models to the Chandra X-ray survey of the two ellipticals NGC3379 and NGC4278. Finally, I worked on population synthesismodels of black holeX-ray binaries in the MilkyWay. This work was motivated by recent developments in observational techniques for the measurement of black hole spin magnitudes in black hole X-ray binaries. The accuracy of these techniques depend on misalignment of the black hole spin with respect to the orbital angular momentum. In black hole X-ray binaries, this misalignment can occur during the supernova explosion that forms the compact object. In this study, I presented population synthesis models of Galactic black hole X-ray binaries, and examined the distribution of misalignment angles, and its dependence on the model parameters.

Analysis of Pulsating Components in the Eclipsing Binary Systems LT Herculis, RZ Microscopii, LY Puppis, V632 Scorpii, and V638 Scorpii

NASA Astrophysics Data System (ADS)

Streamer, M.; Bohlsen, T.; Ogmen, Y.

2016-06-01

Eclipsing binary stars are especially valuable for studies of stellar evolution. If pulsating components are also present then the stellar interior can be studied using asteroseismology techniques. We present photometric data and the analysis of the delta Scuti pulsations that we have discovered in five eclipsing binary systems. The systems are: LT Herculis, RZ Microscopii, LY Puppis, V632 Scorpii and V638 Scorpii. The dominant pulsation frequencies range between 13 - 29 cycles per day with semi-amplitudes of 4 - 20 millimagnitudes.

Phase relations in the system NaCl-KCl-H2O: IV. Differential thermal analysis of the sylvite liquidus in the KCl-H2O binary, the liquidus in the NaCl-KCl-H2O ternary, and the solidus in the NaCl-KCl binary to 2 kb pressure, and a summary of experimental data for thermodynamic-PTX analysis of solid-liquid equilibria at elevated P-T conditions

USGS Publications Warehouse

Chou, I.-Ming; Sterner, S.M.; Pitzer, Kenneth S.

1992-01-01

The sylvite liquidus in the binary system KCl-H2O and the liquidus in the ternary system NaCl-KCl-H2O were determined by using isobaric differential thermal analysis (DTA) cooling scans at pressures up to 2 kbars. Sylvite solubilities along the three-phase curve in the binary system KCl-H2O were obtained by the intersection of sylvite-liquidus isopleths with the three-phase curve in a P-T plot. These solubility data can be represented by the equation Wt.% KCl (??0.2) = 12.19 + 0.1557T - 5.4071 ?? 10-5 T2, where 400 ??? T ??? 770??C. These data are consistent with previous experimental observations. The solidus in the binary system NaCl-KCl was determined by using isobaric DTA heating scans at pressures up to 2 kbars. Using these liquidus and solidus data and other published information, a thermodynamic-PTX analysis of solid-liquid equilibria at high pressures and temperatures for the ternary system has been performed and is presented in an accompanying paper (Part V of this series). However, all experimental liquidus, solidus, and solvus data used in this analysis are summarized in this report (Part IV) and they are compared with the calculated values based on the analysis. ?? 1992.

The PyCBC search for binary black hole coalescences in Advanced LIGO's first observing run

NASA Astrophysics Data System (ADS)

Willis, Joshua; LIGO Scientific Collaboration

2017-01-01

Advanced LIGO's first observing run saw the first detections of binary black hole coalescences. We describe the PyCBC matched filter analysis, and the results of that search for binary systems with total mass up to 100 solar masses. This is a matched filter search for general-relativistic signals from binary black hole systems. Two signals, GW150914 and GW151226, were identified with very high significance, and a third possible signal, LVT151012, was found, though at much lower significance. Supported by NSF award PHY-1506254.

The respective roles of polar/nonpolar binary patterns and amino acid composition in protein regular secondary structures explored exhaustively using hydrophobic cluster analysis.

PubMed

Rebehmed, Joseph; Quintus, Flavien; Mornon, Jean-Paul; Callebaut, Isabelle

2016-05-01

Several studies have highlighted the leading role of the sequence periodicity of polar and nonpolar amino acids (binary patterns) in the formation of regular secondary structures (RSS). However, these were based on the analysis of only a few simple cases, with no direct mean to correlate binary patterns with the limits of RSS. Here, HCA-derived hydrophobic clusters (HC) which are conditioned binary patterns whose positions fit well those of RSS, were considered. All the HC types, defined by unique binary patterns, which were commonly observed in three-dimensional (3D) structures of globular domains, were analyzed. The 180 HC types with preferences for either α-helices or β-strands distinctly contain basic binary units typical of these RSS. Therefore a general trend supporting the "binary pattern preference" assumption was observed. HC for which observed RSS are in disagreement with their expected behavior (discordant HC) were also examined. They were separated in HC types with moderate preferences for RSS, having "weak" binary patterns and versatile RSS and HC types with high preferences for RSS, having "strong" binary patterns and then displaying nonpolar amino acids at the protein surface. It was shown that in both cases, discordant HC could be distinguished from concordant ones by well-differentiated amino acid compositions. The obtained results could, thus, help to complement the currently available methods for the accurate prediction of secondary structures in proteins from the only information of a single amino acid sequence. This can be especially useful for characterizing orphan sequences and for assisting protein engineering and design. © 2016 Wiley Periodicals, Inc.

Hopelessness and Suicidal Ideation among Patients with Depression and Neurotic Disorders Attending a Tertiary Care Centre at Eastern Nepal.

PubMed

Pokharel, R; Lama, S; Adhikari, B R

2016-09-01

Hopelessness is thought to result from a negative appraisal system and interacts with, and worsens, appraisals of defeat and trap which in turn interact with suicide schema and lead to suicidal behaviour. This study was intended to assess hopelessness and suicidal ideation among patients with depression and neurotic disorders at tertiary care centre of eastern Nepal. A cross sectional design included 70 respondents by purposive sampling technique. Beck Hopelessness Scale and Scale of Suicidal Ideation were used to measure hopelessness and suicidal ideation, respectively. Data were analyzed using SPSS statistical software. Pearson chi-square, binary logistic regression and Spearmans' rho, test were applied at 95% confidence interval. Mean ± SD age was 32.8 ± 13.5 years. Most (62.8%) of the patients were female and with the diagnosis of depression. Majority (66%) of the patients had hopelessness. There was no significant difference in hopelessness among patients with depression and neurotic disorders. About 17% respondents had suicidal ideation, among them 82.4% were female. There was no significant difference of suicidal ideation among patients with depression and neurotic disorders (p=0.013). Significant positive correlation between hopelessness and suicidal ideation was found (p=0.001). Binary logistic regression revealed hopelessness was independently related to income and family history of mental illness. Similarly, suicidal ideation was independently related to depression and family history of mental illness. Female respondents, people living under poverty and positive family history of mental illness had more hopelessness and suicidal ideation.

[Developing a predictive model for the caregiver strain index].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Praena-Fernández, Juan Manuel; Ortega-Calvo, Manuel

Patient homecare with multiple morbidities is an increasingly common occurrence. The caregiver strain index is tool in the form of questionnaire that is designed to measure the perceived burden of those who care for their families. The aim of this study is to construct a diagnostic nomogram of informal caregiver burden using data from a predictive model. The model was drawn up using binary logistic regression and the questionnaire items as dichotomous factors. The dependent variable was the final score obtained with the questionnaire but categorised in accordance with that in the literature. Scores between 0 and 6 were labelled as "no" (no caregiver stress) and at or greater than 7 as "yes". The version 3.1.1R statistical software was used. To construct confidence intervals for the ROC curve 2000 boot strap replicates were used. A sample of 67 caregivers was obtained. A diagnosing nomogram was made up with its calibration graph (Brier scaled = 0.686, Nagelkerke R 2 =0.791), and the corresponding ROC curve (area under the curve=0.962). The predictive model generated using binary logistic regression and the nomogram contain four items (1, 4, 5 and 9) of the questionnaire. R plotting functions allow a very good solution for validating a model like this. The area under the ROC curve (0.96; 95% CI: 0.994-0.941) achieves a high discriminative value. Calibration also shows high goodness of fit values, suggesting that it may be clinically useful in community nursing and geriatric establishments. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

Injury risk functions for frontal oblique collisions.

PubMed

Andricevic, Nino; Junge, Mirko; Krampe, Jonas

2018-03-09

The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set. Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes-a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured). IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18-64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes. The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.

Mental health, employment and gender. Cross-sectional evidence in a sample of refugees from Bosnia-Herzegovina living in two Swedish regions.

PubMed

Blight, Karin Johansson; Ekblad, Solvig; Persson, Jan-Olov; Ekberg, Jan

2006-04-01

Large regional differences regarding access to employment have been observed amongst persons from Bosnia-Herzegovina coming to Sweden in 1993-1994. This has led to questions about the role of mental health. To explore this further, postal survey questionnaires were distributed to a community sample (N = 650) that was stratified and, within strata, randomly selected from a sampling frame of persons coming to Sweden from Bosnia-Herzegovina in 1993-1994. Four hundred and thirteen persons returned the questionnaire providing a response rate of 63.5%. The aim was to increase knowledge about the relationship between mental health and employment in the chosen population. The main mental health outcome measure was the Göteborg Quality of Life instrument from which 360 respondents were grouped according to low or high symptom levels. Data were cross tabulated (chi2-tested) against background variables such as age, gender and occupational status, and then tested using binary logistic regression. Binary logistic regression revealed unemployed men but not women, and women who had been working for longer periods during 1993-1999, to be associated with high levels of symptoms of poor mental health. Women living in the urban region were also overrepresented in the high symptom group. These findings indicate that, job occupancy is important to the health of men in the study. However, for the women, further understanding is needed, as job occupancy at some level as well as living in the urban region appear to be associated with poor mental health.

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.

Characterization of serum microRNAs profile of PCOS and identification of novel non-invasive biomarkers.

PubMed

Long, Wei; Zhao, Chun; Ji, Chenbo; Ding, Hongjuan; Cui, Yugui; Guo, Xirong; Shen, Rong; Liu, Jiayin

2014-01-01

Polycystic ovary syndrome (PCOS), the most common endocrinopathy in women of reproductive age, is characterized by polycystic ovaries, chronic anovulation, hyperandrogenism and insulin resistance. Despite the high prevalence of hyperandrogenemia, a definitive endocrine marker for PCOS has so far not been identified. Circulating miRNAs have recently been shown to serve as diagnostic/prognostic biomarkers in patients with cancers. Our current study focused on the altered expression of serum miRNAs and their correlation with PCOS. We systematically used the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays to identify and validate the expression of serum miRNAs of PCOS patients. The expression levels of three miRNAs (miR-222, miR-146a and miR-30c) were significantly increased in PCOS patients with respect to the controls in our discovery evaluation and followed validation. The area under the receiver operating characteristic (ROC) curve (AUC) is 0.799, 0.706, and 0.688, respectively. The combination of the three miRNAs using multiple logistic regression analysis showed a larger AUC (0.852) that was more efficient for the diagnosis of PCOS. In addition, logistic binary regression analyses show miR-222 is positively associated with serum insulin, while miR-146a is negatively associated with serum testosterone. Furthermore, bioinformatics analysis indicated that the predicted targets function of the three miRNAs mainly involved in the metastasis, cell cycle, apoptosis and endocrine. Serum miRNAs are differentially expressed between PCOS patients and controls. We identified and validated a class of three serum miRNAs that could act as novel non-invasive biomarkers for diagnosis of PCOS. These miRNAs may be involved in the pathogenesis of PCOS. © 2014 S. Karger AG, Basel.

Coffee consumption modifies risk of estrogen-receptor negative breast cancer

PubMed Central

2011-01-01

Introduction Breast cancer is a complex disease and may be sub-divided into hormone-responsive (estrogen receptor (ER) positive) and non-hormone-responsive subtypes (ER-negative). Some evidence suggests that heterogeneity exists in the associations between coffee consumption and breast cancer risk, according to different estrogen receptor subtypes. We assessed the association between coffee consumption and postmenopausal breast cancer risk in a large population-based study (2,818 cases and 3,111 controls), overall, and stratified by ER tumour subtypes. Methods Odds ratios (OR) and corresponding 95% confidence intervals (CI) were estimated using the multivariate logistic regression models fitted to examine breast cancer risk in a stratified case-control analysis. Heterogeneity among ER subtypes was evaluated in a case-only analysis, by fitting binary logistic regression models, treating ER status as a dependent variable, with coffee consumption included as a covariate. Results In the Swedish study, coffee consumption was associated with a modest decrease in overall breast cancer risk in the age-adjusted model (OR> 5 cups/day compared to OR≤ 1 cup/day: 0.80, 95% CI: 0.64, 0.99, P trend = 0.028). In the stratified case-control analyses, a significant reduction in the risk of ER-negative breast cancer was observed in heavy coffee drinkers (OR> 5 cups/day compared to OR≤ 1 cup/day : 0.43, 95% CI: 0.25, 0.72, P trend = 0.0003) in a multivariate-adjusted model. The breast cancer risk reduction associated with higher coffee consumption was significantly higher for ER-negative compared to ER-positive tumours (P heterogeneity (age-adjusted) = 0.004). Conclusions A high daily intake of coffee was found to be associated with a statistically significant decrease in ER-negative breast cancer among postmenopausal women. PMID:21569535

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

[Behaviors on drug-abuse and prevalence of sexually transmitted diseases among drug users in Tianjin, China, from 2011 to 2015].

PubMed

Guo, Y; Zhou, N; Li, J; Ning, T L; Guo, W

2016-02-01

To understand the change of behavioral characteristics among drug users (DUS) in Tianjin and the prevalence rates of major sexually transmitted disease infections. A series of cross-sectional surveys were used. Between April and June, 2011 to 2015, a cross-sectional survey with face to face interview, was undertaken. Interview was conducted among DUS who entered the drug rehabilitation center and blood samples were drawn to test for HIV/syphilis/HCV infections. Multivariate logistic regression analysis was used to analyze the relationship between the infection of major sexually transmitted diseases and drug abuse or sexual behavior. 2 000 DUS were included during the 5-year study, with the average age of the DUS as 34.5 ± 8.7. Female accounted for 17.9% and club drug (new drugs) users accounted 45.4% of the participants, with its proportion increasing over the years. Comparing to traditional drug users, club drug users showed more sexual activities with partners, but lower proportion of condom use. Prevalence rates of HIV/Syphilis and HCV were 1.3%, 11.0%, 52.0%, respectively. The prevalence of syphilis among club drug users was significantly higher than those on traditional-drug use (χ(2)=67.778,P<0.001). Data from Binary logistic regression analysis showed that club drug use (adjusted OR=1.607, 95% CI:1.191-2.170) and females (adjusted OR=5.287, 95%CI: 3.824-7.311) were associated with syphilis infection among DUS. Drug abuse behavior changed among the drug abuse in Tianjin. Proportion of club drug use continued to increase so as the risk of infected sexually transmitted diseases.

Incidence and risk factors of workplace violence against nurses in a Chinese top-level teaching hospital: A cross-sectional study.

PubMed

Chen, Xiaoming; Lv, Ming; Wang, Min; Wang, Xiufeng; Liu, Junyan; Zheng, Nan; Liu, Chunlan

2018-04-01

To investigate the incidence of workplace violence involving nurses and to identify related risk factors in a high-quality Chinese teaching hospital. A cross-sectional study design was used. The final sample comprised responses from 1831 registered nurses collected with a whole-hospital survey from June 1 to June 15, 2016. The demographic characteristics of the nurses who had experienced any form of violence were collected, and logistic regression analysis was applied to evaluate the risk factors for nurses related to workplace violence. Out of the total number of nurses surveyed, 904 (49.4%) nurses reported having experienced any type of violence in the past year. The frequencies of exposure to physical and non-physical violence were 6.3% (116) and 49.0% (897), respectively. All the incidence rates of violence were lower than those of other studies based on regional hospitals in China and were at the same level found in developed countries and districts. Binary logistic regression analysis revealed that nurses at levels 2 to 4 and female nurses in clinical departments were the most vulnerable to non-physical violence. For physical violence, the two independent risk factors were working in an emergency department and having 6-10 years of work experience. Workplace violence directly threatens nurses from high-quality Chinese teaching hospitals. However, the incidence of WPV against nurses in this teaching hospital was better than that in regional hospitals. This study also provides reference material to identify areas where nurses encounter relatively high levels of workplace violence in high-quality Chinese teaching hospitals. Copyright © 2018 Elsevier Inc. All rights reserved.

The Young Visual Binary Survey

NASA Astrophysics Data System (ADS)

Prato, Lisa; Avilez, Ian; Lindstrom, Kyle; Graham, Sean; Sullivan, Kendall; Biddle, Lauren; Skiff, Brian; Nofi, Larissa; Schaefer, Gail; Simon, Michal

2018-01-01

Differences in the stellar and circumstellar properties of the components of young binaries provide key information about star and disk formation and evolution processes. Because objects with separations of a few to a few hundred astronomical units share a common environment and composition, multiple systems allow us to control for some of the factors which play into star formation. We are completing analysis of a rich sample of about 100 pre-main sequence binaries and higher order multiples, primarily located in the Taurus and Ophiuchus star forming regions. This poster will highlight some of out recent, exciting results. All reduced spectra and the results of our analysis will be publicly available to the community at http://jumar.lowell.edu/BinaryStars/. Support for this research was provided in part by NSF award AST-1313399 and by NASA Keck KPDA funding.

MicroDAIMON study: Microcirculatory DAIly MONitoring in critically ill patients: a prospective observational study.

PubMed

Scorcella, Claudia; Damiani, Elisa; Domizi, Roberta; Pierantozzi, Silvia; Tondi, Stefania; Carsetti, Andrea; Ciucani, Silvia; Monaldi, Valentina; Rogani, Mara; Marini, Benedetto; Adrario, Erica; Romano, Rocco; Ince, Can; Boerma, E Christiaan; Donati, Abele

2018-05-15

Until now, the prognostic value of microcirculatory alterations in critically ill patients has been mainly evaluated in highly selected subgroups. Aim of this study is to monitor the microcirculation daily in mixed group of Intensive Care Unit (ICU)-patients and to establish the association between (the evolution of) microcirculatory alterations and outcome. This is a prospective longitudinal observational single-centre study in adult patients admitted to a 12-bed ICU in an Italian teaching hospital. Sublingual microcirculation was evaluated daily, from admission to discharge/death, using Sidestream Dark Field imaging. Videos were analysed offline to assess flow and density variables. Laboratory and clinical data were recorded simultaneously. A priori, a Microvascular Flow Index (MFI) < 2.6 was defined as abnormal. A binary logistic regression analysis was performed to evaluate the association between microcirculatory variables and outcomes; a Kaplan-Meier survival curve was built. Outcomes were ICU and 90-day mortality. A total of 97 patients were included. An abnormal MFI was present on day 1 in 20.6%, and in 55.7% of cases during ICU admission. Patients with a baseline MFI < 2.6 had higher ICU, in-hospital and 90-day mortality (45 vs. 15.6%, p = 0.012; 55 vs. 28.6%, p = 0.035; 55 vs. 26%, p = 0.017, respectively). An independent association between baseline MFI < 2.6 and outcome was confirmed in a binary logistic analysis (odds ratio 4.594 [1.340-15.754], p = 0.015). A heart rate (HR) ≥ 90 bpm was an adjunctive predictor of mortality. However, a model with stepwise inclusion of mean arterial pressure < 65 mmHg, HR ≥ 90 bpm, lactate > 2 mmol/L and MFI < 2.6 did not detect significant differences in ICU mortality. In case an abnormal MFI was present on day 1, ICU mortality was significantly higher in comparison with patients with an abnormal MFI after day 1 (38 vs. 6%, p = 0.001), indicating a time-dependent significant difference in prognostic value. In a general ICU population, an abnormal microcirculation at baseline is an independent predictor for mortality. In this setting, additional routine daily microcirculatory monitoring did not reveal extra prognostic information. Further research is needed to integrate microcirculatory monitoring in a set of commonly available hemodynamic variables. Trial registration NCT 02649088, www.clinicaltrials.gov . Date of registration: 23 December 2015, retrospectively registered.

Lean and Efficient Software: Whole-Program Optimization of Executables

DTIC Science & Technology

2015-09-30

libraries. Many levels of library interfaces—where some libraries are dynamically linked and some are provided in binary form only—significantly limit...software at build time. The opportunity: Our objective in this project is to substantially improve the performance, size, and robustness of binary ...executables by using static and dynamic binary program analysis techniques to perform whole-program optimization directly on compiled programs

First photometric study of two southern eclipsing binaries IS Tel and DW Aps

NASA Astrophysics Data System (ADS)

Özer, S.; Sürgit, D.; Erdem, A.; Öztürk, O.

2017-02-01

The paper presents the first photometric analysis of two southern eclipsing binary stars, IS Tel and DW Aps. Their V light curves from the All Sky Automated Survey were modelled by using Wilson-Devinney method. The final models give these two Algol-like binary stars as having detached configurations. Absolute parameters of the components of the systems were also estimated.

A cross-sectional assessment of health-related quality of life in Chinese patients with chronic hepatitis c virus infection with EQ-5D.

PubMed

Huang, Rui; Rao, Huiying; Shang, Jia; Chen, Hong; Li, Jun; Xie, Qing; Gao, Zhiliang; Wang, Lei; Wei, Jia; Jiang, Jianning; Sun, Jian; Jiang, Jiaji; Wei, Lai

2018-06-15

Hepatitis C virus (HCV) infection is one of the most common liver infections, with a decrement in HRQoL of HCV patients. This study aims to assess Health-related quality of life (HRQoL) in Chinese patients with chronic HCV infection, and to identify significant predictors of the HRQoL in these patients of China. In this cross-sectional observational study, treatment-naïve Han ethnic adults with chronic HCV infection were enrolled. Adopting European Quality of Life scale (EQ-5D) and EuroQOL visual analogue scale (EQ-VAS) were used to qualify HRQoL. Results were reported in descriptive analyses to describe sociodemographic and clinical characteristics. Multiple linear regression analysis was applied to investigate the associations of these variables with HRQoL. Binary logistic regression analysis was performed to identify associations of these variables with HRQoL by dimensions of EQ-5D. Nine hundred ninety-seven patients were enrolled in the study [median age 46.0 (37.0, 56.0) years; male 54.8%]. Mean EQ-5D index and EQ-VAS score were 0.780 ± 0.083 and 77.2 ± 14.8. Multiple Linear regression analysis showed that income (< 2000 RMB, β = - 0.134; 2000-4999 RMB, β = - 0.085), moderate or severe symptoms of discomfort (more than one symptoms, β = - 0.090), disease profile (cirrhosis, β = - 0.114), hyperlipidemia (β = - 0.065) and depression (β = - 0.065) were independently associated with EQ-5D index. Residence (the west, β = 0.087), income (< 2000 RMB, β = - 0.129; 2000-4999 RMB, β = - 0.052), moderate or severe symptoms of discomfort (more than one symptoms, β = - 0.091), disease profile and depression (β = - 0.316) were the influencing factors on EQ-VAS. Binary logistic regression indicated that disease profile and clinical depression were the major influencing factors on all five dimensions of EQ-5D. In this cross-sectional assessment of HCV patients in China, we indicated HRQoL of Chinese HCV patients. Significant negative associations between HRQoL and sociodemographic and clinical factors such as moderate or severe symptoms of discomfort, disease profile and depression emerged. We have to focus on optimally managing care of HCV patients and improving their HRQoL. ClinicalTrials.gov identifier NCT01293279. Date of registration: February 10, 2011.

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

PubMed

Van Hertem, T; Bahr, C; Schlageter Tello, A; Viazzi, S; Steensels, M; Romanini, C E B; Lokhorst, C; Maltz, E; Halachmi, I; Berckmans, D

2016-09-01

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Parallel Analysis with Unidimensional Binary Data

ERIC Educational Resources Information Center

Weng, Li-Jen; Cheng, Chung-Ping

2005-01-01

The present simulation investigated the performance of parallel analysis for unidimensional binary data. Single-factor models with 8 and 20 indicators were examined, and sample size (50, 100, 200, 500, and 1,000), factor loading (.45, .70, and .90), response ratio on two categories (50/50, 60/40, 70/30, 80/20, and 90/10), and types of correlation…

Different spectrophotometric methods applied for the analysis of binary mixture of flucloxacillin and amoxicillin: A comparative study.

PubMed

Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed

2016-05-15

Three different spectrophotometric methods were applied for the quantitative analysis of flucloxacillin and amoxicillin in their binary mixture, namely, ratio subtraction, absorbance subtraction and amplitude modulation. A comparative study was done listing the advantages and the disadvantages of each method. All the methods were validated according to the ICH guidelines and the obtained accuracy, precision and repeatability were found to be within the acceptable limits. The selectivity of the proposed methods was tested using laboratory prepared mixtures and assessed by applying the standard addition technique. So, they can be used for the routine analysis of flucloxacillin and amoxicillin in their binary mixtures. Copyright © 2016 Elsevier B.V. All rights reserved.

Detection and phylogenetic analysis of hepatitis A virus and norovirus in marine recreational waters of Mexico.

PubMed

Félix, Josefina León; Fernandez, Yuridia Cháidez; Velarde-Félix, Jesús Salvador; Torres, Benigno Valdez; Cháidez, Cristobal

2010-06-01

An investigation was conducted to determine hepatitis A virus (HAV) and norovirus (NV) presence in marine recreational waters (MRWs) from two Mexican tourists beaches (Altata and Mazatlan), located at the northwestern state of Sinaloa, Mexico. Also, Binary Logistic Regression (BLR) analyses were conducted between physicochemical parameters (temperature, turbidity and salinity) and viral organisms (HAV and NV). A total of 32 MRWs samples were collected from April to July of 2006. Samples were processed according to the Environmental Protection Agency (EPA) adsorption-elution method. Overall, 18 MRWs samples (56.3%) were positive for HAV and NV; 4 (22.2%) were obtained from Altata and 14 (77.8%) from Mazatlan. HAV was detected in 3 MRWs samples (9.4%) and NV in 15 samples (46.8%). Phylogenetic analysis showed the presence of genotype I sub genotype B for HAV and NV genogroup II. BLR analysis showed significant correlations between NV and physicochemical parameters (temperature, turbidity and salinity) (p=0.017, p=0.08, p=0.048, respectively). No significant correlation between physicochemical parameters and HAV was observed. The results indicated that MRW quality of Sinaloa beaches is affected by human faecal pollution. Viral surveillance programs should be implemented to minimize health risks to bathers.

Altered Esthetics in Primary Central Incisors: The Child's Perception.

PubMed

Soares, Fernanda Cunha; Cardoso, Mariane; Bolan, Michele

2015-01-01

This study's purpose was to determine preschool-age children's social perceptions and self-perceptions regarding altered dental esthetics. A cross-sectional study was carried out involving 431 four- to five-year-olds. The participants were shown four photographs of children with incisors exhibiting discoloration, crown fracture, missing tooth, or normal teeth. The children were asked four questions for analysis of social perceptions and two additional questions for analysis of self-perceptions. Binary logistic regression was used for the statistical analysis. Children had negative social perceptions, as a significant association was found between their negative feelings and the altered dental esthetics in children pictured in the photographs. The affected anterior incisor was indicated as the main reason for this feeling (odds ratio equals 4.68, 95 percent confidence interval [CI] equals 2.39 to 9.15). When analyzing self-perceptions, a significant association was found between negative feelings and the child's own altered dental esthetics. Children with altered esthetics felt 1.92-fold sadder than those without altered esthetics (95 percent CI equals 1.22 to 3.02). Again, the affected teeth were indicated as the main reason for this feeling (prevalence ratio equals 1.22) in comparison to reasons cited. Four- to five-year-olds have negative social perceptions and self-perceptions regarding altered dental esthetics.

Sensory impairments of the lower limb after stroke: a pooled analysis of individual patient data.

PubMed

Tyson, Sarah F; Crow, J Lesley; Connell, Louise; Winward, Charlotte; Hillier, Susan

2013-01-01

To obtain more generalizable information on the frequency and factors influencing sensory impairment after stroke and their relationship to mobility and function. A pooled analysis of individual data of stroke survivors (N = 459); mean (SD) age = 67.2 (14.8) years, 54% male, mean (SD) time since stroke = 22.33 (63.1) days, 50% left-sided weakness. Where different measurement tools were used, data were recorded. Descriptive statistics described frequency of sensory impairments, kappa coefficients investigated relationships between sensory modalities, binary logistic regression explored the factors influencing sensory impairments, and linear regression assessed the impact of sensory impairments on activity limitations. Most patients' sensation was intact (55%), and individual sensory modalities were highly associated (κ = 0.60, P < .001). Weakness and neglect influenced sensory impairment (P < .001), but demographics, stroke pathology, and spasticity did not. Sensation influenced independence in activities of daily living, mobility, and balance but less strongly than weakness. Pooled individual data analysis showed sensation of the lower limb is grossly preserved in most stroke survivors but, when present, it affects function. Sensory modalities are highly interrelated; interventions that treat the motor system during functional tasks may be as effective at treating the sensory system as sensory retraining alone.

Characteristics of Maxillofacial Trauma Among Alcohol and Drug Users.

PubMed

Goulart, Douglas Rangel; Durante, Letícia; de Moraes, Márcio; Asprino, Luciana

2015-11-01

The aim of the current study was to identify and compare the characteristics of maxillofacial trauma in alcohol and drug users with those of nonusers. A retrospective study was conducted using the medical records of patients treated for facial trauma between April 1999 and March 2012 at the Maxillofacial Surgery Division of the Piracicaba Dental School. The data were analyzed by descriptive analysis, binary logistic regression, and correlational analysis using SPSS 18.0 software. The results were considered relevant at P < 0.05. Medical records of 3724 patients with facial trauma were analyzed, of which 173 were illicit drug users and 19.36% reported alcohol intake. The use of illicit drugs was reported by 4.64%. The prevalent etiological factor among drug and alcohol users was interpersonal violence. The mandible was the face part most affected by fractures. Male patients exhibited increased odds of experiencing fractures (OR = 1.43), as did users of illicit drugs (OR = 1.62), when compared with nonusers. When faced with maxillofacial trauma, male drug users exhibited an increased chance of experiencing fractures. This knowledge should be used as a baseline to implement more efficient prevention strategies for this population.

Risk Factors for Problem Gambling in California: Demographics, Comorbidities and Gambling Participation.

PubMed

Volberg, Rachel A; McNamara, Lauren M; Carris, Kari L

2018-06-01

While population surveys have been carried out in numerous jurisdictions internationally, little has been done to assess the relative strength of different risk factors that may contribute to the development of problem gambling. This is an important preparatory step for future research on the etiology of problem gambling. Using data from the 2006 California Problem Gambling Prevalence Survey, a telephone survey of adult California residents that used the NODS to assess respondents for gambling problems, binary logistic regression analysis was used to identify demographic characteristics, health-related behaviors, and gambling participation variables that statistically predicted the odds of being a problem or pathological gambler. In a separate approach, linear regression analysis was used to assess the impact of changes in these variables on the severity of the disorder. In both of the final models, the greatest statistical predictor of problem gambling status was past year Internet gambling. Furthermore, the unique finding of a significant interaction between physical or mental disability, Internet gambling, and problem gambling highlights the importance of exploring the interactions between different forms of gambling, the experience of mental and physical health issues, and the development of problem gambling using a longitudinal lens.

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

Frequency of postnatal hydronephrosis in infants with a renal anterior-posterior pelvic diameter > 4 mm on midtrimester ultrasound.

PubMed

Chou, Ching-Yu; Chen, Li-Ching; Cheong, Mei-Leng; Tsai, Ming-Song

2015-10-01

To examine the association of antenatal renal pelvic dilatation observed on midtrimester ultrasound screening with the presence of hydronephrosis in newborn infants. The records of patients who received fetal ultrasound examination at 18-28 weeks' gestation from May 2008 to March 2012 were retrospectively reviewed. A fetal renal pelvic anterior-posterior (AP) diameter > 4 mm was considered abnormal and ≤ 4 mm was considered normal. On postnatal ultrasound, a renal pelvic AP diameter > 3 mm was considered to indicate hydronephrosis and ≤ 3 mm was considered normal. The association of postnatal hydronephrosis with prenatal pelvic AP diameter was determined using binary logistic regression analysis. The study comprised 1310 newborn infants: 684 (52.2%) male and 626 (47.8%) female. Multivariate analysis showed a right or left prenatal AP renal pelvic diameter > 4 mm was associated with a higher risk of postnatal hydronephrosis compared with a right and left prenatal AP renal pelvic diameter ≤ 4 mm. Boys had a higher risk for postnatal hydronephrosis than girls (odds ratio = 2.42, p < 0.05). An antenatal renal pelvic AP diameter > 4 mm on midtrimester ultrasound is predictive of postnatal hydronephrosis. Copyright © 2015. Published by Elsevier B.V.

Clinical and socio-demographic correlates of anxious distress in Asian outpatients with major depressive disorder.

PubMed

Maneeton, Narong; Suttajit, Sirijit; Maneeton, Benchalak; Likhitsathian, Surinporn; Eurviyanukul, Kanokkwan; Udomratn, Pichet; Chan, Edwin Shih-Yen; Si, Tian-Mei; Sulaiman, Ahmad Hatim; Chen, Chia-Hui; Bautista, Dianne; Srisurapanont, Manit

2017-10-01

Anxious distress in major depressive disorder (MDD) is common and associated with poor outcomes and management difficulties. This post hoc analysis aimed to examine the socio-demographic and clinical correlates of anxiety distress in Asian outpatients with MDD. Instead of two out of five specifiers defined by the Diagnostic and Statistical Manual Version-5, anxious distress defined in this study was operationalized as the presence of at least two out of four proxy items drawn from the 90-item Symptom Checklist, Revised (SCL-90-R). Other measures included the Montgomery-Asberg Depression Rating Scale (MADRS), the Fatigue Severity Scale, the Sheehan Disability Scale and the Multidimensional Scale of Perceived Social Support. The data of 496 patients with MDD were included. Anxious distress was found in 371 participants (74.8%). The binary logistic regression analysis found that anxious distress was independently and significantly correlated with working status, higher MADRS scores, severe insomnia and functional impairment. Three-fourths of Asian patients with MDD in tertiary care settings may have DSM-5 anxious distress of at least moderate distress. Its prevalence may vary among working groups. The specifier was associated with greater depressive symptom severity, severe insomnia and functional impairment.

[Day hospitals--predictors for utilisation and quality expectations from the perspective of family caregivers of dementia patients].

PubMed

Donath, Carolin; Bleich, Stefan; Grässel, Elmar

2009-05-01

To relieve the burden on family caregivers of dementia patients, the utilisation of day hospitals should be increased. Therefore, the predictive variables for utilisation as well as family caregivers' views regarding the quality of day hospitals must be investigated. The cross-sectional study was carried out as an anonymous, written survey of family caregivers of dementia patients in four regions of Germany. Quantitative and qualitative data from 404 family caregivers was analysed using binary logistic regression analysis and qualitative content analysis, respectively. In addition, 11 day hospital managers were interviewed concerning their quality concepts. The only significant predictor for the utilisation of day hospitals is the estimate of how helpful this support is for the family caregiver's situation. Those who have already had experiences with a day hospital expressed a wish for medical and psychiatric care by "well-trained" staff and a reasonable form of occupation for the dementia patient. In order to increase utilisation, family caregivers must be convinced of the advantages of using day hospitals. A day hospital that combines both activating occupational therapy and medical care by well-trained staff is what family caregivers wish most for their care-receivers.

[Predictive factors of complications during CT-guided transthoracic biopsy].

PubMed

Fontaine-Delaruelle, C; Souquet, P-J; Gamondes, D; Pradat, E; de Leusse, A; Ferretti, G R; Couraud, S

2017-04-01

CT-guided transthoracic core-needle biopsy (TTNB) is frequently used for the diagnosis of lung nodules. The aim of this study is to describe TTNBs' complications and to investigate predictive factors of complications. All consecutive TTNBs performed in three centers between 2006 and 2012 were included. Binary logistic regression was used for multivariate analysis. Overall, 970 TTNBs were performed in 929 patients. The complication rate was 34% (life-threatening complication in 6%). The most frequent complications were pneumothorax (29% included 4% which required chest-tube) and hemoptysis (5%). The mortality rate was 0.1% (n=1). In multivariate analysis, predictive factor for a complication was small target size (AOR=0.984; 95% CI [0.976-0.992]; P<0.001). This predictive factor was also found for occurrence of life-threatening complication (AOR=0.982; [0.965-0.999]; P=0.037), of pneumothorax (AOR=0.987; [0.978-0.995]; P=0.002) and of hemoptysis (AOR=0.973; [0.951-0.997]; P=0.024). One complication occurred in one-third of TTNBs. The proportion of life-threatening complication was 6%. A small lesion size was predictive of complication occurrence. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer

PubMed Central

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-01-01

Background: The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Methods: Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Results: Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Conclusion: Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer. PMID:22294182

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer.

PubMed

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-02-28

The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer.

Constraints on the Progenitor System of SN 2016gkg from a Comprehensive Statistical Analysis

NASA Astrophysics Data System (ADS)

Sravan, Niharika; Marchant, Pablo; Kalogera, Vassiliki; Margutti, Raffaella

2018-01-01

Type IIb supernovae (SNe) present a unique opportunity for understanding the progenitors of stripped-envelope SNe because the stellar progenitor of several SNe IIb have been identified in pre-explosion images. In this paper, we use Bayesian inference and a large grid of non-rotating solar-metallicity single and binary stellar models to derive the associated probability distributions of single and binary progenitors of the SN IIb 2016gkg using existing observational constraints. We find that potential binary star progenitors have smaller pre-SN hydrogen-envelope and helium-core masses than potential single-star progenitors typically by 0.1 M ⊙ and 2 M ⊙, respectively. We find that, a binary companion, if present, is a main-sequence or red-giant star. Apart from this, we do not find strong constraints on the nature of the companion star. We demonstrate that the range of progenitor helium-core mass inferred from observations could help improve constraints on the progenitor. We find that the probability that the progenitor of SN 2016gkg was a binary is 22% when we use constraints only on the progenitor luminosity and effective temperature. Imposing the range of pre-SN progenitor hydrogen-envelope mass and radius inferred from SN light curves, the probability that the progenitor is a binary increases to 44%. However, there is no clear preference for a binary progenitor. This is in contrast to binaries being the currently favored formation channel for SNe IIb. Our analysis demonstrates the importance of statistical inference methods to constrain progenitor channels.

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

PubMed

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

Binarity and Variable Stars in the Open Cluster NGC 2126

NASA Astrophysics Data System (ADS)

Chehlaeh, Nareemas; Mkrtichian, David; Kim, Seung-Lee; Lampens, Patricia; Komonjinda, Siramas; Kusakin, Anatoly; Glazunova, Ljudmila

2018-04-01

We present the results of an analysis of photometric time-series observations for NGC 2126 acquired at the Thai National Observatory (TNO) in Thailand and the Mount Lemmon Optical Astronomy Observatory (LOAO) in USA during the years 2004, 2013 and 2015. The main purpose is to search for new variable stars and to study the light curves of binary systems as well as the oscillation spectra of pulsating stars. NGC 2126 is an intermediate-age open cluster which has a population of stars inside the δ Scuti instability strip. Several variable stars are reported including three eclipsing binary stars, one of which is an eclipsing binary star with a pulsating component (V551 Aur). The Wilson-Devinney technique was used to analyze its light curves and to determine a new set of the system’s parameters. A frequency analysis of the eclipse-subtracted light curve was also performed. Eclipsing binaries which are members of open clusters are capable of delivering strong constraints on the cluster’s properties which are in turn useful for a pulsational analysis of their pulsating components. Therefore, high-resolution, high-quality spectra will be needed to derive accurate component radial velocities of the faint eclipsing binaries which are located in the field of NGC 2126. The new Devasthal Optical Telescope, suitably equipped, could in principle do this.

Analysis of Logistics in Support of a Human Lunar Outpost

NASA Technical Reports Server (NTRS)

Cirillo, William; Earle, Kevin; Goodliff, Kandyce; Reeves, j. D.; Andrashko, Mark; Merrill, R. Gabe; Stromgren, Chel

2008-01-01

Strategic level analysis of the integrated behavior of lunar transportation system and lunar surface system architecture options is performed to inform NASA Constellation Program senior management on the benefit, viability, affordability, and robustness of system design choices. This paper presents an overview of the approach used to perform the campaign (strategic) analysis, with an emphasis on the logistics modeling and the impacts of logistics resupply on campaign behavior. An overview of deterministic and probabilistic analysis approaches is provided, with a discussion of the importance of each approach to understanding the integrated system behavior. The logistics required to support lunar surface habitation are analyzed from both 'macro-logistics' and 'micro-logistics' perspectives, where macro-logistics focuses on the delivery of goods to a destination and micro-logistics focuses on local handling of re-supply goods at a destination. An example campaign is provided to tie the theories of campaign analysis to results generation capabilities.

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Development of a statistical model for the determination of the probability of riverbank erosion in a Meditteranean river basin

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Kourgialas, Nektarios; Karatzas, George; Giannakis, Georgios; Lilli, Maria; Nikolaidis, Nikolaos

2014-05-01

Riverbank erosion affects the river morphology and the local habitat and results in riparian land loss, damage to property and infrastructures, ultimately weakening flood defences. An important issue concerning riverbank erosion is the identification of the areas vulnerable to erosion, as it allows for predicting changes and assists with stream management and restoration. One way to predict the vulnerable to erosion areas is to determine the erosion probability by identifying the underlying relations between riverbank erosion and the geomorphological and/or hydrological variables that prevent or stimulate erosion. A statistical model for evaluating the probability of erosion based on a series of independent local variables and by using logistic regression is developed in this work. The main variables affecting erosion are vegetation index (stability), the presence or absence of meanders, bank material (classification), stream power, bank height, river bank slope, riverbed slope, cross section width and water velocities (Luppi et al. 2009). In statistics, logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable, e.g. binary response, based on one or more predictor variables (continuous or categorical). The probabilities of the possible outcomes are modelled as a function of independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. 1 = "presence of erosion" and 0 = "no erosion") for any value of the independent variables. The regression coefficients are estimated by using maximum likelihood estimation. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested (Atkinson et al. 2003). The developed statistical model is applied to the Koiliaris River Basin in the island of Crete, Greece. The aim is to determine the probability of erosion along the Koiliaris' riverbanks considering a series of independent geomorphological and/or hydrological variables. Data for the river bank slope and for the river cross section width are available at ten locations along the river. The riverbank has indications of erosion at six of the ten locations while four has remained stable. Based on a recent work, measurements for the two independent variables and data regarding bank stability are available at eight different locations along the river. These locations were used as validation points for the proposed statistical model. The results show a very close agreement between the observed erosion indications and the statistical model as the probability of erosion was accurately predicted at seven out of the eight locations. The next step is to apply the model at more locations along the riverbanks. In November 2013, stakes were inserted at selected locations in order to be able to identify the presence or absence of erosion after the winter period. In April 2014 the presence or absence of erosion will be identified and the model results will be compared to the field data. Our intent is to extend the model by increasing the number of independent variables in order to indentify the key factors favouring erosion along the Koiliaris River. We aim at developing an easy to use statistical tool that will provide a quantified measure of the erosion probability along the riverbanks, which could consequently be used to prevent erosion and flooding events. Atkinson, P. M., German, S. E., Sear, D. A. and Clark, M. J. 2003. Exploring the relations between riverbank erosion and geomorphological controls using geographically weighted logistic regression. Geographical Analysis, 35 (1), 58-82. Luppi, L., Rinaldi, M., Teruggi, L. B., Darby, S. E. and Nardi, L. 2009. Monitoring and numerical modelling of riverbank erosion processes: A case study along the Cecina River (central Italy). Earth Surface Processes and Landforms, 34 (4), 530-546. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Serological Survey and Associated Risk Factors of Visceral Leish-maniasis in Qom Province, Central Iran.

PubMed

Rakhshanpour, Arash; Mohebali, Mehdi; Akhondi, Behnaz; Rahimi, Mohammad Taghi; Rokni, Mohammad Bagher

2014-01-01

Visceral leishmaniasis (VL) or kala-azar is considered as a parasitic disease caused by the species of Leishmania donovani complex which is intracellular parasites. This systemic disease is endemic in some parts of provinc-es of Iran. The aim of this study was to determine the seroprevalence of VL in Qom Province, central Iran using di-rect agglutination test (DAT). Overall, 1564 serum samples (800 males and 764 females) were collected from selected subjects by random-ized cluster sampling in 2011-2012. Sera were tested and analyzed by DAT. Before sampling; a questionnaire was filled out for each case. Data were analyzed using Chi-square test and multivariate logistic regression for risk factors analysis. Of 1564 individuals, 53 cases (3.38%) showed Leishmania specific antibodies as follows: with 1:400 titer 16 cases (1.02%), with 1:800 titer 20 cases (1.27%), with 1:1600 titer 16 cases (1.02%) whereas only one subject (0.06%) showed titers of ≥ 1:3200. There was no significant association between VL seropositivity and gender, age group and occupation. Binary logistic regression showed that rural areas was 0.44 times at higher risk of infection than urban areas (OR= 0.44; %95 CI= 0.25- 0.78). Although the seroprevalence of VL is relatively low in Qom Province, yet due to the importance of the disease, the surveillance system should be monitored by health authorities.

Serological Survey and Associated Risk Factors of Visceral Leish-maniasis in Qom Province, Central Iran

PubMed Central

RAKHSHANPOUR, Arash; MOHEBALI, Mehdi; AKHONDI, Behnaz; RAHIMI, Mohammad Taghi; ROKNI, Mohammad Bagher

2014-01-01

Abstract Background Visceral leishmaniasis (VL) or kala-azar is considered as a parasitic disease caused by the species of Leishmania donovani complex which is intracellular parasites. This systemic disease is endemic in some parts of provinc-es of Iran. The aim of this study was to determine the seroprevalence of VL in Qom Province, central Iran using di-rect agglutination test (DAT). Methods Overall, 1564 serum samples (800 males and 764 females) were collected from selected subjects by random-ized cluster sampling in 2011-2012. Sera were tested and analyzed by DAT. Before sampling; a questionnaire was filled out for each case. Data were analyzed using Chi-square test and multivariate logistic regression for risk factors analysis. Results Of 1564 individuals, 53 cases (3.38%) showed Leishmania specific antibodies as follows: with 1:400 titer 16 cases (1.02%), with 1:800 titer 20 cases (1.27%), with 1:1600 titer 16 cases (1.02%) whereas only one subject (0.06%) showed titers of ≥ 1:3200. There was no significant association between VL seropositivity and gender, age group and occupation. Binary logistic regression showed that rural areas was 0.44 times at higher risk of infection than urban areas (OR= 0.44; %95 CI= 0.25- 0.78). Conclusion Although the seroprevalence of VL is relatively low in Qom Province, yet due to the importance of the disease, the surveillance system should be monitored by health authorities. PMID:26060679

Education, Employment, Income, and Marital Status Among Adults Diagnosed With Inflammatory Bowel Diseases During Childhood or Adolescence.

PubMed

El-Matary, Wael; Dufault, Brenden; Moroz, Stan P; Schellenberg, Jeannine; Bernstein, Charles N

2017-04-01

We aimed to assess levels of education attained, employment, and marital status of adults diagnosed with inflammatory bowel diseases (IBD) during childhood or adolescence, compared with healthy individuals in Canada. We performed a cross-sectional study of adults diagnosed with IBD in childhood or adolescence at Children's Hospital in Winnipeg, Manitoba from January 1978 through December 2007. Participants (n = 112) answered a semi-structured questionnaire on educational achievements, employment, and marital status. Patients were matched for age and sex with random healthy individuals from the 2012 Canadian Community Health Survey (controls, 5 per patient). Conditional binary logistic regression and random-effects ordinal logistic regression models were used for analysis. Patients were followed for a mean duration of 14.3 years (range, 3.1-34.5 years). Persons with IBD were more likely to earn more money per annum and attain a post-secondary school degree or receive a diploma than controls (odds ratio, 1.72; 95% confidence interval, 1.13-2.60; P < .01 and odds ratio, 2.73; 95% confidence interval, 1.48-5.04; P < .01, respectively). There was no significant difference between patients and controls in employment or marital status. Adults diagnosed with IBD during childhood seem to achieve higher education levels than individuals without IBD. This observation should provide reassurance to children with IBD and their parents. ClinicalTrials.gov number: NCT02152241. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Potentially Modifiable Factors Associated With Physical Activity in Individuals With Multiple Sclerosis.

PubMed

Reider, Nadia; Salter, Amber R; Cutter, Gary R; Tyry, Tuula; Marrie, Ruth Ann

2017-04-01

Physical activity levels among persons with multiple sclerosis (MS) are worryingly low. We aimed to identify the factors associated with physical activity for people with MS, with an emphasis on factors that have not been studied previously (bladder and hand dysfunction) and are potentially modifiable. This study was a secondary analysis of data collected in the spring of 2012 during the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry. NARCOMS participants were surveyed regarding smoking using questions from the Behavioral Risk Factor Surveillance Survey; disability using the Patient Determined Disease Steps; fatigue, cognition, spasticity, sensory, bladder, vision and hand function using self-reported Performance Scales; health literacy using the Medical Term Recognition Test; and physical activity using questions from the Health Information National Trends Survey. We used a forward binary logistic regression to develop a predictive model in which physical activity was the outcome variable. Of 8,755 respondents, 1,707 (19.5%) were classified as active and 7,068 (80.5%) as inactive. In logistic regression, being a current smoker, moderate or severe level of disability, depression, fatigue, hand, or bladder dysfunction and minimal to mild spasticity were associated with lower odds of meeting physical activity guidelines. MS type was not linked to activity level. Several modifiable clinical and lifestyle factors influenced physical activity in MS. Prospective studies are needed to evaluate whether modification of these factors can increase physical activity participation in persons with MS. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Neighborhood Social Cohesion and Sleep Outcomes in the Native Hawaiian and Pacific Islander National Health Interview Survey.

PubMed

Young, Marielle C; Gerber, Monica W; Ash, Tayla; Horan, Christine M; Taveras, Elsie M

2018-05-16

Native Hawaiians and Pacific Islanders (NHPIs) have the lowest attainment of healthy sleep duration among all racial and ethnic groups in the United States. We examined associations of neighborhood social cohesion with sleep duration and quality. Cross-sectional analysis of 2,464 adults in the NHPI National Health Interview Survey (2014). Neighborhood social cohesion was categorized as a continuous and categorical variable into low (<12), medium (12-14) and high (>15) according to tertiles of the distribution of responses. We used multinomial logistic regression to examine the adjusted odds ratio of short and long sleep duration relative to intermediate sleep duration. We used binary logistic regression for dichotomous sleep quality outcomes. Sleep outcomes were modeled as categorical variables. 40% of the cohort reported short (<7 hours) sleep duration and only 4% reported long (>9 hours) duration. Mean (SE, range) social cohesion score was 12.4 units (0.11, 4-16) and 23% reported low social cohesion. In multivariable models, each 1 SD decrease in neighborhood social cohesion score was associated with higher odds of short sleep duration (OR: 1.14, 95% CI: 1.02, 1.29). Additionally, low social cohesion was associated with increased odds of short sleep duration (OR: 1.53, 95% CI: 1.10, 2.13). No associations between neighborhood social cohesion and having trouble falling or staying asleep and feeling well rested were found. Low neighborhood social cohesion is associated with short sleep duration in NHPIs.

Self-Reported Dental Fear among Dental Students and Their Patients

PubMed Central

Serra-Negra, Junia; Paiva, Saul M.; Oliveira, Mauricio; Ferreira, Efigenia; Freire-Maia, Fernanda; Pordeus, Isabela

2011-01-01

The aim of the present study was to compare self-reported dental fear among dental students and patients at a School of Dentistry in Belo Horizonte, Brazil. Eighty students ranging in age from 20 to 29 years and 80 patients ranging in age from 18 to 65 years participated in the study. A self-administered pre-tested questionnaire consisting of 13 items was used for data acquisition. The city of Belo Horizonte Social Vulnerability Index (SVI) was employed for socioeconomic classification. The chi-square test and binary and multinomial logistic regression were employed in the statistical analysis, with the significance level set at 0.05. The majority of dental students (76.5%) sought the dentist for the first time for a routine exam, while patients (77.3%) mostly sought a dentist for the treatment of dental pain. Dental fear was more prevalent among the patients (72.5%) than the students (27.5%). A total of 47.1% of the students and 52.9% of the patients reported having had negative dental experiences in childhood. The logistic model revealed an association between dental fear and a pain-related experience (OR: 1.8; 95%CI: 1.3–2.6). Patients were more prone to dental fear (OR: 2.2; 95%CI: 1.0–5.0). Although at different percentages, both students and patients experienced dental fear. Current patient with previous experience of dental pain had more dental fear. PMID:22470277

Bayesian inference for joint modelling of longitudinal continuous, binary and ordinal events.

PubMed

Li, Qiuju; Pan, Jianxin; Belcher, John

2016-12-01

In medical studies, repeated measurements of continuous, binary and ordinal outcomes are routinely collected from the same patient. Instead of modelling each outcome separately, in this study we propose to jointly model the trivariate longitudinal responses, so as to take account of the inherent association between the different outcomes and thus improve statistical inferences. This work is motivated by a large cohort study in the North West of England, involving trivariate responses from each patient: Body Mass Index, Depression (Yes/No) ascertained with cut-off score not less than 8 at the Hospital Anxiety and Depression Scale, and Pain Interference generated from the Medical Outcomes Study 36-item short-form health survey with values returned on an ordinal scale 1-5. There are some well-established methods for combined continuous and binary, or even continuous and ordinal responses, but little work was done on the joint analysis of continuous, binary and ordinal responses. We propose conditional joint random-effects models, which take into account the inherent association between the continuous, binary and ordinal outcomes. Bayesian analysis methods are used to make statistical inferences. Simulation studies show that, by jointly modelling the trivariate outcomes, standard deviations of the estimates of parameters in the models are smaller and much more stable, leading to more efficient parameter estimates and reliable statistical inferences. In the real data analysis, the proposed joint analysis yields a much smaller deviance information criterion value than the separate analysis, and shows other good statistical properties too. © The Author(s) 2014.

Spectroscopic observations of V443 Herculis - A symbiotic binary with a low mass white dwarf

NASA Technical Reports Server (NTRS)

Dobrzycka, Danuta; Kenyon, Scott J.; Mikolajewska, Joanna

1993-01-01

We present an analysis of new and existing photometric and spectroscopic observations of the symbiotic binary V443 Herculis. This binary system consists of a normal M5 giant and a hot compact star. These two objects have comparable luminosities: about 1500 solar for the M5 giant and about 1000 solar for the compact star. We identify three nebular regions in this binary: a small, highly ionized volume surrounding the hot component, a modestly ionized shell close to the red giant photosphere, and a less dense region of intermediate ionization encompassing both binary components. The system parameters for V443 Her suggest the hot component currently declines from a symbiotic nova eruption.

Mal-Xtract: Hidden Code Extraction using Memory Analysis

NASA Astrophysics Data System (ADS)

Lim, Charles; Syailendra Kotualubun, Yohanes; Suryadi; Ramli, Kalamullah

2017-01-01

Software packer has been used effectively to hide the original code inside a binary executable, making it more difficult for existing signature based anti malware software to detect malicious code inside the executable. A new method of written and rewritten memory section is introduced to to detect the exact end time of unpacking routine and extract original code from packed binary executable using Memory Analysis running in an software emulated environment. Our experiment results show that at least 97% of the original code from the various binary executable packed with different software packers could be extracted. The proposed method has also been successfully extracted hidden code from recent malware family samples.

DANCING IN THE DARK: NEW BROWN DWARF BINARIES FROM KERNEL PHASE INTERFEROMETRY

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

Pope, Benjamin; Tuthill, Peter; Martinache, Frantz, E-mail: bjsp@physics.usyd.edu.au, E-mail: p.tuthill@physics.usyd.edu.au, E-mail: frantz@naoj.org

2013-04-20

This paper revisits a sample of ultracool dwarfs in the solar neighborhood previously observed with the Hubble Space Telescope's NICMOS NIC1 instrument. We have applied a novel high angular resolution data analysis technique based on the extraction and fitting of kernel phases to archival data. This was found to deliver a dramatic improvement over earlier analysis methods, permitting a search for companions down to projected separations of {approx}1 AU on NIC1 snapshot images. We reveal five new close binary candidates and present revised astrometry on previously known binaries, all of which were recovered with the technique. The new candidate binariesmore » have sufficiently close separation to determine dynamical masses in a short-term observing campaign. We also present four marginal detections of objects which may be very close binaries or high-contrast companions. Including only confident detections within 19 pc, we report a binary fraction of at least #Greek Lunate Epsilon Symbol#{sub b} = 17.2{sub -3.7}{sup +5.7}%. The results reported here provide new insights into the population of nearby ultracool binaries, while also offering an incisive case study of the benefits conferred by the kernel phase approach in the recovery of companions within a few resolution elements of the point-spread function core.« less

Dielectric and spectroscopic study of binary mixture of Acrylonitrile with Chlorobenzene

NASA Astrophysics Data System (ADS)

Deshmukh, Snehal D.; Pattebahadur, K. L.; Mohod, A. G.; Undre, P. B.; Patil, S. S.; Khirade, P. W.

2018-05-01

In this paper, study of binary mixture of Acrylonitrile (ACN) with Chlorobenzene (CBZ) has been carried out at eleven concentrations at room temperature. The determined Dielectric Constant (ɛ0) Density (ρ) and Refractive index (nD) values of binary mixture are used to calculate the excess properties of mixture over the entire composition range and fitted to the Redlich-Kister equation. From the above parameters, intermolecular interaction and dynamics of molecules of binary mixture at molecular level are discussed. The Conformational analysis of the intermolecular interaction between Acrylonitrile and Chlorobenzene is supported by the FTIR spectra.

A unifying framework for marginalized random intercept models of correlated binary outcomes

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian M.

2013-01-01

We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood-based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized random intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts. PMID:25342871

Analytic gravitational waveforms for generic precessing compact binaries

NASA Astrophysics Data System (ADS)

Chatziioannou, Katerina; Klein, Antoine; Cornish, Neil; Yunes, Nicolas

2017-01-01

Gravitational waves from compact binaries are subject to amplitude and phase modulations arising from interactions between the angular momenta of the system. Failure to account for such spin-precession effects in gravitational wave data analysis could hinder detection and completely ruin parameter estimation. In this talk I will describe the construction of closed-form, frequency-domain waveforms for fully-precessing, quasi-circular binary inspirals. The resulting waveforms can model spinning binaries of arbitrary spin magnitudes, spin orientations, and masses during the inspiral phase. I will also describe ongoing efforts to extend these inspiral waveforms to the merger and ringdown phases.

Demand Analysis of Logistics Information Matching Platform: A Survey from Highway Freight Market in Zhejiang Province

NASA Astrophysics Data System (ADS)

Chen, Daqiang; Shen, Xiahong; Tong, Bing; Zhu, Xiaoxiao; Feng, Tao

With the increasing competition in logistics industry and promotion of lower logistics costs requirements, the construction of logistics information matching platform for highway transportation plays an important role, and the accuracy of platform design is the key to successful operation or not. Based on survey results of logistics service providers, customers and regulation authorities to access to information and in-depth information demand analysis of logistics information matching platform for highway transportation in Zhejiang province, a survey analysis for framework of logistics information matching platform for highway transportation is provided.

Randomizing world trade. II. A weighted network analysis

NASA Astrophysics Data System (ADS)

Squartini, Tiziano; Fagiolo, Giorgio; Garlaschelli, Diego

2011-10-01

Based on the misleading expectation that weighted network properties always offer a more complete description than purely topological ones, current economic models of the International Trade Network (ITN) generally aim at explaining local weighted properties, not local binary ones. Here we complement our analysis of the binary projections of the ITN by considering its weighted representations. We show that, unlike the binary case, all possible weighted representations of the ITN (directed and undirected, aggregated and disaggregated) cannot be traced back to local country-specific properties, which are therefore of limited informativeness. Our two papers show that traditional macroeconomic approaches systematically fail to capture the key properties of the ITN. In the binary case, they do not focus on the degree sequence and hence cannot characterize or replicate higher-order properties. In the weighted case, they generally focus on the strength sequence, but the knowledge of the latter is not enough in order to understand or reproduce indirect effects.

Chemical composition and binary mixture of human urinary stones using FT-Raman spectroscopy method.

PubMed

Selvaraju, R; Raja, A; Thiruppathi, G

2013-10-01

In the present study the human urinary stones were observed in their different chemical compositions of calcium oxalate monohydrate, calcium oxalate dihydrate, calcium phosphate, struvite (magnesium ammonium phosphate), uric acid, cystine, oxammite (ammonium oxalate monohydrate), natroxalate (sodium oxalate), glushinkite (magnesium oxalate dihydrate) and moolooite (copper oxalate) were analyzed using Fourier Transform-Raman (FT-Raman) spectroscopy. For the quantitative analysis, various human urinary stone samples are used for ratios calculation of binary mixtures compositions such as COM/COD, HAP/COD, HAP/COD, Uric acid/COM, uric acid/COD and uric acid/HAP. The calibration curve is used for further analysis of binary mixture of human urinary stones. For the binary mixture calculation the various intensities bands at 1462 cm(-1) (I(COM)), 1473 cm(-1) (I(COD)), 961 cm(-1) (I(HAP)) and 1282 cm(-1) (I(UA)) were used. Copyright © 2013 Elsevier B.V. All rights reserved.

OGLE-2016-BLG-1003: First Resolved Caustic-crossing Binary-source Event Discovered by Second-generation Microlensing Surveys

NASA Astrophysics Data System (ADS)

Jung, Y. K.; Udalski, A.; Bond, I. A.; Yee, J. C.; Gould, A.; Han, C.; Albrow, M. D.; Lee, C.-U.; Kim, S.-L.; Hwang, K.-H.; Chung, S.-J.; Ryu, Y.-H.; Shin, I.-G.; Zhu, W.; Cha, S.-M.; Kim, D.-J.; Lee, Y.; Park, B.-G.; Kim, H.-W.; Pogge, R. W.; KMTNet Collaboration; Skowron, J.; Szymański, M. K.; Poleski, R.; Mróz, P.; Kozłowski, S.; Pietrukowicz, P.; Soszyński, I.; Ulaczyk, K.; Pawlak, M.; OGLE Collaboration; Abe, F.; Bennett, D. P.; Barry, R.; Sumi, T.; Asakura, Y.; Bhattacharya, A.; Donachie, M.; Fukui, A.; Hirao, Y.; Itow, Y.; Koshimoto, N.; Li, M. C. A.; Ling, C. H.; Masuda, K.; Matsubara, Y.; Muraki, Y.; Nagakane, M.; Rattenbury, N. J.; Evans, P.; Sharan, A.; Sullivan, D. J.; Suzuki, D.; Tristram, P. J.; Yamada, T.; Yamada, T.; Yonehara, A.; MOA Collaboration

2017-06-01

We report the analysis of the first resolved caustic-crossing binary-source microlensing event OGLE-2016-BLG-1003. The event is densely covered by round-the-clock observations of three surveys. The light curve is characterized by two nested caustic-crossing features, which is unusual for typical caustic-crossing perturbations. From the modeling of the light curve, we find that the anomaly is produced by a binary source passing over a caustic formed by a binary lens. The result proves the importance of high-cadence and continuous observations, and the capability of second-generation microlensing experiments to identify such complex perturbations that are previously unknown. However, the result also raises the issues of the limitations of current analysis techniques for understanding lens systems beyond two masses and of determining the appropriate multiband observing strategy of survey experiments.

Observations, Analysis, and Spectroscopic Classification of HO Piscium: A Bright Shallow-Contact Binary with G- and M-Type Components

NASA Astrophysics Data System (ADS)

Samec, Ronald G.; Smith, Paul M.; Robb, Russell; Faulkner, Danny R.; Van Hamme, W.

2012-07-01

We present a spectrum and a photometric analysis of the newly discovered, high-amplitude, solar-type, eclipsing binary HO Piscium. A spectroscopic identification, a period study, q-search, and a simultaneous UBVRc Ic light-curve solution are presented. The spectra and our photometric solution indicate that HO Psc is a W-type W UMa shallow-contact (fill-out ˜8%) binary system. The primary component has a G6V spectral type with an apparently precontact spectral type of M2V for the secondary component. The small fill-out indicates that the system has not yet achieved thermal contact and thus has recently come into physical contact. This may mean that this solar-type binary system has not attained its ˜0.4 mass ratio via a long period of magnetic braking, as would normally be assumed.

Measuring Parameters of Massive Black Hole Binaries with Partially-Aligned Spins

NASA Technical Reports Server (NTRS)

Lang, Ryan N.; Hughes, Scott A.; Cornish, Neil J.

2010-01-01

It is important to understand how well the gravitational-wave observatory LISA can measure parameters of massive black hole binaries. It has been shown that including spin precession in the waveform breaks degeneracies and produces smaller expected parameter errors than a simpler, precession-free analysis. However, recent work has shown that gas in binaries can partially align the spins with the orbital angular momentum, thus reducing the precession effect. We show how this degrades the earlier results, producing more pessimistic errors in gaseous mergers. However, we then add higher harmonics to the signal model; these also break degeneracies, but they are not affected by the presence of gas. The harmonics often restore the errors in partially-aligned binaries to the same as, or better than/ those that are obtained for fully precessing binaries with no harmonics. Finally, we investigate what LISA measurements of spin alignment can tell us about the nature of gas around a binary,

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

ERIC Educational Resources Information Center

Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

Outcome-based anatomic criteria for defining the hostile aortic neck.

PubMed

Jordan, William D; Ouriel, Kenneth; Mehta, Manish; Varnagy, David; Moore, William M; Arko, Frank R; Joye, James; de Vries, Jean-Paul P M

2015-06-01

There is abundant evidence linking hostile proximal aortic neck anatomy to poor outcome after endovascular aortic aneurysm repair (EVAR), yet the definition of hostile anatomy varies from study to study. This current analysis was undertaken to identify anatomic criteria that are most predictive of success or failure at the aortic neck after EVAR. The study group comprised 221 patients in the Aneurysm Treatment using the Heli-FX Aortic Securement System Global Registry (ANCHOR) clinical trial, a population enriched with patients with challenging aortic neck anatomy and failure of sealing. Imaging protocols were not protocol specified but were performed according to the institution's standard of care. Core laboratory analysis assessed the three-dimensional centerline-reformatted computed tomography scans. Failure at the aortic neck was defined by type Ia endoleak occurring at the time of the initial endograft implantation or during follow-up. Receiver operating characteristic curve analysis was used to assess the value of each anatomic measure in the classification of aortic neck success and failure and to identify optimal thresholds of discrimination. Binary logistic regression was performed after excluding highly intercorrelated variables, creating a final model with significant predictors of outcome after EVAR. Among the 221 patients, 121 (54.8%) remained free of type Ia endoleak and 100 (45.2%) did not. Type Ia endoleaks presented immediately after endograft deployment in 58 (58.0%) or during follow-up in 42 (42.0%). Receiver operating characteristic curve analysis identified 12 variables where the classification of patients with type Ia endoleak was significantly more accurate than chance alone. Increased aortic neck diameter at the lowest renal artery (P = .013) and at 5 mm (P = .008), 10 mm (P = .008), and 15 mm (P = .010) distally; aneurysm sac diameter (P = .001), common iliac artery diameters (right, P = .012; left, P = .032), and a conical (P = .049) neck configuration were predictive of endoleak. By contrast, increased aortic neck length (P = .050), a funnel-shaped aortic neck (P = .036), and neck mural thrombus content, as measured by average thickness (P = .044) or degrees of circumferential coverage (P = .029), were protective against endoleak. Binary logistic regression identified three variables independently predictive of type Ia endoleak. Neck diameter at the lowest renal artery (P = .002, cutpoint 26 mm) and neck length (P = .017, cutpoint 17 mm) were associated with endoleak, whereas some mural neck thrombus content was protective (P = .001, cutpoint 11° of circumferential coverage). A limited number of independent anatomic variables are predictive of type Ia endoleak after EVAR, including aortic neck diameter and aortic neck length, whereas mural thrombus in the neck is protective. This study suggests that anatomic measures with identifiable threshold cutpoints should be considered when defining the hostile aortic neck and assessing the risk of complications after EVAR. Copyright © 2015 Society for Vascular Surgery. All rights reserved.

An analysis of respondent-driven sampling with injecting drug users in a high HIV prevalent state of India.

PubMed

Phukan, Sanjib Kumar; Medhi, Gajendra Kumar; Mahanta, Jagadish; Adhikary, Rajatashuvra; Thongamba, Gay; Paranjape, Ramesh S; Akoijam, Brogen S

2017-07-03

Personal networks are significant social spaces to spread of HIV or other blood-borne infections among hard-to-reach population, viz., injecting drug users, female sex workers, etc. Sharing of infected needles or syringes among drug users is one of the major routes of HIV transmission in Manipur, a high HIV prevalence state in India. This study was carried out to describe the network characteristics and recruitment patterns of injecting drug users and to assess the association of personal network with injecting risky behaviors in Manipur. A total of 821 injecting drug users were recruited into the study using respondent-driven sampling (RDS) from Bishnupur and Churachandpur districts of Manipur; data on demographic characteristics, HIV risk behaviors, and network size were collected from them. Transition probability matrices and homophily indices were used to describe the network characteristics, and recruitment patterns of injecting drug users. Univariate and multivariate binary logistic regression models were performed to analyze the association between the personal networks and sharing of needles or syringes. The average network size was similar in both the districts. Recruitment analysis indicates injecting drug users were mostly engaged in mixed age group setting for injecting practice. Ever married and new injectors showed lack of in-group ties. Younger injecting drug users had mainly recruited older injecting drug users from their personal network. In logistic regression analysis, higher personal network was found to be significantly associated with increased likelihood of injecting risky behaviors. Because of mixed personal network of new injectors and higher network density associated with HIV exposure, older injecting drug users may act as a link for HIV transmission or other blood-borne infections to new injectors and also to their sexual partners. The information from this study may be useful to understanding the network pattern of injecting drug users for enriching the HIV prevention in this region.

Comparison Between 64Cu-PSMA-617 PET/CT and 18F-Choline PET/CT Imaging in Early Diagnosis of Prostate Cancer Biochemical Recurrence.

PubMed

Cantiello, Francesco; Crocerossa, Fabio; Russo, Giorgio Ivan; Gangemi, Vincenzo; Ferro, Matteo; Vartolomei, Mihai Dorin; Lucarelli, Giuseppe; Mirabelli, Maria; Scafuro, Chiara; Ucciero, Giuseppe; De Cobelli, Ottavio; Morgia, Giuseppe; Damiano, Rocco; Cascini, Giuseppe Lucio

2018-06-04

To evaluate the diagnostic performance of 64 Cu-PSMA-617 positron emission tomography (PET) with computed tomography (CT) for restaging prostate cancer after biochemical recurrence (BCR) and to compare it with 18 F-choline PET/CT in a per-patient analysis. An observational study was performed of 43 patients with BCR after laparoscopic radical prostatectomy who underwent 64 Cu-PSMA-617 PET/CT and subsequently 18 F-choline PET/CT for restaging. The detection rates (DR) of 64 Cu-PSMA-617 PET/CT and of 18 F-choline PET/CT were calculated by standardized maximum uptake value (SUV max ) at 4 hours and SUV max at 1 hour as reference, respectively. Furthermore, univariate logistic regression analysis was carried out to identify independent predictive factors of positivity with 64 Cu-PSMA-617 PET/CT. An overall positivity with 64 Cu-PSMA-617 PET/CT was found in 32 patients (74.4%) versus 19 (44.2%) with 18 F-choline PET/CT. Specifically, after stratifying for prostate-specific antigen (PSA) values, we found a good performance of 64 Cu-PSMA-617 PET/CT at low PSA levels compared to 18 F-choline PET/CT, with a DR of 57.1% versus 14.3% for PSA 0.2-0.5 ng/mL (P = .031), and of 60% versus 30% with PSA 0.5-1 ng/mL. At univariate binary logistic regression analysis, PSA level was the only independent predictor of 64 Cu-PSMA-617 PET/CT positivity. No significant difference in terms of DR for both 64 Cu-PSMA-617 PET/CT and 18 F-choline PET/CT was found according to different Gleason score subgroups. In our study cohort, a better performance was observed for 64 Cu-PSMA-617 PET/CT compared to 18 F-choline PET/CT in restaging after BCR, especially in patients with low PSA values. Copyright © 2018 Elsevier Inc. All rights reserved.

Computation of elementary modes: a unifying framework and the new binary approach

PubMed Central

Gagneur, Julien; Klamt, Steffen

2004-01-01

Background Metabolic pathway analysis has been recognized as a central approach to the structural analysis of metabolic networks. The concept of elementary (flux) modes provides a rigorous formalism to describe and assess pathways and has proven to be valuable for many applications. However, computing elementary modes is a hard computational task. In recent years we assisted in a multiplication of algorithms dedicated to it. We require a summarizing point of view and a continued improvement of the current methods. Results We show that computing the set of elementary modes is equivalent to computing the set of extreme rays of a convex cone. This standard mathematical representation provides a unified framework that encompasses the most prominent algorithmic methods that compute elementary modes and allows a clear comparison between them. Taking lessons from this benchmark, we here introduce a new method, the binary approach, which computes the elementary modes as binary patterns of participating reactions from which the respective stoichiometric coefficients can be computed in a post-processing step. We implemented the binary approach in FluxAnalyzer 5.1, a software that is free for academics. The binary approach decreases the memory demand up to 96% without loss of speed giving the most efficient method available for computing elementary modes to date. Conclusions The equivalence between elementary modes and extreme ray computations offers opportunities for employing tools from polyhedral computation for metabolic pathway analysis. The new binary approach introduced herein was derived from this general theoretical framework and facilitates the computation of elementary modes in considerably larger networks. PMID:15527509

Two-dimensional PCA-based human gait identification

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

Low-mass Pre-He White Dwarf Stars in Kepler Eclipsing Binaries with Multi-periodic Pulsations

NASA Astrophysics Data System (ADS)

Zhang, X. B.; Fu, J. N.; Liu, N.; Luo, C. Q.; Ren, A. B.

2017-12-01

We report the discovery of two thermally bloated low-mass pre-He white dwarfs (WDs) in two eclipsing binaries, KIC 10989032 and KIC 8087799. Based on the Kepler long-cadence photometry, we determined comprehensive photometric solutions of the two binary systems. The light curve analysis reveals that KIC 10989032 is a partially eclipsed detached binary system containing a probable low-mass WD with the temperature of about 10,300 K. Having a WD with the temperature of about 13,300, KKIC 8087799 is typical of an EL CVn system. By utilizing radial velocity measurements available for the A-type primary star of KIC 10989032, the mass and radius of the WD component are determined to be 0.24+/- 0.02 {M}⊙ and 0.50+/- 0.01 {R}⊙ , respectively. The values of mass and radius of the WD in KIC 8087799 are estimated as 0.16 ± 0.02 M ⊙ and 0.21 ± 0.01 R ⊙, respectively, according to the effective temperature and mean density of the A-type star derived from the photometric solution. We therefore introduce KIC 10989032 and KIC 8087799 as the eleventh and twelfth dA+WD eclipsing binaries in the Kepler field. Moreover, both binaries display marked multi-periodic pulsations superimposed on binary effects. A preliminary frequency analysis is applied to the light residuals when subtracting the synthetic eclipsing light curves from the observations, revealing that the light pulsations of the two systems are both due to the δ Sct-type primaries. We hence classify KIC 10989032 and KIC 8087799 as two WD+δ Sct binaries.

Measuring Close Binary Stars with Speckle Interferometry

DTIC Science & Technology

2014-09-01

extra effort to be measured. One method of observing such binary star systems is to use adaptive optics to correct the atmospheric blur in real-time...simplicity, and with no loss in generalization, this analysis will be reduced to one dimension . From equation (4), it can be seen that the frequency (u...the binary pair are systematically too large , due to the displacement of the minima of the fringes by the atmospheric OTF, when left uncorrected

Kepler eclipsing binary stars. IV. Precise eclipse times for close binaries and identification of candidate three-body systems

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

Conroy, Kyle E.; Stassun, Keivan G.; Prša, Andrej

2014-02-01

We present a catalog of precise eclipse times and analysis of third-body signals among 1279 close binaries in the latest Kepler Eclipsing Binary Catalog. For these short-period binaries, Kepler's 30 minute exposure time causes significant smearing of light curves. In addition, common astrophysical phenomena such as chromospheric activity, as well as imperfections in the light curve detrending process, can create systematic artifacts that may produce fictitious signals in the eclipse timings. We present a method to measure precise eclipse times in the presence of distorted light curves, such as in contact and near-contact binaries which exhibit continuously changing light levelsmore » in and out of eclipse. We identify 236 systems for which we find a timing variation signal compatible with the presence of a third body. These are modeled for the light travel time effect and the basic properties of the third body are derived. This study complements J. A. Orosz et al. (in preparation), which focuses on eclipse timing variations of longer period binaries with flat out-of-eclipse regions. Together, these two papers provide comprehensive eclipse timings for all binaries in the Kepler Eclipsing Binary Catalog, as an ongoing resource freely accessible online to the community.« less

Retention of the rural allied health workforce in New South Wales: a comparison of public and private practitioners.

PubMed

Keane, Sheila; Lincoln, Michelle; Rolfe, Margaret; Smith, Tony

2013-01-27

Policy initiatives to improve retention of the rural health workforce have relied primarily on evidence for rural doctors, most of whom practice under a private business model. Much of the literature for rural allied health (AH) workforce focuses on the public sector. The AH professions are diverse, with mixed public, private or combined practice settings. This study explores sector differences in factors affecting retention of rural AH professionals. This study compared respondents from the 2008 Rural Allied Health Workforce (RAHW) survey recruiting all AH professionals in rural New South Wales. Comparisons between public (n = 833) and private (n = 756) groups were undertaken using Chi square analysis to measure association for demographics, job satisfaction and intention to leave. The final section of the RAHW survey comprised 33 questions relating to retention. A factor analysis was conducted for each cohort. Factor reliability was assessed and retained factors were included in a binary logistic regression analysis for each cohort predicting intention to leave. Six factors were identified: professional isolation, participation in community, clinical demand, taking time away from work, resources and 'specialist generalist' work. Factors differed slightly between groups. A seventh factor (management) was present only in the public cohort. Gender was not a significant predictor of intention to leave. Age group was the strongest predictor of intention to leave with younger and older groups being significantly more likely to leave than middle aged.In univariate logistic analysis (after adjusting for age group), the ability to get away from work did not predict intention to leave in either group. In multivariate analysis, high clinical demand predicted intention to leave in both the public (OR = 1.40, 95% CI = 1.08, 1.83) and private (OR = 1.61, 95% CI = 1.15, 2.25) cohorts. Professional isolation (OR = 1.39. 95% CI = 1.11, 1.75) and Participation in community (OR = 1.57, 95% CI = 1.13, 2.19) also contributed to the model in the public cohort. This paper demonstrates differences between those working in public versus private sectors and suggests that effectiveness of policy initiatives may be improved through better targeting.

THE EFFECT OF UNRESOLVED BINARIES ON GLOBULAR CLUSTER PROPER-MOTION DISPERSION PROFILES

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

Bianchini, P.; Norris, M. A.; Ven, G. van de

2016-03-20

High-precision kinematic studies of globular clusters (GCs) require an accurate knowledge of all possible sources of contamination. Among other sources, binary stars can introduce systematic biases in the kinematics. Using a set of Monte Carlo cluster simulations with different concentrations and binary fractions, we investigate the effect of unresolved binaries on proper-motion dispersion profiles, treating the simulations like Hubble Space Telescope proper-motion samples. Since GCs evolve toward a state of partial energy equipartition, more-massive stars lose energy and decrease their velocity dispersion. As a consequence, on average, binaries have a lower velocity dispersion, since they are more-massive kinematic tracers. Wemore » show that, in the case of clusters with high binary fractions (initial binary fractions of 50%) and high concentrations (i.e., closer to energy equipartition), unresolved binaries introduce a color-dependent bias in the velocity dispersion of main-sequence stars of the order of 0.1–0.3 km s{sup −1} (corresponding to 1%−6% of the velocity dispersion), with the reddest stars having a lower velocity dispersion, due to the higher fraction of contaminating binaries. This bias depends on the ability to distinguish binaries from single stars, on the details of the color–magnitude diagram and the photometric errors. We apply our analysis to the HSTPROMO data set of NGC 7078 (M15) and show that no effect ascribable to binaries is observed, consistent with the low binary fraction of the cluster. Our work indicates that binaries do not significantly bias proper-motion velocity-dispersion profiles, but should be taken into account in the error budget of kinematic analyses.« less

Nowcasting sunshine number using logistic modeling

NASA Astrophysics Data System (ADS)

Brabec, Marek; Badescu, Viorel; Paulescu, Marius

2013-04-01

In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127-136, 2002). Our statistical approach is based on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different frequencies and with a short discussion of technical problems that such a goal brings.

Space logistics simulation: Launch-on-time

NASA Technical Reports Server (NTRS)

Nii, Kendall M.

1990-01-01

During 1989-1990 the Center for Space Construction developed the Launch-On-Time (L-O-T) Model to help asses and improve the likelihood of successfully supporting space construction requiring multi-logistic delivery flights. The model chose a reference by which the L-O-T probability and improvements to L-O-T probability can be judged. The measure of improvement was chosen as the percent reduction in E(S(sub N)), the total expected amount of unscheduled 'hold' time. We have also previously developed an approach to determining the reduction in E(S(sub N)) by reducing some of the causes of unscheduled holds and increasing the speed at which the problems causing the holds may be 'fixed.' We provided a mathematical (binary linear programming) model for measuring the percent reduction in E(S(sub N)) given such improvements. In this presentation we shall exercise the model which was developed and draw some conclusions about the following: methods used, data available and needed, and make suggestions for areas of improvement in 'real world' application of the model.

Approximate Genealogies Under Genetic Hitchhiking

PubMed Central

Pfaffelhuber, P.; Haubold, B.; Wakolbinger, A.

2006-01-01

The rapid fixation of an advantageous allele leads to a reduction in linked neutral variation around the target of selection. The genealogy at a neutral locus in such a selective sweep can be simulated by first generating a random path of the advantageous allele's frequency and then a structured coalescent in this background. Usually the frequency path is approximated by a logistic growth curve. We discuss an alternative method that approximates the genealogy by a random binary splitting tree, a so-called Yule tree that does not require first constructing a frequency path. Compared to the coalescent in a logistic background, this method gives a slightly better approximation for identity by descent during the selective phase and a much better approximation for the number of lineages that stem from the founder of the selective sweep. In applications such as the approximation of the distribution of Tajima's D, the two approximation methods perform equally well. For relevant parameter ranges, the Yule approximation is faster. PMID:17182733

Investigation of intermolecular interaction of binary mixture of acrylonitrile with bromobenzene

NASA Astrophysics Data System (ADS)

Deshmukh, S. D.; Pattebahadur, K. L.; Mohod, A. G.; Patil, S. S.; Khirade, P. W.

2018-04-01

In this paper, study of binary mixture of Acrylonitrile (ACN)with Bromobenzene(BB) has been carried out at eleven concentrations at room temperature. The determined density(ρ) and refractive index (nD) values of binary mixture are used to calculate the excess properties of mixture over the entire composition range. The aforesaid parameters are used to calculate excess parameters and fitted to the Redlich-Kister equation to determine the bj coefficients. From the above parameters, intermolecular interaction and dynamics of molecules of binary mixture at molecular level are discussed. The Conformational analysis of the intermolecular interaction between Acrylonitrile and Bromobenzene is supported by the FTIR spectra.

Predicting the Risk of Breakthrough Urinary Tract Infections: Primary Vesicoureteral Reflux.

PubMed

Hidas, Guy; Billimek, John; Nam, Alexander; Soltani, Tandis; Kelly, Maryellen S; Selby, Blake; Dorgalli, Crystal; Wehbi, Elias; McAleer, Irene; McLorie, Gordon; Greenfield, Sheldon; Kaplan, Sherrie H; Khoury, Antoine E

2015-11-01

We constructed a risk prediction instrument stratifying patients with primary vesicoureteral reflux into groups according to their 2-year probability of breakthrough urinary tract infection. Demographic and clinical information was retrospectively collected in children diagnosed with primary vesicoureteral reflux and followed for 2 years. Bivariate and binary logistic regression analyses were performed to identify factors associated with breakthrough urinary tract infection. The final regression model was used to compute an estimation of the 2-year probability of breakthrough urinary tract infection for each subject. Accuracy of the binary classifier for breakthrough urinary tract infection was evaluated using receiver operator curve analysis. Three distinct risk groups were identified. The model was then validated in a prospective cohort. A total of 252 bivariate analyses showed that high grade (IV or V) vesicoureteral reflux (OR 9.4, 95% CI 3.8-23.5, p <0.001), presentation after urinary tract infection (OR 5.3, 95% CI 1.1-24.7, p = 0.034) and female gender (OR 2.6, 95% CI 0.097-7.11, p <0.054) were important risk factors for breakthrough urinary tract infection. Subgroup analysis revealed bladder and bowel dysfunction was a significant risk factor more pronounced in low grade (I to III) vesicoureteral reflux (OR 2.8, p = 0.018). The estimation model was applied for prospective validation, which demonstrated predicted vs actual 2-year breakthrough urinary tract infection rates of 19% vs 21%. Stratifying the patients into 3 risk groups based on parameters in the risk model showed 2-year risk for breakthrough urinary tract infection was 8.6%, 26.0% and 62.5% in the low, intermediate and high risk groups, respectively. This proposed risk stratification and probability model allows prediction of 2-year risk of patient breakthrough urinary tract infection to better inform parents of possible outcomes and treatment strategies. Copyright © 2015 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Predictive Risk Factors in the Development of Intraoperative Hyperkalemia in Adult Living Donor Liver Transplantation.

PubMed

Juang, S-E; Huang, C-E; Chen, C-L; Wang, C-H; Huang, C-J; Cheng, K-W; Wu, S-C; Shih, T-H; Yang, S-C; Wong, Z-W; Jawan, B; Lee, Y-E

2016-05-01

Hyperkalemia, defined as a serum potassium level higher than 5 mEq/L, is common in the liver transplantation setting. Severe hyperkalemia may induce fatal cardiac arrhythmias; therefore, it should be monitored and treated accordingly. The aim of the current retrospective study is to evaluate and indentify the predictive risk factors of hyperkalemia during living-donor liver transplantation (LDLT). Four hundred eighty-seven adult LDLT patients were included in the study. Intraoperative serum potassium levels were monitored at least five times during LDLT; patients with a potassium level higher than 5 mEq/L were included in group 1, and the others with normokalemia in group 2. Patients' categorical characteristics and intraoperative numeric variables with a P value <.1 were selected into a multiple binary logistic regression model. In multivariate analysis, a P value of <.05 is regarded as a risk factor in the development of hyperkalemia. Fifty-one of 487 (10.4%) patients had hyperkalemia with a serum potassium level higher than 5.0 mEq/L during LDLT. Predictive factors with P < .1 in univariate analysis (Table 1), such as anesthesia time, preoperative albumin level, Model for End-stage Liver Disease score, preoperative bilirubin level, amount of blood loss, red blood cell (RBC) and fresh frozen plasma transfused, 5% albumin administered, hemoglobin at the end of surgery, and the amount of furosemide used, were further analyzed by multivariate binary regression. Results show that the anesthesia time, preoperative serum albumin level, and RBC count are determinant risk factors in the development of the hyperkalemia in our LDLT serials. Prolonged anesthesia time, preoperative serum albumin level, and intraoperative RBC transfusion are three determinant factors in the development of intraoperative hyperkalemia, and close monitoring of serum potassium levels in patients with abovementioned risk factors are recommended. Copyright © 2016 Elsevier Inc. All rights reserved.

Association of Ghrelin Gene Polymorphisms and Serum Ghrelin Levels with the Risk of Hepatitis B Virus-Related Liver Diseases in a Chinese Population

PubMed Central

Rong, Chengzhi; Qin, Xue; Li, Shan

2015-01-01

Background The functions of ghrelin (GHRL) include anti-inflammatory effects, reduction of the fibrogenic response, protection of liver tissue, and regulation of cell proliferation. Genetic variations in the GHRL gene may play an important role in the development of chronic hepatitis B (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Therefore, we investigated whether GHRL gene polymorphisms and its serum levels are associated with hepatitis B virus (HBV)-related diseases risk in a Chinese population. Methods 176 patients with CHB, 106 patients with HBV-related LC, 151 patients with HBV-related HCC, and 167 healthy controls were recruited in the study. Genotyping of GHRL rs26311, rs27647, rs696217, and rs34911341 polymorphisms were determined with the polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) and DNA sequencing. The serum GHRL concentrations were determined using enzyme-linked immunosorbent assay (ELISA). Results Binary logistic regression analyses adjusting for gender and age revealed that a significant increased risk of LC was found in the GHRL rs26311 GC genotype and combined GC+CC genotypes when compared with the GG genotype (GC vs. GG: OR = 1.671, 95% CI = 1.013–2.757, P = 0.044; GC+CC vs. GG: OR = 1.674, 95% CI = 1.040–2.696, P = 0.034). In subgroup analysis by gender, binary logistic regression analyses adjusting for age showed that the GHRL rs26311 C allele and combined GC+CC genotypes were associated with a significantly increased risk to LC in males (C vs. G OR = 1.416, 95% CI = 1.017–1.972, P = 0.040; GC+CC vs. GG: OR = 1.729, 95% CI = 1.019–2.933, P = 0.042). In addition, we found significant decreased serum GHRL levels in LC patients compared with the healthy controls. However, there was no significant association of the GHRL rs26311 polymorphism with serum GHRL levels in LC patients. Conclusions These observations suggest that the GHRL rs26311 polymorphism is associated with an increased risk to HBV-related LC, especially in men. We also found an inverse association of serum GHRL levels with LC. PMID:26599409

Low-grade Glioma Surgery in Intraoperative Magnetic Resonance Imaging: Results of a Multicenter Retrospective Assessment of the German Study Group for Intraoperative Magnetic Resonance Imaging.

PubMed

Coburger, Jan; Merkel, Andreas; Scherer, Moritz; Schwartz, Felix; Gessler, Florian; Roder, Constantin; Pala, Andrej; König, Ralph; Bullinger, Lars; Nagel, Gabriele; Jungk, Christine; Bisdas, Sotirios; Nabavi, Arya; Ganslandt, Oliver; Seifert, Volker; Tatagiba, Marcos; Senft, Christian; Mehdorn, Maximilian; Unterberg, Andreas W; Rössler, Karl; Wirtz, Christian Rainer

2016-06-01

The ideal treatment strategy for low-grade gliomas (LGGs) is a controversial topic. Additionally, only smaller single-center series dealing with the concept of intraoperative magnetic resonance imaging (iMRI) have been published. To investigate determinants for patient outcome and progression-free-survival (PFS) after iMRI-guided surgery for LGGs in a multicenter retrospective study initiated by the German Study Group for Intraoperative Magnetic Resonance Imaging. A retrospective consecutive assessment of patients treated for LGGs (World Health Organization grade II) with iMRI-guided resection at 6 neurosurgical centers was performed. Eloquent location, extent of resection, first-line adjuvant treatment, neurophysiological monitoring, awake brain surgery, intraoperative ultrasound, and field-strength of iMRI were analyzed, as well as progression-free survival (PFS), new permanent neurological deficits, and complications. Multivariate binary logistic and Cox regression models were calculated to evaluate determinants of PFS, gross total resection (GTR), and adjuvant treatment. A total of 288 patients met the inclusion criteria. On multivariate analysis, GTR significantly increased PFS (hazard ratio, 0.44; P < .01), whereas "failed" GTR did not differ significantly from intended subtotal-resection. Combined radiochemotherapy as adjuvant therapy was a negative prognostic factor (hazard ratio: 2.84, P < .01). Field strength of iMRI was not associated with PFS. In the binary logistic regression model, use of high-field iMRI (odds ratio: 0.51, P < .01) was positively and eloquent location (odds ratio: 1.99, P < .01) was negatively associated with GTR. GTR was not associated with increased rates of new permanent neurological deficits. GTR was an independent positive prognostic factor for PFS in LGG surgery. Patients with accidentally left tumor remnants showed a similar prognosis compared with patients harboring only partially resectable tumors. Use of high-field iMRI was significantly associated with GTR. However, the field strength of iMRI did not affect PFS. EoR, extent of resectionFLAIR, fluid-attenuated inversion recoveryGTR, gross total resectionIDH1, isocitrate dehydrogenase 1iMRI, intraoperative magnetic resonance imagingLGG, low-grade gliomaMGMT, methylguanine-deoxyribonucleic acid methyltransferasenPND, new permanent neurological deficitOS, overall survivalPFS, progression-free survivalSTR, subtotal resectionWHO, World Health Organization.

Instability of a solidifying binary mixture

NASA Technical Reports Server (NTRS)

Antar, B. N.

1982-01-01

An analysis is performed on the stability of a solidifying binary mixture due to surface tension variation of the free liquid surface. The basic state solution is obtained numerically as a nonstationary function of time. Due to the time dependence of the basic state, the stability analysis is of the global type which utilizes a variational technique. Also due to the fact that the basic state is a complex function of both space and time, the stability analysis is performed through numerical means.

Affordable Care Act Qualified Health Plan Coverage: Association With Improved HIV Viral Suppression for AIDS Drug Assistance Program Clients in a Medicaid Nonexpansion State

PubMed Central

McManus, Kathleen A.; Rhodes, Anne; Bailey, Steven; Yerkes, Lauren; Engelhard, Carolyn L.; Ingersoll, Karen S.; Stukenborg, George J.; Dillingham, Rebecca

2016-01-01

Background. With the Patient Protection and Affordable Care Act, many state AIDS Drug Assistance Programs (ADAPs) shifted their healthcare delivery model from direct medication provision to purchasing qualified health plans (QHPs). The objective of this study was to characterize the demographic and healthcare delivery factors associated with Virginia ADAP clients' QHP enrollment and to assess the relationship between QHP coverage and human immunodeficiency virus (HIV) viral suppression. Methods. The cohort included persons living with HIV who were enrolled in the Virginia ADAP (n = 3933). Data were collected from 1 January 2013 through 31 December 2014. Multivariable binary logistic regression was conducted to assess for associations with QHP enrollment and between QHP coverage and viral load (VL) suppression. Results. In the cohort, 47.1% enrolled in QHPs, and enrollment varied significantly based on demographic and healthcare delivery factors. In multivariable binary logistic regression, controlling for time, age, sex, race/ethnicity, and region, factors significantly associated with achieving HIV viral suppression included QHP coverage (adjusted odds ratio, 1.346; 95% confidence interval, 1.041–1.740; P = .02), an initially undetectable VL (2.809; 2.174–3.636; P < .001), HIV rather than AIDS disease status (1.377; 1.049–1.808; P = .02), and HIV clinic (P < .001). Conclusions. QHP coverage was associated with viral suppression, an essential outcome for individuals and for public health. Promoting QHP coverage in clinics that provide care to persons living with HIV may offer a new opportunity to increase rates of viral suppression. PMID:27143661

Clinical utility of calf front hoof circumference and maternal intrapelvic area in predicting dystocia in 103 late gestation Holstein-Friesian heifers and cows.

PubMed

Hiew, Mark W H; Megahed, Ameer A; Townsend, Jonathan R; Singleton, Wayne L; Constable, Peter D

2016-02-01

The objective of this study was to determine the clinical utility of measuring calf front hoof circumference, maternal intrapelvic area, and selected morphometric values in predicting dystocia in dairy cattle. An observational study using a convenience sample of 103 late-gestation Holstein-Friesian heifers and cows was performed. Intrapelvic height and width of the dam were measured using a pelvimeter, and the intrapelvic area was calculated. Calf front hoof circumference and birth weight were also measured. Data were analyzed using Spearman's correlation coefficient (rs), Mann-Whitney U test, and binary or ordered logistic regression; P < 0.05 was significant. The calving difficulty score (1-5) was greater in heifers (median, 3.0) than in cows (median, 1.0). Median intrapelvic area immediately before parturition was smaller in heifers (268 cm(2)) than in cows (332 cm(2)), whereas front hoof circumference and birth weight of the calf were similar in both groups. The calving difficulty score was positively associated with calf birth weight in heifers (rs = 0.39) and cows (rs = 0.24). Binary logistic regression using both dam and calf data indicated that the ratio of front hoof circumference of the calf to the maternal intrapelvic area provided the best predictor of dystocia (calving difficulty score = 4 or 5), with sensitivity = 0.50 and specificity = 0.93 at the optimal cutpoint for the ratio (>0.068 cm/cm(2)). Determining the ratio of calf front hoof circumference to maternal intrapelvic area has clinical utility in predicting the calving difficulty score in Holstein-Friesian cattle. Copyright © 2016 Elsevier Inc. All rights reserved.

Using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) for Predicting Institutionalization of Patients With Dementia in Taiwan

PubMed Central

Huang, Shih-Wei; Chang, Kwang-Hwa; Escorpizo, Reuben; Hu, Chaur-Jong; Chi, Wen-Chou; Yen, Chia-Feng; Liao, Hua-Fang; Chiu, Wen-Ta; Liou, Tsan-Hon

2015-01-01

Abstract World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is an assessment tool and it has been applied for disability status assessment of Taiwanese dementia patients since July 2012. The aim of this study was to investigate the predicting accuracy of WHODAS 2.0 for institutionalization of dementia patients. Of these patients, 13,774 resided in a community and 4406 in a long-term care facility. Demographic data and WHODAS 2.0 standardized scores were analyzed using the Chi-square test and independent t test to compare patients with dementia in an institution with those in a community. The receiver operating characteristic (ROC) curve was applied to investigate accuracy in predicting institutionalization, and the optimal cutoff point was determined using the Youden index. Binary logistic regression was used to analyze variables to determine risk factors for the institutionalization of patients with dementia. WHODAS 2.0 scores in all domains were higher in patients with dementia in a long-term care facility than in those in a community (P < 0.01). The ROC curve showed moderate accuracy for all domains of WHODAS 2.0 (area under curve 0.6∼0.8). Binary logistic regression revealed that the male gender, severity of disease, and standardized WHODAS 2.0 scores surpassing the cutoff values were risk factors for the institutionalization of patients with dementia. Although the accuracy of WHODAS 2.0 in predicting institutionalization is not considerably high for patients with dementia, our study found that the WHODAS 2.0 scores, the male gender, education status, urbanization level, and severity of disease were risk factors for institutionalization in long-term care facilities. PMID:26632747

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F

2017-04-01

Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.

Frontal lobe function and behavioral changes in amyotrophic lateral sclerosis: a study from Southwest China.

PubMed

Wei, QianQian; Chen, XuePing; Zheng, ZhenZhen; Huang, Rui; Guo, XiaoYan; Cao, Bei; Zhao, Bi; Shang, Hui-Fang

2014-12-01

Despite growing interest, the frequency and characteristics of frontal lobe functional and behavioral deficits in Chinese people with amyotrophic lateral sclerosis (ALS), as well as their impact on the survival of ALS patients, remain unknown. The Chinese version of the frontal assessment battery (FAB) and frontal behavioral inventory (FBI) were used to evaluate 126 sporadic ALS patients and 50 healthy controls. The prevalence of frontal lobe dysfunction was 32.5%. The most notable impairment domain of the FAB was lexical fluency (30.7%). The binary logistic regression model revealed that an onset age older than 45 years (OR 5.976, P = 0.002) and a lower educational level (OR 0.858, P = 0.002) were potential determinants of an abnormal FAB. Based on the FBI score, 46.0% of patients showed varied degrees of frontal behavioral changes. The most common impaired neurobehavioral domains were irritability (25.4%), logopenia (20.6%) and apathy (19.0%). The binary logistic regression model revealed that the ALS Functional Rating Scale-Revised scale score (OR 0.127, P = 0.001) was a potential determinant of an abnormal FBI. Frontal functional impairment and the severity of frontal behavioral changes were not associated with the survival status or the progression of ALS by the cox proportional hazard model and multivariate regression analyses, respectively. Frontal lobe dysfunction and frontal behavioral changes are common in Chinese ALS patients. Frontal lobe dysfunction may be related to the onset age and educational level. The severity of frontal behavioral changes may be associated with the ALSFRS-R. However, the frontal functional impairment and the frontal behavioral changes do not worsen the progression or survival of ALS.

Exposure to Tobacco Advertising and Promotion among School Children Aged 13-15 in Vietnam - an Overview from GYTS 2014.

PubMed

Long, Tran Khanh; Son, Phung Xuan; Giang, Kim Bao; Hai, Phan Thi; Huyen, Doan Thi Thu; Khue, Luong Ngoc; Nga, Pham Thi Quynh; Lam, Nguyen Tuan; Minh, Hoang Van; Huong, Le Thi Thanh

2016-01-01

Evidence shows that tobacco advertising and promotion activities may increase tobacco consumption and usage, especially in youth. Despite the regulation on prohibiting advertisement of any tobacco product, tobacco advertisement and promotion activities are still common in Vietnam. This article presents current exposure to tobacco advertising and promotion (TAP) among school children aged 13 to 15 years in Vietnam in 2014 and potential influencing factors. Data from the Global Youth Tobacco Survey 2014 in Vietnam covering 3,430 school aged children were used. Both descriptive and analytical statistics were carried out with Stata 13 statistical software. Binary logistic regression was applied to explain the exposure to TAP among youth and examine relationships with individual factors. A significance level of p<0.05 and sampling weights were used in all of the computations. In the past 30 days, 48.6% of the students experienced exposure to at least 1 type of tobacco advertising or promotion. Wearing or otherwise using products related to tobacco was the most exposure TAP type reported by students (22.3%). The internet (22.1), points of sales (19.2) and social events (11.5) were three places that students aged 13-15 frequently were exposed to TAP. Binary logistic results showed that gender (female vs male) (OR = 0.61, 95%CI: 0.52 - 0.71), susceptibility to smoking (OR = 2.12, 95%CI: 1.53 - 2.92), closest friends' smoked (OR = 1.43, 95%CI: 1.2 - 1.7) and parents smoking status (OR = 2.83, 95%CI: 1.6 - 5.01) were significantly associated with TAP exposure among school-aged children. The research findings should contribute to effective implementation of measures for preventing and controlling tobacco use among students aged 13-15 in Viet Nam.

Contamination of RR Lyrae stars from Binary Evolution Pulsators

NASA Astrophysics Data System (ADS)

Karczmarek, Paulina; Pietrzyński, Grzegorz; Belczyński, Krzysztof; Stępień, Kazimierz; Wiktorowicz, Grzegorz; Iłkiewicz, Krystian

2016-06-01

Binary Evolution Pulsator (BEP) is an extremely low-mass member of a binary system, which pulsates as a result of a former mass transfer to its companion. BEP mimics RR Lyrae-type pulsations but has different internal structure and evolution history. We present possible evolution channels to produce BEPs, and evaluate the contamination value, i.e. how many objects classified as RR Lyrae stars can be undetected BEPs. In this analysis we use population synthesis code StarTrack.

Calculating Mass Diffusion in High-Pressure Binary Fluids

NASA Technical Reports Server (NTRS)

Bellan, Josette; Harstad, Kenneth

2004-01-01

A comprehensive mathematical model of mass diffusion has been developed for binary fluids at high pressures, including critical and supercritical pressures. Heretofore, diverse expressions, valid for limited parameter ranges, have been used to correlate high-pressure binary mass-diffusion-coefficient data. This model will likely be especially useful in the computational simulation and analysis of combustion phenomena in diesel engines, gas turbines, and liquid rocket engines, wherein mass diffusion at high pressure plays a major role.

LUT observations of the mass-transferring binary AI Dra

NASA Astrophysics Data System (ADS)

Liao, Wenping; Qian, Shengbang; Li, Linjia; Zhou, Xiao; Zhao, Ergang; Liu, Nianping

2016-06-01

Complete UV band light curve of the eclipsing binary AI Dra was observed with the Lunar-based Ultraviolet Telescope (LUT) in October 2014. It is very useful to adopt this continuous and uninterrupted light curve to determine physical and orbital parameters of the binary system. Photometric solutions of the spot model are obtained by using the W-D (Wilson and Devinney) method. It is confirmed that AI Dra is a semi-detached binary with secondary component filling its critical Roche lobe, which indicates that a mass transfer from the secondary component to the primary one should happen. Orbital period analysis based on all available eclipse times suggests a secular period increase and two cyclic variations. The secular period increase was interpreted by mass transfer from the secondary component to the primary one at a rate of 4.12 ×10^{-8}M_{⊙}/yr, which is in agreement with the photometric solutions. Two cyclic oscillations were due to light travel-time effect (LTTE) via the presence of two cool stellar companions in a near 2:1 mean-motion resonance. Both photometric solutions and orbital period analysis confirm that AI Dra is a mass-transferring binary, the massive primary is filling 69 % of its critical Roche lobe. After the primary evolves to fill the critical Roche lobe, the mass transfer will be reversed and the binary will evolve into a contact configuration.

Improving the analysis of composite endpoints in rare disease trials.

PubMed

McMenamin, Martina; Berglind, Anna; Wason, James M S

2018-05-22

Composite endpoints are recommended in rare diseases to increase power and/or to sufficiently capture complexity. Often, they are in the form of responder indices which contain a mixture of continuous and binary components. Analyses of these outcomes typically treat them as binary, thus only using the dichotomisations of continuous components. The augmented binary method offers a more efficient alternative and is therefore especially useful for rare diseases. Previous work has indicated the method may have poorer statistical properties when the sample size is small. Here we investigate small sample properties and implement small sample corrections. We re-sample from a previous trial with sample sizes varying from 30 to 80. We apply the standard binary and augmented binary methods and determine the power, type I error rate, coverage and average confidence interval width for each of the estimators. We implement Firth's adjustment for the binary component models and a small sample variance correction for the generalized estimating equations, applying the small sample adjusted methods to each sub-sample as before for comparison. For the log-odds treatment effect the power of the augmented binary method is 20-55% compared to 12-20% for the standard binary method. Both methods have approximately nominal type I error rates. The difference in response probabilities exhibit similar power but both unadjusted methods demonstrate type I error rates of 6-8%. The small sample corrected methods have approximately nominal type I error rates. On both scales, the reduction in average confidence interval width when using the adjusted augmented binary method is 17-18%. This is equivalent to requiring a 32% smaller sample size to achieve the same statistical power. The augmented binary method with small sample corrections provides a substantial improvement for rare disease trials using composite endpoints. We recommend the use of the method for the primary analysis in relevant rare disease trials. We emphasise that the method should be used alongside other efforts in improving the quality of evidence generated from rare disease trials rather than replace them.

Dancing in the Dark: New Brown Dwarf Binaries from Kernel Phase Interferometry

NASA Astrophysics Data System (ADS)

Pope, Benjamin; Martinache, Frantz; Tuthill, Peter

2013-04-01

This paper revisits a sample of ultracool dwarfs in the solar neighborhood previously observed with the Hubble Space Telescope's NICMOS NIC1 instrument. We have applied a novel high angular resolution data analysis technique based on the extraction and fitting of kernel phases to archival data. This was found to deliver a dramatic improvement over earlier analysis methods, permitting a search for companions down to projected separations of ~1 AU on NIC1 snapshot images. We reveal five new close binary candidates and present revised astrometry on previously known binaries, all of which were recovered with the technique. The new candidate binaries have sufficiently close separation to determine dynamical masses in a short-term observing campaign. We also present four marginal detections of objects which may be very close binaries or high-contrast companions. Including only confident detections within 19 pc, we report a binary fraction of at least \\epsilon _b = 17.2^{+5.7}_{-3.7} %. The results reported here provide new insights into the population of nearby ultracool binaries, while also offering an incisive case study of the benefits conferred by the kernel phase approach in the recovery of companions within a few resolution elements of the point-spread function core. Based on observations performed with the NASA/ESA Hubble Space Telescope. The Hubble observations are associated with proposal ID 10143 and 10879 and were obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

Organic–inorganic binary mixture matrix for comprehensive laser-desorption ionization mass spectrometric analysis and imaging of medium-size molecules including phospholipids, glycerolipids, and oligosaccharides

DOE PAGES

Feenstra, Adam D.; Ames Lab., Ames, IA; O'Neill, Kelly C.; ...

2016-10-13

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a widely adopted, versatile technique, especially in high-throughput analysis and imaging. However, matrix-dependent selectivity of analytes is often a severe limitation. In this work, a mixture of organic 2,5-dihydroxybenzoic acid and inorganic Fe 3O 4 nanoparticles is developed as a binary MALDI matrix to alleviate the well-known issue of triacylglycerol (TG) ion suppression by phosphatidylcholine (PC). In application to lipid standards and maize seed cross-sections, the binary matrix not only dramatically reduced the ion suppression of TG, but also efficiently desorbed and ionized a wide variety of lipids such as cationic PC, anionicmore » phosphatidylethanolamine (PE) and phosphatidylinositol (PI), and neutral digalactosyldiacylglycerol (DGDG). The binary matrix was also very efficient for large polysaccharides, which were not detected by either of the individual matrices. As a result, the usefulness of the binary matrix is demonstrated in MS imaging of maize seed sections, successfully visualizing diverse medium-size molecules and acquiring high-quality MS/MS spectra for these compounds.« less

The Binary Pulsar: Gravity Waves Exist.

ERIC Educational Resources Information Center

Will, Clifford

1987-01-01

Reviews the history of pulsars generally and the 1974 discovery of the binary pulsar by Joe Taylor and Russell Hulse specifically. Details the data collection and analysis used by Taylor and Hulse. Uses this discussion as support for Albert Einstein's theory of gravitational waves. (CW)

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C

2011-04-01

The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

Explaining Match Outcome During The Men’s Basketball Tournament at The Olympic Games

PubMed Central

Leicht, Anthony S.; Gómez, Miguel A.; Woods, Carl T.

2017-01-01

In preparation for the Olympics, there is a limited opportunity for coaches and athletes to interact regularly with team performance indicators providing important guidance to coaches for enhanced match success at the elite level. This study examined the relationship between match outcome and team performance indicators during men’s basketball tournaments at the Olympic Games. Twelve team performance indicators were collated from all men’s teams and matches during the basketball tournament of the 2004-2016 Olympic Games (n = 156). Linear and non-linear analyses examined the relationship between match outcome and team performance indicator characteristics; namely, binary logistic regression and a conditional interference (CI) classification tree. The most parsimonious logistic regression model retained ‘assists’, ‘defensive rebounds’, ‘field-goal percentage’, ‘fouls’, ‘fouls against’, ‘steals’ and ‘turnovers’ (delta AIC <0.01; Akaike weight = 0.28) with a classification accuracy of 85.5%. Conversely, four performance indicators were retained with the CI classification tree with an average classification accuracy of 81.4%. However, it was the combination of ‘field-goal percentage’ and ‘defensive rebounds’ that provided the greatest probability of winning (93.2%). Match outcome during the men’s basketball tournaments at the Olympic Games was identified by a unique combination of performance indicators. Despite the average model accuracy being marginally higher for the logistic regression analysis, the CI classification tree offered a greater practical utility for coaches through its resolution of non-linear phenomena to guide team success. Key points A unique combination of team performance indicators explained 93.2% of winning observations in men’s basketball at the Olympics. Monitoring of these team performance indicators may provide coaches with the capability to devise multiple game plans or strategies to enhance their likelihood of winning. Incorporation of machine learning techniques with team performance indicators may provide a valuable and strategic approach to explain patterns within multivariate datasets in sport science. PMID:29238245

An Astrometric Analysis of eta Carinae’s Eruptive History Using HST WF/PC2 and ACS Observations

DTIC Science & Technology

2007-07-11

Std Z39-18 to address the question of binarity. Based on an astrometric analysis of the data, binary reflex motion is detected in the primary and, by...Measurement Results 96 5.1 Primary Luminosity and Mass . . . . . . . . . . . . . . . . . . . . . . 96 5.2 Secondary Mass and Luminosity...Binary Models . . . . . . . . . . . 100 5.5 Primary –Secondary Distance . . . . . . . . . . . . . . . . . . . . . . . 102 5.6 Periastron passage

Correcting Velocity Dispersions of Dwarf Spheroidal Galaxies for Binary Orbital Motion

NASA Astrophysics Data System (ADS)

Minor, Quinn E.; Martinez, Greg; Bullock, James; Kaplinghat, Manoj; Trainor, Ryan

2010-10-01

We show that the measured velocity dispersions of dwarf spheroidal galaxies from about 4 to 10 km s-1 are unlikely to be inflated by more than 30% due to the orbital motion of binary stars and demonstrate that the intrinsic velocity dispersions can be determined to within a few percent accuracy using two-epoch observations with 1-2 yr as the optimal time interval. The crucial observable is the threshold fraction—the fraction of stars that show velocity changes larger than a given threshold between measurements. The threshold fraction is tightly correlated with the dispersion introduced by binaries, independent of the underlying binary fraction and distribution of orbital parameters. We outline a simple procedure to correct the velocity dispersion to within a few percent accuracy by using the threshold fraction and provide fitting functions for this method. We also develop a methodology for constraining properties of binary populations from both single- and two-epoch velocity measurements by including the binary velocity distribution in a Bayesian analysis.

Refining Stimulus Parameters in Assessing Infant Speech Perception Using Visual Reinforcement Infant Speech Discrimination: Sensation Level.

PubMed

Uhler, Kristin M; Baca, Rosalinda; Dudas, Emily; Fredrickson, Tammy

2015-01-01

Speech perception measures have long been considered an integral piece of the audiological assessment battery. Currently, a prelinguistic, standardized measure of speech perception is missing in the clinical assessment battery for infants and young toddlers. Such a measure would allow systematic assessment of speech perception abilities of infants as well as the potential to investigate the impact early identification of hearing loss and early fitting of amplification have on the auditory pathways. To investigate the impact of sensation level (SL) on the ability of infants with normal hearing (NH) to discriminate /a-i/ and /ba-da/ and to determine if performance on the two contrasts are significantly different in predicting the discrimination criterion. The design was based on a survival analysis model for event occurrence and a repeated measures logistic model for binary outcomes. The outcome for survival analysis was the minimum SL for criterion and the outcome for the logistic regression model was the presence/absence of achieving the criterion. Criterion achievement was designated when an infant's proportion correct score was >0.75 on the discrimination performance task. Twenty-two infants with NH sensitivity participated in this study. There were 9 males and 13 females, aged 6-14 mo. Testing took place over two to three sessions. The first session consisted of a hearing test, threshold assessment of the two speech sounds (/a/ and /i/), and if time and attention allowed, visual reinforcement infant speech discrimination (VRISD). The second session consisted of VRISD assessment for the two test contrasts (/a-i/ and /ba-da/). The presentation level started at 50 dBA. If the infant was unable to successfully achieve criterion (>0.75) at 50 dBA, the presentation level was increased to 70 dBA followed by 60 dBA. Data examination included an event analysis, which provided the probability of criterion distribution across SL. The second stage of the analysis was a repeated measures logistic regression where SL and contrast were used to predict the likelihood of speech discrimination criterion. Infants were able to reach criterion for the /a-i/ contrast at statistically lower SLs when compared to /ba-da/. There were six infants who never reached criterion for /ba-da/ and one never reached criterion for /a-i/. The conditional probability of not reaching criterion by 70 dB SL was 0% for /a-i/ and 21% for /ba-da/. The predictive logistic regression model showed that children were more likely to discriminate the /a-i/ even when controlling for SL. Nearly all normal-hearing infants can demonstrate discrimination criterion of a vowel contrast at 60 dB SL, while a level of ≥70 dB SL may be needed to allow all infants to demonstrate discrimination criterion of a difficult consonant contrast. American Academy of Audiology.

Influence of protein size on surface-enhanced Raman scattering (SERS) spectra in binary protein mixtures.

PubMed

Avci, Ertug; Culha, Mustafa

2014-01-01

The size-dependent interactions of eight blood proteins with silver nanoparticles (AgNPs) in their binary mixtures were investigated using surface-enhanced Raman scattering (SERS). Principal component analysis (PCA) was performed on the SERS spectra of each binary mixture, and the differentiation ability of the mixtures was tested. It was found that the effect of relative concentration change on the SERS spectra of the binary mixtures of small proteins could be detected using PCA. However, this change was not observed with the binary mixtures of large proteins. This study demonstrated that the relative interactions of the smaller proteins with an average size of 50 nm AgNPs smaller than the large proteins could be monitored, and this information can be used for the detection of proteins in protein mixtures.

Evidence for a planetary mass third body orbiting the binary star KIC 5095269

NASA Astrophysics Data System (ADS)

Getley, A. K.; Carter, B.; King, R.; O'Toole, S.

2017-07-01

In this paper, we report the evidence for a planetary mass body orbiting the close binary star KIC 5095269. This detection arose from a search for eclipse timing variations amongst the more than 2000 eclipsing binaries observed by Kepler. Light curve and periodic eclipse time variations have been analysed using systemic and a custom Binary Eclipse Timings code based on the Transit Analysis Package which indicates a 7.70 ± 0.08MJup object orbiting every 237.7 ± 0.1 d around a 1.2 M⊙ primary and a 0.51 M⊙ secondary in an 18.6 d orbit. A dynamical integration over 107 yr suggests a stable orbital configuration. Radial velocity observations are recommended to confirm the properties of the binary star components and the planetary mass of the companion.

Modeling the rate of HIV testing from repeated binary data amidst potential never-testers.

PubMed

Rice, John D; Johnson, Brent A; Strawderman, Robert L

2018-01-04

Many longitudinal studies with a binary outcome measure involve a fraction of subjects with a homogeneous response profile. In our motivating data set, a study on the rate of human immunodeficiency virus (HIV) self-testing in a population of men who have sex with men (MSM), a substantial proportion of the subjects did not self-test during the follow-up study. The observed data in this context consist of a binary sequence for each subject indicating whether or not that subject experienced any events between consecutive observation time points, so subjects who never self-tested were observed to have a response vector consisting entirely of zeros. Conventional longitudinal analysis is not equipped to handle questions regarding the rate of events (as opposed to the odds, as in the classical logistic regression model). With the exception of discrete mixture models, such methods are also not equipped to handle settings in which there may exist a group of subjects for whom no events will ever occur, i.e. a so-called "never-responder" group. In this article, we model the observed data assuming that events occur according to some unobserved continuous-time stochastic process. In particular, we consider the underlying subject-specific processes to be Poisson conditional on some unobserved frailty, leading to a natural focus on modeling event rates. Specifically, we propose to use the power variance function (PVF) family of frailty distributions, which contains both the gamma and inverse Gaussian distributions as special cases and allows for the existence of a class of subjects having zero frailty. We generalize a computational algorithm developed for a log-gamma random intercept model (Conaway, 1990. A random effects model for binary data. Biometrics46, 317-328) to compute the exact marginal likelihood, which is then maximized to obtain estimates of model parameters. We conduct simulation studies, exploring the performance of the proposed method in comparison with competitors. Applying the PVF as well as a Gaussian random intercept model and a corresponding discrete mixture model to our motivating data set, we conclude that the group assigned to receive follow-up messages via SMS was self-testing at a significantly lower rate than the control group, but that there is no evidence to support the existence of a group of never-testers. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Near-Earth asteroid satellite spins under spin-orbit coupling

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

Naidu, Shantanu P.; Margot, Jean-Luc

We develop a fourth-order numerical integrator to simulate the coupled spin and orbital motions of two rigid bodies having arbitrary mass distributions under the influence of their mutual gravitational potential. We simulate the dynamics of components in well-characterized binary and triple near-Earth asteroid systems and use surface of section plots to map the possible spin configurations of the satellites. For asynchronous satellites, the analysis reveals large regions of phase space where the spin state of the satellite is chaotic. For synchronous satellites, we show that libration amplitudes can reach detectable values even for moderately elongated shapes. The presence of chaoticmore » regions in the phase space has important consequences for the evolution of binary asteroids. It may substantially increase spin synchronization timescales, explain the observed fraction of asychronous binaries, delay BYORP-type evolution, and extend the lifetime of binaries. The variations in spin rate due to large librations also affect the analysis and interpretation of light curve and radar observations.« less

Velocity Curve Analysis of Spectroscopic Binary Stars AI Phe, GM Dra, HD 93917 and V502 Oph by Nonlinear Regression

NASA Astrophysics Data System (ADS)

Karami, K.; Mohebi, R.

2007-08-01

We introduce a new method to derive the orbital parameters of spectroscopic binary stars by nonlinear least squares of (o-c). Using the measured radial velocity data of the four double lined spectroscopic binary systems, AI Phe, GM Dra, HD 93917 and V502 Oph, we derived both the orbital and combined spectroscopic elements of these systems. Our numerical results are in good agreement with the those obtained using the method of Lehmann-Filhé.

Dental enamel defects in Italian children with cystic fibrosis: an observational study.

PubMed

Ferrazzano, G F; Sangianantoni, G; Cantile, T; Amato, I; Orlando, S; Ingenito, A

2012-03-01

The relationship between cystic fibrosis (CF) and caries experience has already been explored, but relatively little information is available on dental enamel defects prevalence among children affected by cystic fibrosis. The aim of this study was to investigate this issue in deciduous and permanent teeth of children with CF resident in southern Italy. This cross sectional observational study was undertaken between October 2009 and March 2010. 88 CF patients and 101 healthy age-matched participated in this study. The prevalence of dental enamel defects was calculated using a modified Developmental Defects of Enamel (DDE) index. The comparison of dental enamel defects prevalence among groups was carried out using regression binary logistic analysis. In the CF subjects there was a higher prevalence (56%) of enamel defects in comparison to the healthy group (22%). The most prevalent enamel defect was hypoplasia with loss of enamel (23% of CF patients vs 1 1/2% of control group) in permanent teeth. This study confirms that children with cystic fibrosis are at increased risk of developing hypoplastic defects on their permanent teeth.

Excessive internet use in European adolescents: what determines differences in severity?

PubMed

Blinka, Lukas; Škařupová, Kateřina; Ševčíková, Anna; Wölfling, Klaus; Müller, Kai W; Dreier, Michael

2015-02-01

This study investigated the differences between non-excessive, moderately excessive, and highly excessive internet use among adolescents. These differences were explored in terms of personal characteristics, psychological difficulties, environmental factors, and manner of internet use. A representative sample was investigated, consisting of 18,709 adolescents aged 11-16 and their parents, from 25 European countries. Excessive internet use was measured using a five item scale covering following factors: salience, conflict, tolerance, withdrawal symptoms, and relapse and reinstatement. The main data analysis utilised multinomial and binary logistic regression models. The vast majority of respondents reported no signs of excessive internet use. Moderately excessive users (4.4%) reported higher emotional and behavioural difficulties, but also more sophisticated digital skills and a broader range of online activities. The highly excessive users (1.4%) differed from the non-excessive and moderately excessive users in their preference for online games and in having more difficulties with self-control. Adolescents who struggle with attention and self-control and who are inclined toward online gaming may be especially vulnerable to the otherwise uncommon phenomenon of excessive internet use.

Improving Consumer Satisfaction with Addiction Treatment: An Analysis of Alumni Preferences.

PubMed

Sanghani, Ruchi M; Moler, Alexander K

2015-01-01

Objective. The primary objective of this investigation is to determine which individual and aggregate factors of residential addiction treatment centers are most significant influencers of alumni satisfaction. Design. Survey targeted alumni of residential addiction treatment facilities. Alumni were queried through a survey, which utilized Likert-scale matrices and binary response options: 379 respondents met the completion threshold. Alumni rated amenities and individual and group counseling factors; additionally, respondents provided feedback on two satisfaction proxies: cost worthiness and future recommendations. Descriptive and relational analyses were conducted, with the latter utilizing logistic regression models. Results. Individual factors' scores of group counseling, and overall aggregate group counseling score, are most enthusiastically positive. Group counseling is also the most significant influencer of satisfaction. Other significant influencers of satisfaction are met expectations for individual counseling and psychiatric care offerings. Conclusions. While individual counseling and facility amenities should not be ignored, group counseling may be the most significant influencer of alumni satisfaction. Long-term outcomes are not single-faceted; however, treatment providers should be encouraged to invest in high-quality group counseling offerings in order to best satisfy, and thereby empower, clients.

An optimal ultrasonographic diagnostic test for early gout: A prospective controlled study

PubMed Central

Petraitis, Mykolas; Apanaviciene, Indre; Virviciute, Dalia; Baranauskaite, Asta

2017-01-01

Objective To identify the optimal sites for classification of early gout by ultrasonography. Methods Sixty patients with monosodium urate crystal-proven gout (25 with early gout [≤2-year symptom duration], 35 with late gout [>2-year symptom duration], and 36 normouricemic healthy controls) from one centre were prospectively evaluated. Standardized blinded ultrasound examination of 36 joints and the triceps and patellar tendons was performed to identify tophi and the double contour (DC) sign. Results Ultrasonographic sensitivity was lower in early than late gout. Binary logistic regression analysis showed that two ultrasonographic signs (tophi in the first metatarsophalangeal joint [odds ratio, 16.46] and the DC sign in the ankle [odds ratio, 25.18]) significantly contributed to the final model for early gout diagnosis (sensitivity and specificity of 84% and 81%, respectively). The inter-reader reliability kappa value for the DC sign and tophi was 0.712. Conclusions Four-joint investigation (both first metatarsophalangeal joints for tophi and both ankles for the DC sign) is feasible and reliable and could be proposed as a screening test for early ultrasonographic gout classification in daily practice. PMID:28617199

An optimal ultrasonographic diagnostic test for early gout: A prospective controlled study.

PubMed

Norkuviene, Eleonora; Petraitis, Mykolas; Apanaviciene, Indre; Virviciute, Dalia; Baranauskaite, Asta

2017-08-01

Objective To identify the optimal sites for classification of early gout by ultrasonography. Methods Sixty patients with monosodium urate crystal-proven gout (25 with early gout [≤2-year symptom duration], 35 with late gout [>2-year symptom duration], and 36 normouricemic healthy controls) from one centre were prospectively evaluated. Standardized blinded ultrasound examination of 36 joints and the triceps and patellar tendons was performed to identify tophi and the double contour (DC) sign. Results Ultrasonographic sensitivity was lower in early than late gout. Binary logistic regression analysis showed that two ultrasonographic signs (tophi in the first metatarsophalangeal joint [odds ratio, 16.46] and the DC sign in the ankle [odds ratio, 25.18]) significantly contributed to the final model for early gout diagnosis (sensitivity and specificity of 84% and 81%, respectively). The inter-reader reliability kappa value for the DC sign and tophi was 0.712. Conclusions Four-joint investigation (both first metatarsophalangeal joints for tophi and both ankles for the DC sign) is feasible and reliable and could be proposed as a screening test for early ultrasonographic gout classification in daily practice.

Gestational syphilis and stillbirth in Latin America and the Caribbean.

PubMed

Arnesen, Lauren; Martínez, Gerardo; Mainero, Luis; Serruya, Suzanne; Durán, Pablo

2015-03-01

To measure the association between gestational syphilis and stillbirth in Latin America and the Caribbean. In a retrospective study, data on stillbirth and gestational syphilis extracted from the Sistema Informático Perinatal database were analyzed for deliveries in 11 countries between January 1, 2009, and December 31, 2012. Potential confounders were examined, and binary logistic regression analysis was performed to assess the association between gestational syphilis and stillbirth. Among 368 151 deliveries, 3875 (1.1%) were by women with a positive syphilis test, and 1461 (0.4%) were stillbirths. Among the stillbirths, 29 (2.0%) were delivered by women with a positive syphilis test. After controlling for country, congenital anomalies, gestational age at labor, maternal age, and previous stillbirth, gestational syphilis was significantly associated with stillbirth (odds ratio 1.88, 95% confidence interval 1.25-2.83; P=0.002). Gestational syphilis contributes to stillbirth in Latin America and the Caribbean. Interventions targeting gestational syphilis are highly cost-effective and should be implemented across the region. Copyright © 2014 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

[Lifestyle and probabilty of dementia in the elderly].

PubMed

León-Ortiz, Pablo; Ruiz-Flores, Manuel Leonardo; Ramírez-Bermúdez, Jesús; Sosa-Ortiz, Ana Luisa

2013-01-01

there is evidence of a relationship between physical and cognitive activity and the development of dementia, although this hypothesis has not been tested in Mexican population. analyze the association between an increased participation in physical and cognitive activities and the probability of having dementia, using a Mexican open population sample. we made a cross sectional survey in open Mexican population of residents in urban and rural areas of 65 of age and older; we performed cognitive assessments to identify subjects with dementia, as well as questionnaires to assess the level of participation in physical and cognitive activities. We performed a binary logistic regression analysis to establish the association between participation and the probability of having dementia. we included 2003 subjects, 180 with diagnosis of dementia. Subjects with dementia were older, had less education and higher prevalence of some chronic diseases. The low participation in cognitive activities was associated with a higher probability of developing dementia. Patients with dementia had significantly lower scores on physical activity scales. this study supports the hypothesis of a relationship between low cognitive and physical activity and the presentation of dementia.

EFFECT OF RELIGIOUS BELIEFS ON SUBSTANCE USE AMONG SOUTH AFRICAN HIGH SCHOOL STUDENTS.

PubMed

Ghuman, S; Hoque, M E

2015-03-01

Substance use is a common problem among South African youth. We conducted this study to determine whether religious beliefs influenced substance use among South African youth. We conducted a cross sectional study of 704 students from five high schools in South Africa. We used a questionnaire to assess self reported substance use and religious beliefs among the study subjects. We used binary logistic regression analysis to evaluate the relationship between the subjects' religious beliefs and substance use. Thirty-six point six percent of students reported being very religious. More female students reported being very religious than male students (p = 0.039). Fifty-four percent of students had ever consumed alcohol. Comparing alcohol and drug use between religious and non-religious students, it was found that alcohol and drug use were more common among non-religious students (28.3%, 30.4%) than very religious students (8.4%, 11.5%) (p < 0.05). Those who considered themselves religious had lower odds of substance use. Religious beliefs had an influence on substance use among South African youth in our study.

Drawing Nomograms with R: applications to categorical outcome and survival data.

PubMed

Zhang, Zhongheng; Kattan, Michael W

2017-05-01

Outcome prediction is a major task in clinical medicine. The standard approach to this work is to collect a variety of predictors and build a model of appropriate type. The model is a mathematical equation that connects the outcome of interest with the predictors. A new patient with given clinical characteristics can be predicted for outcome with this model. However, the equation describing the relationship between predictors and outcome is often complex and the computation requires software for practical use. There is another method called nomogram which is a graphical calculating device allowing an approximate graphical computation of a mathematical function. In this article, we describe how to draw nomograms for various outcomes with nomogram() function. Binary outcome is fit by logistic regression model and the outcome of interest is the probability of the event of interest. Ordinal outcome variable is also discussed. Survival analysis can be fit with parametric model to fully describe the distributions of survival time. Statistics such as the median survival time, survival probability up to a specific time point are taken as the outcome of interest.

Associated factors with attention deficit hyperactivity disorder (ADHD): a case-control study.

PubMed

Malek, Ayyoub; Amiri, Shahrokh; Sadegfard, Majid; Abdi, Salman; Amini, Saeedeh

2012-09-01

The current study attempted to investigate factors associated with attention deficit hyperactivity disorder (ADHD) in children without co-morbidities. In this case-control study, 164 ADHD children who attended the Child and Adolescent Psychiatric Clinics of Tabriz University of Medical Sciences, Iran were compared with 166 normal children selected in a random-cluster method from primary and secondary schools. Clinical interviews based on DSM-IV-TR using K-SADS were used to diagnose ADHD cases and to select the control group. Participants were matched for age. We used chi-square and binary logistic regression for data analysis. Among the associated factors with ADHD were gender and maternal employment. Boys (OR 0.54; 95% confidence interval: 0.34 - 0.86) and those children with working mothers (OR 0.16: 95% confidence interval: 0.06 - 0.86) suffered more from ADHD. The birth season, family size, birth order, and parental kinship were not among risk factors for ADHD. The results of the study show that maternal employment and male gender are among the associated risk factors for ADHD.

Stimulus Modality and Smoking Behavior: Moderating Role of Implicit Attitudes.

PubMed

Ezeh, Valentine C; Mefoh, Philip

2015-07-20

This study investigated whether stimulus modality influences smoking behavior among smokers in South Eastern Nigeria and also whether implicit attitudes moderate the relationship between stimulus modality and smoking behavior. 60 undergraduate students of University of Nigeria, Nsukka were used. Participants were individually administered the IAT task as a measure of implicit attitude toward smoking and randomly assigned into either image condition that paired images of cigarette with aversive images of potential health consequences or text condition that paired images of cigarette with aversive texts of potential health consequences. A one- predictor and one-moderator binary logistic analysis indicates that stimulus modality significantly predicts smoking behavior (p = < .05) with those in the image condition choosing not to smoke with greater probability than the text condition. The interaction between stimulus modality and IAT scores was also significant (p = < .05). Specifically, the modality effect was larger for participants in the image group who held more negative implicit attitudes towards smoking. The finding shows the urgent need to introduce the use of aversive images of potential health consequences on cigarette packs in Nigeria.

Mental health of deaf and hard-of-hearing adolescents: what the students say.

PubMed

Brown, P Margaret; Cornes, Andrew

2015-01-01

This study investigated the mental health problems of 89 deaf and hard-of-hearing (DHH) adolescents in New South Wales, Tasmania, and Western Australia. Participants completed the written (for oral students) or signed version for competent Australian Sign Language (Auslan) users version of the Youth Self Report (YSR). Students were educated in a range of educational settings, had varying degrees of hearing loss, and used a range of communication modes. Results showed that, overall, DHH students reported increased levels of mental health problems compared with hearing peers. The broadband syndromes were more than 3 times more likely to be reported, while the narrowband syndromes were between 2 and 7 times more likely. A binary logistic regression analysis showed that the language used at home was a significant predictor of mental health problems. The implications of these findings for the social, emotional, and mental well-being of DHH students and the training of professionals are discussed. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mitochondrial DNA Haplogroup Confers Genetic Susceptibility to Nasopharyngeal Carcinoma in Chaoshanese from Guangdong, China

PubMed Central

Hu, Sheng-Ping; Du, Ju-Ping; Li, De-Rui; Yao, Yong-Gang

2014-01-01

Recent studies have shown association of mtDNA background with cancer development. We analyzed mitochondrial DNA (mtDNA) control region variation of 201 patients with nasopharyngeal carcinoma (NPC) and of 201 normal controls from Chaoshan Han Chinese to discern mtDNA haplogroup effect on the disease onset. Binary logistic regression analysis with adjustment for gender and age revealed that the haplogroup R9 (P = 0.011, OR = 1.91, 95% CI = 1.16–3.16), particularly its sub-haplogroup F1 (P = 0.015, OR = 2.43, 95% CI = 1.18–5.00), were associated significantly with increased NPC risk. These haplogroups were further confirmed to confer high NPC risk in males and/or individuals ≥40 years of age, but not in females or in subjects <40 years old. Our results indicated that mtDNA background confers genetic susceptibility to NPC in Chaoshan Han Chinese, and R9, particularly its sub-haplogroup F1, is a risk factor for NPC. PMID:24498198