Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

NASA Technical Reports Server (NTRS)

Wolf, S. F.; Lipschutz, M. E.

1993-01-01

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Risk Factors Associated with Preterm Delivery after Fetoscopic Laser Surgery for Twin Twin Transfusion Syndrome

PubMed Central

PAPANNA, Ramesha; BLOCK-ABRAHAM, Dana; Mann, Lovepreet K; BUHIMSCHI, Irina A.; BEBBINGTON, Michael; GARCIA, Elisa; KAHLEK, Nahla; HARMAN, Christopher; JOHNSON, Anthony; BASCHAT, Ahmet; MOISE, Kenneth J.

2014-01-01

OBJECTIVE Despite improved perinatal survival following fetoscopic laser surgery (FLS) for twin twin transfusion syndrome (TTTS), prematurity remains an important contributor to perinatal mortality and morbidity. The objective of the study was to identify risk factors for complicated preterm delivery after FLS. STUDY DESIGN Retrospective cohort study of prospectively collected data on maternal/fetal demographics and pre-operative, operative and post-operative variables of 459 patients treated in 3 U.S. fetal centers. Multivariate linear regression was performed to identify significant risk factors associated with preterm delivery, which was cross-validated using K-fold method. Multivariate logistic regression was performed to identify risk factors for early vs. late preterm delivery based on median gestational age at delivery of 32 weeks. RESULTS There were significant differences in case selection and outcomes between the centers. After controlling for the center of surgery, a multivariate analysis indicated a lower maternal age at procedure, history of previous prematurity, shortened cervical length, use of amnioinfusion, 12 Fr cannula diameter, lack of a collagen plug placement and iatrogenic preterm premature rupture of membranes (iPPROM) were significantly associated with a lower gestational age at delivery. CONCLUSION Specific fetal/maternal and operative variables are associated with preterm delivery after FLS for the treatment of TTTS. Further studies to modify some of these variables may decrease the perinatal morbidity after laser therapy. PMID:24013922

Concentration-Dependent Antagonism and Culture Conversion in Pulmonary Tuberculosis

PubMed Central

Pasipanodya, Jotam G.; Denti, Paolo; Sirgel, Frederick; Lesosky, Maia; Gumbo, Tawanda; Meintjes, Graeme; McIlleron, Helen; Wilkinson, Robert J.

2017-01-01

Abstract Background. There is scant evidence to support target drug exposures for optimal tuberculosis outcomes. We therefore assessed whether pharmacokinetic/pharmacodynamic (PK/PD) parameters could predict 2-month culture conversion. Methods. One hundred patients with pulmonary tuberculosis (65% human immunodeficiency virus coinfected) were intensively sampled to determine rifampicin, isoniazid, and pyrazinamide plasma concentrations after 7–8 weeks of therapy, and PK parameters determined using nonlinear mixed-effects models. Detailed clinical data and sputum for culture were collected at baseline, 2 months, and 5–6 months. Minimum inhibitory concentrations (MICs) were determined on baseline isolates. Multivariate logistic regression and the assumption-free multivariate adaptive regression splines (MARS) were used to identify clinical and PK/PD predictors of 2-month culture conversion. Potential PK/PD predictors included 0- to 24-hour area under the curve (AUC0-24), maximum concentration (Cmax), AUC0-24/MIC, Cmax/MIC, and percentage of time that concentrations persisted above the MIC (%TMIC). Results. Twenty-six percent of patients had Cmax of rifampicin <8 mg/L, pyrazinamide <35 mg/L, and isoniazid <3 mg/L. No relationship was found between PK exposures and 2-month culture conversion using multivariate logistic regression after adjusting for MIC. However, MARS identified negative interactions between isoniazid Cmax and rifampicin Cmax/MIC ratio on 2-month culture conversion. If isoniazid Cmax was <4.6 mg/L and rifampicin Cmax/MIC <28, the isoniazid concentration had an antagonistic effect on culture conversion. For patients with isoniazid Cmax >4.6 mg/L, higher isoniazid exposures were associated with improved rates of culture conversion. Conclusions. PK/PD analyses using MARS identified isoniazid Cmax and rifampicin Cmax/MIC thresholds below which there is concentration-dependent antagonism that reduces 2-month sputum culture conversion. PMID:28205671

Multivariate logistic regression analysis of postoperative complications and risk model establishment of gastrectomy for gastric cancer: A single-center cohort report.

PubMed

Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing

2016-01-01

Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.

Access disparities to Magnet hospitals for patients undergoing neurosurgical operations

PubMed Central

Missios, Symeon; Bekelis, Kimon

2017-01-01

Background Centers of excellence focusing on quality improvement have demonstrated superior outcomes for a variety of surgical interventions. We investigated the presence of access disparities to hospitals recognized by the Magnet Recognition Program of the American Nurses Credentialing Center (ANCC) for patients undergoing neurosurgical operations. Methods We performed a cohort study of all neurosurgery patients who were registered in the New York Statewide Planning and Research Cooperative System (SPARCS) database from 2009–2013. We examined the association of African-American race and lack of insurance with Magnet status hospitalization for neurosurgical procedures. A mixed effects propensity adjusted multivariable regression analysis was used to control for confounding. Results During the study period, 190,535 neurosurgical patients met the inclusion criteria. Using a multivariable logistic regression, we demonstrate that African-Americans had lower admission rates to Magnet institutions (OR 0.62; 95% CI, 0.58–0.67). This persisted in a mixed effects logistic regression model (OR 0.77; 95% CI, 0.70–0.83) to adjust for clustering at the patient county level, and a propensity score adjusted logistic regression model (OR 0.75; 95% CI, 0.69–0.82). Additionally, lack of insurance was associated with lower admission rates to Magnet institutions (OR 0.71; 95% CI, 0.68–0.73), in a multivariable logistic regression model. This persisted in a mixed effects logistic regression model (OR 0.72; 95% CI, 0.69–0.74), and a propensity score adjusted logistic regression model (OR 0.72; 95% CI, 0.69–0.75). Conclusions Using a comprehensive all-payer cohort of neurosurgery patients in New York State we identified an association of African-American race and lack of insurance with lower rates of admission to Magnet hospitals. PMID:28684152

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Independent Correlates of Reported Gambling Problems amongst Indigenous Australians

ERIC Educational Resources Information Center

Stevens, Matthew; Young, Martin

2010-01-01

To identify independent correlates of reported gambling problems amongst the Indigenous population of Australia. A cross-sectional design was applied to a nationally representative sample of the Indigenous population. Estimates of reported gambling problems are presented by remoteness and jurisdiction. Multivariable logistic regression was used to…

Neurophysiological correlates of depressive symptoms in young adults: A quantitative EEG study.

PubMed

Lee, Poh Foong; Kan, Donica Pei Xin; Croarkin, Paul; Phang, Cheng Kar; Doruk, Deniz

2018-01-01

There is an unmet need for practical and reliable biomarkers for mood disorders in young adults. Identifying the brain activity associated with the early signs of depressive disorders could have important diagnostic and therapeutic implications. In this study we sought to investigate the EEG characteristics in young adults with newly identified depressive symptoms. Based on the initial screening, a total of 100 participants (n = 50 euthymic, n = 50 depressive) underwent 32-channel EEG acquisition. Simple logistic regression and C-statistic were used to explore if EEG power could be used to discriminate between the groups. The strongest EEG predictors of mood using multivariate logistic regression models. Simple logistic regression analysis with subsequent C-statistics revealed that only high-alpha and beta power originating from the left central cortex (C3) have a reliable discriminative value (ROC curve >0.7 (70%)) for differentiating the depressive group from the euthymic group. Multivariate regression analysis showed that the single most significant predictor of group (depressive vs. euthymic) is the high-alpha power over C3 (p = 0.03). The present findings suggest that EEG is a useful tool in the identification of neurophysiological correlates of depressive symptoms in young adults with no previous psychiatric history. Our results could guide future studies investigating the early neurophysiological changes and surrogate outcomes in depression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Multivariate logistic regression for predicting total culturable virus presence at the intake of a potable-water treatment plant: novel application of the atypical coliform/total coliform ratio.

PubMed

Black, L E; Brion, G M; Freitas, S J

2007-06-01

Predicting the presence of enteric viruses in surface waters is a complex modeling problem. Multiple water quality parameters that indicate the presence of human fecal material, the load of fecal material, and the amount of time fecal material has been in the environment are needed. This paper presents the results of a multiyear study of raw-water quality at the inlet of a potable-water plant that related 17 physical, chemical, and biological indices to the presence of enteric viruses as indicated by cytopathic changes in cell cultures. It was found that several simple, multivariate logistic regression models that could reliably identify observations of the presence or absence of total culturable virus could be fitted. The best models developed combined a fecal age indicator (the atypical coliform [AC]/total coliform [TC] ratio), the detectable presence of a human-associated sterol (epicoprostanol) to indicate the fecal source, and one of several fecal load indicators (the levels of Giardia species cysts, coliform bacteria, and coprostanol). The best fit to the data was found when the AC/TC ratio, the presence of epicoprostanol, and the density of fecal coliform bacteria were input into a simple, multivariate logistic regression equation, resulting in 84.5% and 78.6% accuracies for the identification of the presence and absence of total culturable virus, respectively. The AC/TC ratio was the most influential input variable in all of the models generated, but producing the best prediction required additional input related to the fecal source and the fecal load. The potential for replacing microbial indicators of fecal load with levels of coprostanol was proposed and evaluated by multivariate logistic regression modeling for the presence and absence of virus.

Relationship between Job Burnout and Personal Wellness in Mental Health Professionals

ERIC Educational Resources Information Center

Puig, Ana; Baggs, Adrienne; Mixon, Kacy; Park, Yang Min; Kim, Bo Young; Lee, Sang Min

2012-01-01

This study aimed to determine the nature of the relationship between job burnout and personal wellness among mental health professionals. The authors performed intercorrelations and multivariate multiple regression analyses to identify the relationship between subscales of job burnout and personal wellness. Results showed that all subscales of job…

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Risk factor assessment to anticipate performance in the National Developmental Screening Test in children from a disadvantaged area.

PubMed

Montes, Alejandro; Pazos, Gustavo

2016-02-01

Identifying children at risk of failing the National Developmental Screening Test by combining prevalences of children suspected of having inapparent developmental disorders (IDDs) and associated risk factors (RFs) would allow to save resources. 1. To estimate the prevalence of children suspected of having IDDs. 2. To identify associated RFs. 3. To assess three methods developed based on observed RFs and propose a pre-screening procedure. The National Developmental Screening Test was administered to 60 randomly selected children aged between 2 and 4 years old from a socioeconomically disadvantaged area from Puerto Madryn. Twenty-four biological and socioenvironmental outcome measures were assessed in order to identify potential RFs using bivariate and multivariate analyses. The likelihood of failing the screening test was estimated as follows: 1. a multivariate logistic regression model was developed; 2. a relationship was established between the number of RFs present in each child and the percentage of children who failed the test; 3. these two methods were combined. The prevalence of children suspected of having IDDs was 55.0% (95% confidence interval: 42.4%-67.6%). Six RFs were initially identified using the bivariate approach. Three of them (maternal education, number of health checkups and Z scores for height-for-age, and maternal age) were included in the logistic regression model, which has a greater explanatory power. The third method included in the assessment showed greater sensitivity and specificity (85% and 79%, respectively). The estimated prevalence of children suspected of having IDDs was four times higher than the national standards. Seven RFs were identified. Combining the analysis of risk factor accumulation and a multivariate model provides a firm basis for developing a sensitive, specific and practical pre-screening procedure for socioeconomically disadvantaged areas. Sociedad Argentina de Pediatría.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Missing data may lead to changes in hip fracture database studies: a study of the American College of Surgeons National Surgical Quality Improvement Program.

PubMed

Basques, B A; McLynn, R P; Lukasiewicz, A M; Samuel, A M; Bohl, D D; Grauer, J N

2018-02-01

The aims of this study were to characterize the frequency of missing data in the National Surgical Quality Improvement Program (NSQIP) database and to determine how missing data can influence the results of studies dealing with elderly patients with a fracture of the hip. Patients who underwent surgery for a fracture of the hip between 2005 and 2013 were identified from the NSQIP database and the percentage of missing data was noted for demographics, comorbidities and laboratory values. These variables were tested for association with 'any adverse event' using multivariate regressions based on common ways of handling missing data. A total of 26 066 patients were identified. The rate of missing data was up to 77.9% for many variables. Multivariate regressions comparing three methods of handling missing data found different risk factors for postoperative adverse events. Only seven of 35 identified risk factors (20%) were common to all three analyses. Missing data is an important issue in national database studies that researchers must consider when evaluating such investigations. Cite this article: Bone Joint J 2018;100-B:226-32. ©2018 The British Editorial Society of Bone & Joint Surgery.

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

PubMed

Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

2015-01-01

Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing.

PubMed

Stamate, Mirela Cristina; Todor, Nicolae; Cosgarea, Marcel

2015-01-01

The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing

PubMed Central

STAMATE, MIRELA CRISTINA; TODOR, NICOLAE; COSGAREA, MARCEL

2015-01-01

Background and aim The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. Methods The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. Results We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Conclusion Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies. PMID:26733749

Factors Associated with Participation in Employment for High School Leavers with Autism

ERIC Educational Resources Information Center

Chiang, Hsu-Min; Cheung, Ying Kuen; Li, Huacheng; Tsai, Luke Y.

2013-01-01

This study aimed to identify the factors associated with participation in employment for high school leavers with autism. A secondary data analysis of the National Longitudinal Transition Study 2 (NLTS2) data was performed. Potential factors were assessed using a weighted multivariate logistic regression. This study found that annual household…

Time Poverty Thresholds and Rates for the US Population

ERIC Educational Resources Information Center

Kalenkoski, Charlene M.; Hamrick, Karen S.; Andrews, Margaret

2011-01-01

Time constraints, like money constraints, affect Americans' well-being. This paper defines what it means to be time poor based on the concepts of necessary and committed time and presents time poverty thresholds and rates for the US population and certain subgroups. Multivariate regression techniques are used to identify the key variables…

Differences in Health Determinants between International and Domestic Students at a German.

ERIC Educational Resources Information Center

Kramer, Alexander; Prufer-Kramer, Luise; Stock, Christiane; Tshiananga, Jacques Tshiang

2004-01-01

The authors used a standardized questionnaire to survey 201 international and 193 German students at the University of Bielefeld, Germany, to determine differences in health practices between the 2 groups and to identify targets for health-promoting interventions. Multivariate logistic regression models revealed that long-term female international…

A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression

USDA-ARS?s Scientific Manuscript database

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly ...

Regression analysis for LED color detection of visual-MIMO system

NASA Astrophysics Data System (ADS)

Banik, Partha Pratim; Saha, Rappy; Kim, Ki-Doo

2018-04-01

Color detection from a light emitting diode (LED) array using a smartphone camera is very difficult in a visual multiple-input multiple-output (visual-MIMO) system. In this paper, we propose a method to determine the LED color using a smartphone camera by applying regression analysis. We employ a multivariate regression model to identify the LED color. After taking a picture of an LED array, we select the LED array region, and detect the LED using an image processing algorithm. We then apply the k-means clustering algorithm to determine the number of potential colors for feature extraction of each LED. Finally, we apply the multivariate regression model to predict the color of the transmitted LEDs. In this paper, we show our results for three types of environmental light condition: room environmental light, low environmental light (560 lux), and strong environmental light (2450 lux). We compare the results of our proposed algorithm from the analysis of training and test R-Square (%) values, percentage of closeness of transmitted and predicted colors, and we also mention about the number of distorted test data points from the analysis of distortion bar graph in CIE1931 color space.

Pediatric Irritable Bowel Syndrome Patient and Parental Characteristics Differ by Care Management Type.

PubMed

Hollier, John M; Czyzewski, Danita I; Self, Mariella M; Weidler, Erica M; Smith, E O'Brian; Shulman, Robert J

2017-03-01

This study evaluates whether certain patient or parental characteristics are associated with gastroenterology (GI) referral versus primary pediatrics care for pediatric irritable bowel syndrome (IBS). A retrospective clinical trial sample of patients meeting pediatric Rome III IBS criteria was assembled from a single metropolitan health care system. Baseline socioeconomic status (SES) and clinical symptom measures were gathered. Various instruments measured participant and parental psychosocial traits. Study outcomes were stratified by GI referral versus primary pediatrics care. Two separate analyses of SES measures and GI clinical symptoms and psychosocial measures identified key factors by univariate and multiple logistic regression analyses. For each analysis, identified factors were placed in unadjusted and adjusted multivariate logistic regression models to assess their impact in predicting GI referral. Of the 239 participants, 152 were referred to pediatric GI, and 87 were managed in primary pediatrics care. Of the SES and clinical symptom factors, child self-assessment of abdominal pain duration and lower percentage of people living in poverty were the strongest predictors of GI referral. Among the psychosocial measures, parental assessment of their child's functional disability was the sole predictor of GI referral. In multivariate logistic regression models, all selected factors continued to predict GI referral in each model. Socioeconomic environment, clinical symptoms, and functional disability are associated with GI referral. Future interventions designed to ameliorate the effect of these identified factors could reduce unnecessary specialty consultations and health care overutilization for IBS.

Impact of hyperglycemia on outcomes of patients with Pseudomonas aeruginosa bacteremia.

PubMed

Patel, Twisha S; Cottreau, Jessica M; Hirsch, Elizabeth B; Tam, Vincent H

2016-02-01

Bacteremia caused by Pseudomonas aeruginosa is associated with significant morbidity and mortality. In other bacterial infections, hyperglycemia has been identified as a risk factor for mortality in nondiabetic patients. The objective of this study was to determine the impact of early hyperglycemia on outcomes in diabetic and nondiabetic patients with P. aeruginosa bacteremia. A retrospective cohort study was performed in adult patients (≥18 years old) with P. aeruginosa bacteremia. Patients received at least 1 drug empirically to which the isolate was susceptible in vitro. Classification and regression tree analysis was used to determine the threshold breakpoint for average blood glucose concentration within 48 hours of positive blood culture (BG48). Logistic regression was used to explore independent risk factors for 30-day mortality. A total of 176 bacteremia episodes were identified; patients in 66 episodes were diabetic. Diabetic patients had higher BG48 (165.2±64.8 mg/dL versus 123.7±31.5 mg/dL, P<0.001) and lower 30-day mortality (10.7% versus 22.7%, P=0.046) than nondiabetic patients. Multivariate regression revealed 30-day mortality in nondiabetic patients was associated with Acute Physiology and Chronic Health Evaluation II score (odds ratio [OR] 1.1; 95% confidence interval [CI] 1.0-1.2) and BG48 >168 mg/dL (OR 6.3; 95% CI 1.7-23.3). However, blood glucose concentration was not identified as an independent risk factor for mortality in diabetic patients by multivariate regression analysis. Hyperglycemia did not appear to affect outcomes in diabetic patients, whereas nondiabetic patients had a higher risk of mortality from P. aeruginosa bacteremia. Prospective studies evaluating the impact of glycemic control in these patients are needed. Copyright © 2016 Elsevier Inc. All rights reserved.

Effect of duration of denervation on outcomes of ansa-recurrent laryngeal nerve reinnervation.

PubMed

Li, Meng; Chen, Shicai; Wang, Wei; Chen, Donghui; Zhu, Minhui; Liu, Fei; Zhang, Caiyun; Li, Yan; Zheng, Hongliang

2014-08-01

To investigate the efficacy of laryngeal reinnervation with ansa cervicalis among unilateral vocal fold paralysis (UVFP) patients with different denervation durations. We retrospectively reviewed 349 consecutive UVFP cases of delayed ansa cervicalis to the recurrent laryngeal nerve (RLN) anastomosis. Potential influencing factors were analyzed in multivariable logistic regression analysis. Stratification analysis performed was aimed at one of the identified significant variables: denervation duration. Videostroboscopy, perceptual evaluation, acoustic analysis, maximum phonation time (MPT), and laryngeal electromyography (EMG) were performed preoperatively and postoperatively. Gender, age, preoperative EMG status and denervation duration were analyzed in multivariable logistic regression analysis. Stratification analysis was performed on denervation duration, which was divided into three groups according to the interval between RLN injury and reinnervation: group A, 6 to 12 months; group B, 12 to 24 months; and group C, > 24 months. Age, preoperative EMG, and denervation duration were identified as significant variables in multivariable logistic regression analysis. Stratification analysis on denervation duration showed significant differences between group A and C and between group B and C (P < 0.05)-but showed no significant difference between group A and B (P > 0.05) with regard to parameters overall grade, jitter, shimmer, noise-to-harmonics ratio, MPT, and postoperative EMG. In addition, videostroboscopic and laryngeal EMG data, perceptual and acoustic parameters, and MPT values were significantly improved postoperatively in each denervation duration group (P < 0.01). Although delayed laryngeal reinnervation is proved valid for UVFP, surgical outcome is better if the procedure is performed within 2 years after nerve injury than that over 2 years. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Vitamin D insufficiency and subclinical atherosclerosis in non-diabetic males living with HIV.

PubMed

Portilla, Joaquín; Moreno-Pérez, Oscar; Serna-Candel, Carmen; Escoín, Corina; Alfayate, Rocio; Reus, Sergio; Merino, Esperanza; Boix, Vicente; Giner, Livia; Sánchez-Payá, José; Picó, Antonio

2014-01-01

Vitamin D insufficiency (VDI) has been associated with increased cardiovascular risk in the non-HIV population. This study evaluates the relationship among serum 25-hydroxyvitamin D [25(OH)D] levels, cardiovascular risk factors, adipokines, antiviral therapy (ART) and subclinical atherosclerosis in HIV-infected males. A cross-sectional study in ambulatory care was made in non-diabetic patients living with HIV. VDI was defined as 25(OH)D serum levels <75 nmol/L. Fasting lipids, glucose, inflammatory markers (tumour necrosis factor-α, interleukin-6, high-sensitivity C-reactive protein) and endothelial markers (plasminogen activator inhibitor-1, or PAI-I) were measured. The common carotid artery intima-media thickness (C-IMT) was determined. A multivariate logistic regression analysis was made to identify factors associated with the presence of VDI, while multivariate linear regression analysis was used to identify factors associated with common C-IMT. Eighty-nine patients were included (age 42 ± 8 years), 18.9% were in CDC (US Centers for Disease Control and Prevention) stage C and 75 were on ART. VDI was associated with ART exposure, sedentary lifestyle, higher triglycerides levels and PAI-I. In univariate analysis, VDI was associated with greater common C-IMT. The multivariate linear regression model, adjusted by confounding factors, revealed an independent association between common C-IMT and patient age, time of exposure to protease inhibitors (PIs) and impaired fasting glucose (IFG). In contrast, there were no independent associations between common C-IMT and VDI or inflammatory and endothelial markers. VDI was not independently associated with subclinical atherosclerosis in non-diabetic males living with HIV. Older age, a longer exposure to PIs, and IFG were independent factors associated with common C-IMT in this population.

Partial Least Squares Regression Models for the Analysis of Kinase Signaling.

PubMed

Bourgeois, Danielle L; Kreeger, Pamela K

2017-01-01

Partial least squares regression (PLSR) is a data-driven modeling approach that can be used to analyze multivariate relationships between kinase networks and cellular decisions or patient outcomes. In PLSR, a linear model relating an X matrix of dependent variables and a Y matrix of independent variables is generated by extracting the factors with the strongest covariation. While the identified relationship is correlative, PLSR models can be used to generate quantitative predictions for new conditions or perturbations to the network, allowing for mechanisms to be identified. This chapter will provide a brief explanation of PLSR and provide an instructive example to demonstrate the use of PLSR to analyze kinase signaling.

Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

PubMed Central

Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

2013-01-01

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

Self-reported mental health among US military personnel prior and subsequent to the terrorist attacks of September 11, 2001.

PubMed

Smith, Tyler C; Smith, Besa; Corbeil, Thomas E; Riddle, James R; Ryan, Margaret A K

2004-08-01

There is much concern over the potential for short- and long-term adverse mental health effects caused by the terrorist attacks on September 11, 2001. This analysis used data from the Millennium Cohort Study to identify subgroups of US military members who enrolled in the cohort and reported their mental health status before the traumatic events of September 11 and soon after September 11. While adjusting for confounding, multivariable logistic regression, analysis of variance, and multivariate ordinal, or polychotomous logistic regression were used to compare 18 self-reported mental health measures in US military members who enrolled in the cohort before September 11, 2001 with those military personnel who enrolled after September 11, 2001. In contrast to studies of other populations, military respondents reported fewer mental health problems in the months immediately after September 11, 2001.

[Multivariate Adaptive Regression Splines (MARS), an alternative for the analysis of time series].

PubMed

Vanegas, Jairo; Vásquez, Fabián

Multivariate Adaptive Regression Splines (MARS) is a non-parametric modelling method that extends the linear model, incorporating nonlinearities and interactions between variables. It is a flexible tool that automates the construction of predictive models: selecting relevant variables, transforming the predictor variables, processing missing values and preventing overshooting using a self-test. It is also able to predict, taking into account structural factors that might influence the outcome variable, thereby generating hypothetical models. The end result could identify relevant cut-off points in data series. It is rarely used in health, so it is proposed as a tool for the evaluation of relevant public health indicators. For demonstrative purposes, data series regarding the mortality of children under 5 years of age in Costa Rica were used, comprising the period 1978-2008. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery.

PubMed

Liu, Han; Wang, Lie; Zhao, Tuo

2015-08-01

We propose a calibrated multivariate regression method named CMR for fitting high dimensional multivariate regression models. Compared with existing methods, CMR calibrates regularization for each regression task with respect to its noise level so that it simultaneously attains improved finite-sample performance and tuning insensitiveness. Theoretically, we provide sufficient conditions under which CMR achieves the optimal rate of convergence in parameter estimation. Computationally, we propose an efficient smoothed proximal gradient algorithm with a worst-case numerical rate of convergence O (1/ ϵ ), where ϵ is a pre-specified accuracy of the objective function value. We conduct thorough numerical simulations to illustrate that CMR consistently outperforms other high dimensional multivariate regression methods. We also apply CMR to solve a brain activity prediction problem and find that it is as competitive as a handcrafted model created by human experts. The R package camel implementing the proposed method is available on the Comprehensive R Archive Network http://cran.r-project.org/web/packages/camel/.

Predictors of effects of lifestyle intervention on diabetes mellitus type 2 patients.

PubMed

Jacobsen, Ramune; Vadstrup, Eva; Røder, Michael; Frølich, Anne

2012-01-01

The main aim of the study was to identify predictors of the effects of lifestyle intervention on diabetes mellitus type 2 patients by means of multivariate analysis. Data from a previously published randomised clinical trial, which compared the effects of a rehabilitation programme including standardised education and physical training sessions in the municipality's health care centre with the same duration of individual counseling in the diabetes outpatient clinic, were used. Data from 143 diabetes patients were analysed. The merged lifestyle intervention resulted in statistically significant improvements in patients' systolic blood pressure, waist circumference, exercise capacity, glycaemic control, and some aspects of general health-related quality of life. The linear multivariate regression models explained 45% to 80% of the variance in these improvements. The baseline outcomes in accordance to the logic of the regression to the mean phenomenon were the only statistically significant and robust predictors in all regression models. These results are important from a clinical point of view as they highlight the more urgent need for and better outcomes following lifestyle intervention for those patients who have worse general and disease-specific health.

Sex Differences in Contraception Non-Use among Urban Adolescents: Risk Factors for Unintended Pregnancy

ERIC Educational Resources Information Center

Casola, Allison R.; Nelson, Deborah B.; Patterson, Freda

2017-01-01

Background: Contraception non-use among sexually active adolescents is a major cause of unintended pregnancy (UP). Methods: In this cross-sectional study we sought to identify overall and sex-specific correlates of contraception non-use using the 2015 Philadelphia Youth Risk Behavior Survey (YRBS) (N = 9540). Multivariate regression models were…

Using Performance Data Gathered at Several Stages of Achievement in Predicting Subsequent Performance.

ERIC Educational Resources Information Center

Owen, Steven V.; Feldhusen, John F.

This study compares the effectiveness of three models of multivariate prediction for academic success in identifying the criterion variance of achievement in nursing education. The first model involves the use of an optimum set of predictors and one equation derived from a regression analysis on first semester grade average in predicting the…

Community-Based Addiction Treatment Staff Attitudes about the Usefulness of Evidence-Based Addiction Treatment and CBO Organizational Linkages to Research Institutions

ERIC Educational Resources Information Center

Lundgren, Lena; Krull, Ivy; Zerden, Lisa de Saxe; McCarty, Dennis

2011-01-01

This national study of community-based addiction-treatment organizations' (CBOs) implementation of evidence-based practices explored CBO Program Directors' (n = 296) and clinical staff (n = 518) attitudes about the usefulness of science-based addiction treatment. Through multivariable regression modeling, the study identified that identical…

A Multivariate Analysis of Personality, Values and Expectations as Correlates of Career Aspirations of Final Year Medical Students

ERIC Educational Resources Information Center

Rogers, Mary E.; Searle, Judy; Creed, Peter A.; Ng, Shu-Kay

2010-01-01

This study reports on the career intentions of 179 final year medical students who completed an online survey that included measures of personality, values, professional and lifestyle expectations, and well-being. Logistic regression analyses identified the determinants of preferred medical specialty, practice location and hours of work.…

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Socioeconomic Factors Associated with Post-Mastectomy Immediate Reconstruction in a Contemporary Cohort of Breast Cancer Survivors.

PubMed

Schumacher, Jessica R; Taylor, Lauren J; Tucholka, Jennifer L; Poore, Samuel; Eggen, Amanda; Steiman, Jennifer; Wilke, Lee G; Greenberg, Caprice C; Neuman, Heather B

2017-10-01

Post-mastectomy reconstruction is a critical component of high-quality breast cancer care. Prior studies demonstrate socioeconomic disparity in receipt of reconstruction. Our objective was to evaluate trends in receipt of immediate reconstruction and examine socioeconomic factors associated with reconstruction in a contemporary cohort. Using the National Cancer Database, we identified women <75 years of age with stage 0-1 breast cancer treated with mastectomy (n = 297,121). Trends in immediate reconstruction rates (2004-2013) for the overall cohort and stratified by socioeconomic factors were examined using Join-point regression analysis, and annual percentage change (APC) was calculated. We then restricted our sample to a contemporary cohort (2010-2013, n = 145,577). Multivariable logistic regression identified socioeconomic factors associated with immediate reconstruction. Average adjusted predicted probabilities of receiving reconstruction were calculated. Immediate reconstruction rates increased from 27 to 48%. Although absolute rates of reconstruction for each stratification group increased, similar APCs across strata led to persistent gaps in receipt of reconstruction. On multivariable logistic regression using our contemporary cohort, race, income, education, and insurance type were all strongly associated with immediate reconstruction. Patients with the lowest predicted probability of receiving reconstruction were patients with Medicaid who lived in areas with the lowest rates of high-school graduation (Black 42.4% [95% CI 40.5-44.3], White 45.7% [95% CI 43.9-47.4]). Although reconstruction rates have increased dramatically over the past decade, lower rates persist for disadvantaged patients. Understanding how socioeconomic factors influence receipt of reconstruction, and identifying modifiable factors, are critical next steps towards identifying interventions to reduce disparities in breast cancer surgical care.

Job stress models, depressive disorders and work performance of engineers in microelectronics industry.

PubMed

Chen, Sung-Wei; Wang, Po-Chuan; Hsin, Ping-Lung; Oates, Anthony; Sun, I-Wen; Liu, Shen-Ing

2011-01-01

Microelectronic engineers are considered valuable human capital contributing significantly toward economic development, but they may encounter stressful work conditions in the context of a globalized industry. The study aims at identifying risk factors of depressive disorders primarily based on job stress models, the Demand-Control-Support and Effort-Reward Imbalance models, and at evaluating whether depressive disorders impair work performance in microelectronics engineers in Taiwan. The case-control study was conducted among 678 microelectronics engineers, 452 controls and 226 cases with depressive disorders which were defined by a score 17 or more on the Beck Depression Inventory and a psychiatrist's diagnosis. The self-administered questionnaires included the Job Content Questionnaire, Effort-Reward Imbalance Questionnaire, demography, psychosocial factors, health behaviors and work performance. Hierarchical logistic regression was applied to identify risk factors of depressive disorders. Multivariate linear regressions were used to determine factors affecting work performance. By hierarchical logistic regression, risk factors of depressive disorders are high demands, low work social support, high effort/reward ratio and low frequency of physical exercise. Combining the two job stress models may have better predictive power for depressive disorders than adopting either model alone. Three multivariate linear regressions provide similar results indicating that depressive disorders are associated with impaired work performance in terms of absence, role limitation and social functioning limitation. The results may provide insight into the applicability of job stress models in a globalized high-tech industry considerably focused in non-Western countries, and the design of workplace preventive strategies for depressive disorders in Asian electronics engineering population.

Empirical Bayes approach to the estimation of "unsafety": the multivariate regression method.

PubMed

Hauer, E

1992-10-01

There are two kinds of clues to the unsafety of an entity: its traits (such as traffic, geometry, age, or gender) and its historical accident record. The Empirical Bayes approach to unsafety estimation makes use of both kinds of clues. It requires information about the mean and the variance of the unsafety in a "reference population" of similar entities. The method now in use for this purpose suffers from several shortcomings. First, a very large reference population is required. Second, the choice of reference population is to some extent arbitrary. Third, entities in the reference population usually cannot match the traits of the entity the unsafety of which is estimated. To alleviate these shortcomings the multivariate regression method for estimating the mean and variance of unsafety in reference populations is offered. Its logical foundations are described and its soundness is demonstrated. The use of the multivariate method makes the Empirical Bayes approach to unsafety estimation applicable to a wider range of circumstances and yields better estimates of unsafety. The application of the method to the tasks of identifying deviant entities and of estimating the effect of interventions on unsafety are discussed and illustrated by numerical examples.

Clinical management provided by board-certificated physiatrists in early rehabilitation is a significant determinant of functional improvement in acute stroke patients: a retrospective analysis of Japan rehabilitation database.

PubMed

Kinoshita, Shoji; Kakuda, Wataru; Momosaki, Ryo; Yamada, Naoki; Sugawara, Hidekazu; Watanabe, Shu; Abo, Masahiro

2015-05-01

Early rehabilitation for acute stroke patients is widely recommended. We tested the hypothesis that clinical outcome of stroke patients who receive early rehabilitation managed by board-certificated physiatrists (BCP) is generally better than that provided by other medical specialties. Data of stroke patients who underwent early rehabilitation in 19 acute hospitals between January 2005 and December 2013 were collected from the Japan Rehabilitation Database and analyzed retrospectively. Multivariate linear regression analysis using generalized estimating equations method was performed to assess the association between Functional Independence Measure (FIM) effectiveness and management provided by BCP in early rehabilitation. In addition, multivariate logistic regression analysis was also performed to assess the impact of management provided by BCP in acute phase on discharge destination. After setting the inclusion criteria, data of 3838 stroke patients were eligible for analysis. BCP provided early rehabilitation in 814 patients (21.2%). Both the duration of daily exercise time and the frequency of regular conferencing were significantly higher for patients managed by BCP than by other specialties. Although the mortality rate was not different, multivariate regression analysis showed that FIM effectiveness correlated significantly and positively with the management provided by BCP (coefficient, .35; 95% confidence interval [CI], .012-.059; P < .005). In addition, multivariate logistic analysis identified clinical management by BCP as a significant determinant of home discharge (odds ratio, 1.24; 95% CI, 1.08-1.44; P < .005). Our retrospective cohort study demonstrated that clinical management provided by BCP in early rehabilitation can lead to functional recovery of acute stroke. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Predictors of in-hospital mortality amongst octogenarians undergoing emergency general surgery: a retrospective cohort study.

PubMed

Wilson, Iain; Paul Barrett, Michael; Sinha, Ashish; Chan, Shirley

2014-11-01

Elderly patients are often judged to be fit for emergency surgery based on age alone. This study identified risk factors predictive of in-hospital mortality amongst octogenarians undergoing emergency general surgery. A retrospective review of octogenarians undergoing emergency general surgery over 3 years was performed. Parametric survival analysis using Cox multivariate regression model was used to identify risk factors predictive of in-hospital mortality. Hazard ratios (HR) and corresponding 95% confidence interval were calculated. Seventy-three patients with a median age of 84 years were identified. Twenty-eight (38%) patients died post-operatively. Multivariate analysis identified ASA grade (ASA 5 HR 23.4 95% CI 2.38-230, p = 0.007) and chronic obstructive pulmonary disease (COPD) (HR 3.35 95% CI 1.15-9.69, p = 0.026) to be the only significant predictors of in-hospital mortality. Identification of high risk surgical patients should be based on physiological fitness for surgery rather than chronological age. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Nutrition knowledge, attitudes, behaviours and the influencing factors among non-parent caregivers of rural left-behind children under 7 years old in China.

PubMed

Tan, Cai; Luo, Jiayou; Zong, Rong; Fu, Chuhui; Zhang, Lingli; Mou, Jinsong; Duan, Danhui

2010-10-01

To explore and compare nutrition knowledge, attitudes and behaviours (KAB) between non-parent and parent caregivers of children under 7 years old in Chinese rural areas, and to identify the factors influencing their nutrition KAB. Face-to-face interviews were carried out with 1691 non-parent caregivers and 1670 parent caregivers in the selected study areas; multivariate logistic regression models were used to identify the factors influencing nutrition KAB in caregivers. The awareness rate of nutrition knowledge, the rate of positive attitudes and the rate of optimal behaviours in non-parent caregivers (52.2 %, 56.9 % and 37.7 %, respectively) were significantly lower than in the parent group (63.8 %, 62.1 % and 42.8 %, respectively). Multivariate logistic regression modelling showed that caregivers' family income and care will, and children's age and gender, were associated with caregivers' nutrition KAB after controlling the possible confounding variables (caregivers' age, gender, education and occupation). Non-parent caregivers had relatively poor nutrition KAB. Extra efforts and targeted education programmes aimed to improve rural non-parent caregivers' nutrition KAB are wanted and need to be emphasized.

Factors Influencing Cecal Intubation Time during Retrograde Approach Single-Balloon Enteroscopy

PubMed Central

Chen, Peng-Jen; Shih, Yu-Lueng; Huang, Hsin-Hung; Hsieh, Tsai-Yuan

2014-01-01

Background and Aim. The predisposing factors for prolonged cecal intubation time (CIT) during colonoscopy have been well identified. However, the factors influencing CIT during retrograde SBE have not been addressed. The aim of this study was to determine the factors influencing CIT during retrograde SBE. Methods. We investigated patients who underwent retrograde SBE at a medical center from January 2011 to March 2014. The medical charts and SBE reports were reviewed. The patients' characteristics and procedure-associated data were recorded. These data were analyzed with univariate analysis as well as multivariate logistic regression analysis to identify the possible predisposing factors. Results. We enrolled 66 patients into this study. The median CIT was 17.4 minutes. With univariate analysis, there was no statistical difference in age, sex, BMI, or history of abdominal surgery, except for bowel preparation (P = 0.021). Multivariate logistic regression analysis showed that inadequate bowel preparation (odds ratio 30.2, 95% confidence interval 4.63–196.54; P < 0.001) was the independent predisposing factors for prolonged CIT during retrograde SBE. Conclusions. For experienced endoscopist, inadequate bowel preparation was the independent predisposing factor for prolonged CIT during retrograde SBE. PMID:25505904

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Alternatives for using multivariate regression to adjust prospective payment rates

PubMed Central

Sheingold, Steven H.

1990-01-01

Multivariate regression analysis has been used in structuring three of the adjustments to Medicare's prospective payment rates. Because the indirect-teaching adjustment, the disproportionate-share adjustment, and the adjustment for large cities are responsible for distributing approximately $3 billion in payments each year, the specification of regression models for these adjustments is of critical importance. In this article, the application of regression for adjusting Medicare's prospective rates is discussed, and the implications that differing specifications could have for these adjustments are demonstrated. PMID:10113271

Electricity Consumption in the Industrial Sector of Jordan: Application of Multivariate Linear Regression and Adaptive Neuro-Fuzzy Techniques

NASA Astrophysics Data System (ADS)

Samhouri, M.; Al-Ghandoor, A.; Fouad, R. H.

2009-08-01

In this study two techniques, for modeling electricity consumption of the Jordanian industrial sector, are presented: (i) multivariate linear regression and (ii) neuro-fuzzy models. Electricity consumption is modeled as function of different variables such as number of establishments, number of employees, electricity tariff, prevailing fuel prices, production outputs, capacity utilizations, and structural effects. It was found that industrial production and capacity utilization are the most important variables that have significant effect on future electrical power demand. The results showed that both the multivariate linear regression and neuro-fuzzy models are generally comparable and can be used adequately to simulate industrial electricity consumption. However, comparison that is based on the square root average squared error of data suggests that the neuro-fuzzy model performs slightly better for future prediction of electricity consumption than the multivariate linear regression model. Such results are in full agreement with similar work, using different methods, for other countries.

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

PubMed

Zakrzewski, Martha; Proietti, Carla; Ellis, Jonathan J; Hasan, Shihab; Brion, Marie-Jo; Berger, Bernard; Krause, Lutz

2017-03-01

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. The web-interface is accessible via http://cgenome.net/calypso/ . The software is programmed in Java, PERL and R and the source code is available from Zenodo ( https://zenodo.org/record/50931 ). The software is freely available for non-commercial users. l.krause@uq.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Neuropsychiatric and cognitive profile of early Richardson's syndrome, Progressive Supranuclear Palsy-parkinsonism and Parkinson's disease.

PubMed

Pellicano, Clelia; Assogna, Francesca; Cellupica, Nystya; Piras, Federica; Pierantozzi, Mariangela; Stefani, Alessandro; Cerroni, Rocco; Mercuri, Bruno; Caltagirone, Carlo; Pontieri, Francesco E; Spalletta, Gianfranco

2017-12-01

The two main variants of Progressive Supranuclear Palsy (PSP), Richardson's syndrome (PSP-RS) and PSP-parkinsonism (PSP-P), share motor and non-motor features with Parkinson's disease (PD) particularly in the early stages. This makes the precocious diagnosis more challenging. We aimed at defining qualitative and quantitative differences of neuropsychiatric and neuropsychological profiles between PSP-P, PSP-RS and PD patients recruited within 24 months after the onset of symptoms, in order to clarify if the identification of peculiar cognitive and psychiatric symptoms is of help for early PSP diagnosis. PD (n = 155), PSP-P (n = 11) and PSP-RS (n = 14) patients were identified. All patients were submitted to clinical, neurological, neuropsychiatric diagnostic evaluation and to a comprehensive neuropsychiatric and neuropsychological battery. Predictors of PSP-P and PSP-RS diagnosis were identified by multivariate logistic regressions including neuropsychiatric and neuropsychological features that differed significantly among groups. The three groups differed significantly at the Apathy Rating Scale score and at several neuropsychological domains. The multivariate logistic regressions indicated that the diagnosis of PSP-RS was predicted by phonological verbal fluency deficit whereas the presence of apathy significantly predicted the PSP-P diagnosis. Peculiar neuropsychiatric and neuropsychological symptoms are identifiable very precociously in PSP-P, PSP-RS and PD patients. Early phonological verbal fluency deficit identifies patients with PSP-RS whereas apathy supports the diagnosis of PSP-P. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spontaneous passage of ureteral stones in patients with indwelling ureteral stents.

PubMed

Baumgarten, Lee; Desai, Anuj; Shipman, Scott; Eun, Daniel D; Pontari, Michel A; Mydlo, Jack H; Reese, Adam C

2017-10-01

To determine rates of spontaneous ureteral stone passage in patients with indwelling ureteral stents, and to identify factors associated with the spontaneous passage of stones while a ureteral stent is in place. From our institutional database, we identified patients who underwent ureteroscopic procedures for stone disease between January 1, 2013 and March 1, 2015. We compared the rates of spontaneous stone passage between patients who had previously undergone ureteral stent placement and those who had not. In patients with indwelling stents, multivariate logistic regression was performed to identify factors associated with spontaneous stone passage. A total of 194 patients met inclusion criteria. Spontaneous stone passage rates were similar in the stented (17/119, 14%) and non-stented (15/75, 20%) groups (p = 0.30). In bivariate analysis of stented patients, smaller stone size (p < 0.001) and distal stone location (p = 0.01) were significantly associated with spontaneous stone passage. Multivariate logistic regression analysis of stented patients showed that only small stone size was significantly associated with the likelihood of stone passage (p = 0.01), whereas stent duration, stone location, and stone laterality were not. A small, but clinically significant percentage of ureteral stones pass spontaneously with a ureteral stent in place. Small stone size is associated with an increased likelihood of spontaneous passage in patients with indwelling stents. These findings may help to identify patients who can potentially avoid additional surgical procedures for definitive stone removal after ureteral stent placement.

Penalized regression procedures for variable selection in the potential outcomes framework

PubMed Central

Ghosh, Debashis; Zhu, Yeying; Coffman, Donna L.

2015-01-01

A recent topic of much interest in causal inference is model selection. In this article, we describe a framework in which to consider penalized regression approaches to variable selection for causal effects. The framework leads to a simple ‘impute, then select’ class of procedures that is agnostic to the type of imputation algorithm as well as penalized regression used. It also clarifies how model selection involves a multivariate regression model for causal inference problems, and that these methods can be applied for identifying subgroups in which treatment effects are homogeneous. Analogies and links with the literature on machine learning methods, missing data and imputation are drawn. A difference LASSO algorithm is defined, along with its multiple imputation analogues. The procedures are illustrated using a well-known right heart catheterization dataset. PMID:25628185

Marital status and survival in patients with renal cell carcinoma.

PubMed

Li, Yan; Zhu, Ming-Xi; Qi, Si-Hua

2018-04-01

Previous studies have shown that marital status is an independent prognostic factor for survival in several types of cancer. In this study, we investigated the effects of marital status on survival outcomes among renal cell carcinoma (RCC) patients.We identified patients diagnosed with RCC between 1973 and 2013 from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan-Meier analysis and Cox regression were used to identify the effects of marital status on overall survival (OS) and cancer-specific survival (CSS).We enrolled 97,662 eligible RCC patients, including 64,884 married patients, and 32,778 unmarried (9831 divorced/separated, 9692 widowed, and 13,255 single) patients at diagnosis. The 5-year OS and CSS rates of the married, separated/divorced, widowed, and single patients were 73.7%, 69.5%, 58.3%, and 73.2% (OS), and 82.2%, 80.7%, 75.7%, and 83.3% (CSS), respectively. Multivariate Cox regression showed that, compared with married patients, widowed individuals showed poorer OS (hazard ratio, 1.419; 95% confidence interval, 1.370-1.469) and CSS (hazard ratio, 1.210; 95% confidence interval, 1.144-1.279). Stratified analyses and multivariate Cox regression showed that, in the insured and uninsured groups, married patients had better survival outcomes while widowed patients suffered worse OS outcomes; however, this trend was not significant for CSS.In RCC patients, married patients had better survival outcomes while widowed patients tended to suffer worse survival outcomes in terms of both OS and CSS.

Marital status and survival in patients with renal cell carcinoma

PubMed Central

Li, Yan; Zhu, Ming-xi; Qi, Si-hua

2018-01-01

Abstract Previous studies have shown that marital status is an independent prognostic factor for survival in several types of cancer. In this study, we investigated the effects of marital status on survival outcomes among renal cell carcinoma (RCC) patients. We identified patients diagnosed with RCC between 1973 and 2013 from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan–Meier analysis and Cox regression were used to identify the effects of marital status on overall survival (OS) and cancer-specific survival (CSS). We enrolled 97,662 eligible RCC patients, including 64,884 married patients, and 32,778 unmarried (9831 divorced/separated, 9692 widowed, and 13,255 single) patients at diagnosis. The 5-year OS and CSS rates of the married, separated/divorced, widowed, and single patients were 73.7%, 69.5%, 58.3%, and 73.2% (OS), and 82.2%, 80.7%, 75.7%, and 83.3% (CSS), respectively. Multivariate Cox regression showed that, compared with married patients, widowed individuals showed poorer OS (hazard ratio, 1.419; 95% confidence interval, 1.370–1.469) and CSS (hazard ratio, 1.210; 95% confidence interval, 1.144–1.279). Stratified analyses and multivariate Cox regression showed that, in the insured and uninsured groups, married patients had better survival outcomes while widowed patients suffered worse OS outcomes; however, this trend was not significant for CSS. In RCC patients, married patients had better survival outcomes while widowed patients tended to suffer worse survival outcomes in terms of both OS and CSS. PMID:29668592

Factors Associated with Pain Severity in Children with Calcaneal Apophysitis (Sever Disease).

PubMed

James, Alicia M; Williams, Cylie M; Luscombe, Michelle; Hunter, Reshele; Haines, Terry P

2015-08-01

To identify any association between the pain experienced as a result of calcaneal apophysitis, anthropometric data, and lower limb measurements. This study was a cross-sectional study, nested within a wider randomized, comparative efficacy trial. One hundred twenty-four children between the ages of 8 and 14 years with a clinical diagnosis of calcaneal apophysitis were recruited for this study. Of the participating children, 72 were male. The measures recorded were height, weight, waist circumference, body mass index, foot posture, and ankle joint range of motion; comparison with normative values was also completed. Univariate and multivariable regression analyses were undertaken to identify factors associated with the severity of pain experienced (visual analog scale). The children within this study had a higher mean body mass index (P < .001), increased weight (P < .001), and were taller (P < .001) compared with normative values. The children also demonstrated differences in foot posture and ankle joint range of motion. Multivariable regression analyses identified that older participants (P = .046) and those who had experienced pain for longer (P = .043) reported higher pain severity. Children presenting with calcaneal apophysitis were anthropometrically different from their peers and had experienced a lengthy period of pain. Therefore, early management focussing on the anthropometric differences may minimize the intensity and duration of pain experienced. Registered with Australian New Zealand Clinical Trials Registry: ACTRN12609000696291. Copyright © 2015 Elsevier Inc. All rights reserved.

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Effect of Contact Damage on the Strength of Ceramic Materials.

DTIC Science & Technology

1982-10-01

variables that are important to erosion, and a multivariate , linear regression analysis is used to fit the data to the dimensional analysis. The...of Equations 7 and 8 by a multivariable regression analysis (room tem- perature data) Exponent Regression Standard error Computed coefficient of...1980) 593. WEAVER, Proc. Brit. Ceram. Soc. 22 (1973) 125. 39. P. W. BRIDGMAN, "Dimensional Analaysis ", (Yale 18. R. W. RICE, S. W. FREIMAN and P. F

Serum Irisin Predicts Mortality Risk in Acute Heart Failure Patients.

PubMed

Shen, Shutong; Gao, Rongrong; Bei, Yihua; Li, Jin; Zhang, Haifeng; Zhou, Yanli; Yao, Wenming; Xu, Dongjie; Zhou, Fang; Jin, Mengchao; Wei, Siqi; Wang, Kai; Xu, Xuejuan; Li, Yongqin; Xiao, Junjie; Li, Xinli

2017-01-01

Irisin is a peptide hormone cleaved from a plasma membrane protein fibronectin type III domain containing protein 5 (FNDC5). Emerging studies have indicated association between serum irisin and many major chronic diseases including cardiovascular diseases. However, the role of serum irisin as a predictor for mortality risk in acute heart failure (AHF) patients is not clear. AHF patients were enrolled and serum was collected at the admission and all patients were followed up for 1 year. Enzyme-linked immunosorbent assay was used to measure serum irisin levels. To explore predictors for AHF mortality, the univariate and multivariate logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis were used. To determine the role of serum irisin levels in predicting survival, Kaplan-Meier survival analysis was used. In this study, 161 AHF patients were enrolled and serum irisin level was found to be significantly higher in patients deceased in 1-year follow-up. The univariate logistic regression analysis identified 18 variables associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 2 variables namely blood urea nitrogen and serum irisin. ROC curve analysis indicated that blood urea nitrogen and the most commonly used biomarker, NT-pro-BNP, displayed poor prognostic value for AHF (AUCs ≤ 0.700) compared to serum irisin (AUC = 0.753). Kaplan-Meier survival analysis demonstrated that AHF patients with higher serum irisin had significantly higher mortality (P<0.001). Collectively, our study identified serum irisin as a predictive biomarker for 1-year all-cause mortality in AHF patients though large multicenter studies are highly needed. © 2017 The Author(s). Published by S. Karger AG, Basel.

Transport modeling and multivariate adaptive regression splines for evaluating performance of ASR systems in freshwater aquifers

NASA Astrophysics Data System (ADS)

Forghani, Ali; Peralta, Richard C.

2017-10-01

The study presents a procedure using solute transport and statistical models to evaluate the performance of aquifer storage and recovery (ASR) systems designed to earn additional water rights in freshwater aquifers. The recovery effectiveness (REN) index quantifies the performance of these ASR systems. REN is the proportion of the injected water that the same ASR well can recapture during subsequent extraction periods. To estimate REN for individual ASR wells, the presented procedure uses finely discretized groundwater flow and contaminant transport modeling. Then, the procedure uses multivariate adaptive regression splines (MARS) analysis to identify the significant variables affecting REN, and to identify the most recovery-effective wells. Achieving REN values close to 100% is the desire of the studied 14-well ASR system operator. This recovery is feasible for most of the ASR wells by extracting three times the injectate volume during the same year as injection. Most of the wells would achieve RENs below 75% if extracting merely the same volume as they injected. In other words, recovering almost all the same water molecules that are injected requires having a pre-existing water right to extract groundwater annually. MARS shows that REN most significantly correlates with groundwater flow velocity, or hydraulic conductivity and hydraulic gradient. MARS results also demonstrate that maximizing REN requires utilizing the wells located in areas with background Darcian groundwater velocities less than 0.03 m/d. The study also highlights the superiority of MARS over regular multiple linear regressions to identify the wells that can provide the maximum REN. This is the first reported application of MARS for evaluating performance of an ASR system in fresh water aquifers.

Chordee and Penile Shortening Rather Than Voiding Function Are Associated With Patient Dissatisfaction After Urethroplasty.

PubMed

Maciejewski, Conrad C; Haines, Trevor; Rourke, Keith F

2017-05-01

To identify factors that predict patient satisfaction after urethroplasty by prospectively examining patient-reported quality of life scores using 3 validated instruments. A 3-part prospective survey consisting of the International Prostate Symptom Score (IPSS), the International Index of Erectile Function (IIEF) score, and a urethroplasty quality of life survey was completed by patients who underwent urethroplasty preoperatively and at 6 months postoperatively. The quality of life score included questions on genitourinary pain, urinary tract infection (UTI), postvoid dribbling, chordee, shortening, overall satisfaction, and overall health. Data were analyzed using descriptive statistics, paired t test, univariate and multivariate logistic regression analyses, and Wilcoxon signed-rank analysis. Patients were enrolled in the study from February 2011 to December 2014, and a total of 94 patients who underwent a total of 102 urethroplasties completed the study. Patients reported statistically significant improvements in IPSS (P < .001). Ordinal linear regression analysis revealed no association between age, IPSS, or IIEF score and patient satisfaction. Wilcoxon signed-rank analysis revealed significant improvements in pain scores (P = .02), UTI (P < .001), perceived overall health (P = .01), and satisfaction (P < .001). Univariate logistic regression identified a length >4 cm and the absence of UTI, pain, shortening, and chordee as predictors of patient satisfaction. Multivariate analysis of quality of life domain scores identified absence of shortening and absence of chordee as independent predictors of patient satisfaction following urethroplasty (P < .01). Patient voiding function and quality of life improve significantly following urethroplasty, but improvement in voiding function is not associated with patient satisfaction. Chordee status and perceived penile shortening impact patient satisfaction, and should be included in patient-reported outcome measures. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

Local polynomial estimation of heteroscedasticity in a multivariate linear regression model and its applications in economics.

PubMed

Su, Liyun; Zhao, Yanyong; Yan, Tianshun; Li, Fenglan

2012-01-01

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.

Risk factors for highly pathogenic avian influenza in commercial layer chicken farms in bangladesh during 2011.

PubMed

Osmani, M G; Thornton, R N; Dhand, N K; Hoque, M A; Milon, Sk M A; Kalam, M A; Hossain, M; Yamage, M

2014-12-01

A case-control study conducted during 2011 involved 90 randomly selected commercial layer farms infected with highly pathogenic avian influenza type A subtype H5N1 (HPAI) and 175 control farms randomly selected from within 5 km of infected farms. A questionnaire was designed to obtain information about potential risk factors for contracting HPAI and was administered to farm owners or managers. Logistic regression analyses were conducted to identify significant risk factors. A total of 20 of 43 risk factors for contracting HPAI were identified after univariable logistic regression analysis. A multivariable logistic regression model was derived by forward stepwise selection. Both unmatched and matched analyses were performed. The key risk factors identified were numbers of staff, frequency of veterinary visits, presence of village chickens roaming on the farm and staff trading birds. Aggregating these findings with those from other studies resulted in a list of 16 key risk factors identified in Bangladesh. Most of these related to biosecurity. It is considered feasible for Bangladesh to achieve a very low incidence of HPAI. Using the cumulative list of risk factors to enhance biosecurity pertaining to commercial farms would facilitate this objective. © 2013 Blackwell Verlag GmbH.

Risk factors for baclofen pump infection in children: a multivariate analysis.

PubMed

Spader, Heather S; Bollo, Robert J; Bowers, Christian A; Riva-Cambrin, Jay

2016-06-01

OBJECTIVE Intrathecal baclofen infusion systems to manage severe spasticity and dystonia are associated with higher infection rates in children than in adults. Factors unique to this population, such as poor nutrition and physical limitations for pump placement, have been hypothesized as the reasons for this disparity. The authors assessed potential risk factors for infection in a multivariate analysis. METHODS Patients who underwent implantation of a programmable pump and intrathecal catheter for baclofen infusion at a single center between January 1, 2000, and March 1, 2012, were identified in this retrospective cohort study. The primary end point was infection. Potential risk factors investigated included preoperative (i.e., demographics, body mass index [BMI], gastrostomy tube, tracheostomy, previous spinal fusion), intraoperative (i.e., surgeon, antibiotics, pump size, catheter location), and postoperative (i.e., wound dehiscence, CSF leak, and number of revisions) factors. Univariate analysis was performed, and a multivariate logistic regression model was created to identify independent risk factors for infection. RESULTS A total of 254 patients were evaluated. The overall infection rate was 9.8%. Univariate analysis identified young age, shorter height, lower weight, dehiscence, CSF leak, and number of revisions within 6 months of pump placement as significantly associated with infection. Multivariate analysis identified young age, dehiscence, and number of revisions as independent risk factors for infection. CONCLUSIONS Young age, wound dehiscence, and number of revisions were independent risk factors for infection in this pediatric cohort. A low BMI and the presence of either a gastrostomy or tracheostomy were not associated with infection and may not be contraindications for this procedure.

Variable Selection in Logistic Regression.

DTIC Science & Technology

1987-06-01

23 %. AUTIOR(.) S. CONTRACT OR GRANT NUMBE Rf.i %Z. D. Bai, P. R. Krishnaiah and . C. Zhao F49620-85- C-0008 " PERFORMING ORGANIZATION NAME AND AOORESS...d I7 IOK-TK- d 7 -I0 7’ VARIABLE SELECTION IN LOGISTIC REGRESSION Z. D. Bai, P. R. Krishnaiah and L. C. Zhao Center for Multivariate Analysis...University of Pittsburgh Center for Multivariate Analysis University of Pittsburgh Y !I VARIABLE SELECTION IN LOGISTIC REGRESSION Z- 0. Bai, P. R. Krishnaiah

Comparative study of contrast-enhanced ultrasound qualitative and quantitative analysis for identifying benign and malignant breast tumor lumps.

PubMed

Liu, Jian; Gao, Yun-Hua; Li, Ding-Dong; Gao, Yan-Chun; Hou, Ling-Mi; Xie, Ting

2014-01-01

To compare the value of contrast-enhanced ultrasound (CEUS) qualitative and quantitative analysis in the identification of breast tumor lumps. Qualitative and quantitative indicators of CEUS for 73 cases of breast tumor lumps were retrospectively analyzed by univariate and multivariate approaches. Logistic regression was applied and ROC curves were drawn for evaluation and comparison. The CEUS qualitative indicator-generated regression equation contained three indicators, namely enhanced homogeneity, diameter line expansion and peak intensity grading, which demonstrated prediction accuracy for benign and malignant breast tumor lumps of 91.8%; the quantitative indicator-generated regression equation only contained one indicator, namely the relative peak intensity, and its prediction accuracy was 61.5%. The corresponding areas under the ROC curve for qualitative and quantitative analyses were 91.3% and 75.7%, respectively, which exhibited a statistically significant difference by the Z test (P<0.05). The ability of CEUS qualitative analysis to identify breast tumor lumps is better than with quantitative analysis.

Using Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

2008-01-01

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

Medication and Dietary Supplement Interactions among a Low-Income, Hospitalized Patient Population Who Take Cardiac Medications.

PubMed

Gardiner, Paula; Filippelli, Amanda C; Sadikova, Ekaterina; White, Laura F; Jack, Brian W

2015-01-01

Purpose. To identify characteristics associated with the use of potentially harmful combinations of dietary supplements (DS) and cardiac prescription medications in an urban, underserved, inpatient population. Methods. Cardiac prescription medication users were identified to assess the prevalence and risk factors of potentially harmful dietary supplement-prescription medication interactions (PHDS-PMI). We examined sociodemographic and clinical characteristics for crude (χ (2) or t-tests) and adjusted multivariable logistic regression associations with the outcome. Results. Among 558 patients, there were 121 who also used a DS. Of the 110 participants having a PHDS-PMI, 25% were asked about their DS use at admission, 75% had documentation of DS in their chart, and 21% reported the intention to continue DS use after discharge. A multivariable logistic regression model noted that for every additional medication or DS taken the odds of having a PHDS-PMI increase and that those with a high school education are significantly less likely to have a PHDS-PMI than those with a college education. Conclusion. Inpatients at an urban safety net hospital taking a combination of cardiac prescription medications and DS are at a high risk of harmful supplement-drug interactions. Providers must ask about DS use and should consider the potential for interactions when having patient discussions about cardiac medications and DS.

Uterine fibroids at routine second-trimester ultrasound survey and risk of sonographic short cervix.

PubMed

Blitz, Matthew J; Rochelson, Burton; Augustine, Stephanie; Greenberg, Meir; Sison, Cristina P; Vohra, Nidhi

2016-11-01

To determine whether women with sonographically identified uterine fibroids are at higher risk for a short cervix. This retrospective cohort study evaluated all women with singleton gestations who had a routine second-trimester ultrasound at 17-23 weeks gestational age from 2010 to 2013. When fibroids were noted, their presence, number, location and size were recorded. Exclusion criteria included a history of cervical conization or loop electrosurgical excision procedure (LEEP), uterine anomalies, maternal age greater than 40 years, and a previously placed cerclage. The primary variable of interest was short cervix (<25 mm). Secondary variables of interest included gestational age at delivery, mode of delivery, indication for cesarean, malpresentation, birth weight, and Apgar scores. A multivariable logistic regression analysis was performed. Fibroids were identified in 522/10 314 patients (5.1%). In the final multivariable logistic regression model, short cervix was increased in women with fibroids (OR 2.29, 95% CI: 1.40, 3.74). The number of fibroids did not affect the frequency of short cervix. Fibroids were significantly associated with preterm delivery (<37 weeks), primary cesarean, breech presentation, lower birth weight infants, and lower Apgar scores. Women with uterine fibroids may be at higher risk for a short cervix. Fibroids are also associated with several adverse obstetric and neonatal outcomes.

Influences on call outcomes among Veteran callers to the National Veterans Crisis Line

PubMed Central

Britton, Peter C.; Bossarte, Robert M.; Thompson, Caitlin; Kemp, Janet; Conner, Kenneth R.

2016-01-01

This evaluation examined the association of caller and call characteristics with proximal outcomes of Veterans Crisis Line calls. From October 1-7, 2010, 665 Veterans with recent suicidal ideation or a history of attempted suicide called the Veterans Crisis Line, 646 had complete data and were included in the analyses. A multivariable multinomial logistic regression was conducted to identify correlates of a favorable outcome, either a resolution or a referral, when compared to an unfavorable outcome, no resolution or referral. A multivariable logistic regression was used to identify correlates of responder-rated caller risk in a subset of calls. Approximately 84% of calls ended with a favorable outcome, 25% with a resolution and 59% with a referral to a local health care provider. Calls from high-risk callers had greater odds of ending with a referral than without a resolution or referral, as did weekday calls (6:00 am to 5:59 pm EST, Monday through Friday). Responders used caller intent to die and the absence of future plans to determine caller risk. Findings suggest that the Veterans Crisis Line is a useful mechanism for generating referrals for high-risk Veteran callers. Responders appeared to use known risk and protective factors to determine caller risk. PMID:23611446

Landscape controls on total and methyl Hg in the Upper Hudson River basin, New York, USA

USGS Publications Warehouse

Burns, Douglas A.; Riva-Murray, K.; Bradley, P.M.; Aiken, G.R.; Brigham, M.E.

2012-01-01

Approaches are needed to better predict spatial variation in riverine Hg concentrations across heterogeneous landscapes that include mountains, wetlands, and open waters. We applied multivariate linear regression to determine the landscape factors and chemical variables that best account for the spatial variation of total Hg (THg) and methyl Hg (MeHg) concentrations in 27 sub-basins across the 493 km2 upper Hudson River basin in the Adirondack Mountains of New York. THg concentrations varied by sixfold, and those of MeHg by 40-fold in synoptic samples collected at low-to-moderate flow, during spring and summer of 2006 and 2008. Bivariate linear regression relations of THg and MeHg concentrations with either percent wetland area or DOC concentrations were significant but could account for only about 1/3 of the variation in these Hg forms in summer. In contrast, multivariate linear regression relations that included metrics of (1) hydrogeomorphology, (2) riparian/wetland area, and (3) open water, explained about 66% to >90% of spatial variation in each Hg form in spring and summer samples. These metrics reflect the influence of basin morphometry and riparian soils on Hg source and transport, and the role of open water as a Hg sink. Multivariate models based solely on these landscape metrics generally accounted for as much or more of the variation in Hg concentrations than models based on chemical and physical metrics, and show great promise for identifying waters with expected high Hg concentrations in the Adirondack region and similar glaciated riverine ecosystems.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation.

PubMed

Bayar, Belhassen; Bouaynaya, Nidhal; Shterenberg, Roman

2017-03-01

We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly).

Use of an operating microscope during spine surgery is associated with minor increases in operating room times and no increased risk of infection.

PubMed

Basques, Bryce A; Golinvaux, Nicholas S; Bohl, Daniel D; Yacob, Alem; Toy, Jason O; Varthi, Arya G; Grauer, Jonathan N

2014-10-15

Retrospective database review. To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. The American College of Surgeons National Surgical Quality Improvement Program database, which includes data from more than 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without the use of an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. A total of 23,670 elective spine procedures were identified, of which 2226 (9.4%) used an operating microscope. The average patient age was 55.1±14.4 years. The average operative time (incision to closure) was 125.7±82.0 minutes.Microscope use was associated with minor increases in preoperative room time (+2.9 min, P=0.013), operative time (+13.2 min, P<0.001), and total room time (+18.6 min, P<0.001) on multivariate analysis.A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and nonmicroscope groups for occurrence of any infection, superficial surgical site infection, deep surgical site infection, organ space infection, or sepsis/septic shock, regardless of surgery type. We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. 3.

Use of an operating microscope during spine surgery is associated with minor increases in operating room times and no increased risk of infection

PubMed Central

Basques, Bryce A.; Golinvaux, Nicholas S.; Bohl, Daniel D.; Yacob, Alem; Toy, Jason O.; Varthi, Arya G.; Grauer, Jonathan N.

2014-01-01

Study Design Retrospective database review. Objective To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Summary of Background Data Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, which includes data from over 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. Results A total of 23,670 elective spine procedures were identified, of which 2,226 (9.4%) used an operating microscope. The average patient age was 55.1 ± 14.4 years. The average operative time (incision to closure) was 125.7 ± 82.0 minutes. Microscope use was associated with minor increases in preoperative room time (+2.9 minutes, p=0.013), operative time (+13.2 minutes, p<0.001), and total room time (+18.6 minutes, p<0.001) on multivariate analysis. A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and non-microscope groups for occurrence of any infection, superficial surgical site infection (SSI), deep SSI, organ space infection, or sepsis/septic shock, regardless of surgery type. Conclusions We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. PMID:25188600

Development of Predictive Algorithms for Pre-Treatment Motor Deficit and 90-Day Mortality in Spinal Epidural Abscess.

PubMed

Shah, Akash A; Ogink, Paul T; Harris, Mitchel B; Schwab, Joseph H

2018-06-20

Spinal epidural abscess is a high-risk condition that can lead to paralysis or death. It would be of clinical and prognostic utility to identify which subset of patients with spinal epidural abscess is likely to develop a motor deficit or die within 90 days of discharge. We identified all patients ≥18 years of age who were admitted to our hospital system with a diagnosis of spinal epidural abscess during the period of 1993 to 2016. Explanatory variables were collected retrospectively. Bivariate and multivariable logistic regression was performed using these variables to identify independent predictors of motor deficit and 90-day mortality. Nomograms were then constructed to quantify the risk of these outcomes. Of the 1,053 patients we identified with spinal epidural abscess, 362 presented with motor weakness. One hundred and thirty-four patients died within 90 days of discharge, inclusive of those who died during hospitalization. Multivariable logistic regression yielded 8 independent predictors of pre-treatment motor deficit and 8 independent predictors of 90-day mortality. We constructed nomograms that generated a probability of pre-treatment motor deficit or 90-day mortality on the basis of the presence of these factors. By quantifying the risk of pre-treatment motor deficit and 90-day mortality, our nomograms may provide useful prognostic information for the treatment team. Timely treatment of neurologically intact patients with a high risk of developing a motor deficit is necessary to avoid residual motor weakness and improve survival. Therapeutic Level IV. See Instructions for Authors for a complete description of Levels of Evidence.

Frequent hospital admissions in Singapore: clinical risk factors and impact of socioeconomic status.

PubMed

Low, Lian Leng; Tay, Wei Yi; Ng, Matthew Joo Ming; Tan, Shu Yun; Liu, Nan; Lee, Kheng Hock

2018-01-01

Frequent admitters to hospitals are high-cost patients who strain finite healthcare resources. However, the exact risk factors for frequent admissions, which can be used to guide risk stratification and design effective interventions locally, remain unknown. Our study aimed to identify the clinical and sociodemographic risk factors associated with frequent hospital admissions in Singapore. An observational study was conducted using retrospective 2014 data from the administrative database at Singapore General Hospital, Singapore. Variables were identified a priori and included patient demographics, comorbidities, prior healthcare utilisation, and clinical and laboratory variables during the index admission. Multivariate logistic regression analysis was used to identify independent risk factors for frequent admissions. A total of 16,306 unique patients were analysed and 1,640 (10.1%) patients were classified as frequent admitters. On multivariate logistic regression, 16 variables were independently associated with frequent hospital admissions, including age, cerebrovascular disease, history of malignancy, haemoglobin, serum creatinine, serum albumin, and number of specialist outpatient clinic visits, emergency department visits, admissions preceding index admission and medications dispensed at discharge. Patients staying in public rental housing had a 30% higher risk of being a frequent admitter after adjusting for demographics and clinical conditions. Our study, the first in our knowledge to examine the clinical risk factors for frequent admissions in Singapore, validated the use of public rental housing as a sensitive indicator of area-level socioeconomic status in Singapore. These risk factors can be used to identify high-risk patients in the hospital so that they can receive interventions that reduce readmission risk. Copyright: © Singapore Medical Association

Novel risk score of contrast-induced nephropathy after percutaneous coronary intervention.

PubMed

Ji, Ling; Su, XiaoFeng; Qin, Wei; Mi, XuHua; Liu, Fei; Tang, XiaoHong; Li, Zi; Yang, LiChuan

2015-08-01

Contrast-induced nephropathy (CIN) post-percutaneous coronary intervention (PCI) is a major cause of acute kidney injury. In this study, we established a comprehensive risk score model to assess risk of CIN after PCI procedure, which could be easily used in a clinical environment. A total of 805 PCI patients, divided into analysis cohort (70%) and validation cohort (30%), were enrolled retrospectively in this study. Risk factors for CIN were identified using univariate analysis and multivariate logistic regression in the analysis cohort. Risk score model was developed based on multiple regression coefficients. Sensitivity and specificity of the new risk score system was validated in the validation cohort. Comparisons between the new risk score model and previous reported models were applied. The incidence of post-PCI CIN in the analysis cohort (n = 565) was 12%. Considerably high CIN incidence (50%) was observed in patients with chronic kidney disease (CKD). Age >75, body mass index (BMI) >25, myoglobin level, cardiac function level, hypoalbuminaemia, history of chronic kidney disease (CKD), Intra-aortic balloon pump (IABP) and peripheral vascular disease (PVD) were identified as independent risk factors of post-PCI CIN. A novel risk score model was established using multivariate regression coefficients, which showed highest sensitivity and specificity (0.917, 95%CI 0.877-0.957) compared with previous models. A new post-PCI CIN risk score model was developed based on a retrospective study of 805 patients. Application of this model might be helpful to predict CIN in patients undergoing PCI procedure. © 2015 Asian Pacific Society of Nephrology.

Analysis of threats to research validity introduced by audio recording clinic visits: Selection bias, Hawthorne effect, both, or neither?

PubMed Central

Henry, Stephen G.; Jerant, Anthony; Iosif, Ana-Maria; Feldman, Mitchell D.; Cipri, Camille; Kravitz, Richard L.

2015-01-01

Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient-clinician interactions Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P=0.003) and having worked longer at their current practice (P=0.02) were associated with increased likelihood of consent. For patients, white race (P=0.002) and diabetes (P=0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any dependent variables. Practice Implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting. PMID:25837372

Intracerebral hemorrhage after external ventricular drain placement: an evaluation of risk factors for post-procedural hemorrhagic complications.

PubMed

Rowe, A Shaun; Rinehart, Derrick R; Lezatte, Stephanie; Langdon, J Russell

2018-03-07

The objective of this study was to evaluate and identify the risk factors for developing a new or enlarged intracranial hemorrhage (ICH) after the placement of an external ventricular drain. A single center, nested case-control study of individuals who received an external ventricular drain from June 1, 2011 to June 30, 2014 was conducted at a large academic medical center. A bivariate analysis was conducted to compare those individuals who experienced a post-procedural intracranial hemorrhage to those who did not experience a new bleed. The variables identified as having a p-value less than 0.15 in the bivariate analysis were then evaluated using a multivariate logistic regression model. Twenty-seven of the eighty-one study participants experienced a new or enlarged intracranial hemorrhage after the placement of an external ventricular drain. Of these twenty-seven patients, 6 individuals received an antiplatelet within ninety-six hours of external ventricular drain placement (p = 0.024). The multivariate logistic regression model identified antiplatelet use within 96 h of external ventricular drain insertion as an independent risk factor for post-EVD ICH (OR 13.1; 95% CI 1.95-88.6; p = 0.008). Compared to those study participants who did not receive an antiplatelet within 96 h of external ventricular drain placement, those participants who did receive an antiplatelet were 13.1 times more likely to exhibit a new or enlarged intracranial hemorrhage.

Incidence and timing of presentation of necrotizing enterocolitis in preterm infants.

PubMed

Yee, Wendy H; Soraisham, Amuchou Singh; Shah, Vibhuti S; Aziz, Khalid; Yoon, Woojin; Lee, Shoo K

2012-02-01

To examine the variation in the incidence and to identify the timing of the presentation of necrotizing enterocolitis (NEC) in a cohort of preterm infants within the Canadian Neonatal Network (CNN). This was a population-based cohort of 16 669 infants with gestational age (GA) <33 weeks, admitted to 25 NICUs participating in the CNN between January 1, 2003, and December 31(,) 2008. Variations in NEC incidence among the participating NICUs for the study period were examined. We categorized early-onset NEC as occurring at <14 days of age and late-onset NEC occurring at ≥14 days. Multivariate logistic regression analysis was performed to identify risk factors for early-onset NEC. The overall incidence of NEC was 5.1%, with significant variation in the risk adjusted incidence among the participating NICUs in the CNN. Early-onset NEC occurred at a mean of 7 days compared with 32 days for late-onset NEC. Early-onset NEC infants had lower incidence of respiratory distress syndrome, patent ductus treated with indomethacin, less use of postnatal steroids, and shorter duration of ventilation days. Multivariate logistic regression analysis identified that greater GA and vaginal delivery were associated with increased risk of early-onset NEC. Among infants <33 weeks' gestation, NEC appears to present at mean age of 7 days in more mature infants, whereas onset of NEC is delayed to 32 days of age in smaller, lower GA infants. Further studies are required to understand the etiology of this disease process.

Identifying patients with cost-related medication non-adherence: a big-data approach.

PubMed

Zhang, James X; Meltzer, David O

2016-08-01

Millions of Americans encounter access barriers to medication due to cost; however, to date, there is no effective screening tool that identifies patients at risk of cost-related medication non-adherence (CRN). By utilizing a big-data approach to combining the survey data and electronic health records (EHRs), this study aimed to develop a method of identifying patients at risk of CRN. CRN data were collected by surveying patients about CRN behaviors in the past 3 months. By matching the dates of patients' receipt of monthly Social Security (SS) payments and the dates of prescription orders for 559 Medicare beneficiaries who were primary SS claimants at high risk of hospitalization in an urban academic medical center, this study identified patients who ordered their outpatient prescription within 2 days of receipt of monthly SS payments in 2014. The predictive power of this information on CRN was assessed using multivariate logistic regression analysis. Among the 559 Medicare patients at high risk of hospitalization, 137 (25%) reported CRN. Among those with CRN, 96 (70%) had ordered prescriptions on receipt of SS payments one or more times in 2014. The area under the Receiver Operating Curve was 0.70 using the predictive model in multivariate logistic regression analysis. With a new approach to combining the survey data and EHR data, patients' behavior in delaying filling of prescription until funds from SS checks become available can be measured, providing some predictive value for cost-related medication non-adherence. The big-data approach is a valuable tool to identify patients at risk of CRN and can be further expanded to the general population and sub-populations, providing a meaningful risk-stratification for CRN and facilitating physician-patient communication to reduce CRN.

Multivariate regression model for predicting lumber grade volumes of northern red oak sawlogs

Treesearch

Daniel A. Yaussy; Robert L. Brisbin

1983-01-01

A multivariate regression model was developed to predict green board-foot yields for the seven common factory lumber grades processed from northern red oak (Quercus rubra L.) factory grade logs. The model uses the standard log measurements of grade, scaling diameter, length, and percent defect. It was validated with an independent data set. The model...

Predictive and mechanistic multivariate linear regression models for reaction development

PubMed Central

Santiago, Celine B.; Guo, Jing-Yao

2018-01-01

Multivariate Linear Regression (MLR) models utilizing computationally-derived and empirically-derived physical organic molecular descriptors are described in this review. Several reports demonstrating the effectiveness of this methodological approach towards reaction optimization and mechanistic interrogation are discussed. A detailed protocol to access quantitative and predictive MLR models is provided as a guide for model development and parameter analysis. PMID:29719711

Multivariate regression model for predicting yields of grade lumber from yellow birch sawlogs

Treesearch

Andrew F. Howard; Daniel A. Yaussy

1986-01-01

A multivariate regression model was developed to predict green board-foot yields for the common grades of factory lumber processed from yellow birch factory-grade logs. The model incorporates the standard log measurements of scaling diameter, length, proportion of scalable defects, and the assigned USDA Forest Service log grade. Differences in yields between band and...

G/SPLINES: A hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) algorithm with Holland's genetic algorithm

NASA Technical Reports Server (NTRS)

Rogers, David

1991-01-01

G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.

Validation of cross-sectional time series and multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents using doubly labeled water

USDA-ARS?s Scientific Manuscript database

Accurate, nonintrusive, and inexpensive techniques are needed to measure energy expenditure (EE) in free-living populations. Our primary aim in this study was to validate cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on observable participant cha...

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

NASA Astrophysics Data System (ADS)

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-03-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

PubMed Central

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-01-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states. PMID:26996254

Regression Models For Multivariate Count Data

PubMed Central

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2016-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data. PMID:28348500

Regression Models For Multivariate Count Data.

PubMed

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2017-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

The association between tranexamic acid and convulsive seizures after cardiac surgery: a multivariate analysis in 11 529 patients.

PubMed

Sharma, V; Katznelson, R; Jerath, A; Garrido-Olivares, L; Carroll, J; Rao, V; Wasowicz, M; Djaiani, G

2014-02-01

Because of a lack of contemporary data regarding seizures after cardiac surgery, we undertook a retrospective analysis of prospectively collected data from 11 529 patients in whom cardiopulmonary bypass was used from January 2004 to December 2010. A convulsive seizure was defined as a transient episode of disturbed brain function characterised by abnormal involuntary motor movements. Multivariate regression analysis was performed to identify independent predictors of postoperative seizures. A total of 100 (0.9%) patients developed postoperative convulsive seizures. Generalised and focal seizures were identified in 68 and 32 patients, respectively. The median (IQR [range]) time after surgery when the seizure occurred was 7 (6-12 [1-216]) h and 8 (6-11 [4-18]) h, respectively. Epileptiform findings on electroencephalography were seen in 19 patients. Independent predictors of postoperative seizures included age, female sex, redo cardiac surgery, calcification of ascending aorta, congestive heart failure, deep hypothermic circulatory arrest, duration of aortic cross-clamp and tranexamic acid. When tested in a multivariate regression analysis, tranexamic acid was a strong independent predictor of seizures (OR 14.3, 95% CI 5.5-36.7; p < 0.001). Patients with convulsive seizures had 2.5 times higher in-hospital mortality rates and twice the length of hospital stay compared with patients without convulsive seizures. Mean (IQR [range]) length of stay in the intensive care unit was 115 (49-228 [32-481]) h in patients with convulsive seizures compared with 26 (22-69 [14-1080]) h in patients without seizures (p < 0.001). Convulsive seizures are a serious postoperative complication after cardiac surgery. As tranexamic acid is the only modifiable factor, its administration, particularly in doses exceeding 80 mg.kg(-1), should be weighed against the risk of postoperative seizures.

Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects.

PubMed

Mostafa, Hamza; Amin, Arwa M; Teh, Chin-Hoe; Murugaiyah, Vikneswaran; Arif, Nor Hayati; Ibrahim, Baharudin

2016-12-01

Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD. To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics. Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC). The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0). This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative fibrosis parameters highly predict esophageal-gastro varices in primary biliary cirrhosis.

PubMed

Wu, Q-M; Zhao, X-Y; You, H

2016-01-01

Esophageal-gastro Varices (EGV) may develop in any histological stages of primary biliary cirrhosis (PBC). We aim to establish and validate quantitative fibrosis (qFibrosis) parameters in portal, septal and fibrillar areas as ideal predictors of EGV in PBC patients. PBC patients with liver biopsy, esophagogastroscopy and Second Harmonic Generation (SHG)/Two-photon Excited Fluorescence (TPEF) microscopy images were retrospectively enrolled in this study. qFibrosis parameters in portal, septal and fibrillar areas were acquired by computer-assisted SHG/TPEF imaging system. Independent predictor was identified using multivariate logistic regression analysis. PBC patients with liver biopsy, esophagogastroscopy and Second Harmonic Generation (SHG)/Two-photon Excited Fluorescence (TPEF) microscopy images were retrospectively enrolled in this study. qFibrosis parameters in portal, septal and fibrillar areas were acquired by computer-assisted SHG/TPEF imaging system. Independent predictor was identified using multivariate logistic regression analysis. Among the forty-nine PBC patients with qFibrosis images, twenty-nine PBC patients with both esophagogastroscopy data and qFibrosis data were selected out for EGV prognosis analysis and 44.8% (13/29) of them had EGV. The qFibrosis parameters of collagen percentage and number of crosslink in fibrillar area, short/long/thin strings number and length/width of the strings in septa area were associated with EGV (p < 0.05). Multivariate logistic analysis showed that the collagen percentage in fibrillar area ≥ 3.6% was an independent factor to predict EGV (odds ratio 6.9; 95% confidence interval 1.6-27.4). The area under receiver operating characteristic (ROC), diagnostic sensitivity and specificity was 0.9, 100% and 75% respectively. Collagen percentage in Collagen percentage in the fibrillar area as an independent predictor can highly predict EGV in PBC patients.

Changes of visual-field global indices after cataract surgery in primary open-angle glaucoma patients.

PubMed

Seol, Bo Ram; Jeoung, Jin Wook; Park, Ki Ho

2016-11-01

To determine changes of visual-field (VF) global indices after cataract surgery and the factors associated with the effect of cataracts on those indices in primary open-angle glaucoma (POAG) patients. A retrospective chart review of 60 POAG patients who had undergone phacoemulsification and intraocular lens insertion was conducted. All of the patients were evaluated with standard automated perimetry (SAP; 30-2 Swedish interactive threshold algorithm; Carl Zeiss Meditec Inc.) before and after surgery. VF global indices before surgery were compared with those after surgery. The best-corrected visual acuity, intraocular pressure (IOP), number of glaucoma medications before surgery, mean total deviation (TD) values, mean pattern deviation (PD) value, and mean TD-PD value were also compared with the corresponding postoperative values. Additionally, postoperative peak IOP and mean IOP were evaluated. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with the effect of cataract on global indices. Mean deviation (MD) after cataract surgery was significantly improved compared with the preoperative MD. Pattern standard deviation (PSD) and visual-field index (VFI) after surgery were similar to those before surgery. Also, mean TD and mean TD-PD were significantly improved after surgery. The posterior subcapsular cataract (PSC) type showed greater MD changes than did the non-PSC type in both the univariate and multivariate logistic regression analyses. In the univariate logistic regression analysis, the preoperative TD-PD value and type of cataract were associated with MD change. However, in the multivariate logistic regression analysis, type of cataract was the only associated factor. None of the other factors was associated with MD change. MD was significantly affected by cataracts, whereas PSD and VFI were not. Most notably, the PSC type showed better MD improvement compared with the non-PSC type after cataract surgery. Clinicians therefore should carefully analyze VF examination results for POAG patients with the PSC type.

Insufficient sleep predicts clinical burnout.

PubMed

Söderström, Marie; Jeding, Kerstin; Ekstedt, Mirjam; Perski, Aleksander; Akerstedt, Torbjörn

2012-04-01

The present prospective study aimed to identify risk factors for subsequent clinical burnout. Three hundred eighty-eight working individuals completed a baseline questionnaire regarding work stress, sleep, mood, health, and so forth. During a 2-year period, 15 subjects (7 women and 8 men) of the total sample were identified as "burnout cases," as they were assessed and referred to treatment for clinical burnout. Questionnaire data from the baseline measurement were used as independent variables in a series of logistic regression analyses to predict clinical burnout. The results identified "too little sleep (< 6 h)" as the main risk factor for burnout development, with adjustment for "work demands," "thoughts of work during leisure time," and "sleep quality." The first two factors were significant predictors in earlier steps of the multivariate regression. The results indicate that insufficient sleep, preoccupation with thoughts of work during leisure time, and high work demands are risk factors for subsequent burnout. The results suggest a chain of causation. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Risk Factors for Brachial Plexus Birth Injury

PubMed Central

Louden, Emily; Marcotte, Michael; Mehlman, Charles; Lippert, William; Huang, Bin; Paulson, Andrea

2018-01-01

Over the course of decades, the incidence of brachial plexus birth injury (BPBI) has increased despite advances in healthcare which would seem to assist in decreasing the rate. The aim of this study is to identify previously unknown risk factors for BPBI and the risk factors with potential to guide preventative measures. A case control study of 52 mothers who had delivered a child with a BPBI injury and 132 mothers who had delivered without BPBI injury was conducted. Univariate, multivariable and logistic regressions identified risk factors and their combinations. The odds of BPBI were 2.5 times higher when oxytocin was used and 3.7 times higher when tachysystole occurred. The odds of BPBI injury are increased when tachysystole and oxytocin occur during the mother’s labor. Logistic regression identified a higher risk for BPBI when more than three of the following variables (>30 lbs gained during the pregnancy, stage 2 labor >61.5 min, mother’s age >26.4 years, tachysystole, or fetal malpresentation) were present in any combination. PMID:29596309

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Treesearch

Michael S. Balshi; A. David McGuire; Paul Duffy; Mike Flannigan; John Walsh; Jerry Melillo

2009-01-01

We developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5o (latitude x longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was...

Differences in passenger car and large truck involved crash frequencies at urban signalized intersections: an exploratory analysis.

PubMed

Dong, Chunjiao; Clarke, David B; Richards, Stephen H; Huang, Baoshan

2014-01-01

The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car-truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Arteriopathy after transarterial chemo-lipiodolization for hepatocellular carcinoma.

PubMed

Matsui, Y; Figi, A; Horikawa, M; Jahangiri Noudeh, Y; Tomozawa, Y; Hashimoto, K; Kaufman, J A; Farsad, K

2017-12-01

The purpose of this study was to investigate the incidence of and the risk factors for arteriopathy in hepatic arteries after transarterial chemo-lipiodolization in patients with hepatocellular carcinoma and the subsequent treatment strategy changes due to arteriopathy. A total of 365 arteries in 167 patients (126 men and 41 women; mean age, 60.4±15.0 [SD] years [range: 18-87 years]) were evaluated for the development of arteriopathy after chemo-lipiodolization with epirubicin- or doxorubicin-Lipiodol ® emulsion. The development of arteriopathy after chemo-lipiodolization was assessed on arteriograms performed during subsequent transarterial treatments. The treatment strategy changes due to arteriopathy, including change in the chemo-lipiodolization method and the application of alternative therapies was also investigated. Univariate and multivariate binary logistic regression models were used to identify risk factors for arteriopathy and subsequent treatment strategy change. One hundred two (27.9%) arteriopathies were detected in 62/167 (37.1%) patients (45 men, 17 women) with a mean age of 63.3±7.1 [SD] years (age range, 50-86 years). The incidence of arteriopathy was highly patient dependent, demonstrating significant correlation in a fully-adjusted multivariate regression model (P<0.0001). Multivariate-adjusted regression analysis with adjustment for the patient effect showed a statistically significant association of super-selective chemo-lipiodolization (P=0.003) with the incidence of arteriopathy. Thirty of the 102 arteriopathies (29.4%) caused a change in treatment strategy. No factors were found to be significantly associated with the treatment strategy change. The incidence of arteriopathy after chemo-lipiodolization is 27.9%. Among them, 29.4% result in a change in treatment strategy. Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Nomogram for prediction of level 2 axillary lymph node metastasis in proven level 1 node-positive breast cancer patients.

PubMed

Jiang, Yanlin; Xu, Hong; Zhang, Hao; Ou, Xunyan; Xu, Zhen; Ai, Liping; Sun, Lisha; Liu, Caigang

2017-09-22

The current management of the axilla in level 1 node-positive breast cancer patients is axillary lymph node dissection regardless of the status of the level 2 axillary lymph nodes. The goal of this study was to develop a nomogram predicting the probability of level 2 axillary lymph node metastasis (L-2-ALNM) in patients with level 1 axillary node-positive breast cancer. We reviewed the records of 974 patients with pathology-confirmed level 1 node-positive breast cancer between 2010 and 2014 at the Liaoning Cancer Hospital and Institute. The patients were randomized 1:1 and divided into a modeling group and a validation group. Clinical and pathological features of the patients were assessed with uni- and multivariate logistic regression. A nomogram based on independent predictors for the L-2-ALNM identified by multivariate logistic regression was constructed. Independent predictors of L-2-ALNM by the multivariate logistic regression analysis included tumor size, Ki-67 status, histological grade, and number of positive level 1 axillary lymph nodes. The areas under the receiver operating characteristic curve of the modeling set and the validation set were 0.828 and 0.816, respectively. The false-negative rates of the L-2-ALNM nomogram were 1.82% and 7.41% for the predicted probability cut-off points of < 6% and < 10%, respectively, when applied to the validation group. Our nomogram could help predict L-2-ALNM in patients with level 1 axillary lymph node metastasis. Patients with a low probability of L-2-ALNM could be spared level 2 axillary lymph node dissection, thereby reducing postoperative morbidity.

Predictors of unsuccessful outcome in cemented femoral revisions using bone impaction grafting; Cox regression analysis of 208 cases.

PubMed

Te Stroet, Martijn A J; Rijnen, Wim H C; Gardeniers, Jean W M; Schreurs, B Willem; Hannink, Gerjon

2016-09-29

Despite improvements in the technique of femoral impaction bone grafting, reconstruction failures still can occur. Therefore, the aim of our study was to determine risk factors for the endpoint re-revision for any reason. We used prospectively collected demographic, clinical and surgical data of all 202 patients who underwent 208 femoral revisions using the X-change Femoral Revision System (Stryker-Howmedica), fresh-frozen morcellised allograft and a cemented polished Exeter stem in our department from 1991 to 2007. Univariable and multivariable Cox regression analyses were performed to identify potential factors associated with re-revision. The mean follow-up was 10.6 (5-21) years. The cumulative re-revision rate was 6.3% (13/208). After univariable selection, sex, age, body mass index (BMI), American Association of Anesthesiologists (ASA) classification, type of removed femoral component, and mesh used for reconstruction were included in multivariable regression analysis.In the multivariable analysis, BMI was the only factor that was significantly associated with the risk of re-revision after bone impaction grafting (BMI ≥30 vs. BMI <30, HR = 6.54 [95% CI 1.89-22.65]; p = 0.003). BMI was the only factor associated with the risk of re-revision for any reason. Besides BMI also other factors, such as Endoklinik score and the type of removed femoral component, can provide guidance in the process of preclinical decision making. With the knowledge obtained from this study, preoperative patient selection, informed consent, and treatment protocols can be better adjusted to the individual patient who needs to undergo a femoral revision with impaction bone grafting.

Does clinical presentation predict response to a nonsurgical chronic disease management program for endstage hip and knee osteoarthritis?

PubMed

Eyles, Jillian P; Lucas, Barbara R; Patterson, Jillian A; Williams, Matthew J; Weeks, Kate; Fransen, Marlene; Hunter, David J

2014-11-01

To identify baseline characteristics of participants who will respond favorably following 6 months of participation in a chronic disease management program for hip and knee osteoarthritis (OA). This prospective cohort study assessed 559 participants at baseline and following 6 months of participation in the Osteoarthritis Chronic Care Program. Response was defined as the minimal clinically important difference of an 18% and 9-point absolute improvement in the Western Ontario and McMaster Universities Arthritis Index global score. Multivariate logistic regression modeling was used to identify predictors of response. Complete data were available for 308 participants. Those who withdrew within the study period were imputed as nonresponders. Three variables were independently associated with response: signal joint (knee vs hip), sex, and high level of comorbidity. Index joint and sex were significant in the multivariate model, but the model was not a sensitive predictor of response. Strong predictors of response to a chronic disease management program for hip and knee OA were not identified. The significant predictors that were found should be considered in future studies.

Performances on the CogState and standard neuropsychological batteries among HIV patients without dementia.

PubMed

Overton, Edgar Turner; Kauwe, John S K; Paul, Robert; Tashima, Karen; Tate, David F; Patel, Pragna; Carpenter, Charles C J; Patty, David; Brooks, John T; Clifford, David B

2011-11-01

HIV-associated neurocognitive disorders remain prevalent but challenging to diagnose particularly among non-demented individuals. To determine whether a brief computerized battery correlates with formal neurocognitive testing, we identified 46 HIV-infected persons who had undergone both formal neurocognitive testing and a brief computerized battery. Simple detection tests correlated best with formal neuropsychological testing. By multivariable regression model, 53% of the variance in the composite Global Deficit Score was accounted for by elements from the brief computerized tool (P < 0.01). These data confirm previous correlation data with the computerized battery. Using the five significant parameters from the regression model in a Receiver Operating Characteristic curve, 90% of persons were accurately classified as being cognitively impaired or not. The test battery requires additional evaluation, specifically for identifying persons with mild impairment, a state upon which interventions may be effective.

Factors associated with obstructive sleep apnea among commercial motor vehicle drivers.

PubMed

Xie, Wen; Chakrabarty, Sangita; Levine, Robert; Johnson, Roy; Talmage, James B

2011-02-01

Identify factors associated with obstructive sleep apnea (OSA) risk during commercial driver medical examinations. A case-control study was conducted at an occupational health clinic by reviewing the commercial driver medical examinations medical records performed from January 2007 to December 2008. The magnitude of association with OSA was estimated with logistic regression. Among 1890 commercial motor vehicle drivers, 51 were confirmed positive for OSA by polysomnography after initial screening by Joint Task Force guidelines, yielding estimated positive predictive values of 78.5% for the screening criteria. Multivariable logistic regression showed that body mass index ≥ 30 (odds ratio: 26.86), hypertension (odds ratio: 2.57), and diabetes (odds ratio: 2.03) were independently associated with OSA. Medical examiners' use of objectively measurable risk factors, such as obesity, history of hypertension, and/or diabetes, rather than symptoms, may be more effective in identifying undiagnosed OSA in commercial drivers during the commercial driver medical examinations.

Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data

PubMed Central

Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian

2015-01-01

In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213

The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

PubMed

Warton, David I; Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.

The PIT-trap—A “model-free” bootstrap procedure for inference about regression models with discrete, multivariate responses

PubMed Central

Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)—common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of “model-free bootstrap”, adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods. PMID:28738071

Identifying Factors That Predict Promotion Time to E-4 and Re-Enlistment Eligibility for U.S. Marine Corps Field Radio Operators

DTIC Science & Technology

2014-12-01

Primary Military Occupational Specialty PRO Proficiency Q-Q Quantile - Quantile RSS Residual Sum of Squares SI Shop Information T&R Training and...construct multivariate linear regression models to estimate Marines’ Computed Tier Score and time to achieve E-4 based on their individual personal...Science (GS) score, ASVAB Mathematics Knowledge (MK) score, ASVAB Paragraph Comprehension (PC) score, weight , and whether a Marine receives a weight

Analysis of Anterior Cervical Discectomy and Fusion Healthcare Costs via the Value-Driven Outcomes Tool.

PubMed

Reese, Jared C; Karsy, Michael; Twitchell, Spencer; Bisson, Erica F

2018-04-11

Examining the costs of single- and multilevel anterior cervical discectomy and fusion (ACDF) is important for the identification of cost drivers and potentially reducing patient costs. A novel tool at our institution provides direct costs for the identification of potential drivers. To assess perioperative healthcare costs for patients undergoing an ACDF. Patients who underwent an elective ACDF between July 2011 and January 2017 were identified retrospectively. Factors adding to total cost were placed into subcategories to identify the most significant contributors, and potential drivers of total cost were evaluated using a multivariable linear regression model. A total of 465 patients (mean, age 53 ± 12 yr, 54% male) met the inclusion criteria for this study. The distribution of total cost was broken down into supplies/implants (39%), facility utilization (37%), physician fees (14%), pharmacy (7%), imaging (2%), and laboratory studies (1%). A multivariable linear regression analysis showed that total cost was significantly affected by the number of levels operated on, operating room time, and length of stay. Costs also showed a narrow distribution with few outliers and did not vary significantly over time. These results suggest that facility utilization and supplies/implants are the predominant cost contributors, accounting for 76% of the total cost of ACDF procedures. Efforts at lowering costs within these categories should make the most impact on providing more cost-effective care.

Is Heart Rate Variability Better Than Routine Vital Signs for Prehospital Identification of Major Hemorrhage

DTIC Science & Technology

2015-01-01

different PRBC transfusion volumes. We performed multivariate regression analysis using HRV metrics and routine vital signs to test the hypothesis that...study sponsors did not have any role in the study design, data collection, analysis and interpretation of data, report writing, or the decision to...primary outcome was hemorrhagic injury plus different PRBC transfusion volumes. We performed multivariate regression analysis using HRV metrics and

Correlates of health-related quality of life in children with drug resistant epilepsy.

PubMed

Conway, Lauryn; Smith, Mary Lou; Ferro, Mark A; Speechley, Kathy N; Connoly, Mary B; Snead, O Carter; Widjaja, Elysa

2016-08-01

Health-related quality of life (HRQL) is compromised in children with epilepsy. The current study aimed to identify correlates of HRQL in children with drug resistant epilepsy. Data came from 115 children enrolled in the Impact of Pediatric Epilepsy Surgery on Health-Related Quality of Life Study (PEPSQOL), a multicenter prospective cohort study. Individual, clinical, and family factors were evaluated. HRQL was measured using the Quality of Life in Childhood Epilepsy Questionnaire (QOLCE), a parent-rated epilepsy-specific instrument, with composite scores ranging from 0 to 100. A series of univariable linear regression analyses were conducted to identify significant associations with HRQL, followed by a multivariable regression analysis. Children had a mean age of 11.85 ± 3.81 years and 65 (56.5%) were male. The mean composite QOLCE score was 60.18 ± 16.69. Child age, sex, age at seizure onset, duration of epilepsy, caregiver age, caregiver education, and income were not significantly associated with HRQL. Univariable regression analyses revealed that a higher number of anti-seizure medications (p = 0.020), lower IQ (p = 0.002), greater seizure frequency (p = 0.048), caregiver unemployment (p = 0.010), higher caregiver depressive and anxiety symptoms (p < 0.001 for both), poorer family adaptation, fewer family resources, and a greater number of family demands (p < 0.001 for all) were associated with lower HRQL. Multivariable regression analysis showed that lower child IQ (β = 0.20, p = 0.004), fewer family resources (β = 0.43, p = 0.012), and caregiver unemployment (β = 6.53, p = 0.018) were associated with diminished HRQL in children. The results emphasize the importance of child cognition and family variables in the HRQL of children with drug-resistant epilepsy. The findings speak to the importance of offering comprehensive care to children and their families to address the nonmedical features that impact on HRQL. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Knowledge, Attitude, and Practices Regarding Vector-borne Diseases in Western Jamaica.

PubMed

Alobuia, Wilson M; Missikpode, Celestin; Aung, Maung; Jolly, Pauline E

2015-01-01

Outbreaks of vector-borne diseases (VBDs) such as dengue and malaria can overwhelm health systems in resource-poor countries. Environmental management strategies that reduce or eliminate vector breeding sites combined with improved personal prevention strategies can help to significantly reduce transmission of these infections. The aim of this study was to assess the knowledge, attitudes, and practices (KAPs) of residents in western Jamaica regarding control of mosquito vectors and protection from mosquito bites. A cross-sectional study was conducted between May and August 2010 among patients or family members of patients waiting to be seen at hospitals in western Jamaica. Participants completed an interviewer-administered questionnaire on sociodemographic factors and KAPs regarding VBDs. KAP scores were calculated and categorized as high or low based on the number of correct or positive responses. Logistic regression analyses were conducted to identify predictors of KAP and linear regression analysis conducted to determine if knowledge and attitude scores predicted practice scores. In all, 361 (85 men and 276 women) people participated in the study. Most participants (87%) scored low on knowledge and practice items (78%). Conversely, 78% scored high on attitude items. By multivariate logistic regression, housewives were 82% less likely than laborers to have high attitude scores; homeowners were 65% less likely than renters to have high attitude scores. Participants from households with 1 to 2 children were 3.4 times more likely to have high attitude scores compared with those from households with no children. Participants from households with at least 5 people were 65% less likely than those from households with fewer than 5 people to have high practice scores. By multivariable linear regression knowledge and attitude scores were significant predictors of practice score. The study revealed poor knowledge of VBDs and poor prevention practices among participants. It identified specific groups that can be targeted with vector control and personal protection interventions to decrease transmission of the infections. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Comparison of Various Anthropometric and Body Fat Indices in Identifying Cardiometabolic Disturbances in Chinese Men and Women

PubMed Central

Zhang, Zhe-qing; Deng, Juan; He, Li-ping; Ling, Wen-hua; Su, Yi-xiang; Chen, Yu-ming

2013-01-01

Background Although many adiposity indices may be used to predict obesity-related health risks, uncertainty remains over which of them performs best. Objective This study compared the predictive capability of direct and indirect adiposity measures in identifying people at higher risk of metabolic abnormalities. Methods This population-based cross-sectional study recruited 2780 women and 1160 men. Body weight and height, waist circumference (WC), and hip circumference (HC) were measured and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were calculated. Body fat (and percentage of fat) over the whole body and the trunk were determined by bioelectrical impedance analysis (BIA). Blood pressure, fasting lipid profiles, and glucose and urine acid levels were assessed. Results In women, the ROC and the multivariate logistic regression analyses both showed that WHtR consistently had the best performance in identifying hypertension, dyslipidemia, hyperuricemia, diabetes/IFG, and metabolic syndrome (MetS). In men, the ROC analysis showed that WHtR was the best predictor of hypertension, WHtR and WC were equally good predictors of dyslipidemia and MetS, and WHtR was the second-best predictor of hyperuricemia and diabetes/IFG. The multivariate logistic regression also found WHtR to be superior in discriminating between MetS, diabetes/IFG, and dyslipidemia while BMI performed better in predicting hypertension and hyperuricemia in men. The BIA-derived indices were the second-worst predictors for all of the endpoints, and HC was the worst. Conclusion WHtR was the best predictor of various metabolic abnormalities. BMI may be used as an alternative measure of obesity for identifying hypertension in both sexes. PMID:23951031

Evaluating treatment outcomes and durations among cases of smear-positive pulmonary tuberculosis in Yemen: a prospective follow-up study.

PubMed

Jaber, Ammar Ali Saleh; Khan, Amer Hayat; Sulaiman, Syed Azhar Syed

2017-01-01

Evaluating outcomes after tuberculosis (TB) treatment can help identify the primary reasons for treatment success or failure. However, Yemen has a treatment success rate that remains below the World Health Organization's target. This study aimed to identify factors that were associated with unsuccessful treatment and prolonged treatment (>1 year). Newly diagnosed cases of smear-positive pulmonary TB were prospectively followed at two centers (Taiz and Alhodidah, Yemen) between April 2014 and March 2015. Standardized forms were used to obtain information from the patients regarding their socio-demographic and clinical characteristics, treatment duration, and TB-related information. Multivariate logistic regression analyses were performed to identify factors that were associated with unsuccessful treatment and prolonged treatment (>1 year). The study included data from 273 cases of newly diagnosed TB, with treatment being successful in 227 cases (83.1%) and unsuccessful in 46 cases (16.9%). Among the 46 patients with unsuccessful treatment, 29 patients (10.6%) stopped treatment, 6 patients (2.2%) transferred to another facility, 6 patients (2.2%) experienced treatment failure, and 5 patients (1.8%) died. The multivariate logistic regression analyses revealed that unsuccessful treatment was associated with female sex, illiterate status, and the presence of comorbidities. Prolonged treatment durations were associated with living in a rural area, smoking, chewing khat, a cough that lasted for >3 weeks at the beginning of treatment, and bilateral cavities during radiography. These results confirm that the treatment success rate in Yemen is lower than the World Health Organization's target for smear-positive pulmonary tuberculosis. Targeting the risk factors that we identified may help improve treatment outcomes. Furthermore, it may not be prudent to re-treat patients using first-line TB drugs after an initial treatment failure.

Patterns of Care in Proton Radiation Therapy for Pediatric Central Nervous System Malignancies

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

Odei, Bismarck; Frandsen, Jonathan E.; Boothe, Dustin

Purpose: Proton beam therapy (PBT) potentially allows for improved sparing of normal tissues, hopefully leading to decreased late side effects in children. Using a national registry, we sought to perform a patterns-of-care analysis for children receiving PBT for primary malignancies of the central nervous system (CNS). Methods and Materials: Using the National Cancer Data Base, we identified pediatric patients with primary CNS malignancies that were diagnosed between 2004 and 2012. We used a standard t test for comparison of means and χ{sup 2} testing to identify differences in demographic and clinical characteristics. Univariate and multivariate logistical regression was applied tomore » identify predictors of PBT use. Results: We identified 4637 pediatric patients receiving radiation therapy from 2004 to 2012, including a subset of 267 patients treated with PBT. We found that PBT use increased with time from <1% in 2004 to 15% in 2012. In multivariate logistical regression, we found the following to be predictors of receipt of PBT: private insurance, the highest income bracket, younger age, living in a metropolitan area, and residing >200 miles from a radiation treatment facility (P<.05). Conclusions: We noted the proportion of children receiving PBT to be significantly increasing over time from <1% to 15% from 2004 to 2012. We also observed important disparities in receipt of PBT based on socioeconomic status. Children from higher-income households and with private insurance were more likely to use this expensive technology. As we continue to demonstrate the potential benefits of PBT in children, efforts are needed to expand the accessibility of PBT for children of all socioeconomic backgrounds and regions of the country.« less

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

Primary Surgery vs Radiotherapy for Early Stage Oral Cavity Cancer.

PubMed

Ellis, Mark A; Graboyes, Evan M; Wahlquist, Amy E; Neskey, David M; Kaczmar, John M; Schopper, Heather K; Sharma, Anand K; Morgan, Patrick F; Nguyen, Shaun A; Day, Terry A

2018-04-01

Objective The goal of this study is to determine the effect of primary surgery vs radiotherapy (RT) on overall survival (OS) in patients with early stage oral cavity squamous cell carcinoma (OCSCC). In addition, this study attempts to identify factors associated with receiving primary RT. Study Design Retrospective cohort study. Setting National Cancer Database (NCDB, 2004-2013). Subjects and Methods Reviewing the NCDB from 2004 to 2013, patients with early stage I to II OCSCC were identified. Kaplan-Meier estimates of survival, Cox regression analysis, and propensity score matching were used to examine differences in OS between primary surgery and primary RT. Multivariable logistic regression analysis was performed to identify factors associated with primary RT. Results Of the 20,779 patients included in the study, 95.4% (19,823 patients) underwent primary surgery and 4.6% (956 patients) underwent primary RT. After adjusting for covariates, primary RT was associated with an increased risk of mortality (adjusted hazard ratio [aHR], 1.97; 99% confidence interval [CI], 1.74-2.22). On multivariable analysis, factors associated with primary RT included age ≥70 years, black race, Medicaid or Medicare insurance, no insurance, oral cavity subsite other than tongue, clinical stage II disease, low-volume treatment facilities, and earlier treatment year. Conclusion Primary RT for early stage OCSCC is associated with increased mortality. Approximately 5% of patients receive primary RT; however, this percentage is decreasing. Patients at highest risk for receiving primary RT include those who are elderly, black, with public insurance, and treated at low-volume facilities.

Spatial variation of pneumonia hospitalization risk in Twin Cities metro area, Minnesota.

PubMed

Iroh Tam, P Y; Krzyzanowski, B; Oakes, J M; Kne, L; Manson, S

2017-11-01

Fine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their census block group, and pneumonia hospitalization risk was analyzed in relation to socioeconomic, demographic and environmental factors. Spatial analyses were performed using Esri's ArcGIS software, and multivariate Poisson regression was used. Hospital encounters of 17 840 patients were included in the analysis. Multivariate Poisson regression identified several significant associations, including a 40% increased risk of pneumonia hospitalization among census block groups with large, compared with small, populations of ⩾65 years, a 56% increased risk among census block groups in the bottom (first) quartile of median household income compared to the top (fourth) quartile, a 44% higher risk in the fourth quartile of average nitrogen dioxide emissions compared with the first quartile, and a 47% higher risk in the fourth quartile of average annual solar insolation compared to the first quartile. After adjusting for income, moving from the first to the second quartile of the race/ethnic diversity index resulted in a 21% significantly increased risk of pneumonia hospitalization. In conclusion, the risk of pneumonia hospitalization at the census-block level is associated with age, income, race/ethnic diversity index, air quality, and solar insolation, and varies by region-specific factors. Identifying correlates using fine spatial analysis provides opportunities for targeted prevention and control.

Socioeconomic Factors Are Associated With Readmission After Lobectomy for Early Stage Lung Cancer.

PubMed

Medbery, Rachel L; Gillespie, Theresa W; Liu, Yuan; Nickleach, Dana C; Lipscomb, Joseph; Sancheti, Manu S; Pickens, Allan; Force, Seth D; Fernandez, Felix G

2016-11-01

Data regarding risk factors for readmissions after surgical resection for lung cancer are limited and largely focus on postoperative outcomes, including complications and hospital length of stay. The current study aims to identify preoperative risk factors for postoperative readmission in early stage lung cancer patients. The National Cancer Data Base was queried for all early stage lung cancer patients with clinical stage T2N0M0 or less who underwent lobectomy in 2010 and 2011. Patients with unplanned readmission within 30 days of hospital discharge were identified. Univariate analysis was utilized to identify preoperative differences between readmitted and not readmitted cohorts; multivariable logistic regression was used to identify risk factors resulting in readmission. In all, 840 of 19,711 patients (4.3%) were readmitted postoperatively. Male patients were more likely to be readmitted than female patients (4.9% versus 3.8%, p < 0.001), as were patients who received surgery at a nonacademic rather than an academic facility (4.6% versus 3.6%; p = 0.001) and had underlying medical comorbidities (Charlson/Deyo score 1+ versus 0; 4.8% versus 3.7%; p < 0.001). Readmitted patients had a longer median hospital length of stay (6 days versus 5; p < 0.001) and were more likely to have undergone a minimally invasive approach (5.1% video-assisted thoracic surgery versus 3.9% open; p < 0.001). In addition to those variables, multivariable logistic regression analysis identified that median household income level, insurance status (government versus private), and geographic residence (metropolitan versus urban versus rural) had significant influence on readmission. The socioeconomic factors identified significantly influence hospital readmission and should be considered during preoperative and postoperative discharge planning for patients with early stage lung cancer. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Prenatal Sonographic Predictors of Neonatal Coarctation of the Aorta.

PubMed

Anuwutnavin, Sanitra; Satou, Gary; Chang, Ruey-Kang; DeVore, Greggory R; Abuel, Ashley; Sklansky, Mark

2016-11-01

To identify practical prenatal sonographic markers for the postnatal diagnosis of coarctation of the aorta. We reviewed the fetal echocardiograms and postnatal outcomes of fetal cases of suspected coarctation of the aorta seen at a single institution between 2010 and 2014. True- and false-positive cases were compared. Logistic regression analysis was used to determine echocardiographic predictors of coarctation of the aorta. Optimal cutoffs for these markers and a multivariable threshold scoring system were derived to discriminate fetuses with coarctation of the aorta from those without coarctation of the aorta. Among 35 patients with prenatal suspicion of coarctation of the aorta, the diagnosis was confirmed postnatally in 9 neonates (25.7% true-positive rate). Significant predictors identified from multivariate analysis were as follows: Z score for the ascending aorta diameter of -2 or less (P = < .001), Z score for the mitral valve annulus of -2 or less (P= .033), Zscore for the transverse aortic arch diameter of -2 or less (P= .028), and abnormal aortic valve morphologic features (P= .026). Among all variables studied, the ascending aortic Z score had the highest sensitivity (78%) and specificity (92%) for detection of coarctation of the aorta. A multivariable threshold scoring system identified fetuses with coarctation of the aorta with still greater sensitivity (89%) and only mildly decreased specificity (88%). The finding of a diminutive ascending aorta represents a powerful and practical prenatal predictor of neonatal coarctation of the aorta. A multivariable scoring system, including dimensions of the ascending and transverse aortas, mitral valve annulus, and morphologic features of the aortic valve, provides excellent sensitivity and specificity. The use of these practical sonographic markers may improve prenatal detection of coarctation of the aorta. © 2016 by the American Institute of Ultrasound in Medicine.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Postoperative Radiotherapy Patterns of Care and Survival Implications for Medulloblastoma in Young Children.

PubMed

Kann, Benjamin H; Park, Henry S; Lester-Coll, Nataniel H; Yeboa, Debra N; Benitez, Viviana; Khan, Atif J; Bindra, Ranjit S; Marks, Asher M; Roberts, Kenneth B

2016-12-01

Postoperative radiotherapy to the craniospinal axis is standard-of-care for pediatric medulloblastoma but is associated with long-term morbidity, particularly in young children. With the advent of modern adjuvant chemotherapy strategies, postoperative radiotherapy deferral has gained acceptance in children younger than 3 years, although it remains controversial in older children. To analyze recent postoperative radiotherapy national treatment patterns and implications for overall survival in patients with medulloblastoma ages 3 to 8 years. Using the National Cancer Data Base, patients ages 3 to 8 years diagnosed as having histologically confirmed medulloblastoma in 2004 to 2012, without distant metastases, who underwent surgery and adjuvant chemotherapy with or without postoperative radiotherapy at facilities nationwide accredited by the Commission on Cancer were identified. Patients were designated as having "postoperative radiotherapy upfront" if they received radiotherapy within 90 days of surgery or "postoperative radiotherapy deferred" otherwise. Factors associated with postoperative radiotherapy deferral were identified using multivariable logistic regression. Overall survival (OS) was compared using Kaplan-Meier analysis with log-rank tests and multivariable Cox regression. Statistical tests were 2-sided. Postoperative radiotherapy utilization and overall survival. Among 816 patients, 123 (15.1%) had postoperative radiotherapy deferred, and 693 (84.9%) had postoperative radiotherapy upfront; 36.8% of 3-year-olds and 4.1% of 8-year-olds had postoperative radiotherapy deferred (P < .001). On multivariable logistic regression, variables associated with postoperative radiotherapy deferral were age (odds ratio [OR], 0.57 per year; 95% CI, 0.49-0.67 per year) and year of diagnosis (OR, 1.18 per year; 95% CI, 1.08-1.29 per year). On survival analysis, with median follow-up of 4.8 years, OS was improved for those receiving postoperative radiotherapy upfront vs postoperative radiotherapy deferred (5-year OS: 82.0% vs 63.4%; P < .001). On multivariable analysis, variables associated with poorer OS were postoperative radiotherapy deferral (hazards ratio [HR], 1.95; 95% CI, 1.15-3.31); stage M1-3 disease (HR, 1.86; 95% CI, 1.10-3.16), and low facility volume (HR, 1.75; 95% CI, 1.04-2.94). Our national database analysis reveals a higher-than-expected and increasing rate of postoperative radiotherapy deferral in children with medulloblastoma ages 3 to 8 years. The analysis suggests that postoperative radiotherapy deferral is associated with worse survival in this age group, even in the modern era of chemotherapy.

Optimizing complex phenotypes through model-guided multiplex genome engineering

DOE PAGES

Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.; ...

2017-05-25

Here, we present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.

Optimizing complex phenotypes through model-guided multiplex genome engineering

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

Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.

Here, we present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.

SPReM: Sparse Projection Regression Model For High-dimensional Linear Regression *

PubMed Central

Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.

2014-01-01

The aim of this paper is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issue of many standard statistical approaches, such as the Hotelling’s T2 test statistic or a mass univariate analysis, for high-dimensional data. We formulate the estimation problem of SPREM as a novel sparse unit rank projection (SURP) problem and propose a fast optimization algorithm for SURP. Furthermore, we extend SURP to the sparse multi-rank projection (SMURP) by adopting a sequential SURP approximation. Theoretically, we have systematically investigated the convergence properties of SURP and the convergence rate of SURP estimates. Our simulation results and real data analysis have shown that SPReM out-performs other state-of-the-art methods. PMID:26527844

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.

Association between serum CA 19-9 and metabolic syndrome: A cross-sectional study.

PubMed

Du, Rui; Cheng, Di; Lin, Lin; Sun, Jichao; Peng, Kui; Xu, Yu; Xu, Min; Chen, Yuhong; Bi, Yufang; Wang, Weiqing; Lu, Jieli; Ning, Guang

2017-11-01

Increasing evidence suggests that serum CA 19-9 is associated with abnormal glucose metabolism. However, data on the association between CA 19-9 and metabolic syndrome is limited. The aim of the present study was to investigate the association between serum CA 19-9 and metabolic syndrome. A cross-sectional study was conducted on 3641 participants aged ≥40 years from the Songnan Community, Baoshan District in Shanghai, China. Logistic regression analysis was used to evaluate the association between serum CA 19-9 and metabolic syndrome. Multivariate logistic regression analysis showed that compared with participants in the first tertile of serum CA 19-9, those in the second and third tertiles had increased odds ratios (OR) for prevalent metabolic syndrome (multivariate adjusted OR 1.46 [95% confidence interval {CI} 1.11-1.92] and 1.51 [95% CI 1.14-1.98]; P trend  = 0.005). In addition, participants with elevated serum CA 19-9 (≥37 U/mL) had an increased risk of prevalent metabolic syndrome compared with those with serum CA 19-9 < 37 U/mL (multivariate adjusted OR 2.10; 95% CI 1.21-3.65). Serum CA 19-9 is associated with an increased risk of prevalent metabolic syndrome. In order to confirm this association and identify potential mechanisms, prospective cohort and mechanic studies should be performed. © 2017 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

Predictive factors that influence treatment outcomes of innovative single incision sling: comparing TVT-Secur to an established transobturator sling for female stress urinary incontinence.

PubMed

Hwang, Eugene; Shin, Ju Hyun; Lim, Jae Sung; Song, Ki Hak; Sul, Chong Koo; Na, Yong Gil

2012-07-01

This study aims to identify independent risk factors for treatment failure of tension-free vaginal tape TVT-Secur (TVT-S) compared to that of the well-established transobturator tape. Of a total of 175 consecutive patients with urodynamically confirmed stress urinary incontinence (SUI) identified between July 2007 and March 2010, 89 patients underwent TVT-S, and 86 underwent TOT. Cure was defined using the Urogenital Distress Inventory as no urinary leakage during physical activity, coughing, or sneezing as reported by patients during a telephone survey. To identify predictors of treatment failure, multivariable logistic regression models were used, and odds ratios (ORs) were calculated using variables identified during univariate analysis. There were more patients with cystocele ≥ grade 2 in the TVT-S group (p = 0.031); otherwise the groups were well matched. After a median follow-up of 32 months (range, 12-44 months), the overall cure rate was 80.6%; it was 70.8% for those treated with TVT-S and 90.7% for those treated with TOT (p = 0.001). In a multivariate model, previous incontinence surgery (OR 27.1, p = 0.005) and a cystocele ≥ grade 2 (OR 3.0, p = 0.020) were independent risk factors influencing the outcome of TVT-S procedures. For the TOT procedures, detrusor overactivity was an independent risk factor in a multivariate model (OR 8.6, p = 0.033). TVT-S could be performed for selected patients, but conventional TOT procedures are still superior to the novel TVT-S device.

Development and validation of prognostic models in metastatic breast cancer: a GOCS study.

PubMed

Rabinovich, M; Vallejo, C; Bianco, A; Perez, J; Machiavelli, M; Leone, B; Romero, A; Rodriguez, R; Cuevas, M; Dansky, C

1992-01-01

The significance of several prognostic factors and the magnitude of their influence on response rate and survival were assessed by means of uni- and multivariate analyses in 362 patients with stage IV (UICC) breast carcinoma receiving combination chemotherapy as first systemic treatment over an 8-year period. Univariate analyses identified performance status and prior adjuvant radiotherapy as predictors of objective regression (OR), whereas the performance status, prior chemotherapy and radiotherapy (adjuvants), white blood cells count, SGOT and SGPT levels, and metastatic pattern were significantly correlated to survival. In multivariate analyses favorable characteristics associated to OR were prior adjuvant radiotherapy, no prior chemotherapy and postmenopausal status. Regarding survival, the performance status and visceral involvement were selected by the Cox model. The predictive accuracy of the logistic and the proportional hazards models was retrospectively tested in the training sample, and prospectively in a new population of 126 patients also receiving combined chemotherapy as first treatment for metastatic breast cancer. A certain overfitting to data in the training sample was observed with the regression model for response. However, the discriminative ability of the Cox model for survival was clearly confirmed.

Psychological distress among re-education through labour camp detainees in Guangxi Autonomous Region, China.

PubMed

Yap, Lorraine; Shu, Su; Zhang, Lei; Liu, Wei; Chen, Yi; Wu, Zunyou; Li, Jianghong; Wand, Handan; Donovan, Basil; Butler, Tony

2017-02-01

There is currently no information about the prevalence of, and factors contributing to psychological distress experienced by re-education through labour camp detainees in China. A cross-sectional face-to-face survey was conducted in three labour camps in Guangxi, China. The questionnaire covered socio-demographic characteristics; sexually transmissible infections (STIs); drug use; psychological distress (K-10); and health service usage and access inside the labour camps. K-10 scores were categorised as ≤30 (low to moderate distress) and  >30 or more (highly distressed). Univariate and multivariate logistic regression models identified factors independently associated with high K-10 scores for men and women separately. In total, 755 detainees, 576 (76%) men and 179 (24%) women, participated in the health survey. The study found 11.6% men versus 11.2% women detainees experienced high psychological distress, but no significant gender differences were observed (p> 0.05). Multivariate logistic regression showed that multiple physical health problems were significantly associated with high psychological distress among men. Drug treatment and forensic mental health services need to be established in detention centres in China to treat more than 10% of detainees with drug use and mental health disorders.

Combining fibre optic Raman spectroscopy and tactile resonance measurement for tissue characterization

NASA Astrophysics Data System (ADS)

Candefjord, Stefan; Nyberg, Morgan; Jalkanen, Ville; Ramser, Kerstin; Lindahl, Olof A.

2010-12-01

Tissue characterization is fundamental for identification of pathological conditions. Raman spectroscopy (RS) and tactile resonance measurement (TRM) are two promising techniques that measure biochemical content and stiffness, respectively. They have potential to complement the golden standard--histological analysis. By combining RS and TRM, complementary information about tissue content can be obtained and specific drawbacks can be avoided. The aim of this study was to develop a multivariate approach to compare RS and TRM information. The approach was evaluated on measurements at the same points on porcine abdominal tissue. The measurement points were divided into five groups by multivariate analysis of the RS data. A regression analysis was performed and receiver operating characteristic (ROC) curves were used to compare the RS and TRM data. TRM identified one group efficiently (area under ROC curve 0.99). The RS data showed that the proportion of saturated fat was high in this group. The regression analysis showed that stiffness was mainly determined by the amount of fat and its composition. We concluded that RS provided additional, important information for tissue identification that was not provided by TRM alone. The results are promising for development of a method combining RS and TRM for intraoperative tissue characterization.

Determinants of children's use of and time spent in fast-food and full-service restaurants.

PubMed

McIntosh, Alex; Kubena, Karen S; Tolle, Glen; Dean, Wesley; Kim, Mi-Jeong; Jan, Jie-Sheng; Anding, Jenna

2011-01-01

Identify parental and children's determinants of children's use of and time spent in fast-food (FF) and full-service (FS) restaurants. Analysis of cross-sectional data. Parents were interviewed by phone; children were interviewed in their homes. Parents and children ages 9-11 or 13-15 from 312 families were obtained via random-digit dialing. Dependent variables were the use of and the time spent in FF and FS restaurants by children. Determinants included parental work schedules, parenting style, and family meal ritual perceptions. Logistic regression was used for multivariate analysis of use of restaurants. Least squares regression was used for multivariate analysis of time spent in restaurants. Significance set at P < .05. Factors related to use of and time spent in FF and FS restaurants included parental work schedules, fathers' use of such restaurants, and children's time spent in the family automobile. Parenting style, parental work, parental eating habits and perceptions of family meals, and children's other uses of their time influence children's use of and time spent in FF and FS restaurants. Copyright © 2011 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

Serum Iron Level Is Associated with Time to Antibiotics in Cystic Fibrosis.

PubMed

Gifford, Alex H; Dorman, Dana B; Moulton, Lisa A; Helm, Jennifer E; Griffin, Mary M; MacKenzie, Todd A

2015-12-01

Serum levels of hepcidin-25, a peptide hormone that reduces blood iron content, are elevated when patients with cystic fibrosis (CF) develop pulmonary exacerbation (PEx). Because hepcidin-25 is unavailable as a clinical laboratory test, we questioned whether a one-time serum iron level was associated with the subsequent number of days until PEx, as defined by the need to receive systemic antibiotics (ABX) for health deterioration. Clinical, biochemical, and microbiological parameters were simultaneously checked in 54 adults with CF. Charts were reviewed to determine when they first experienced a PEx after these parameters were assessed. Time to ABX was compared in subgroups with and without specific attributes. Multivariate linear regression was used to identify parameters that significantly explained variation in time to ABX. In univariate analyses, time to ABX was significantly shorter in subjects with Aspergillus-positive sputum cultures and CF-related diabetes. Multivariate linear regression models demonstrated that shorter time to ABX was associated with younger age, lower serum iron level, and Aspergillus sputum culture positivity. Serum iron, age, and Aspergillus sputum culture positivity are factors associated with shorter time to subsequent PEx in CF adults. © 2015 Wiley Periodicals, Inc.

Use of Pre-exposure Prophylaxis (PrEP) in Young Men Who Have Sex with Men is Associated with Race, Sexual Risk Behavior and Peer Network Size.

PubMed

Kuhns, Lisa M; Hotton, Anna L; Schneider, John; Garofalo, Robert; Fujimoto, Kayo

2017-05-01

Pre-exposure prophylaxis (PrEP) is efficacious to prevent HIV infection, however, uptake among young men who have sex with men (YMSM) is relatively low. The purpose of this study was to describe PrEP use and related factors in a representative sample of YMSM in two cities, Chicago and Houston. YMSM, ages 16-29, were recruited via respondent-driven sampling (RDS) from 2014 to 2016. Correlates of PrEP uptake were assessed in weighted multivariable logistic regression models. A total of 12.2% of participants (of 394) reported ever taking PrEP; Black YMSM had the lowest rates of uptake (4.7%) and Whites the highest (29.5%). In a multivariable regression model, having an HIV positive sex partner, reporting recent group sex, peer network size, and city (Chicago) were significantly and positively associated with use of PrEP, while Black race was negatively associated with it. Given evidence of racial/ethnic disparities in PrEP uptake in this study, further research is needed to identify potential mechanisms of action and points of intervention.

EXTENDING MULTIVARIATE DISTANCE MATRIX REGRESSION WITH AN EFFECT SIZE MEASURE AND THE ASYMPTOTIC NULL DISTRIBUTION OF THE TEST STATISTIC

PubMed Central

McArtor, Daniel B.; Lubke, Gitta H.; Bergeman, C. S.

2017-01-01

Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes. Multivariate distance matrix regression (MDMR) tests the significance of associations of response profile (dis)similarities and a set of predictors using permutation tests. This paper extends MDMR by deriving and empirically validating the asymptotic null distribution of its test statistic, and by proposing an effect size for individual outcome variables, which is shown to recover true associations. These extensions alleviate the computational burden of permutation tests currently used in MDMR and render more informative results, thus making MDMR accessible to new research domains. PMID:27738957

Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic.

PubMed

McArtor, Daniel B; Lubke, Gitta H; Bergeman, C S

2017-12-01

Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes. Multivariate distance matrix regression (MDMR) tests the significance of associations of response profile (dis)similarities and a set of predictors using permutation tests. This paper extends MDMR by deriving and empirically validating the asymptotic null distribution of its test statistic, and by proposing an effect size for individual outcome variables, which is shown to recover true associations. These extensions alleviate the computational burden of permutation tests currently used in MDMR and render more informative results, thus making MDMR accessible to new research domains.

Logistic models--an odd(s) kind of regression.

PubMed

Jupiter, Daniel C

2013-01-01

The logistic regression model bears some similarity to the multivariable linear regression with which we are familiar. However, the differences are great enough to warrant a discussion of the need for and interpretation of logistic regression. Copyright © 2013 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

External Validation of the European Hernia Society Classification for Postoperative Complications after Incisional Hernia Repair: A Cohort Study of 2,191 Patients.

PubMed

Kroese, Leonard F; Kleinrensink, Gert-Jan; Lange, Johan F; Gillion, Jean-Francois

2018-03-01

Incisional hernia is a frequent complication after midline laparotomy. Surgical hernia repair is associated with complications, but no clear predictive risk factors have been identified. The European Hernia Society (EHS) classification offers a structured framework to describe hernias and to analyze postoperative complications. Because of its structured nature, it might prove to be useful for preoperative patient or treatment classification. The objective of this study was to investigate the EHS classification as a predictor for postoperative complications after incisional hernia surgery. An analysis was performed using a registry-based, large-scale, prospective cohort study, including all patients undergoing incisional hernia surgery between September 1, 2011 and February 29, 2016. Univariate analyses and multivariable logistic regression analysis were performed to identify risk factors for postoperative complications. A total of 2,191 patients were included, of whom 323 (15%) had 1 or more complications. Factors associated with complications in univariate analyses (p < 0.20) and clinically relevant factors were included in the multivariable analysis. In the multivariable analysis, EHS width class, incarceration, open surgery, duration of surgery, Altemeier wound class, and therapeutic antibiotic treatment were independent risk factors for postoperative complications. Third recurrence and emergency surgery were associated with fewer complications. Incisional hernia repair is associated with a 15% complication rate. The EHS width classification is associated with postoperative complications. To identify patients at risk for complications, the EHS classification is useful. Copyright © 2017. Published by Elsevier Inc.

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

NASA Technical Reports Server (NTRS)

MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

Parameter estimation of multivariate multiple regression model using bayesian with non-informative Jeffreys’ prior distribution

NASA Astrophysics Data System (ADS)

Saputro, D. R. S.; Amalia, F.; Widyaningsih, P.; Affan, R. C.

2018-05-01

Bayesian method is a method that can be used to estimate the parameters of multivariate multiple regression model. Bayesian method has two distributions, there are prior and posterior distributions. Posterior distribution is influenced by the selection of prior distribution. Jeffreys’ prior distribution is a kind of Non-informative prior distribution. This prior is used when the information about parameter not available. Non-informative Jeffreys’ prior distribution is combined with the sample information resulting the posterior distribution. Posterior distribution is used to estimate the parameter. The purposes of this research is to estimate the parameters of multivariate regression model using Bayesian method with Non-informative Jeffreys’ prior distribution. Based on the results and discussion, parameter estimation of β and Σ which were obtained from expected value of random variable of marginal posterior distribution function. The marginal posterior distributions for β and Σ are multivariate normal and inverse Wishart. However, in calculation of the expected value involving integral of a function which difficult to determine the value. Therefore, approach is needed by generating of random samples according to the posterior distribution characteristics of each parameter using Markov chain Monte Carlo (MCMC) Gibbs sampling algorithm.

Field applications of stand-off sensing using visible/NIR multivariate optical computing

NASA Astrophysics Data System (ADS)

Eastwood, DeLyle; Soyemi, Olusola O.; Karunamuni, Jeevanandra; Zhang, Lixia; Li, Hongli; Myrick, Michael L.

2001-02-01

12 A novel multivariate visible/NIR optical computing approach applicable to standoff sensing will be demonstrated with porphyrin mixtures as examples. The ultimate goal is to develop environmental or counter-terrorism sensors for chemicals such as organophosphorus (OP) pesticides or chemical warfare simulants in the near infrared spectral region. The mathematical operation that characterizes prediction of properties via regression from optical spectra is a calculation of inner products between the spectrum and the pre-determined regression vector. The result is scaled appropriately and offset to correspond to the basis from which the regression vector is derived. The process involves collecting spectroscopic data and synthesizing a multivariate vector using a pattern recognition method. Then, an interference coating is designed that reproduces the pattern of the multivariate vector in its transmission or reflection spectrum, and appropriate interference filters are fabricated. High and low refractive index materials such as Nb2O5 and SiO2 are excellent choices for the visible and near infrared regions. The proof of concept has now been established for this system in the visible and will later be extended to chemicals such as OP compounds in the near and mid-infrared.

Mortality Prediction Model of Septic Shock Patients Based on Routinely Recorded Data

PubMed Central

Carrara, Marta; Baselli, Giuseppe; Ferrario, Manuela

2015-01-01

We studied the problem of mortality prediction in two datasets, the first composed of 23 septic shock patients and the second composed of 73 septic subjects selected from the public database MIMIC-II. For each patient we derived hemodynamic variables, laboratory results, and clinical information of the first 48 hours after shock onset and we performed univariate and multivariate analyses to predict mortality in the following 7 days. The results show interesting features that individually identify significant differences between survivors and nonsurvivors and features which gain importance only when considered together with the others in a multivariate regression model. This preliminary study on two small septic shock populations represents a novel contribution towards new personalized models for an integration of multiparameter patient information to improve critical care management of shock patients. PMID:26557154

Sex-Based Differences in Rates, Causes, and Predictors of Death Among Injection Drug Users in Vancouver, Canada

PubMed Central

Hayashi, Kanna; Dong, Huiru; Marshall, Brandon D. L.; Milloy, Michael-John; Montaner, Julio S. G.; Wood, Evan; Kerr, Thomas

2016-01-01

In the present study, we sought to identify rates, causes, and predictors of death among male and female injection drug users (IDUs) in Vancouver, British Columbia, Canada, during a period of expanded public health interventions. Data from prospective cohorts of IDUs in Vancouver were linked to the provincial database of vital statistics to ascertain rates and causes of death between 1996 and 2011. Mortality rates were analyzed using Poisson regression and indirect standardization. Predictors of mortality were identified using multivariable Cox regression models stratified by sex. Among the 2,317 participants, 794 (34.3%) of whom were women, there were 483 deaths during follow-up, with a rate of 32.1 (95% confidence interval (CI): 29.3, 35.0) deaths per 1,000 person-years. Standardized mortality ratios were 7.28 (95% CI: 6.50, 8.14) for men and 15.56 (95% CI: 13.31, 18.07) for women. During the study period, mortality rates related to infection with human immunodeficiency virus (HIV) declined among men but remained stable among women. In multivariable analyses, HIV seropositivity was independently associated with mortality in both sexes (all P < 0.05). The excess mortality burden among IDUs in our cohorts was primarily attributable to HIV infection; compared with men, women remained at higher risk of HIV-related mortality, indicating a need for sex-specific interventions to reduce mortality among female IDUs in this setting. PMID:26865265

Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values

PubMed Central

Huang, Hairong; Xu, Zanzan; Shao, Xianhong; Wismeijer, Daniel; Sun, Ping; Wang, Jingxiao

2017-01-01

Objectives This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ) values in clinical practice. Methods We collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem) placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement) and T2 (before dental restoration). A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval. Results The need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5). In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2). Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2. Conclusions These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice. PMID:29084260

Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Balaji, R.

2017-12-01

In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

Learning curve for intracranial angioplasty and stenting in single center.

PubMed

Cai, Qiankun; Li, Yongkun; Xu, Gelin; Sun, Wen; Xiong, Yunyun; Sun, Wenshan; Bao, Yuanfei; Huang, Xianjun; Zhang, Yao; Zhou, Lulu; Zhu, Wusheng; Liu, Xinfeng

2014-01-01

To identify the specific caseload to overcome learning curve effect based on data from consecutive patients treated with Intracranial Angioplasty and Stenting (IAS) in our center. The Stenting and Aggressive Medical Management for Preventing Recurrent Stroke and Intracranial Stenosis trial was prematurely terminated owing to the high rate of periprocedural complications in the endovascular arm. To date, there are no data available for determining the essential caseload sufficient to overcome the learning effect and perform IAS with an acceptable level of complications. Between March 2004 and May 2012, 188 consecutive patients with 194 lesions who underwent IAS were analyzed retrospectively. The outcome variables used to assess the learning curve were periprocedural complications (included transient ischemic attack, ischemic stroke, vessel rupture, cerebral hyperperfusion syndrome, and vessel perforation). Multivariable logistic regression analysis was employed to illustrate the existence of learning curve effect on IAS. A risk-adjusted cumulative sum chart was performed to identify the specific caseload to overcome learning curve effect. The overall rate of 30-days periprocedural complications was 12.4% (24/194). After adjusting for case-mix, multivariate logistic regression analysis showed that operator experience was an independent predictor for periprocedural complications. The learning curve of IAS to overcome complications in a risk-adjusted manner was 21 cases. Operator's level of experience significantly affected the outcome of IAS. Moreover, we observed that the amount of experience sufficient for performing IAS in our center was 21 cases. Copyright © 2013 Wiley Periodicals, Inc.

Shared clinical decision making

PubMed Central

AlHaqwi, Ali I.; AlDrees, Turki M.; AlRumayyan, Ahmad; AlFarhan, Ali I.; Alotaibi, Sultan S.; AlKhashan, Hesham I.; Badri, Motasim

2015-01-01

Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences. Results: The study included 236 participants. The most preferred decision-making style was shared decision-making (57%), followed by paternalistic (28%), and informed consumerism (14%). The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio (AOR) =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04), and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04), and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008). Conclusion: Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes. PMID:26620990

Impact of functional status on 6-month mortality in elderly patients with acute venous thromboembolism: results from a prospective cohort.

PubMed

Gómez-Cuervo, Covadonga; Díaz-Pedroche, Carmen; Pérez-Jacoiste Asín, María Asunción; Lalueza, Antonio; Del Pozo, Roberto; Díaz-Simón, Raquel; Trapiello, Francisco; Paredes, Diana; Lumbreras, Carlos

2018-06-05

Functional status linked to a poor outcome in a broad spectrum of medical disorders. Barthel Activities of Daily Life Index (BADLI) is one of the most extended tools to quantify functional dependence. Whether BADLI can help to predict outcomes in elderly patients with acute venous thromboembolism (VTE) is unknown. The current study aimed to ascertain the influence of BADLI on 6-month all-cause mortality in aged patients with VTE. This is a prospective observational study. We included consecutive patients older than 75-year-old with an acute VTE between April 2015 and April 2017. We analyzed several variables as mortality predictors, including BADLI-measured functional status. Afterward, we performed a multivariate analysis, using logistic regression, to identify all-cause mortality independent predictive factors. Two hundred and two subjects were included. Thirty-five (17%) patients died in the first 6 months. The leading cause of death was cancer (59%). After multivariable logistic regression, we identified BADLI and Charlson index as independent predictors for 6-months mortality [BADLI (every decrease of 10 points) OR 1.21 95% CI (1.03-1.42) and Charlson index OR 1.71 95% CI (1.21-2.43)]. Body mass index (BMI) values were inversely related to mortality [OR 0.85 95% CI (0.75-0.95)]. In conclusion, BADLI, BMI, and Charlson index scores are independent predictive factors for 6-month all-cause mortality in old patients with VTE.

Housing Instability Among Current and Former Welfare Recipients

PubMed Central

Phinney, Robin; Danziger, Sheldon; Pollack, Harold A.; Seefeldt, Kristin

2007-01-01

Objectives. We examined correlates of eviction and homelessness among current and former welfare recipients from 1997 to 2003 in an urban Michigan community. Methods. Longitudinal cohort data were drawn from the Women’s Employment Study, a representative panel study of mothers who were receiving cash welfare in February 1997. We used logistic regression analysis to identify risk factors for both eviction and homelessness over the survey period. Results. Twenty percent (95% confidence interval [CI]=16%, 23%) of respondents were evicted and 12% (95% CI=10%, 15%) experienced homelessness at least once between fall 1997 and fall 2003. Multivariate analyses indicated 2 consistent risk factors: having less than a high school education and having used illicit drugs other than marijuana. Mental and physical health problems were significantly associated with homelessness but not evictions. A multivariate screening algorithm achieved 75% sensitivity and 67% specificity in identifying individuals at risk for homelessness. A corresponding algorithm for eviction achieved 75% sensitivity and 50% specificity. Conclusions. The high prevalence of housing instability among our respondents suggests the need to better target housing assistance and other social services to current and former welfare recipients with identifiable personal problems. PMID:17267717

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.

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

The genetic effect of copy number variations on the risk of alcoholism in a Korean population.

PubMed

Bae, Joon Seol; Jung, Myung Hun; Lee, Boung Chul; Cheong, Hyun Sub; Park, Byung Lae; Kim, Lyoung Hyo; Kim, Jeong-Hyun; Pasaje, Charisse Flerida A; Lee, Jin Sol; Jung, Kyoung Hwa; Chai, Young Gyu; Shin, Hyoung Doo; Choi, Ihn-Geun

2012-01-01

Alcoholism, a chronic behavioral disorder characterized by excessive alcohol consumption, has been a leading cause of morbidity and premature death. This condition is believed to be influenced by genetic factors. As copy number variation (CNV) has been recently discovered in human genome, genomic diversity of human genome is more frequent than previously thought. Many studies have reported evidences that CNV is associated with the development of complex diseases. In this study, we hypothesized that CNV can predict the risk of alcoholism. Using the Illumina HumanHap660W-Quad BeadChip (∼660 k markers), genome-wide genotyping was performed to obtain signal and allelic intensities from 116 alcoholic cases and 1,022 healthy controls (total n = 1,138) in a Korean population. To identify alcoholism-associated CNV regions, we performed a genome-wide association analysis, using multivariate logistic regression model controlling for age and gender. We identified a total of 255,732 individual CNVs and 3,261 CNV regions (1,067 common CNV regions, frequency > 1%) in this study. Results from multivariate logistic regression showed that the chr20:61195302-61195978 regions were significantly associated with the risk of alcoholism after multiple corrections (p = 5.02E-05, p(corr) = 0.04). Most of the identified variations in this study overlapped with the previously reported CNVs in the Database of Genomic Variants (95.3%). The identified CNVs, which encompassed 3,226 functional genes, were significantly enriched in the cellular part, in the membrane-bound organelle, in the cell part, in developmental processes, in cell communication, in neurological system process, in sensory perception of smell and chemical stimulus, and in olfactory receptor activity. This is the first genome-wide association study to investigate the relationship between common CNV and alcoholism. Our results suggest that the newly identified CNV regions may contribute to the development of alcoholism. Copyright © 2011 by the Research Society on Alcoholism.

Newer classification and regression tree techniques: Bagging and Random Forests for ecological prediction

Treesearch

Anantha M. Prasad; Louis R. Iverson; Andy Liaw; Andy Liaw

2006-01-01

We evaluated four statistical models - Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS) - for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model.

Low creatinine clearance is a risk factor for D2 gastrectomy after neoadjuvant chemotherapy.

PubMed

Hayashi, Tsutomu; Aoyama, Toru; Tanabe, Kazuaki; Nishikawa, Kazuhiro; Ito, Yuichi; Ogata, Takashi; Cho, Haruhiko; Morita, Satoshi; Miyashita, Yumi; Tsuburaya, Akira; Sakamoto, Junichi; Yoshikawa, Takaki

2014-09-01

The feasibility and safety of D2 surgery following neoadjuvant chemotherapy (NAC) has not been fully evaluated in patients with gastric cancer. Moreover, risk factor for surgical complications after D2 gastrectomy following NAC is also unknown. The purpose of the present study was to identify risk factors of postoperative complications after D2 surgery following NAC. This study was conducted as an exploratory analysis of a prospective, randomized Phase II trial of NAC. The surgical complications were assessed and classified according to the Clavien-Dindo classification. A uni- and multivariate logistic regression analyses were performed to identify risk factors for morbidity. Among 83 patients who were registered to the Phase II trial, 69 patients received the NAC and D2 gastrectomy. Postoperative complications were identified in 18 patients and the overall morbidity rate was 26.1 %. The results of univariate and multivariate analyses of various factors for overall operative morbidity, creatinine clearance (CCr) ≤ 60 ml/min (P = 0.016) was identified as sole significant independent risk factor for overall morbidity. Occurrence of pancreatic fistula was significantly higher in the patients with a low CCr than in those with a high CCr. Low CCr was a significant risk factor for surgical complications in D2 gastrectomy after NAC. Careful attention is required for these patients.

Multivariate Prediction Equations for HbA1c Lowering, Weight Change, and Hypoglycemic Events Associated with Insulin Rescue Medication in Type 2 Diabetes Mellitus: Informing Economic Modeling.

PubMed

Willis, Michael; Asseburg, Christian; Nilsson, Andreas; Johnsson, Kristina; Kartman, Bernt

2017-03-01

Type 2 diabetes mellitus (T2DM) is chronic and progressive and the cost-effectiveness of new treatment interventions must be established over long time horizons. Given the limited durability of drugs, assumptions regarding downstream rescue medication can drive results. Especially for insulin, for which treatment effects and adverse events are known to depend on patient characteristics, this can be problematic for health economic evaluation involving modeling. To estimate parsimonious multivariate equations of treatment effects and hypoglycemic event risks for use in parameterizing insulin rescue therapy in model-based cost-effectiveness analysis. Clinical evidence for insulin use in T2DM was identified in PubMed and from published reviews and meta-analyses. Study and patient characteristics and treatment effects and adverse event rates were extracted and the data used to estimate parsimonious treatment effect and hypoglycemic event risk equations using multivariate regression analysis. Data from 91 studies featuring 171 usable study arms were identified, mostly for premix and basal insulin types. Multivariate prediction equations for glycated hemoglobin A 1c lowering and weight change were estimated separately for insulin-naive and insulin-experienced patients. Goodness of fit (R 2 ) for both outcomes were generally good, ranging from 0.44 to 0.84. Multivariate prediction equations for symptomatic, nocturnal, and severe hypoglycemic events were also estimated, though considerable heterogeneity in definitions limits their usefulness. Parsimonious and robust multivariate prediction equations were estimated for glycated hemoglobin A 1c and weight change, separately for insulin-naive and insulin-experienced patients. Using these in economic simulation modeling in T2DM can improve realism and flexibility in modeling insulin rescue medication. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

[Gender difference in risk factors for depression in community-dwelling elders].

PubMed

Kim, Chul-Gyu; Park, Seungmi

2012-02-01

This study was conducted to compare the degree of depression between men and women and to identify factors influencing their depression. Participants in this cross-sectional descriptive study were 263 persons over 65 years old (men: 103, women: 160). Data were collected through face to face interviews using questionnaires and were done in two urban areas in 2010. Research instruments utilized in this study were SGDS, MMSE-K, SRH, FILE, sleep pattern scale, family and friend support scale, and social support scale. Multivariate regression analysis was performed to identify factors influencing depression in elders. The proportions of participants with depression were significantly different between men and women (52.4% vs. 67.5%). Regression model for depression in elderly men significantly accounted for 54%; disease stress (32%), economic stress (10%), perceived health status (4%), and family support, educational level, age, and hypertension. Regression model for depression in elderly women significantly accounted for 47%; disease stress (25%), perceived social loneliness (8%), friend support (5%), family stress (4%), and sleep satisfaction, and family support. Results demonstrate that depression is an important health problem for elders, and show gender differences for factors influencing depression. These results could be used in the developing depression prevention programs.

Prevalence and characteristics of abuse experiences and depression symptoms among injection drug-using female sex workers in Mexico.

PubMed

Ulibarri, Monica D; Hiller, Sarah P; Lozada, Remedios; Rangel, M Gudelia; Stockman, Jamila K; Silverman, Jay G; Ojeda, Victoria D

2013-01-01

This mixed methods study examined the prevalence and characteristics of physical and sexual abuse and depression symptoms among 624 injection drug-using female sex workers (FSW-IDUs) in Tijuana and Ciudad Juarez, Mexico; a subset of 47 from Tijuana also underwent qualitative interviews. Linear regressions identified correlates of current depression symptoms. In the interviews, FSW-IDUs identified drug use as a method of coping with the trauma they experienced from abuse that occurred before and after age 18 and during the course of sex work. In a multivariate linear regression model, two factors-ever experiencing forced sex and forced sex in the context of sex work-were significantly associated with higher levels of depression symptoms. Our findings suggest the need for integrated mental health and drug abuse services for FSW-IDUs addressing history of trauma as well as for further research on violence revictimization in the context of sex work in Mexico.

Shared Decision-Making among Caregivers and Health Care Providers of Youth with Type 1 Diabetes

PubMed Central

Valenzuela, Jessica M.; Smith, Laura B.; Stafford, Jeanette M.; Andrews, S.; D’Agostino, Ralph B.; Lawrence, Jean M.; Yi-Frazier, Joyce P.; Seid, Michael; Dolan, Lawrence M.

2014-01-01

The present study aimed to examine perceptions of shared decision-making (SDM) in caregivers of youth with type 1 diabetes (T1D). Interview, survey data, and HbA1c assays were gathered from caregivers of 439 youth with T1D aged 3–18 years. Caregiver-report indicated high perceived SDM during medical visits. Multivariable linear regression indicated that greater SDM is associated with lower HbA1c, older child age, and having a pediatric endocrinologist provider. Multiple logistic regression found that caregivers who did not perceive having made any healthcare decisions in the past year were more likely to identify a non-pediatric endocrinologist provider and to report less optimal diabetes self-care. Findings suggest that youth whose caregivers report greater SDM may show benefits in terms of self-care and glycemic control. Future research should examine the role of youth in SDM and how best to identify youth and families with low SDM in order to improve care. PMID:24952739

Prevalence and Characteristics of Abuse Experiences and Depression Symptoms among Injection Drug-Using Female Sex Workers in Mexico

PubMed Central

Ulibarri, Monica D.; Hiller, Sarah P.; Lozada, Remedios; Rangel, M. Gudelia; Stockman, Jamila K.; Silverman, Jay G.; Ojeda, Victoria D.

2013-01-01

This mixed methods study examined the prevalence and characteristics of physical and sexual abuse and depression symptoms among 624 injection drug-using female sex workers (FSW-IDUs) in Tijuana and Ciudad Juarez, Mexico; a subset of 47 from Tijuana also underwent qualitative interviews. Linear regressions identified correlates of current depression symptoms. In the interviews, FSW-IDUs identified drug use as a method of coping with the trauma they experienced from abuse that occurred before and after age 18 and during the course of sex work. In a multivariate linear regression model, two factors—ever experiencing forced sex and forced sex in the context of sex work—were significantly associated with higher levels of depression symptoms. Our findings suggest the need for integrated mental health and drug abuse services for FSW-IDUs addressing history of trauma as well as for further research on violence revictimization in the context of sex work in Mexico. PMID:23737808

Cytochrome P450 (CYP2D6) genotype is associated with elevated systolic blood pressure in preterm infants after discharge from the neonatal intensive care unit.

PubMed

Dagle, John M; Fisher, Tyler J; Haynes, Susan E; Berends, Susan K; Brophy, Patrick D; Morriss, Frank H; Murray, Jeffrey C

2011-07-01

To determine genetic and clinical risk factors associated with elevated systolic blood pressure (ESBP) in preterm infants after discharge from the neonatal intensive care unit (NICU). A convenience cohort of infants born at <32 weeks gestational age was followed after NICU discharge. We retrospectively identified a subgroup of subjects with ESBP (systolic blood pressure [SBP] >90th percentile for term infants). Genetic testing identified alleles associated with ESBP. Multivariate logistic regression analysis was performed for the outcome ESBP, with clinical characteristics and genotype as independent variables. Predictors of ESBP were cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6) (rs28360521) CC genotype (OR, 2.92; 95% CI, 1.48-5.79), adjusted for outpatient oxygen therapy (OR, 4.53; 95% CI, 2.23-8.81) and history of urinary tract infection (OR, 4.68; 95% CI, 1.47-14.86). Maximum SBP was modeled by multivariate linear regression analysis: maximum SBP=84.8 mm Hg + 6.8 mm Hg if cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6) CC genotype + 6.8 mm Hg if discharged on supplemental oxygen + 4.4 mm Hg if received inpatient glucocorticoids (P=.0002). ESBP is common in preterm infants with residual lung disease after discharge from the NICU. This study defines clinical factors associated with ESBP, identifies a candidate gene for further testing, and supports the recommendation to monitor blood pressure before age 3 years, as is suggested for term infants. Copyright © 2011 Mosby, Inc. All rights reserved.

Treatment of esophageal anastomotic leakage with self-expanding metal stents: analysis of risk factors for treatment failure

PubMed Central

Persson, Saga; Rouvelas, Ioannis; Kumagai, Koshi; Song, Huan; Lindblad, Mats; Lundell, Lars; Nilsson, Magnus; Tsai, Jon A.

2016-01-01

Background and study aim: The endoscopic placement of self-expandable metallic esophageal stents (SEMS) has become the preferred primary treatment for esophageal anastomotic leakage in many institutions. The aim of this study was to investigate possible risk factors for failure of SEMS-based therapy in patients with esophageal anastomotic leakage. Patients and methods: Beginning in 2003, all patients with an esophageal leak were initially approached and assessed for temporary closure with a SEMS. Until 2014, all patients at the Karolinska University Hospital with a leak from an esophagogastric or esophagojejunal anastomosis were identified. Data regarding the characteristics of the patients and leaks and the treatment outcomes were compiled. Failure of the SEMS treatment strategy was defined as death due to the leak or a major change in management strategy. The risk factors for treatment failure were analyzed with simple and multivariable logistic regression statistics. Results: A total of 447 patients with an esophagogastric or esophagojejunal anastomosis were identified. Of these patients, 80 (18 %) had an anastomotic leak, of whom 46 (58 %) received a stent as first-line treatment. In 29 of these 46 patients, the leak healed without any major change in treatment strategy. Continuous leakage after the application of a stent, decreased physical performance preoperatively, and concomitant esophagotracheal fistula were identified as independent risk factors for failure with multivariable logistic regression analysis. Conclusion: Stent treatment for esophageal anastomotic leakage is successful in the majority of cases. Continuous leakage after initial stent insertion, decreased physical performance preoperatively, and the development of an esophagotracheal fistula decrease the probability of successful treatment. PMID:27092321

Risk factors for 30-day postoperative complications and mortality after below-knee amputation: a study of 2,911 patients from the national surgical quality improvement program.

PubMed

Belmont, Philip J; Davey, Shaunette; Orr, Justin D; Ochoa, Leah M; Bader, Julia O; Schoenfeld, Andrew J

2011-09-01

This investigation sought to evaluate risk factors for morbidity and mortality from a large series of below-knee amputees prospectively entered in a national database. All patients undergoing below-knee amputations in the years 2005-2008 were identified in the database of the National Surgical Quality Improvement Program (NSQIP). Demographic data, medical comorbidities, and medical history were obtained. Mortality and postoperative complications within 30 days of the below-knee amputation were also documented. Chi-square test, univariate, and multivariate logistic regression analyses were used to assess the effect of specific risk factors on mortality, as well as the likelihood of developing major, minor, or any complications developing. Below-knee amputations were performed in 2,911 patients registered in the NSQIP database between 2005 and 2008. The average age of patients was 65.8 years old and 64.3% were male. There was a 7.0% 30-day mortality rate and 1,627 complications occurred in 1,013 patients (34.4%). Multivariate logistic regression analysis identified renal insufficiency, cardiac issues, history of sepsis, steroid use, COPD, and increased patient age as independent predictors of mortality. The most common major complications were return to the operating room (15.6%), wound infection (9.3%), and postoperative sepsis (9.3%). History of sepsis, alcohol use, steroid use, cardiac issues, renal insufficiency, and contaminated/infected wounds were independent predictors of one or more complications developing. Renal disease, cardiac issues, history of sepsis, steroid use, COPD, and increased patient age were identified as predictors of mortality after below-knee amputation. Renal disease, cardiac issues, history of sepsis, steroid use, contaminated/infected wounds, and alcohol use were also found to be predictors of postoperative complications. Published by Elsevier Inc.

Risk of radiation pneumonitis in patients receiving taxane-based trimodality therapy for locally advanced esophageal cancer.

PubMed

Shaikh, Talha; Churilla, Thomas M; Monpara, Pooja; Scott, Walter J; Cohen, Steven J; Meyer, Joshua E

There are limited data regarding clinical and treatment factors associated with radiation pneumonitis (RP) in patients receiving taxane-based trimodality therapy for esophageal cancer. The purpose of this study was to identify predictors of RP in patients undergoing trimodality therapy. We retrospectively reviewed patients undergoing chemoradiation followed by esophagectomy between 2006 and 2011. The association between clinical and dosimetric factors with RP was assessed using χ 2 test and Mann-Whitney U test. Multivariable regression was used to assess the relationship between grade 2+ RP and clinical/dosimetric factors. Receiver operator curves were generated to identify threshold doses for RP. A total of 139 patients were included; 19 (13.7%) patients experienced grade 2+ RP. Patients with upper/middle thoracic tumors (P = .038) and receiving higher radiation doses (P = .038) were more likely to develop grade 2+ RP. There was no association between taxane-based therapy and grade 2+ RP (P = .728). The percent volume of lung receiving 5 Gy (V5; P < .001), 10 Gy (P < .001), 20 Gy (V20; P < .001), and 30 Gy (P < .001) was associated with an increased risk of grade 2+ RP. On multivariable regression, the lung V5 (odds ratio, 1.101; 95% confidence interval, 1.1014-1.195) and V20 (odds ratio, 1.149; 95% confidence interval, 1.1015-1.301) remained associated with grade 2+ RP. A V5 ≤65% and V20 ≤25% were identified as optimal thresholds for increased grade 2+ RP. Dosimetric parameters are strong predictors of symptomatic RP in patients undergoing trimodality therapy for esophageal cancer. Mitigating the risk of RP in these patients should be an important consideration during treatment planning. Copyright © 2016 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Functional Relationships and Regression Analysis.

ERIC Educational Resources Information Center

Preece, Peter F. W.

1978-01-01

Using a degenerate multivariate normal model for the distribution of organismic variables, the form of least-squares regression analysis required to estimate a linear functional relationship between variables is derived. It is suggested that the two conventional regression lines may be considered to describe functional, not merely statistical,…

Predictors of success after laparoscopic gastric bypass: a multivariate analysis of socioeconomic factors.

PubMed

Lutfi, R; Torquati, A; Sekhar, N; Richards, W O

2006-06-01

Laparoscopic gastric bypass (LGB) has proven efficacy in causing significant and durable weight loss. However, the degree of postoperative weight loss and metabolic improvement varies greatly among individuals. Our study is aimed to identify independent predictors of successful weight loss after LGB. Socioeconomic demographics were prospectively collected on patients undergoing LGB. Primary endpoint was percent of excess weight loss (EWL) at 1-year follow-up. Insufficient weight loss was defined as EWL or=52.8%. According to this definition, 147 patients (81.7%) achieved successful weight loss 1 year after LGB. On univariate analysis, preoperative BMI had a significant effect on EWL, with patients with BMI <50 achieving a higher percentage of EWL (91.7% vs 61.6%; p = 0.001). Marriage status was also a significant predictor of successful outcome, with single patients achieving a higher percentage of EWL than married patients (89.8% vs 77.7%; p = 0.04). Race had a noticeable but not statistically significant effect, with Caucasian patients achieving a higher percentage of EWL than African Americans (82.9% vs 60%; p = 0.06). Marital status remained an independent predictor of success in the multivariate logistic regression model after adjusting for covariates. Married patients were at more than two times the risk of failure compared to those who were unmarried (OR 2.6; 95% CI: 1.1-6.5, p = 0.04). Weight loss achieved at 1 year after LGB is suboptimal in superobese patients. Single patients with BMI < 50 had the best chance of achieving greater weight loss.

Trends and variations in the use of adjuvant therapy for patients with head and neck cancer.

PubMed

Chen, Michelle M; Roman, Sanziana A; Yarbrough, Wendell G; Burtness, Barbara A; Sosa, Julie A; Judson, Benjamin L

2014-11-01

The National Comprehensive Cancer Network guidelines recommend that patients with surgically resected head and neck cancers that have adverse pathologic features should receive adjuvant therapy in the form of radiotherapy (RT) or chemoradiation (CRT). To the authors' knowledge, the current study is the first analysis of temporal trends and use patterns of adjuvant therapy for these patients. Patients with head and neck cancer and adverse pathologic features were identified in the National Cancer Data Base (1998-2011). Data were analyzed using chi-square, Student t, and log-rank tests; multivariate logistic regression; and Cox multivariate regression. A total of 73,088 patients were identified: 41.5% had received adjuvant RT, 33.5% had received adjuvant CRT, and 25.0% did not receive any adjuvant therapy. From 1998 to 2011, the increase in the use of adjuvant CRT was greatest for patients with oral cavity (6-fold) and laryngeal (5-fold) cancers. Multivariate analysis demonstrated that Medicare/Medicaid insurance (odds ratio [OR], 1.05; 95% confidence interval [95% CI], 1.01-1.11), distance ≥34 miles from the cancer center (OR, 1.66; 95% CI, 1.59-1.74), and academic (OR, 1.26; 95% CI, 1.20-1.31) and high-volume (OR, 1.10; 95% CI, 1.05-1.15) centers were independently associated with patients not receiving adjuvant therapy. Receipt of adjuvant therapy was found to be independently associated with improved overall survival (hazard ratio, 0.84; 95% CI, 0.81-0.86). Approximately 25% of patients are not receiving National Comprehensive Cancer Network guideline-directed adjuvant therapy. Patient-level and hospital-level factors are associated with variations in the receipt of adjuvant therapy. Further evaluation of these differences in practice patterns is needed to standardize practice and potentially improve the quality of care. Cancer 2014;120:3353-3360. © 2014 American Cancer Society. © 2014 American Cancer Society.

MULTIVARIATE ANALYSIS OF DRINKING BEHAVIOUR IN A RURAL POPULATION

PubMed Central

Mathrubootham, N.; Bashyam, V.S.P.; Shahjahan

1997-01-01

This study was carried out to find out the drinking pattern in a rural population, using multivariate techniques. 386 current users identified in a community were assessed with regard to their drinking behaviours using a structured interview. For purposes of the study the questions were condensed into 46 meaningful variables. In bivariate analysis, 14 variables including dependent variables such as dependence, MAST & CAGE (measuring alcoholic status), Q.F. Index and troubled drinking were found to be significant. Taking these variables and other multivariate techniques too such as ANOVA, correlation, regression analysis and factor analysis were done using both SPSS PC + and HCL magnum mainframe computer with FOCUS package and UNIX systems. Results revealed that number of factors such as drinking style, duration of drinking, pattern of abuse, Q.F. Index and various problems influenced drinking and some of them set up a vicious circle. Factor analysis revealed mainly 3 factors, abuse, dependence and social drinking factors. Dependence could be divided into low/moderate dependence. The implications and practical applications of these tests are also discussed. PMID:21584077

Searching for New Biomarkers and the Use of Multivariate Analysis in Gastric Cancer Diagnostics.

PubMed

Kucera, Radek; Smid, David; Topolcan, Ondrej; Karlikova, Marie; Fiala, Ondrej; Slouka, David; Skalicky, Tomas; Treska, Vladislav; Kulda, Vlastimil; Simanek, Vaclav; Safanda, Martin; Pesta, Martin

2016-04-01

The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Laser ablation molecular isotopic spectroscopy (LAMIS) towards the determination of multivariate LODs via PLS calibration model of 10B and 11B Boric acid mixtures

NASA Astrophysics Data System (ADS)

Harris, C. D.; Profeta, Luisa T. M.; Akpovo, Codjo A.; Johnson, Lewis; Stowe, Ashley C.

2017-05-01

A calibration model was created to illustrate the detection capabilities of laser ablation molecular isotopic spectroscopy (LAMIS) discrimination in isotopic analysis. The sample set contained boric acid pellets that varied in isotopic concentrations of 10B and 11B. Each sample set was interrogated with a Q-switched Nd:YAG ablation laser operating at 532 nm. A minimum of four band heads of the β system B2∑ -> Χ2∑transitions were identified and verified with previous literature on BO molecular emission lines. Isotopic shifts were observed in the spectra for each transition and used as the predictors in the calibration model. The spectra along with their respective 10/11B isotopic ratios were analyzed using Partial Least Squares Regression (PLSR). An IUPAC novel approach for determining a multivariate Limit of Detection (LOD) interval was used to predict the detection of the desired isotopic ratios. The predicted multivariate LOD is dependent on the variation of the instrumental signal and other composites in the calibration model space.

Multivariate analysis of prognostic factors in synovial sarcoma.

PubMed

Koh, Kyoung Hwan; Cho, Eun Yoon; Kim, Dong Wook; Seo, Sung Wook

2009-11-01

Many studies have described the diversity of synovial sarcoma in terms of its biological characteristics and clinical features. Moreover, much effort has been expended on the identification of prognostic factors because of unpredictable behaviors of synovial sarcomas. However, with the exception of tumor size, published results have been inconsistent. We attempted to identify independent risk factors using survival analysis. Forty-one consecutive patients with synovial sarcoma were prospectively followed from January 1997 to March 2008. Overall and progression-free survival for age, sex, tumor size, tumor location, metastasis at presentation, histologic subtype, chemotherapy, radiation therapy, and resection margin were analyzed, and standard multivariate Cox proportional hazard regression analysis was used to evaluate potential prognostic factors. Tumor size (>5 cm), nonlimb-based tumors, metastasis at presentation, and a monophasic subtype were associated with poorer overall survival. Multivariate analysis showed metastasis at presentation and monophasic tumor subtype affected overall survival. For the progression-free survival, monophasic subtype was found to be only 1 prognostic factor. The study confirmed that histologic subtype is the single most important independent prognostic factors of synovial sarcoma regardless of tumor stage.

Factors affecting choice between ureterostomy, ileal conduit and continent reservoir after radical cystectomy: Japanese series.

PubMed

Sugihara, Toru; Yasunaga, Hideo; Horiguchi, Hiromasa; Fujimura, Tetsuya; Fushimi, Kiyohide; Yu, Changhong; Kattan, Michael W; Homma, Yukio

2014-12-01

Little is known about the disparity of choices between three urinary diversions after radical cystectomy, focusing on patient and institutional factors. We identified urothelial carcinoma patients who received radical cystectomy with cutaneous ureterostomy, ileal conduit or continent reservoir using the Japanese Diagnosis Procedure Combination database from 2007 to 2012. Data comprised age, sex, comorbidities (converted into the Charlson index), TNM classification (converted into oncological stage), hospitals' academic status, hospital volume, bed volume and geographical region. Multivariate ordinal logistic regression analyses fitted with the proportional odds model were performed to analyze factors affecting urinary diversion choices. For dependent variables, the three diversions were converted into an ordinal variable in order of complexity: cutaneous ureterostomy (reference), ileal conduit and continent reservoir. Geographical variations were also examined by multivariate logistic regression models. A total of 4790 patients (1131 cutaneous ureterostomies [23.6 %], 2970 ileal conduits [62.0 %] and 689 continent reservoirs [14.4 %]) were included. Ordinal logistic regression analyses showed that male sex, lower age, lower Charlson index, early tumor stage, higher hospital volume (≥3.4 cases/year) and larger bed volume (≥450 beds) were significantly associated with the preference of more complex urinary diversion. Significant geographical disparity was also found. Good patient condition and early oncological status, as well as institutional factors, including high hospital volume, large bed volume and specific geographical regions, are independently related to the likelihood of choosing complex diversions. Recognizing this disparity would help reinforce the need for clinical practice uniformity.

Endpoint in plasma etch process using new modified w-multivariate charts and windowed regression

NASA Astrophysics Data System (ADS)

Zakour, Sihem Ben; Taleb, Hassen

2017-09-01

Endpoint detection is very important undertaking on the side of getting a good understanding and figuring out if a plasma etching process is done in the right way, especially if the etched area is very small (0.1%). It truly is a crucial part of supplying repeatable effects in every single wafer. When the film being etched has been completely cleared, the endpoint is reached. To ensure the desired device performance on the produced integrated circuit, the high optical emission spectroscopy (OES) sensor is employed. The huge number of gathered wavelengths (profiles) is then analyzed and pre-processed using a new proposed simple algorithm named Spectra peak selection (SPS) to select the important wavelengths, then we employ wavelet analysis (WA) to enhance the performance of detection by suppressing noise and redundant information. The selected and treated OES wavelengths are then used in modified multivariate control charts (MEWMA and Hotelling) for three statistics (mean, SD and CV) and windowed polynomial regression for mean. The employ of three aforementioned statistics is motivated by controlling mean shift, variance shift and their ratio (CV) if both mean and SD are not stable. The control charts show their performance in detecting endpoint especially W-mean Hotelling chart and the worst result is given by CV statistic. As the best detection of endpoint is given by the W-Hotelling mean statistic, this statistic will be used to construct a windowed wavelet Hotelling polynomial regression. This latter can only identify the window containing endpoint phenomenon.

High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

Membrane Introduction Mass Spectrometry Combined with an Orthogonal Partial-Least Squares Calibration Model for Mixture Analysis.

PubMed

Li, Min; Zhang, Lu; Yao, Xiaolong; Jiang, Xingyu

2017-01-01

The emerging membrane introduction mass spectrometry technique has been successfully used to detect benzene, toluene, ethyl benzene and xylene (BTEX), while overlapped spectra have unfortunately hindered its further application to the analysis of mixtures. Multivariate calibration, an efficient method to analyze mixtures, has been widely applied. In this paper, we compared univariate and multivariate analyses for quantification of the individual components of mixture samples. The results showed that the univariate analysis creates poor models with regression coefficients of 0.912, 0.867, 0.440 and 0.351 for BTEX, respectively. For multivariate analysis, a comparison to the partial-least squares (PLS) model shows that the orthogonal partial-least squares (OPLS) regression exhibits an optimal performance with regression coefficients of 0.995, 0.999, 0.980 and 0.976, favorable calibration parameters (RMSEC and RMSECV) and a favorable validation parameter (RMSEP). Furthermore, the OPLS exhibits a good recovery of 73.86 - 122.20% and relative standard deviation (RSD) of the repeatability of 1.14 - 4.87%. Thus, MIMS coupled with the OPLS regression provides an optimal approach for a quantitative BTEX mixture analysis in monitoring and predicting water pollution.

Prediction of Gestational Diabetes through NMR Metabolomics of Maternal Blood.

PubMed

Pinto, Joana; Almeida, Lara M; Martins, Ana S; Duarte, Daniela; Barros, António S; Galhano, Eulália; Pita, Cristina; Almeida, Maria do Céu; Carreira, Isabel M; Gil, Ana M

2015-06-05

Metabolic biomarkers of pre- and postdiagnosis gestational diabetes mellitus (GDM) were sought, using nuclear magnetic resonance (NMR) metabolomics of maternal plasma and corresponding lipid extracts. Metabolite differences between controls and disease were identified through multivariate analysis of variable selected (1)H NMR spectra. For postdiagnosis GDM, partial least squares regression identified metabolites with higher dependence on normal gestational age evolution. Variable selection of NMR spectra produced good classification models for both pre- and postdiagnostic GDM. Prediagnosis GDM was accompanied by cholesterol increase and minor increases in lipoproteins (plasma), fatty acids, and triglycerides (extracts). Small metabolite changes comprised variations in glucose (up regulated), amino acids, betaine, urea, creatine, and metabolites related to gut microflora. Most changes were enhanced upon GDM diagnosis, in addition to newly observed changes in low-Mw compounds. GDM prediction seems possible exploiting multivariate profile changes rather than a set of univariate changes. Postdiagnosis GDM is successfully classified using a 26-resonance plasma biomarker. Plasma and extracts display comparable classification performance, the former enabling direct and more rapid analysis. Results and putative biochemical hypotheses require further confirmation in larger cohorts of distinct ethnicities.

Sex-specific predictors of inpatient rehabilitation outcomes after traumatic brain injury

PubMed Central

Chan, Vincy; Mollayeva, Tatyana; Ottenbacher, Kenneth J.; Colantonio, Angela

2016-01-01

Objective To identify sex-specific predictors of inpatient rehabilitation outcomes among patients with a traumatic brain injury (TBI) from a population based perspective. Design Retrospective cohort study Setting Ontario, Canada Participants Patients in inpatient rehabilitation for a TBI within one year of acute care discharge between 2008/09 and 2011/12 (N=1,730, 70% male, 30% female). Interventions None Main Outcome Measures Inpatient rehabilitation length of stay, total Functional Independence Measure (FIM™) score, and motor and cognitive FIM™ ratings at discharge. Results Sex, as a covariate in multivariable linear regression models, was not a significant predictor of rehabilitation outcomes. While many of the predictors examined were similar across males and females, sex-specific multivariable models identified some predictors of rehabilitation outcome that are specific for males and females; mechanism of injury (p<.0001) was a significant predictor of functional outcome only among females while comorbidities (p<.0001) was a significant predictor for males only. Conclusions Predictors of outcomes after inpatient rehabilitation differed by sex, providing evidence for a sex-specific approach in planning and resource allocation for inpatient rehabilitation services for patients with TBI. PMID:26836952

Sex-Specific Predictors of Inpatient Rehabilitation Outcomes After Traumatic Brain Injury.

PubMed

Chan, Vincy; Mollayeva, Tatyana; Ottenbacher, Kenneth J; Colantonio, Angela

2016-05-01

To identify sex-specific predictors of inpatient rehabilitation outcomes among patients with a traumatic brain injury (TBI) from a population-based perspective. Retrospective cohort study. Inpatient rehabilitation. Patients in inpatient rehabilitation for a TBI within 1 year of acute care discharge between 2008/2009 and 2011/2012 (N=1730, 70% men, 30% women). None. Inpatient rehabilitation length of stay, total FIM score, and motor and cognitive FIM ratings at discharge. Sex, as a covariate in multivariable linear regression models, was not a significant predictor of rehabilitation outcomes. Although many of the predictors examined were similar across men and women, sex-specific multivariable models identified some predictors of rehabilitation outcome that are specific for men and women; mechanism of injury (P<.0001) was a significant predictor of functional outcome only among women, whereas comorbidities (P<.0001) was a significant predictor for men only. Predictors of outcomes after inpatient rehabilitation differed by sex, providing evidence for a sex-specific approach in planning and resource allocation for inpatient rehabilitation services for patients with TBI. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Decomposing Racial/Ethnic Disparities in Influenza Vaccination among the Elderly

PubMed Central

Yoo, Byung-Kwang; Hasebe, Takuya; Szilagyi, Peter G.

2015-01-01

While persistent racial/ethnic disparities in influenza vaccination have been reported among the elderly, characteristics contributing to disparities are poorly understood. This study aimed to assess characteristics associated with racial/ethnic disparities in influenza vaccination using a nonlinear Oaxaca-Blinder decomposition method. We performed cross-sectional multivariable logistic regression analyses for which the dependent variable was self-reported receipt of influenza vaccine during the 2010–2011 season among community dwelling non-Hispanic African-American (AA), non-Hispanic White (W), English-speaking Hispanic (EH) and Spanish-speaking Hispanic (SH) elderly, enrolled in the 2011 Medicare Current Beneficiary Survey (MCBS) (un-weighted/weighted N= 6,095/19.2million). Using the nonlinear Oaxaca-Blinder decomposition method, we assessed the relative contribution of seventeen covariates—including socio-demographic characteristics, health status, insurance, access, preference regarding healthcare, and geographic regions —to disparities in influenza vaccination. Unadjusted racial/ethnic disparities in influenza vaccination were 14.1 percentage points (pp) (W-AA disparity, p<.001), 25.7 pp (W-SH disparity, p<.001) and 0.6 pp (W-EH disparity, p>.8). The Oaxaca-Blinder decomposition method estimated that the unadjusted W-AA and W-SH disparities in vaccination could be reduced by only 45% even if AA and SH groups become equivalent to Whites in all covariates in multivariable regression models. The remaining 55% of disparities were attributed to (a) racial/ethnic differences in the estimated coefficients (e.g., odds ratios) in the regression models and (b) characteristics not included in the regression models. Our analysis found that only about 45% of racial/ethnic disparities in influenza vaccination among the elderly could be reduced by equalizing recognized characteristics among racial/ethnic groups. Future studies are needed to identify additional modifiable characteristics causing disparities in influenza vaccination. PMID:25900133

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study.

PubMed

Shi, Xiao; Zhang, Ting-Ting; Hu, Wei-Ping; Ji, Qing-Hai

2017-04-25

The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187-1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266-1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role.

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study

PubMed Central

Shi, Xiao; Zhang, Ting-ting; Hu, Wei-ping; Ji, Qing-hai

2017-01-01

Background The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Results Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187–1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266–1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). Materials and Methods 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Conclusions Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role. PMID:28415710

Predictors of aggression in 3.322 patients with affective disorders and schizophrenia spectrum disorders evaluated in an emergency department setting.

PubMed

Blanco, Emily A; Duque, Laura M; Rachamallu, Vivekananda; Yuen, Eunice; Kane, John M; Gallego, Juan A

2018-05-01

The aim of this study is to determine odds of aggression and associated factors in patients with schizophrenia-spectrum disorders (SSD) and affective disorders who were evaluated in an emergency department setting. A retrospective study was conducted using de-identified data from electronic medical records from 3.322 patients who were evaluated at emergency psychiatric settings. Data extracted included demographic information, variables related to aggression towards people or property in the past 6months, and other factors that could potentially impact the risk of aggression, such as comorbid diagnoses, physical abuse and sexual abuse. Bivariate analyses and multivariate regression analyses were conducted to determine the variables significantly associated with aggression. An initial multivariate regression analysis showed that SSD had 3.1 times the odds of aggression, while bipolar disorder had 2.2 times the odds of aggression compared to unipolar depression. A second regression analysis including bipolar subtypes showed, using unipolar depression as the reference group, that bipolar disorder with a recent mixed episode had an odds ratio (OR) of 4.3, schizophrenia had an OR of 2.6 and bipolar disorder with a recent manic episode had an OR of 2.2. Generalized anxiety disorder was associated with lower odds in both regression analyses. As a whole, the SSD group had higher odds of aggression than the bipolar disorder group. However, after subdividing the groups, schizophrenia had higher odds of aggression than bipolar disorder with a recent manic episode and lower odds of aggression than bipolar disorder with a recent mixed episode. Copyright © 2017 Elsevier B.V. All rights reserved.

Multilevel covariance regression with correlated random effects in the mean and variance structure.

PubMed

Quintero, Adrian; Lesaffre, Emmanuel

2017-09-01

Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multivariate classification of small order watersheds in the Quabbin Reservoir Basin, Massachusetts

USGS Publications Warehouse

Lent, R.M.; Waldron, M.C.; Rader, J.C.

1998-01-01

A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wetland density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wetland density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.

Epidemiology of uveitis among the Chinese population in Taiwan: a population-based study.

PubMed

Hwang, De-Kuang; Chou, Yiing-Jeng; Pu, Cheng-Yun; Chou, Pesus

2012-11-01

This study aimed to investigate the incidence and prevalence of uveitis in Taiwan, and then analyzed the risk factors related to uveitis using multivariate regression. Population-based cohort study using medical claims data. We randomly selected 1 000 000 residents from the Taiwan National Health Insurance Research Database. All participants with correct registry data (96%) were included in the study. The study period was from 2000 to 2008. All types of uveitis were identified using the International Classification of Diseases, 9th revision, Clinical Modification diagnostic codes. The annual incidence and cumulative prevalence of uveitis were calculated. A univariate and a multivariate Poisson regression were used to determine the risk factors associated with uveitis. The first diagnosis of uveitis noted during the study period. The annual cumulative incidence rate of uveitis ranged from 102.2 to 122.0 cases per 100 000 persons over the study period, and the average incidence density was 111.3 cases per 100 000 person-years (95% confidence interval, 108.4-114.1). The cumulative prevalence was found to have increased from 318.8 cases per 100 000 persons in 2003 to 622.7 cases per 100 000 persons in 2008. Anterior uveitis was the most common location and accounted for 77.7% of all incident cases, which was followed by panuveitis, posterior uveitis, and intermediate uveitis. Multivariate regression analysis showed that males, the elderly, and individuals who lived in an urban area had higher incidence rates for uveitis. The epidemiology of uveitis in Taiwan differs from most previous studies in other countries. The incidence of uveitis in Taiwan has increased significantly recently. The elderly and individuals living in urban areas are the populations that are most commonly affected by uveitis. These findings are consistent with suggestions found in several recent studies. Copyright © 2012 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Retention of community college students in online courses

NASA Astrophysics Data System (ADS)

Krajewski, Sarah

The issue of attrition in online courses at higher learning institutions remains a high priority in the United States. A recent rapid growth of online courses at community colleges has been instigated by student demand, as they meet the time constraints many nontraditional community college students have as a result of the need to work and care for dependents. Failure in an online course can cause students to become frustrated with the college experience, financially burdened, or to even give up and leave college. Attrition could be avoided by proper guidance of who is best suited for online courses. This study examined factors related to retention (i.e., course completion) and success (i.e., receiving a C or better) in an online biology course at a community college in the Midwest by operationalizing student characteristics (age, race, gender), student skills (whether or not the student met the criteria to be placed in an AFP course), and external factors (Pell recipient, full/part time status, first term) from the persistence model developed by Rovai. Internal factors from this model were not included in this study. Both univariate analyses and multivariate logistic regression were used to analyze the variables. Results suggest that race and Pell recipient were both predictive of course completion on univariate analyses. However, multivariate analyses showed that age, race, academic load and first term were predictive of completion and Pell recipient was no longer predictive. The univariate results for the C or better showed that age, race, Pell recipient, academic load, and meeting AFP criteria were predictive of success. Multivariate analyses showed that only age, race, and Pell recipient were significant predictors of success. Both regression models explained very little (<15%) of the variability within the outcome variables of retention and success. Therefore, although significant predictors were identified for course completion and retention, there are still many factors that remain unaccounted for in both regression models. Further research into the operationalization of Rovai's model, including internal factors, to predict completion and success is necessary.

Polymer surface functionalities that control human embryoid body cell adhesion revealed by high throughput surface characterization of combinatorial material microarrays

PubMed Central

Yang, Jing; Mei, Ying; Hook, Andrew L.; Taylor, Michael; Urquhart, Andrew J.; Bogatyrev, Said R.; Langer, Robert; Anderson, Daniel G.; Davies, Martyn C.; Alexander, Morgan R.

2010-01-01

High throughput materials discovery using combinatorial polymer microarrays to screen for new biomaterials with new and improved function is established as a powerful strategy. Here we combine this screening approach with high throughput surface characterisation (HT-SC) to identify surface structure-function relationships. We explore how this combination can help to identify surface chemical moieties that control protein adsorption and subsequent cellular response. The adhesion of human embryoid body (hEB) cells to a large number (496) of different acrylate polymers synthesized in a microarray format is screened using a high throughput procedure. To determine the role of the polymer surface properties on hEB cell adhesion, detailed HT-SC of these acrylate polymers is carried out using time of flight secondary ion mass spectrometry (ToF SIMS), x-ray photoelectron spectroscopy (XPS), pico litre drop sessile water contact angle (WCA) measurement and atomic force microscopy (AFM). A structure-function relationship is identified between the ToF SIMS analysis of the surface chemistry after a fibronectin (Fn) pre-conditioning step and the cell adhesion to each spot using the multivariate analysis technique partial least squares (PLS) regression. Secondary ions indicative of the adsorbed Fn correlate with increased cell adhesion whereas glycol and other functionalities from the polymers are identified that reduce cell adhesion. Furthermore, a strong relationship between the ToF SIMS spectra of bare polymers and the cell adhesion to each spot is identified using PLS regression. This identifies a role for both the surface chemistry of the bare polymer and the pre-adsorbed Fn, as-represented in the ToF SIMS spectra, in controlling cellular adhesion. In contrast, no relationship is found between cell adhesion and wettability, surface roughness, elemental or functional surface composition. The correlation between ToF SIMS data of the surfaces and the cell adhesion demonstrates the ability of identifying surface moieties that control protein adsorption and subsequent cell adhesion using ToF SIMS and multivariate analysis. PMID:20832108

Papillary type 2 versus clear cell renal cell carcinoma: Survival outcomes.

PubMed

Simone, G; Tuderti, G; Ferriero, M; Papalia, R; Misuraca, L; Minisola, F; Costantini, M; Mastroianni, R; Sentinelli, S; Guaglianone, S; Gallucci, M

2016-11-01

To compare the cancer specific survival (CSS) between p2-RCC and a Propensity Score Matched (PSM) cohort of cc-RCC patients. Fifty-five (4.6%) patients with p2-RCC and 920 cc-RCC patients were identified within a prospectively maintained institutional dataset of 1205 histologically proved RCC patients treated with either RN or PN. Univariable and multivariable Cox regression analyses were used to identify predictors of CSS after surgical treatment. A 1:2 PSM analysis based on independent predictors of oncologic outcomes was employed and CSS was compared between PSM selected cc-RCC patients using Kaplan-Meier and Cox regression analysis. Overall, 55 (4.6%) p2-RCC and 920 (76.3%) cc-RCC patients were selected from the database; p2-RCC were significantly larger (p = 0.001), more frequently locally advanced (p < 0.001) and node positive (p < 0.001) and had significantly higher Fuhrman grade (p < 0.001) than cc-RCC. On multivariable Cox regression analysis age (p = 0.025), histologic subtype (p = 0.029), pN stage (p = 0.006), size, pT stage, cM stage, sarcomatoid features and Fuhrman grade (all p < 0.001) were independent predictors of CSS. After applying the PSM, 82 cc-RCC selected cases were comparable to 41 p2-RCC for age (p = 0.81), tumor size (p = 0.39), pT (p = 1.00) and pN (p = 0.62) stages, cM stage (p = 0.71) and Fuhrman grade (p = 1). In this PSM cohort, 5 yr CSS was significantly lower in the p2-RCC (63% vs 72.4%; p = 0.047). At multivariable Cox analysis p2 histology was an independent predictor of CSM (HR 2.46, 95% CI 1.04-5.83; p = 0.041). We confirmed the tendency of p2-RCC to present as locally advanced and metastatic disease more frequently than cc-RCC and demonstrated p2-RCC histology as an independent predictor of worse oncologic outcomes. Copyright © 2016 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Flood-frequency prediction methods for unregulated streams of Tennessee, 2000

USGS Publications Warehouse

Law, George S.; Tasker, Gary D.

2003-01-01

Up-to-date flood-frequency prediction methods for unregulated, ungaged rivers and streams of Tennessee have been developed. Prediction methods include the regional-regression method and the newer region-of-influence method. The prediction methods were developed using stream-gage records from unregulated streams draining basins having from 1 percent to about 30 percent total impervious area. These methods, however, should not be used in heavily developed or storm-sewered basins with impervious areas greater than 10 percent. The methods can be used to estimate 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence-interval floods of most unregulated rural streams in Tennessee. A computer application was developed that automates the calculation of flood frequency for unregulated, ungaged rivers and streams of Tennessee. Regional-regression equations were derived by using both single-variable and multivariable regional-regression analysis. Contributing drainage area is the explanatory variable used in the single-variable equations. Contributing drainage area, main-channel slope, and a climate factor are the explanatory variables used in the multivariable equations. Deleted-residual standard error for the single-variable equations ranged from 32 to 65 percent. Deleted-residual standard error for the multivariable equations ranged from 31 to 63 percent. These equations are included in the computer application to allow easy comparison of results produced by the different methods. The region-of-influence method calculates multivariable regression equations for each ungaged site and recurrence interval using basin characteristics from 60 similar sites selected from the study area. Explanatory variables that may be used in regression equations computed by the region-of-influence method include contributing drainage area, main-channel slope, a climate factor, and a physiographic-region factor. Deleted-residual standard error for the region-of-influence method tended to be only slightly smaller than those for the regional-regression method and ranged from 27 to 62 percent.

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 ...

Causal diagrams and multivariate analysis II: precision work.

PubMed

Jupiter, Daniel C

2014-01-01

In this Investigators' Corner, I continue my discussion of when and why we researchers should include variables in multivariate regression. My examination focuses on studies comparing treatment groups and situations for which we can either exclude variables from multivariate analyses or include them for reasons of precision. Copyright © 2014 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Predicting drug court outcome among amphetamine-using participants.

PubMed

Wu, Lora J; Altshuler, Sandra J; Short, Robert A; Roll, John M

2012-06-01

Amphetamine use and abuse carry with it substantial social costs. Although there is a perception that amphetamine users are more difficult to treat than other substance users, drug courts have been used to effectively address drug-related crimes and hold the potential to lessen the impact of amphetamine abuse through efficacious treatment and rehabilitation. The objective of this study was to identify predictors of drug court outcome among amphetamine-using participants. A drug court database was obtained (N = 540) and amphetamine-using participants (n= 341) identified. Multivariate binary regression models run for the amphetamine-using participants identified being employed and being a parent as predictive of successful completion of the program, whereas being sanctioned to jail during the program was inversely related to program completion. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Why are we regressing?

PubMed

Jupiter, Daniel C

2012-01-01

In this first of a series of statistical methodology commentaries for the clinician, we discuss the use of multivariate linear regression. Copyright © 2012 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process.

PubMed

Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang

2014-10-01

Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Quantitative investigation of inappropriate regression model construction and the importance of medical statistics experts in observational medical research: a cross-sectional study.

PubMed

Nojima, Masanori; Tokunaga, Mutsumi; Nagamura, Fumitaka

2018-05-05

To investigate under what circumstances inappropriate use of 'multivariate analysis' is likely to occur and to identify the population that needs more support with medical statistics. The frequency of inappropriate regression model construction in multivariate analysis and related factors were investigated in observational medical research publications. The inappropriate algorithm of using only variables that were significant in univariate analysis was estimated to occur at 6.4% (95% CI 4.8% to 8.5%). This was observed in 1.1% of the publications with a medical statistics expert (hereinafter 'expert') as the first author, 3.5% if an expert was included as coauthor and in 12.2% if experts were not involved. In the publications where the number of cases was 50 or less and the study did not include experts, inappropriate algorithm usage was observed with a high proportion of 20.2%. The OR of the involvement of experts for this outcome was 0.28 (95% CI 0.15 to 0.53). A further, nation-level, analysis showed that the involvement of experts and the implementation of unfavourable multivariate analysis are associated at the nation-level analysis (R=-0.652). Based on the results of this study, the benefit of participation of medical statistics experts is obvious. Experts should be involved for proper confounding adjustment and interpretation of statistical models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Guideline-Driven Care Improves Outcomes in Patients with Traumatic Rib Fractures.

PubMed

Flarity, Kathleen; Rhodes, Whitney C; Berson, Andrew J; Leininger, Brian E; Reckard, Paul E; Riley, Keyan D; Shahan, Charles P; Schroeppel, Thomas J

2017-09-01

There is no established national standard for rib fracture management. A clinical practice guideline (CPG) for rib fractures, including monitoring of pulmonary function, early initiation of aggressive loco-regional analgesia, and early identification of deteriorating respiratory function, was implemented in 2013. The objective of the study was to evaluate the effect of the CPG on hospital length of stay. Hospital length of stay (LOS) was compared for adult patients admitted to the hospital with rib fracture(s) two years before and two years after CPG implementation. A separate analysis was done for the patients admitted to the intensive care unit (ICU). Over the 48-month study period, 571 patients met inclusion criteria for the study. Pre-CPG and CPG study groups were well matched with few differences. Multivariable regression did not demonstrate a difference in LOS (B = -0.838; P = 0.095) in the total study cohort. In the ICU cohort (n = 274), patients in the CPG group were older (57 vs 52 years; P = 0.023) and had more rib fractures (4 vs 3; P = 0.003). Multivariable regression identified a significant decrease in LOS for those patients admitted in the CPG period (B = -2.29; P = 0.019). Despite being significantly older with more rib fractures in the ICU cohort, patients admitted after implementation of the CPG had a significantly reduced LOS on multivariable analysis, reducing LOS by over two days. This structured intervention can limit narcotic usage, improve pulmonary function, and decrease LOS in the most injured patients with chest trauma.

Predictors of workplace sexual health policy at sex work establishments in the Philippines.

PubMed

Withers, M; Dornig, K; Morisky, D E

2007-09-01

Based on the literature, we identified manager and establishment characteristics that we hypothesized are related to workplace policies that support HIV protective behavior. We developed a sexual health policy index consisting of 11 items as our outcome variable. We utilized both bivariate and multivariate analysis of variance. The significant variables in our bivariate analyses (establishment type, number of employees, manager age, and membership in manager association) were entered into a multivariate regression model. The model was significant (p<.01), and predicted 42) of the variability in the development and management of a workplace sexual health policy supportive of condom use. The significant predictors were number of employees and establishment type. In addition to individually-focused CSW interventions, HIV prevention programs should target managers and establishment policies. Future HIV prevention programs may need to focus on helping smaller establishments, in particular those with less employees, to build capacity and develop sexual health policy guidelines.

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.

Spatio-temporal variations of nitric acid total columns from 9 years of IASI measurements - a driver study

NASA Astrophysics Data System (ADS)

Ronsmans, Gaétane; Wespes, Catherine; Hurtmans, Daniel; Clerbaux, Cathy; Coheur, Pierre-François

2018-04-01

This study aims to understand the spatial and temporal variability of HNO3 total columns in terms of explanatory variables. To achieve this, multiple linear regressions are used to fit satellite-derived time series of HNO3 daily averaged total columns. First, an analysis of the IASI 9-year time series (2008-2016) is conducted based on various equivalent latitude bands. The strong and systematic denitrification of the southern polar stratosphere is observed very clearly. It is also possible to distinguish, within the polar vortex, three regions which are differently affected by the denitrification. Three exceptional denitrification episodes in 2011, 2014 and 2016 are also observed in the Northern Hemisphere, due to unusually low arctic temperatures. The time series are then fitted by multivariate regressions to identify what variables are responsible for HNO3 variability in global distributions and time series, and to quantify their respective influence. Out of an ensemble of proxies (annual cycle, solar flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and Antarctic oscillations and volume of polar stratospheric clouds), only the those defined as significant (p value < 0.05) by a selection algorithm are retained for each equivalent latitude band. Overall, the regression gives a good representation of HNO3 variability, with especially good results at high latitudes (60-80 % of the observed variability explained by the model). The regressions show the dominance of annual variability in all latitudinal bands, which is related to specific chemistry and dynamics depending on the latitudes. We find that the polar stratospheric clouds (PSCs) also have a major influence in the polar regions, and that their inclusion in the model improves the correlation coefficients and the residuals. However, there is still a relatively large portion of HNO3 variability that remains unexplained by the model, especially in the intertropical regions, where factors not included in the regression model (such as vegetation fires or lightning) may be at play.

PM10 modeling in the Oviedo urban area (Northern Spain) by using multivariate adaptive regression splines

NASA Astrophysics Data System (ADS)

Nieto, Paulino José García; Antón, Juan Carlos Álvarez; Vilán, José Antonio Vilán; García-Gonzalo, Esperanza

2014-10-01

The aim of this research work is to build a regression model of the particulate matter up to 10 micrometers in size (PM10) by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (Northern Spain) at local scale. This research work explores the use of a nonparametric regression algorithm known as multivariate adaptive regression splines (MARS) which has the ability to approximate the relationship between the inputs and outputs, and express the relationship mathematically. In this sense, hazardous air pollutants or toxic air contaminants refer to any substance that may cause or contribute to an increase in mortality or serious illness, or that may pose a present or potential hazard to human health. To accomplish the objective of this study, the experimental dataset of nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3) and dust (PM10) were collected over 3 years (2006-2008) and they are used to create a highly nonlinear model of the PM10 in the Oviedo urban nucleus (Northern Spain) based on the MARS technique. One main objective of this model is to obtain a preliminary estimate of the dependence between PM10 pollutant in the Oviedo urban area at local scale. A second aim is to determine the factors with the greatest bearing on air quality with a view to proposing health and lifestyle improvements. The United States National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of these numerical calculations, using the multivariate adaptive regression splines (MARS) technique, conclusions of this research work are exposed.

Identifying prognostic intratumor heterogeneity using pre- and post-radiotherapy 18F-FDG PET images for pancreatic cancer patients.

PubMed

Yue, Yong; Osipov, Arsen; Fraass, Benedick; Sandler, Howard; Zhang, Xiao; Nissen, Nicholas; Hendifar, Andrew; Tuli, Richard

2017-02-01

To stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients. Twenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images. A total of 48 texture and clinical variables were identified and evaluated for association with overall survival (OS). The prognostic heterogeneity features were selected using lasso/elastic net regression, and further were evaluated by multivariate Cox analysis. Median age was 69 y (range, 46-86 y). The texture map and temporal variations between pre- and post-treatment were well characterized by histograms and statistical fitting. The lasso analysis identified seven predictors (age, node stage, post-RT SUVmax, variations of homogeneity, variance, sum mean, and cluster tendency). The multivariate Cox analysis identified five significant variables: age, node stage, variations of homogeneity, variance, and cluster tendency (with P=0.020, 0.040, 0.065, 0.078, and 0.081, respectively). The patients were stratified into two groups based on the risk score of multivariate analysis with log-rank P=0.001: a low risk group (n=11) with a longer mean OS (29.3 months) and higher texture variation (>30%), and a high risk group (n=15) with a shorter mean OS (17.7 months) and lower texture variation (<15%). Locoregional metabolic texture response provides a feasible approach for evaluating and predicting clinical outcomes following treatment of PA with RT. The proposed method can be used to stratify patient risk and help select appropriate treatment strategies for individual patients toward implementing response-driven adaptive RT.

A Multicentre Evaluation of Risk Factors for Anastomotic Leakage After Restorative Proctocolectomy with Ileal Pouch-Anal Anastomosis for Inflammatory Bowel Disease.

PubMed

Sahami, Saloomeh; Bartels, Sanne A L; D'Hoore, André; Fadok, Tonia Young; Tanis, Pieter J; Lindeboom, Robert; de Buck van Overstraeten, Anthony; Wolthuis, Albert M; Bemelman, Willem A; Buskens, Christianne J

2016-07-01

Anastomotic leakage is a major complication after restorative proctocolectomy with ileal pouch-anal anastomosis [IPAA]. Identification of patients at high risk of leakage may influence surgical decision making. The aim of this study was to identify risk factors associated with anastomotic leakage after restorative proctocolectomy with IPAA. Between September 1990 and January 2015, patients who underwent IPAA for inflammatory bowel disease [IBD] were identified from prospectively maintained databases of three tertiary referral centres. Retrospective chart review identified additional data on demographic and surgical variables. Multivariable regression models were developed to identify risk factors for anastomotic leakage. Separate analyses were performed for type of procedure. A total of 640 patients [56.9% male] were included, with a median age of 38 years [interquartile range 29-48]; 96 [15.0%] patients developed anastomotic leakage. Multivariable regression analysis demonstrated that being overweight (body mass index [BMI] > 25], (odds ratio [OR] 1.92; 95% confidence interval [CI] 1.15 - 3.18), and American Society of Anesthesiologists classification [ASA score > 2] [OR 1.91; 95% CI 1.03 - 3.54] were independent risk factors for anastomotic leakage in patients who underwent a completion proctectomy. A disease course of > 5 years [OR 2.34; 95% CI 1.42 - 3.87] and concurrent combination of anti-tumour necrosis factor [TNF] and steroids [OR 6.40; 95% CI 1.76 - 23.20] were independent risk factors for anastomotic leakage in patients who underwent a proctocolectomy and IPAA. Independent risk factors for anastomotic leakage in IBD patients undergoing IPAA are BMI >25, ASA score >2, disease course > 5 years, and concurrent steroid and anti-TNF treatment, with a different risk profile for one-stage proctocolectomy and completion proctectomy procedures. Copyright © 2015 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A refined method for multivariate meta-analysis and meta-regression

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Predictors of Parent-Adolescent Communication in Post-apartheid South Africa: A Protective Factor in Adolescent Sexual and Reproductive Health

PubMed Central

Coetzee, Jenny; Dietrich, Janan; Otwombe, Kennedy; Nkala, Busi; Khunwane, Mamakiri; van der Watt, Martin; Sikkema, Kathleen J; Gray, Glenda E

2014-01-01

In the HIV context, risky sexual behaviours can be reduced through effective parent-adolescent communication. This study used the Parent Adolescent Communication Scale to determine parent-adolescent communication by ethnicity and identify predictors of high parent-adolescent communication amongst South African adolescents post-apartheid. A cross-sectional interviewer-administered survey was administered to 822 adolescents from Johannesburg, South Africa. Backward stepwise multivariate regressions were performed. The sample was predominantly Black African (62%, n=506) and female (57%, n=469). Of the participants, 57% (n=471) reported high parent-adolescent communication. Multivariate regression showed that gender was a significant predictor of high parent-adolescent communication (Black African OR:1.47,CI:1.0-2.17, Indian OR:2.67,CI:1.05-6.77, White OR:2.96,CI:1.21-7.18). Female-headed households were predictors of high parent-adolescent communication amongst Black Africans (OR:1.49,CI:1.01-2.20), but of low parent-adolescent communication amongst Whites (OR:0.36,CI: 0.15-0.89). Overall levels of parent-adolescent communication in South Africa are low. HIV prevention programmes for South African adolescents should include information and skills regarding effective parent-adolescent communication. PMID:24636691

Correlates of Suicidality: Investigation of a Representative Sample of Manitoba First Nations Adolescents

PubMed Central

Mota, Natalie; Elias, Brenda; Tefft, Bruce; Medved, Maria; Munro, Garry

2012-01-01

Objectives. We examined individual, friend or family, and community or tribe correlates of suicidality in a representative on-reserve sample of First Nations adolescents. Methods. Data came from the 2002–2003 Manitoba First Nations Regional Longitudinal Health Survey of Youth. Interviews were conducted with adolescents aged 12 to 17 years (n = 1125) from 23 First Nations communities in Manitoba. We used bivariate logistic regression analyses to examine the relationships between a range of factors and lifetime suicidality. We conducted sex-by-correlate interactions for each significant correlate at the bivariate level. A multivariate logistic regression analysis identified those correlates most strongly related to suicidality. Results. We found several variables to be associated with an increased likelihood of suicidality in the multivariate model, including being female, depressed mood, abuse or fear of abuse, a hospital stay, and substance use (adjusted odds ratio range = 2.43–11.73). Perceived community caring was protective against suicidality (adjusted odds ratio = 0.93; 95% confidence interval = 0.88, 0.97) in the same model. Conclusions. Results of this study may be important in informing First Nations and government policy related to the implementation of suicide prevention strategies in First Nations communities. PMID:22676500

Recent patterns in antibiotic use for children with group A streptococcal infections in Japan.

PubMed

Okubo, Yusuke; Michihata, Nobuaki; Morisaki, Naho; Kinoshita, Noriko; Miyairi, Isao; Urayama, Kevin Y; Yasunaga, Hideo

2017-11-13

Antibiotics are the most frequently prescribed medicines for children, however inappropriate antibiotic prescribing is prevalent. This study investigated recent trends in antibiotic use and factors associated with appropriate antibiotic selection among children with group A streptococcal infections in Japan. Records of outpatients aged <18years with a diagnosis of group A streptococcal infection were obtained using the Japan Medical Data Center database. Prescription patterns for antibiotics were investigated and factors associated with penicillin use were evaluated using a multivariable log-binomial regression model. Overall, 5030 patients with a diagnosis of group A streptococcal infection were identified. The most commonly prescribed antibiotics were third-generation cephalosporins (53.3%), followed by penicillins (40.1%). In the multivariable log-binomial regression analysis, out-of-hours visits were independently associated with penicillin prescriptions [prevalence ratio (PR)=1.10, 95% confidence interval (CI) 1.03-1.18], whereas clinical departments other than paediatrics and internal medicine were related to non-penicillin prescriptions (PR=0.57, 95% CI 0.46-0.71). Third-generation cephalosporins were overprescribed for children with group A streptococcal infections. This investigation provides important information for promoting education for physicians and for constructing health policies for appropriate antibiotic prescription. Copyright © 2017. Published by Elsevier Ltd.

Candida albicans chronic colonisation in cystic fibrosis may be associated with inhaled antibiotics.

PubMed

Noni, Maria; Katelari, Anna; Kaditis, Athanasios; Theochari, Ioanna; Lympari, Ioulia; Alexandrou-Athanassoulis, Helen; Doudounakis, Stavros-Eleftherios; Dimopoulos, George

2015-07-01

Candida albicans is increasingly recognised as a coloniser of the respiratory tract in cystic fibrosis (CF) patients. Yet, the potential role, if any, of the micro-organism in the progress of the disease remains unclear. In this study, we investigated the association between inhaled antibiotics and C. albicans chronic colonisation in patients with CF. A cohort of 121 CF patients born from 1988 to 1996 was, respectively, studied. The medical records of each patient were reviewed from the first time they attended the CF Centre until the occurrence of C. albicans chronic colonisation or their last visit for the year 2010. Chronic colonisation was defined as the presence of C. albicans in more than 50% of cultures in a given year. A number of possible confounders were included in the multivariate logistic regression analysis to identify an independent association between inhaled antibiotics and C. albicans chronic colonisation. Fifty-four (44.6%) of the 121 patients enrolled in the study developed chronic colonisation by the micro-organism. Multivariate logistic regression analysis determined the independent effect of inhaled antibiotic treatment on the odds of chronic colonisation (OR 1.112, 95% CI [1.007-1.229], P = 0.036). Candida albicans chronic colonisation may be associated with the duration of inhaled antibiotic treatment. © 2015 Blackwell Verlag GmbH.

A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration.

PubMed

Goovaerts, P; Albuquerque, Teresa; Antunes, Margarida

2016-11-01

This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R 2 =0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold's paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.

Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study

PubMed Central

Le Strat, Yann

2017-01-01

The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489

Hepatotoxicity during Treatment for Tuberculosis in People Living with HIV/AIDS.

PubMed

Araújo-Mariz, Carolline; Lopes, Edmundo Pessoa; Acioli-Santos, Bartolomeu; Maruza, Magda; Montarroyos, Ulisses Ramos; Ximenes, Ricardo Arraes de Alencar; Lacerda, Heloísa Ramos; Miranda-Filho, Demócrito de Barros; Albuquerque, Maria de Fátima P Militão de

2016-01-01

Hepatotoxicity is frequently reported as an adverse reaction during the treatment of tuberculosis. The aim of this study was to determine the incidence of hepatotoxicity and to identify predictive factors for developing hepatotoxicity after people living with HIV/AIDS (PLWHA) start treatment for tuberculosis. This was a prospective cohort study with PLWHA who were monitored during the first 60 days of tuberculosis treatment in Pernambuco, Brazil. Hepatotoxicity was considered increased levels of aminotransferase, namely those that rose to three times higher than the level before initiating tuberculosis treatment, these levels being associated with symptoms of hepatitis. We conducted a multivariate logistic regression analysis and the magnitude of the associations was expressed by the odds ratio with a confidence interval of 95%. Hepatotoxicity was observed in 53 (30.6%) of the 173 patients who started tuberculosis treatment. The final multivariate logistic regression model demonstrated that the use of fluconazole, malnutrition and the subject being classified as a phenotypically slow acetylator increased the risk of hepatotoxicity significantly. The incidence of hepatotoxicity during treatment for tuberculosis in PLWHA was high. Those classified as phenotypically slow acetylators and as malnourished should be targeted for specific care to reduce the risk of hepatotoxicity during treatment for tuberculosis. The use of fluconazole should be avoided during tuberculosis treatment in PLWHA.

[Risk factors for anorexia in children].

PubMed

Liu, Wei-Xiao; Lang, Jun-Feng; Zhang, Qin-Feng

2016-11-01

To investigate the risk factors for anorexia in children, and to reduce the prevalence of anorexia in children. A questionnaire survey and a case-control study were used to collect the general information of 150 children with anorexia (case group) and 150 normal children (control group). Univariate analysis and multivariate logistic stepwise regression analysis were performed to identify the risk factors for anorexia in children. The results of the univariate analysis showed significant differences between the case and control groups in the age in months when supplementary food were added, feeding pattern, whether they liked meat, vegetables and salty food, whether they often took snacks and beverages, whether they liked to play while eating, and whether their parents asked them to eat food on time (P<0.05). The results of the multivariate logistic regression analysis showed that late addition of supplementary food (OR=5.408), high frequency of taking snacks and/or drinks (OR=11.813), and eating while playing (OR=6.654) were major risk factors for anorexia in children. Liking of meat (OR=0.093) and vegetables (OR=0.272) and eating on time required by parents (OR=0.079) were protective factors against anorexia in children. Timely addition of supplementary food, a proper diet, and development of children's proper eating and living habits can reduce the incidence of anorexia in children.

Patient acceptance of non-invasive testing for fetal aneuploidy via cell-free fetal DNA.

PubMed

Vahanian, Sevan A; Baraa Allaf, M; Yeh, Corinne; Chavez, Martin R; Kinzler, Wendy L; Vintzileos, Anthony M

2014-01-01

To evaluate factors associated with patient acceptance of noninvasive prenatal testing for trisomy 21, 18 and 13 via cell-free fetal DNA. This was a retrospective study of all patients who were offered noninvasive prenatal testing at a single institution from 1 March 2012 to 2 July 2012. Patients were identified through our perinatal ultrasound database; demographic information, testing indication and insurance coverage were compared between patients who accepted the test and those who declined. Parametric and nonparametric tests were used as appropriate. Significant variables were assessed using multivariate logistic regression. The value p < 0.05 was considered significant. Two hundred thirty-five patients were offered noninvasive prenatal testing. Ninety-three patients (40%) accepted testing and 142 (60%) declined. Women who accepted noninvasive prenatal testing were more commonly white, had private insurance and had more than one testing indication. There was no statistical difference in the number or the type of testing indications. Multivariable logistic regression analysis was then used to assess individual variables. After controlling for race, patients with public insurance were 83% less likely to accept noninvasive prenatal testing than those with private insurance (3% vs. 97%, adjusted RR 0.17, 95% CI 0.05-0.62). In our population, having public insurance was the factor most strongly associated with declining noninvasive prenatal testing.

Epidemiological characteristics of measles from 2000 to 2014: Results of a measles catch-up vaccination campaign in Xianyang, China.

PubMed

Zhang, Rong-Qiang; Li, Hong-Bing; Li, Feng-Ying; Han, Li-Xin; Xiong, Yong-Min

This study was a cross-sectional case-control study aimed at (1) identifying risk factors contributing to the measles epidemic and (2) evaluating the impacts of measles-containing vaccines (MCVs), with the goal of providing evidence-based recommendations for measles elimination strategies in China. Data on measles cases from 2000 to 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang. The effectiveness of MCVs was evaluated in 357 patients with a vaccination history and 503 healthy randomly selected controls. Patient data were subjected to multivariable logistic regression modeling. From 2005 to 2014, the average incidence of measles in Xianyang was 5.42 cases per 100,000 people. The second MCV dose was highly protective in 8-month-old infants. MCVs in general have been highly protective in 8-month-old infants. Multivariable logistic regression modeling indicated that age (≥2 years vs. <2years), MCV dose 2 vaccination, and MV vaccination were each independently associated with measles case status. In conclusions: A MCV should be administered on time to all age-eligible children, reproductive-age women, and migrant populations, to maximize herd immunity to measles. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The association between maternal serious psychological distress and child obesity at 3 years: a cross-sectional analysis of the UK Millennium Cohort Data.

PubMed

Ramasubramanian, L; Lane, S; Rahman, A

2013-01-01

  The prevalence of child obesity is increasing rapidly worldwide. Early childhood has been identified as a critical time period for the development of obesity. Maternal mental health and early life environment are crucial factors and have been linked to adverse child outcomes. The objective of the study was to examine the relationship between maternal serious psychological distress and obesity in early childhood.   A cross-sectional analysis of data from the Millennium Cohort Study was conducted. Subjects consisted of all natural mothers (n= 10 465) who had complete and plausible data for Kessler-6 scores, socio-demographic and anthropometric variables, and their children for whom anthropometric measurements were completed at age 3. Maternal serious psychological distress was defined as a score of 13 or more on the Kessler-6 scale. Obesity was defined as body mass index ≥95th centile of the 1990 reference chart for age and sex in children. The data were analysed using spss 16. Maternal socio-demographic factors that are known to influence maternal mental health and child obesity were identified and adjusted using multivariate logistic regression.   Of the 10 465 mother-child dyads, 3.5% of mothers had serious psychological distress and 5.5% of children were obese at 3 years of age. Logistic regression analysis showed that maternal serious psychological distress was associated with early childhood obesity (P= 0.01; OR 1.62, 95% CI 1.11, 2.37). After adjusting for potential confounding factors using multivariate logistic regression, maternal serious psychological distress remained significantly associated with early childhood obesity (P= 0.01; OR 1.59, 95% CI 1.08, 2.34).   The results show that maternal serious psychological distress is independently associated with early childhood obesity. © 2011 Blackwell Publishing Ltd.

Over- and undersupply in home care: a representative multicenter correlational study.

PubMed

Lahmann, Nils A; Suhr, Ralf; Kuntz, Simone; Kottner, Jan

2015-04-01

Quality assurance and funding of care become a major challenge against the background of demographic changes in western societies. The primary aim of the study was to identify possible misclassification, respectively over and undersupply of care by comparing the Barthel Index of clients of home care service with the level of care (Stage 0, I, II, III) according to the statutory German long-term care insurance. In 2012, a multi-center point prevalence study of 878 randomly selected clients of 100 randomly selected home care services across Germany was conducted. According to a standardized study protocol, demographics, the Barthel Index and the nurses' professional judgment-whether a client requires more nursing care-were assessed. Associations of the Barthel items and professional judgment were analyzed using univariate (Chi-square) and multivariate (logistic regression and classification-regression-tree-models) statistics. In each level of care, the Barthel Index showed large variability e.g. in level II ranging from 0 to 100 points. Multivariate logistic regression regarding possible under- and oversupply revealed occasionally fecal incontinence (2.1; 95 % CI 1.2-3.7), urinary incontinence (2.0; 95 % CI 1.1-3.6), feeding (1.7; 95 % CI 1.0-2.9), immobility (0.2; 95 % CI 0.1-0.6) and to be female (1.8; 95 % CI 1.2-2.6) to be statistically significantly associated. The variability in Barthel Index in each level of care found in this study indicated a large general misclassification of home care clients according to their actual need of care. Professional caregivers identified occasional incontinence, help with eating and drinking and mobility (especially in female clients) as areas of possible under- and oversupply of care. The statutory German long-term care insurance classification should be modified according to the above finding to increase the quality of care in home care clients.

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

PubMed

Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

2016-04-01

Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure surfaces that can be applied in large population-based studies. To address this need, we developed a land use regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Risk factors for exclusive breastfeeding lasting less than two months—Identifying women in need of targeted breastfeeding support

PubMed Central

Sylvén, Sara M.; Lindbäck, Johan; Skalkidou, Alkistis; Rubertsson, Christine

2017-01-01

Background Breastfeeding rates in Sweden are declining, and it is important to identify women at risk for early cessation of exclusive breastfeeding. Objective The aim of this study was to investigate factors associated with exclusive breastfeeding lasting less than two months postpartum. Methods A population-based longitudinal study was conducted at Uppsala University Hospital, Sweden. Six hundred and seventy-nine women were included in this sub-study. Questionnaires were sent at five days, six weeks and six months postpartum, including questions on breastfeeding initiation and duration as well as several other background variables. The main outcome measure was exclusive breastfeeding lasting less than two months postpartum. Multivariable logistic regression analysis was used in order to calculate adjusted Odds Ratios (AOR) and 95% Confidence Intervals (95% CI). Results Seventy-seven percent of the women reported exclusive breastfeeding at two months postpartum. The following variables in the multivariate regression analysis were independently associated with exclusive breastfeeding lasting less than two months postpartum: being a first time mother (AOR 2.15, 95% CI 1.32–3.49), reporting emotional distress during pregnancy (AOR 2.21, 95% CI 1.35–3.62) and giving birth by cesarean section (AOR 2.63, 95% CI 1.34–5.17). Conclusions Factors associated with shorter exclusive breastfeeding duration were determined. Identification of women experiencing emotional distress during pregnancy, as well as scrutiny of caregiving routines on cesarean section need to be addressed, in order to give individual targeted breastfeeding support and promote longer breastfeeding duration. PMID:28614419

Early symptom burden predicts recovery after sport-related concussion

PubMed Central

Mannix, Rebekah; Monuteaux, Michael C.; Stein, Cynthia J.; Bachur, Richard G.

2014-01-01

Objective: To identify independent predictors of and use recursive partitioning to develop a multivariate regression tree predicting symptom duration greater than 28 days after a sport-related concussion. Methods: We conducted a prospective cohort study of patients in a sports concussion clinic. Participants completed questionnaires that included the Post-Concussion Symptom Scale (PCSS). Participants were asked to record the date on which they last experienced symptoms. Potential predictor variables included age, sex, score on symptom inventories, history of prior concussions, performance on computerized neurocognitive assessments, loss of consciousness and amnesia at the time of injury, history of prior medical treatment for headaches, history of migraines, and family history of concussion. We used recursive partitioning analysis to develop a multivariate prediction model for identifying athletes at risk for a prolonged recovery from concussion. Results: A total of 531 patients ranged in age from 7 to 26 years (mean 14.6 ± 2.9 years). The mean PCSS score at the initial visit was 26 ± 26; mean time to presentation was 12 ± 5 days. Only total score on symptom inventory was independently associated with symptoms lasting longer than 28 days (adjusted odds ratio 1.044; 95% confidence interval [CI] 1.034, 1.054 for PCSS). No other potential predictor variables were independently associated with symptom duration or useful in developing the optimal regression decision tree. Most participants (86%; 95% CI 80%, 90%) with an initial PCSS score of <13 had resolution of their symptoms within 28 days of injury. Conclusions: The only independent predictor of prolonged symptoms after sport-related concussion is overall symptom burden. PMID:25381296

Police Victimization Among Persons Who Inject Drugs Along the U.S.-Mexico Border.

PubMed

Pinedo, Miguel; Burgos, Jose Luis; Zuniga, Maria Luisa; Perez, Ramona; Macera, Caroline A; Ojeda, Victoria D

2015-09-01

Problematic policing practices are an important driver of HIV infection among persons who inject drugs (PWID) in the U.S.-Mexico border region. This study identifies factors associated with recent (i.e., past 6 months) police victimization (e.g., extortion, physical and sexual violence) in the border city of Tijuana, Mexico. From 2011 to 2013, 733 PWID (62% male) were recruited in Tijuana and completed a structured questionnaire. Eligible participants were age 18 years or older, injected illicit drugs within the past month, and spoke Spanish or English. Multivariable logistic regression analyses identified correlates of recent experiences of police victimization (e.g., bribes, unlawful confiscation, physical and sexual violence). Overall, 56% of PWID reported a recent police victimization experience in Tijuana. In multivariable logistic regression analyses, factors independently associated with recent police victimization included recent injection of methamphetamine (adjusted odds ratio [AOR] = 1.62; 95% CI [1.18, 2.21]) and recently received injection assistance by a "hit doctor" (AOR = 1.56; 95% CI [1.03, 2.36]). Increased years lived in Tijuana (AOR = 0.98 per year; 95% CI [0.97, 0.99]) and initiating drug use at a later age (AOR = 0.96 per year; 95% CI [0.92, 0.99]) were inversely associated with recent police victimization. Physical drugusing markers may increase PWID susceptibility to police targeting and contribute to experiences of victimization. Interventions aimed at reducing police victimization events in the U.S.-Mexico border region should consider PWID's drug-using behaviors. Reducing problematic policing practices may be a crucial public health strategy to reduce HIV risk among PWID in this region.

Ureteral stents increase risk of postoperative acute kidney injury following colorectal surgery.

PubMed

Hassinger, Taryn E; Mehaffey, J Hunter; Mullen, Matthew G; Michaels, Alex D; Elwood, Nathan R; Levi, Shoshana T; Hedrick, Traci L; Friel, Charles M

2018-07-01

Ureteral stents are commonly placed before colorectal resection to assist in identification of ureters and prevent injury. Acute kidney injury (AKI) is a common cause of morbidity and increased cost following colorectal surgery. Although previously associated with reflex anuria, prophylactic stents have not been found to increase AKI. We sought to determine the impact of ureteral stents on the incidence of AKI following colorectal surgery. All patients undergoing colon or rectal resection at a single institution between 2005 and 2015 were reviewed using American College of Surgeons National Surgical Quality Improvement Program dataset. AKI was defined as a rise in serum creatinine to ≥ 1.5 times the preoperative value. Univariate and multivariate regression analyses were performed to identify independent predictors of AKI. 2910 patients underwent colorectal resection. Prophylactic ureteral stents were placed in 129 patients (4.6%). Postoperative AKI occurred in 335 (11.5%) patients during their hospitalization. The stent group demonstrated increased AKI incidence (32.6% vs. 10.5%; p < 0.0001) with bilateral having a higher rate than unilateral stents. Hospital costs were higher in the stent group ($23,629 vs. $16,091; p < 0.0001), and patients with bilateral stents had the highest costs. Multivariable logistic regression identified predictors of AKI after colorectal surgery including age, procedure duration, and ureteral stent placement. Prophylactic ureteral stents independently increased AKI risk when placed prior to colorectal surgery. These data demonstrate increased morbidity and hospital costs related to usage of stents in colorectal surgery, indicating that placement should be limited to patients with highest potential benefit.

Evolving Epidemiology of Staphylococcus aureus Bacteremia.

PubMed

Rhee, Yoona; Aroutcheva, Alla; Hota, Bala; Weinstein, Robert A; Popovich, Kyle J

2015-12-01

Methicillin-resistant Staphylococcus aureus (MRSA) infections due to USA300 have become widespread in community and healthcare settings. It is unclear whether risk factors for bloodstream infections (BSIs) differ by strain type. To examine the epidemiology of S. aureus BSIs, including USA300 and non-USA300 MRSA strains. Retrospective observational study with molecular analysis. Large urban public hospital. Individuals with S. aureus BSIs from January 1, 2007 through December 31, 2013. We used electronic surveillance data to identify cases of S. aureus BSI. Available MRSA isolates were analyzed by pulsed-field gel electrophoresis. Poisson regression was used to evaluate changes in BSI incidence over time. Risk factor data were collected by medical chart review and logistic regression was used for multivariate analysis of risk factors. A total of 1,015 cases of S. aureus BSIs were identified during the study period; 36% were due to MRSA. The incidence of hospital-onset (HO) MRSA BSIs decreased while that of community-onset (CO) MRSA BSIs remained stable. The rate of CO- and HO- methicillin-susceptible S. aureus infections both decreased over time. More than half of HO-MRSA BSIs were due to the USA300 strain type and for 4 years, the proportion of HO-MRSA BSIs due to USA300 exceeded 60%. On multivariate analysis, current or former drug use was the only epidemiologic risk factor for CO- or HO-MRSA BSIs due to USA300 strains. USA300 MRSA is endemic in communities and hospitals and certain populations (eg, those who use illicit drugs) may benefit from enhanced prevention efforts in the community.

External root resorption of the second molar associated with mesially and horizontally impacted mandibular third molar: evidence from cone beam computed tomography.

PubMed

Wang, Dongmiao; He, Xiaotong; Wang, Yanling; Li, Zhongwu; Zhu, Yumin; Sun, Chao; Ye, Jinhai; Jiang, Hongbing; Cheng, Jie

2017-05-01

The aim of the present study was to assess the incidence and risk factors of ERR in second molars with mesially and horizontally impacted mandibular third molars using cone beam computed tomography (CBCT) images from patients in a Chinese tertiary referral hospital. A total number of 216 patients with 362 mesially and horizontally impacted mandibular third molars who were treated at our institution from 2014 to 2015 was retrospectively included. The ERR in second molars was identified on CBCT multiplanar images. The associations between incidence of ERR and multiple clinical parameters were statistically analyzed by Chi-square test. Moreover, the risk factors for ERR in second molars were further assessed by multivariate regression analysis. The overall incidence of ERR in second molars was 20.17 % (73/362) as detected on CBCT images. The presence of ERR significantly associated with patients age and impaction depth of mandibular third molars. However, no significant relationship was found between ERR severity and impaction depth or ERR location. Multivariate regression analyses further revealed age over 35 years and impaction depth as important risk factors affecting the ERR incidence caused by mesial and horizontal impaction of mandibular third molar. ERR in second molar resulted from mesially and horizontally impacted mandibular third molar is not very rare and can be reliably identified via CBCT scan. Given the possibility of ERR associated with third molar impaction, the prophylactic removal of these impacted teeth could be considered especially for those patients with over 35 years and mesially and horizontally impacted teeth.

Clinicopathologic characteristics associated with long-term survival in advanced epithelial ovarian cancer: an NRG Oncology/Gynecologic Oncology Group ancillary data study.

PubMed

Hamilton, C A; Miller, A; Casablanca, Y; Horowitz, N S; Rungruang, B; Krivak, T C; Richard, S D; Rodriguez, N; Birrer, M J; Backes, F J; Geller, M A; Quinn, M; Goodheart, M J; Mutch, D G; Kavanagh, J J; Maxwell, G L; Bookman, M A

2018-02-01

To identify clinicopathologic factors associated with 10-year overall survival in epithelial ovarian cancer (EOC) and primary peritoneal cancer (PPC), and to develop a predictive model identifying long-term survivors. Demographic, surgical, and clinicopathologic data were abstracted from GOG 182 records. The association between clinical variables and long-term survival (LTS) (>10years) was assessed using multivariable regression analysis. Bootstrap methods were used to develop predictive models from known prognostic clinical factors and predictive accuracy was quantified using optimism-adjusted area under the receiver operating characteristic curve (AUC). The analysis dataset included 3010 evaluable patients, of whom 195 survived greater than ten years. These patients were more likely to have better performance status, endometrioid histology, stage III (rather than stage IV) disease, absence of ascites, less extensive preoperative disease distribution, microscopic disease residual following cyoreduction (R0), and decreased complexity of surgery (p<0.01). Multivariable regression analysis revealed that lower CA-125 levels, absence of ascites, stage, and R0 were significant independent predictors of LTS. A predictive model created using these variables had an AUC=0.729, which outperformed any of the individual predictors. The absence of ascites, a low CA-125, stage, and R0 at the time of cytoreduction are factors associated with LTS when controlling for other confounders. An extensively annotated clinicopathologic prediction model for LTS fell short of clinical utility suggesting that prognostic molecular profiles are needed to better predict which patients are likely to be long-term survivors. Published by Elsevier Inc.

Clinicopathologic characteristics associated with long-term survival in advanced epithelial ovarian cancer: an NRG Oncology/Gynecologic Oncology Group ancillary data study

PubMed Central

Hamilton, C. A.; Miller, A.; Casablanca, Y.; Horowitz, N. S.; Rungruang, B.; Krivak, T. C.; Richard, S. D.; Rodriguez, N.; Birrer, M.J.; Backes, F.J.; Geller, M.A.; Quinn, M.; Goodheart, M.J.; Mutch, D.G.; Kavanagh, J.J.; Maxwell, G. L.; Bookman, M. A.

2018-01-01

Objective To identify clinicopathologic factors associated with 10-year overall survival in epithelial ovarian cancer (EOC) and primary peritoneal cancer (PPC), and to develop a predictive model identifying long-term survivors. Methods Demographic, surgical, and clinicopathologic data were abstracted from GOG 182 records. The association between clinical variables and long-term survival (LTS) (>10 years) was assessed using multivariable regression analysis. Bootstrap methods were used to develop predictive models from known prognostic clinical factors and predictive accuracy was quantified using optimism-adjusted area under the receiver operating characteristic curve (AUC). Results The analysis dataset included 3,010 evaluable patients, of whom 195 survived greater than ten years. These patients were more likely to have better performance status, endometrioid histology, stage III (rather than stage IV) disease, absence of ascites, less extensive preoperative disease distribution, microscopic disease residual following cyoreduction (R0), and decreased complexity of surgery (p<0.01). Multivariable regression analysis revealed that lower CA-125 levels, absence of ascites, stage, and R0 were significant independent predictors of LTS. A predictive model created using these variables had an AUC=0.729, which outperformed any of the individual predictors. Conclusions The absence of ascites, a low CA-125, stage, and R0 at the time of cytoreduction are factors associated with LTS when controlling for other confounders. An extensively annotated clinicopathologic prediction model for LTS fell short of clinical utility suggesting that prognostic molecular profiles are needed to better predict which patients are likely to be long-term survivors. PMID:29195926

Early symptom burden predicts recovery after sport-related concussion.

PubMed

Meehan, William P; Mannix, Rebekah; Monuteaux, Michael C; Stein, Cynthia J; Bachur, Richard G

2014-12-09

To identify independent predictors of and use recursive partitioning to develop a multivariate regression tree predicting symptom duration greater than 28 days after a sport-related concussion. We conducted a prospective cohort study of patients in a sports concussion clinic. Participants completed questionnaires that included the Post-Concussion Symptom Scale (PCSS). Participants were asked to record the date on which they last experienced symptoms. Potential predictor variables included age, sex, score on symptom inventories, history of prior concussions, performance on computerized neurocognitive assessments, loss of consciousness and amnesia at the time of injury, history of prior medical treatment for headaches, history of migraines, and family history of concussion. We used recursive partitioning analysis to develop a multivariate prediction model for identifying athletes at risk for a prolonged recovery from concussion. A total of 531 patients ranged in age from 7 to 26 years (mean 14.6 ± 2.9 years). The mean PCSS score at the initial visit was 26 ± 26; mean time to presentation was 12 ± 5 days. Only total score on symptom inventory was independently associated with symptoms lasting longer than 28 days (adjusted odds ratio 1.044; 95% confidence interval [CI] 1.034, 1.054 for PCSS). No other potential predictor variables were independently associated with symptom duration or useful in developing the optimal regression decision tree. Most participants (86%; 95% CI 80%, 90%) with an initial PCSS score of <13 had resolution of their symptoms within 28 days of injury. The only independent predictor of prolonged symptoms after sport-related concussion is overall symptom burden. © 2014 American Academy of Neurology.

Serum dehydroepiandrosterone sulphate, psychosocial factors and musculoskeletal pain in workers.

PubMed

Marinelli, A; Prodi, A; Pesel, G; Ronchese, F; Bovenzi, M; Negro, C; Larese Filon, F

2017-12-30

The serum level of dehydroepiandrosterone sulphate (DHEA-S) has been suggested as a biological marker of stress. To assess the association between serum DHEA-S, psychosocial factors and musculoskeletal (MS) pain in university workers. The study population included voluntary workers at the scientific departments of the University of Trieste (Italy) who underwent periodical health surveillance from January 2011 to June 2012. DHEA-S level was analysed in serum. The assessment tools included the General Health Questionnaire (GHQ) and a modified Nordic musculoskeletal symptoms questionnaire. The relation between DHEA-S, individual characteristics, pain perception and psychological factors was assessed by means of multivariable linear regression analysis. There were 189 study participants. The study population was characterized by high reward and low effort. Pain perception in the neck, shoulder, upper limbs, upper back and lower back was reported by 42, 32, 19, 29 and 43% of people, respectively. In multivariable regression analysis, gender, age and pain perception in the shoulder and upper limbs were significantly related to serum DHEA-S. Effort and overcommitment were related to shoulder and neck pain but not to DHEA-S. The GHQ score was associated with pain perception in different body sites and inversely to DHEA-S but significance was lost in multivariable regression analysis. DHEA-S was associated with age, gender and perception of MS pain, while effort-reward imbalance dimensions and GHQ score failed to reach the statistical significance in multivariable regression analysis. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

PubMed

Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

2016-05-01

Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

Association Between Treatment at High-Volume Facilities and Improved Overall Survival in Soft Tissue Sarcomas.

PubMed

Venigalla, Sriram; Nead, Kevin T; Sebro, Ronnie; Guttmann, David M; Sharma, Sonam; Simone, Charles B; Levin, William P; Wilson, Robert J; Weber, Kristy L; Shabason, Jacob E

2018-03-15

Soft tissue sarcomas (STS) are rare malignancies that require complex multidisciplinary management. Therefore, facilities with high sarcoma case volume may demonstrate superior outcomes. We hypothesized that STS treatment at high-volume (HV) facilities would be associated with improved overall survival (OS). Patients aged ≥18 years with nonmetastatic STS treated with surgery and radiation therapy at a single facility from 2004 through 2013 were identified from the National Cancer Database. Facilities were dichotomized into HV and low-volume (LV) cohorts based on total case volume over the study period. OS was assessed using multivariable Cox regression with propensity score-matching. Patterns of care were assessed using multivariable logistic regression analysis. Of 9025 total patients, 1578 (17%) and 7447 (83%) were treated at HV and LV facilities, respectively. On multivariable analysis, high educational attainment, larger tumor size, higher grade, and negative surgical margins were statistically significantly associated with treatment at HV facilities; conversely, black race and non-metropolitan residence were negative predictors of treatment at HV facilities. On propensity score-matched multivariable analysis, treatment at HV facilities versus LV facilities was associated with improved OS (hazard ratio, 0.87, 95% confidence interval, 0.80-0.95; P = .001). Older age, lack of insurance, greater comorbidity, larger tumor size, higher tumor grade, and positive surgical margins were associated with statistically significantly worse OS. In this observational cohort study using the National Cancer Database, receipt of surgery and radiation therapy at HV facilities was associated with improved OS in patients with STS. Potential sociodemographic disparities limit access to care at HV facilities for certain populations. Our findings highlight the importance of receipt of care at HV facilities for patients with STS and warrant further study into improving access to care at HV facilities. Copyright © 2017 Elsevier Inc. All rights reserved.

The impact of moderate wine consumption on the risk of developing prostate cancer.

PubMed

Vartolomei, Mihai Dorin; Kimura, Shoji; Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. This study was a meta-analysis that includes data from case-control and cohort studies. A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane's Q test and I 2 statistics. Publication bias was assessed using Egger's regression test. A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92-1.05, p =0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10-1.43, p =0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78-0.999, p =0.047) in the multivariable analysis that comprised 222,447 subjects. In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk.

Predictive factors for rebleeding and death in alcoholic cirrhotic patients with acute variceal bleeding: a multivariate analysis.

PubMed

Krige, Jake E J; Kotze, Urda K; Distiller, Greg; Shaw, John M; Bornman, Philippus C

2009-10-01

Bleeding from esophageal varices is a leading cause of death in alcoholic cirrhotic patients. The aim of the present single-center study was to identify risk factors predictive of variceal rebleeding and death within 6 weeks of initial treatment. Univariate and multivariate analyses were performed on 310 prospectively documented alcoholic cirrhotic patients with acute variceal hemorrhage (AVH) who underwent 786 endoscopic variceal injection treatments between January 1984 and December 2006. All injections were administered during the first 6 weeks after the patients were treated for their first variceal bleed. Seventy-five (24.2%) patients experienced a rebleed, 38 within 5 days of the initial treatment and 37 within 6 weeks of their initial treatment. Of the 15 variables studied and included in a multivariate analysis using a logistic regression model, a bilirubin level >51 mmol/l and transfusion of >6 units of blood during the initial hospital admission were predictors of variceal rebleeding within the first 6 weeks. Seventy-seven (24.8%) patients died, 29 (9.3%) within 5 days and 48 (15.4%) between 6 and 42 days after the initial treatment. Stepwise multivariate logistic regression analysis showed that six variables were predictors of death within the first 6 weeks: encephalopathy, ascites, bilirubin level >51 mmol/l, international normalized ratio (INR) >2.3, albumin <25 g/l, and the need for balloon tube tamponade. Survival was influenced by the severity of liver failure, with most deaths occurring in Child-Pugh grade C patients. Patients with AVH and encephalopathy, ascites, bilirubin levels >51 mmol/l, INR >2.3, albumin <25 g/l and who require balloon tube tamponade are at increased risk of dying within the first 6 weeks. Bilirubin levels >51 mmol/l and transfusion of >6 units of blood were predictors of variceal rebleeding.

MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION

EPA Science Inventory

Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...

A Shortened Version of the Suicide Cognitions Scale for Identifying Chronic Pain Patients at Risk for Suicide.

PubMed

Bryan, Craig J; Kanzler, Kathryn E; Grieser, Emily; Martinez, Annette; Allison, Sybil; McGeary, Donald

2017-03-01

Research in psychiatric outpatient and inpatient populations supports the utility of the Suicide Cognitions Scale (SCS) as an indicator of current and future risk for suicidal thoughts and behaviors. Designed to assess suicide-specific thoughts and beliefs, the SCS has yet to be evaluated among chronic pain patients, a group with elevated risk for suicide. The purpose of the present study was to develop and test a shortened version of the SCS (the SCS-S). A total of 228 chronic pain patients completed a battery of self-report surveys before or after a scheduled appointment. Three outpatient medical clinics (pain medicine, orofacial pain, and clinical health psychology). Confirmatory factor analysis, multivariate regression, and graded item response theory model analyses. Results of the CFAs suggested that a 3-factor solution was optimal. A shortened 9-item scale was identified based on the results of graded item response theory model analyses. Correlation and multivariate analyses supported the construct and incremental validity of the SCS-S. Results support the reliability and validity of the SCS-S among chronic pain patients, and suggest the scale may be a useful method for identifying high-risk patients in medical settings. © 2016 World Institute of Pain.

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.

Identification by random forest method of HLA class I amino acid substitutions associated with lower survival at day 100 in unrelated donor hematopoietic cell transplantation.

PubMed

Marino, S R; Lin, S; Maiers, M; Haagenson, M; Spellman, S; Klein, J P; Binkowski, T A; Lee, S J; van Besien, K

2012-02-01

The identification of important amino acid substitutions associated with low survival in hematopoietic cell transplantation (HCT) is hampered by the large number of observed substitutions compared with the small number of patients available for analysis. Random forest analysis is designed to address these limitations. We studied 2107 HCT recipients with good or intermediate risk hematological malignancies to identify HLA class I amino acid substitutions associated with reduced survival at day 100 post transplant. Random forest analysis and traditional univariate and multivariate analyses were used. Random forest analysis identified amino acid substitutions in 33 positions that were associated with reduced 100 day survival, including HLA-A 9, 43, 62, 63, 76, 77, 95, 97, 114, 116, 152, 156, 166 and 167; HLA-B 97, 109, 116 and 156; and HLA-C 6, 9, 11, 14, 21, 66, 77, 80, 95, 97, 99, 116, 156, 163 and 173. In all 13 had been previously reported by other investigators using classical biostatistical approaches. Using the same data set, traditional multivariate logistic regression identified only five amino acid substitutions associated with lower day 100 survival. Random forest analysis is a novel statistical methodology for analysis of HLA mismatching and outcome studies, capable of identifying important amino acid substitutions missed by other methods.

Salting-out assisted liquid-liquid extraction and partial least squares regression to assay low molecular weight polycyclic aromatic hydrocarbons leached from soils and sediments

NASA Astrophysics Data System (ADS)

Bressan, Lucas P.; do Nascimento, Paulo Cícero; Schmidt, Marcella E. P.; Faccin, Henrique; de Machado, Leandro Carvalho; Bohrer, Denise

2017-02-01

A novel method was developed to determine low molecular weight polycyclic aromatic hydrocarbons in aqueous leachates from soils and sediments using a salting-out assisted liquid-liquid extraction, synchronous fluorescence spectrometry and a multivariate calibration technique. Several experimental parameters were controlled and the optimum conditions were: sodium carbonate as the salting-out agent at concentration of 2 mol L- 1, 3 mL of acetonitrile as extraction solvent, 6 mL of aqueous leachate, vortexing for 5 min and centrifuging at 4000 rpm for 5 min. The partial least squares calibration was optimized to the lowest values of root mean squared error and five latent variables were chosen for each of the targeted compounds. The regression coefficients for the true versus predicted concentrations were higher than 0.99. Figures of merit for the multivariate method were calculated, namely sensitivity, multivariate detection limit and multivariate quantification limit. The selectivity was also evaluated and other polycyclic aromatic hydrocarbons did not interfere in the analysis. Likewise, high performance liquid chromatography was used as a comparative methodology, and the regression analysis between the methods showed no statistical difference (t-test). The proposed methodology was applied to soils and sediments of a Brazilian river and the recoveries ranged from 74.3% to 105.8%. Overall, the proposed methodology was suitable for the targeted compounds, showing that the extraction method can be applied to spectrofluorometric analysis and that the multivariate calibration is also suitable for these compounds in leachates from real samples.

Development and validation of a risk calculator predicting exercise-induced ventricular arrhythmia in patients with cardiovascular disease.

PubMed

Hermes, Ilarraza-Lomelí; Marianna, García-Saldivia; Jessica, Rojano-Castillo; Carlos, Barrera-Ramírez; Rafael, Chávez-Domínguez; María Dolores, Rius-Suárez; Pedro, Iturralde

2016-10-01

Mortality due to cardiovascular disease is often associated with ventricular arrhythmias. Nowadays, patients with cardiovascular disease are more encouraged to take part in physical training programs. Nevertheless, high-intensity exercise is associated to a higher risk for sudden death, even in apparently healthy people. During an exercise testing (ET), health care professionals provide patients, in a controlled scenario, an intense physiological stimulus that could precipitate cardiac arrhythmia in high risk individuals. There is still no clinical or statistical tool to predict this incidence. The aim of this study was to develop a statistical model to predict the incidence of exercise-induced potentially life-threatening ventricular arrhythmia (PLVA) during high intensity exercise. 6415 patients underwent a symptom-limited ET with a Balke ramp protocol. A multivariate logistic regression model where the primary outcome was PLVA was performed. Incidence of PLVA was 548 cases (8.5%). After a bivariate model, thirty one clinical or ergometric variables were statistically associated with PLVA and were included in the regression model. In the multivariate model, 13 of these variables were found to be statistically significant. A regression model (G) with a X(2) of 283.987 and a p<0.001, was constructed. Significant variables included: heart failure, antiarrhythmic drugs, myocardial lower-VD, age and use of digoxin, nitrates, among others. This study allows clinicians to identify patients at risk of ventricular tachycardia or couplets during exercise, and to take preventive measures or appropriate supervision. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Factors related to treatment refusal in Taiwanese cancer patients.

PubMed

Chiang, Ting-Yu; Wang, Chao-Hui; Lin, Yu-Fen; Chou, Shu-Lan; Wang, Ching-Ting; Juang, Hsiao-Ting; Lin, Yung-Chang; Lin, Mei-Hsiang

2015-01-01

Incidence and mortality rates for cancer have increased dramatically in the recent 30 years in Taiwan. However, not all patients receive treatment. Treatment refusal might impair patient survival and life quality. In order to improve this situation, we proposed this study to evaluate factors that are related to refusal of treatment in cancer patients via a cancer case manager system. This study analysed data from a case management system during the period from 2010 to 2012 at a medical center in Northern Taiwan. We enrolled a total of 14,974 patients who were diagnosed with cancer. Using the PRECEDE Model as a framework, we conducted logistic regression analysis to identify independent variables that are significantly associated with refusal of therapy in cancer patients. A multivariate logistic regression model was also applied to estimate adjusted the odds ratios (ORs) with 95% confidence intervals (95%CI). A total of 253 patients (1.69%) refused treatment. The multivariate logistic regression result showed that the high risk factors for refusal of treatment in cancer patient included: concerns about adverse effects (p<0.001), poor performance(p<0.001), changes in medical condition (p<0.001), timing of case manager contact (p=.026), the methods by which case manager contact patients (p<0.001) and the frequency that case managers contact patients (≥10times) (p=0.016). Cancer patients who refuse treatment have poor survival. The present study provides evidence of factors that are related to refusal of therapy and might be helpful for further application and improvement of cancer care.

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

PubMed

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

PubMed Central

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques. PMID:24416353

Predicting volumes in four Hawaii hardwoods...first multivariate equations developed

Treesearch

David A. Sharpnack

1966-01-01

Multivariate regression equations were developed for predicting board-foot (Int. 1/ 4-inch log rule ) and cubic-foot volumes in each 8.15-foot section of trees of four Hawaii hardwood species. The species are koa (Acacia koa), ohia (Metrosideros polymorpha), robusta eucalyptus (Eucalyptus robusta), and...

A Multivariate Test of the Bott Hypothesis in an Urban Irish Setting

ERIC Educational Resources Information Center

Gordon, Michael; Downing, Helen

1978-01-01

Using a sample of 686 married Irish women in Cork City the Bott hypothesis was tested, and the results of a multivariate regression analysis revealed that neither network connectedness nor the strength of the respondent's emotional ties to the network had any explanatory power. (Author)

Molecular Subgroup of Primary Prostate Cancer Presenting with Metastatic Biology.

PubMed

Walker, Steven M; Knight, Laura A; McCavigan, Andrena M; Logan, Gemma E; Berge, Viktor; Sherif, Amir; Pandha, Hardev; Warren, Anne Y; Davidson, Catherine; Uprichard, Adam; Blayney, Jaine K; Price, Bethanie; Jellema, Gera L; Steele, Christopher J; Svindland, Aud; McDade, Simon S; Eden, Christopher G; Foster, Chris; Mills, Ian G; Neal, David E; Mason, Malcolm D; Kay, Elaine W; Waugh, David J; Harkin, D Paul; Watson, R William; Clarke, Noel W; Kennedy, Richard D

2017-10-01

Approximately 4-25% of patients with early prostate cancer develop disease recurrence following radical prostatectomy. To identify a molecular subgroup of prostate cancers with metastatic potential at presentation resulting in a high risk of recurrence following radical prostatectomy. Unsupervised hierarchical clustering was performed using gene expression data from 70 primary resections, 31 metastatic lymph nodes, and 25 normal prostate samples. Independent assay validation was performed using 322 radical prostatectomy samples from four sites with a mean follow-up of 50.3 months. Molecular subgroups were identified using unsupervised hierarchical clustering. A partial least squares approach was used to generate a gene expression assay. Relationships with outcome (time to biochemical and metastatic recurrence) were analysed using multivariable Cox regression and log-rank analysis. A molecular subgroup of primary prostate cancer with biology similar to metastatic disease was identified. A 70-transcript signature (metastatic assay) was developed and independently validated in the radical prostatectomy samples. Metastatic assay positive patients had increased risk of biochemical recurrence (multivariable hazard ratio [HR] 1.62 [1.13-2.33]; p=0.0092) and metastatic recurrence (multivariable HR=3.20 [1.76-5.80]; p=0.0001). A combined model with Cancer of the Prostate Risk Assessment post surgical (CAPRA-S) identified patients at an increased risk of biochemical and metastatic recurrence superior to either model alone (HR=2.67 [1.90-3.75]; p<0.0001 and HR=7.53 [4.13-13.73]; p<0.0001, respectively). The retrospective nature of the study is acknowledged as a potential limitation. The metastatic assay may identify a molecular subgroup of primary prostate cancers with metastatic potential. The metastatic assay may improve the ability to detect patients at risk of metastatic recurrence following radical prostatectomy. The impact of adjuvant therapies should be assessed in this higher-risk population. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Using the Bem and Klein Grid Scores to Predict Health Services Usage by Men

PubMed Central

Reynolds, Grace L.; Fisher, Dennis G.; Dyo, Melissa; Huckabay, Loucine M.

2016-01-01

We examined the association between scores on the Bem Sex Roles Inventory (BSRI), Klein Sexual Orientation Grid (KSOG) and utilization of hospital inpatient services, emergency departments, and outpatient clinic visits in the past 12 months among 53 men (mean age 39 years). The femininity subscale score on the BSRI, ever having had gonorrhea and age were the three variables identified in a multivariate linear regression significantly predicting use of total health services. This supports the hypothesis that sex roles can assist our understanding of men’s use of health services. PMID:27337618

Cognitive and behavioral predictors of MMPI scores in pretrial psychological evaluations of murderers.

PubMed

Holcomb, W R; Adams, N A; Ponder, H M; Anderson, W P

1984-03-01

Tested by multivariate regression the validity of the MMPI with accused murderers (N = 96) who were undergoing pre-trial evaluations. Four significant behavioral and cognitive predictors of MMPI elevated scores were identified. These include low intelligence, history of drug abuse, suspiciousness observed on the ward, and the fact that the accused was a stranger to the victim. These results support the validity of the MMPI with this population and also suggest that high F scale scores on the MMPI are more a measure of psychopathology than invalidity due to test-taking response bias.

Differentiation of benign and malignant ampullary obstruction by multi-row detector CT.

PubMed

Angthong, Wirana; Jiarakoop, Kran; Tangtiang, Kaan

2018-05-21

To determine useful CT parameters to differentiate ampullary carcinomas from benign ampullary obstruction. This study included 93 patients who underwent abdominal CT, 31 patients with ampullary carcinomas, and 62 patients with benign ampullary obstruction. Two radiologists independently evaluated CT parameters then reached consensus decisions. Statistically significant CT parameters were identified through univariate and multivariate analyses. In univariate analysis, the presence of ampullary mass, asymmetric, abrupt narrowing of distal common bile duct (CBD), dilated intrahepatic bile duct (IHD), dilated pancreatic duct (PD), peripancreatic lymphadenopathy, duodenal wall thickening, and delayed enhancement were more frequently in ampullary carcinomas observed (P < 0.05). Multivariate logistic regression analysis using significant CT parameters and clinical data from univariate analysis, and clinical symptom with jaundice (P = 0.005) was an independent predictor of ampullary carcinomas. For multivariate analysis using only significant CT parameters, abrupt narrowing of distal CBD was an independent predictor of ampullary carcinomas (P = 0.019). Among various CT criteria, abrupt narrowing of distal CBD and dilated IHD had highest sensitivity (77.4%) and highest accuracy (90.3%). The abrupt narrowing of distal CBD and dilated IHD is useful for differentiation of ampullary carcinomas from benign entity in patients without the presence of mass.

Men and women show similar survival outcome in stage IV breast cancer.

PubMed

Wu, San-Gang; Zhang, Wen-Wen; Liao, Xu-Lin; Sun, Jia-Yuan; Li, Feng-Yan; Su, Jing-Jun; He, Zhen-Yu

2017-08-01

To evaluate the clinicopathological features, patterns of distant metastases, and survival outcome between stage IV male breast cancer (MBC) and female breast cancer (FBC). Patients diagnosed with stage IV MBC and FBC between 2010 and 2013 were included using the Surveillance, Epidemiology, and End Results program. Univariate and multivariate Cox regression analyses were used to analyze risk factors for overall survival (OS). A total of 4997 patients were identified, including 60 MBC and 4937 FBC. Compared with FBC, patients with MBC were associated with a significantly higher rate of estrogen receptor-positive, progesterone receptor-positive, unmarried, lung metastases, and a lower frequency of liver metastases. Univariate and multivariate analyses showed no significant difference in OS between MBC and FBC. In the propensity score-matched population, there was also no difference in survival between MBC and FBC. Multivariate analysis of MBC showed that OS was longer for patients aged 50-69 years and with estrogen receptor-positive disease. There was no significant difference in survival outcome between stage IV MBC and FBC, but significant differences in clinicopathological features and patterns of metastases between the genders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Endoscopic third ventriculostomy in the treatment of childhood hydrocephalus.

PubMed

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

2009-08-01

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

Comparison of Mental Health Treatment Adequacy and Costs in Public Hospitals in Boston and Madrid.

PubMed

Carmona, Rodrigo; Cook, Benjamin Lê; Baca-García, Enrique; Chavez, Ligia; Alvarez, Kiara; Iza, Miren; Alegría, Margarita

2018-03-07

Analyses of healthcare expenditures and adequacy are needed to identify cost-effective policies and practices that improve mental healthcare quality. Data are from 2010 to 2012 electronic health records from three hospital psychiatry departments in Madrid (n = 29,944 person-years) and three in Boston (n = 14,109 person-years). Two-part multivariate generalized linear regression and logistic regression models were estimated to identify site differences in mental healthcare expenditures and quality of care. Annual total average treatment expenditures were $4442.14 in Boston and $2277.48 in Madrid. Boston patients used inpatient services more frequently and had higher 30-day re-admission rates (23.7 vs. 8.7%) despite higher rates of minimally adequate care (49.5 vs. 34.8%). Patients in Madrid were more likely to receive psychotropic medication, had fewer inpatient stays and readmissions, and had lower expenditures, but had lower rates of minimally adequate care. Differences in insurance and healthcare system policies and mental health professional roles may explain these dissimilarities.

Multivariate research in areas of phosphorus cast-iron brake shoes manufacturing using the statistical analysis and the multiple regression equations

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Alexa, V.; Raţiu, S. A.

2017-05-01

The braking system is one of the most important and complex subsystems of railway vehicles, especially when it comes for safety. Therefore, installing efficient safe brakes on the modern railway vehicles is essential. Nowadays is devoted attention to solving problems connected with using high performance brake materials and its impact on thermal and mechanical loading of railway wheels. The main factor that influences the selection of a friction material for railway applications is the performance criterion, due to the interaction between the brake block and the wheel produce complex thermos-mechanical phenomena. In this work, the investigated subjects are the cast-iron brake shoes, which are still widely used on freight wagons. Therefore, the cast-iron brake shoes - with lamellar graphite and with a high content of phosphorus (0.8-1.1%) - need a special investigation. In order to establish the optimal condition for the cast-iron brake shoes we proposed a mathematical modelling study by using the statistical analysis and multiple regression equations. Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. Multivariate visualization comes to the fore when researchers have difficulties in comprehending many dimensions at one time. Technological data (hardness and chemical composition) obtained from cast-iron brake shoes were used for this purpose. In order to settle the multiple correlation between the hardness of the cast-iron brake shoes, and the chemical compositions elements several model of regression equation types has been proposed. Because a three-dimensional surface with variables on three axes is a common way to illustrate multivariate data, in which the maximum and minimum values are easily highlighted, we plotted graphical representation of the regression equations in order to explain interaction of the variables and locate the optimal level of each variable for maximal response. For the calculation of the regression coefficients, dispersion and correlation coefficients, the software Matlab was used.

Multivariate analysis of risk factors for long-term urethroplasty outcome.

PubMed

Breyer, Benjamin N; McAninch, Jack W; Whitson, Jared M; Eisenberg, Michael L; Mehdizadeh, Jennifer F; Myers, Jeremy B; Voelzke, Bryan B

2010-02-01

We studied the patient risk factors that promote urethroplasty failure. Records of patients who underwent urethroplasty at the University of California, San Francisco Medical Center between 1995 and 2004 were reviewed. Cox proportional hazards regression analysis was used to identify multivariate predictors of urethroplasty outcome. Between 1995 and 2004, 443 patients of 495 who underwent urethroplasty had complete comorbidity data and were included in analysis. Median patient age was 41 years (range 18 to 90). Median followup was 5.8 years (range 1 month to 10 years). Stricture recurred in 93 patients (21%). Primary estimated stricture-free survival at 1, 3 and 5 years was 88%, 82% and 79%. After multivariate analysis smoking (HR 1.8, 95% CI 1.0-3.1, p = 0.05), prior direct vision internal urethrotomy (HR 1.7, 95% CI 1.0-3.0, p = 0.04) and prior urethroplasty (HR 1.8, 95% CI 1.1-3.1, p = 0.03) were predictive of treatment failure. On multivariate analysis diabetes mellitus showed a trend toward prediction of urethroplasty failure (HR 2.0, 95% CI 0.8-4.9, p = 0.14). Length of urethral stricture (greater than 4 cm), prior urethroplasty and failed endoscopic therapy are predictive of failure after urethroplasty. Smoking and diabetes mellitus also may predict failure potentially secondary to microvascular damage. Copyright 2010 American Urological Association. Published by Elsevier Inc. All rights reserved.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China.

PubMed

Pei, Ling-Ling; Li, Qin; Wang, Zheng-Xin

2018-03-08

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China's pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N )) model based on the nonlinear least square (NLS) method. The Gauss-Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N ) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N ) and the NLS-based TNGM (1, N ) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO₂ and dust, alongside GDP per capita in China during the period 1996-2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N ) model presents greater precision when forecasting WDPC, SO₂ emissions and dust emissions per capita, compared to the traditional GM (1, N ) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO₂ and dust reduce accordingly.

Circulating miRNAs in Pediatric Pulmonary Hypertension Show Promise as Biomarkers of Vascular Function

PubMed Central

Sucharov, Carmen C.; Truong, Uyen; Dunning, Jamie; Ivy, Dunbar; Miyamoto, Shelley; Shandas, Robin

2017-01-01

Background/Objectives The objective of this study was to evaluate the utility of circulating miRNAs as biomarkers of vascular function in pediatric pulmonary hypertension. Method Fourteen pediatric pulmonary arterial hypertension patients underwent simultaneous right heart catheterization (RHC) and blood biochemical analysis. Univariate and stepwise multivariate linear regression was used to identify and correlate measures of reactive and resistive afterload with circulating miRNA levels. Furthermore, circulating miRNA candidates that classified patients according to a 20% decrease in resistive afterload in response to oxygen (O2) or inhaled nitric oxide (iNO) were identified using receiver-operating curves. Results Thirty-two circulating miRNAs correlated with the pulmonary vascular resistance index (PVRi), pulmonary arterial distensibility, and PVRi decrease in response to O2 and/or iNO. Multivariate models, combining the predictive capability of multiple promising miRNA candidates, revealed a good correlation with resistive (r = 0.97, P2−tailed < 0.0001) and reactive (r = 0.86, P2−tailed < 0.005) afterloads. Bland-Altman plots showed that 95% of the differences between multivariate models and RHC would fall within 0.13 (mmHg−min/L)m2 and 0.0085/mmHg for resistive and reactive afterloads, respectively. Circulating miR-663 proved to be a good classifier for vascular responsiveness to acute O2 and iNO challenges. Conclusion This study suggests that circulating miRNAs may be biomarkers to phenotype vascular function in pediatric PAH. PMID:28819545

Why so GLUMM? Detecting depression clusters through graphing lifestyle-environs using machine-learning methods (GLUMM).

PubMed

Dipnall, J F; Pasco, J A; Berk, M; Williams, L J; Dodd, S; Jacka, F N; Meyer, D

2017-01-01

Key lifestyle-environ risk factors are operative for depression, but it is unclear how risk factors cluster. Machine-learning (ML) algorithms exist that learn, extract, identify and map underlying patterns to identify groupings of depressed individuals without constraints. The aim of this research was to use a large epidemiological study to identify and characterise depression clusters through "Graphing lifestyle-environs using machine-learning methods" (GLUMM). Two ML algorithms were implemented: unsupervised Self-organised mapping (SOM) to create GLUMM clusters and a supervised boosted regression algorithm to describe clusters. Ninety-six "lifestyle-environ" variables were used from the National health and nutrition examination study (2009-2010). Multivariate logistic regression validated clusters and controlled for possible sociodemographic confounders. The SOM identified two GLUMM cluster solutions. These solutions contained one dominant depressed cluster (GLUMM5-1, GLUMM7-1). Equal proportions of members in each cluster rated as highly depressed (17%). Alcohol consumption and demographics validated clusters. Boosted regression identified GLUMM5-1 as more informative than GLUMM7-1. Members were more likely to: have problems sleeping; unhealthy eating; ≤2 years in their home; an old home; perceive themselves underweight; exposed to work fumes; experienced sex at ≤14 years; not perform moderate recreational activities. A positive relationship between GLUMM5-1 (OR: 7.50, P<0.001) and GLUMM7-1 (OR: 7.88, P<0.001) with depression was found, with significant interactions with those married/living with partner (P=0.001). Using ML based GLUMM to form ordered depressive clusters from multitudinous lifestyle-environ variables enabled a deeper exploration of the heterogeneous data to uncover better understandings into relationships between the complex mental health factors. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Impact of prostate weight on probability of positive surgical margins in patients with low-risk prostate cancer after robotic-assisted laparoscopic radical prostatectomy.

PubMed

Marchetti, Pablo E; Shikanov, Sergey; Razmaria, Aria A; Zagaja, Gregory P; Shalhav, Arieh L

2011-03-01

To evaluate the impact of prostate weight (PW) on probability of positive surgical margin (PSM) in patients undergoing robotic-assisted radical prostatectomy (RARP) for low-risk prostate cancer. The cohort consisted of 690 men with low-risk prostate cancer (clinical stage T1c, prostate-specific antigen <10 ng/mL, biopsy Gleason score ≤6) who underwent RARP with bilateral nerve-sparing at our institution by 1 of 2 surgeons from 2003 to 2009. PW was obtained from the pathologic specimen. The association between probability of PSM and PW was assessed with univariate and multivariate logistic regression analysis. A PSM was identified in 105 patients (15.2%). Patients with PSM had significant higher prostate-specific antigen (P = .04), smaller prostates (P = .0001), higher Gleason score (P = .004), and higher pathologic stage (P < .0001). After logistic regression, we found a significant inverse relation between PSM and PW (OR 0.97%; 95% confidence interval [CI] 0.96, 0.99; P = .0003) in univariate analysis. This remained significant in the multivariate model (OR 0.98%; 95% CI 0.96, 0.99; P = .006) adjusting for age, body mass index, surgeon experience, pathologic Gleason score, and pathologic stage. In this multivariate model, the predicted probability of PSM for 25-, 50-, 100-, and 150-g prostates were 22% (95% CI 16%, 30%), 13% (95% CI 11%, 16%), 5% (95% CI 1%, 8%), and 1% (95% CI 0%, 3%), respectively. Lower PW is independently associated with higher probability of PSM in low-risk patients undergoing RARP with bilateral nerve-sparing. Copyright © 2011 Elsevier Inc. All rights reserved.

Remote Zone Extracellular Volume and Left Ventricular Remodeling in Survivors of ST-Elevation Myocardial Infarction.

PubMed

Carberry, Jaclyn; Carrick, David; Haig, Caroline; Rauhalammi, Samuli M; Ahmed, Nadeem; Mordi, Ify; McEntegart, Margaret; Petrie, Mark C; Eteiba, Hany; Hood, Stuart; Watkins, Stuart; Lindsay, Mitchell; Davie, Andrew; Mahrous, Ahmed; Ford, Ian; Sattar, Naveed; Welsh, Paul; Radjenovic, Aleksandra; Oldroyd, Keith G; Berry, Colin

2016-08-01

The natural history and pathophysiological significance of tissue remodeling in the myocardial remote zone after acute ST-elevation myocardial infarction (STEMI) is incompletely understood. Extracellular volume (ECV) in myocardial regions of interest can now be measured with cardiac magnetic resonance imaging. Patients who sustained an acute STEMI were enrolled in a cohort study (BHF MR-MI [British Heart Foundation Magnetic Resonance Imaging in Acute ST-Segment Elevation Myocardial Infarction study]). Cardiac magnetic resonance was performed at 1.5 Tesla at 2 days and 6 months post STEMI. T1 modified Look-Locker inversion recovery mapping was performed before and 15 minutes after contrast (0.15 mmol/kg gadoterate meglumine) in 140 patients at 2 days post STEMI (mean age: 59 years, 76% male) and in 131 patients at 6 months post STEMI. Remote zone ECV was lower than infarct zone ECV (25.6±2.8% versus 51.4±8.9%; P<0.001). In multivariable regression, left ventricular ejection fraction was inversely associated with remote zone ECV (P<0.001), and diabetes mellitus was positively associated with remote zone ECV (P=0.010). No ST-segment resolution (P=0.034) and extent of ischemic area at risk (P<0.001) were multivariable associates of the change in remote zone ECV at 6 months (ΔECV). ΔECV was a multivariable associate of the change in left ventricular end-diastolic volume at 6 months (regression coefficient [95% confidence interval]: 1.43 (0.10-2.76); P=0.036). ΔECV is implicated in the pathophysiology of left ventricular remodeling post STEMI, but because the effect size is small, ΔECV has limited use as a clinical biomarker of remodeling. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02072850. © 2016 The Authors.

Remote Zone Extracellular Volume and Left Ventricular Remodeling in Survivors of ST-Elevation Myocardial Infarction

PubMed Central

Carberry, Jaclyn; Carrick, David; Haig, Caroline; Rauhalammi, Samuli M.; Ahmed, Nadeem; Mordi, Ify; McEntegart, Margaret; Petrie, Mark C.; Eteiba, Hany; Hood, Stuart; Watkins, Stuart; Lindsay, Mitchell; Davie, Andrew; Mahrous, Ahmed; Ford, Ian; Sattar, Naveed; Welsh, Paul; Radjenovic, Aleksandra; Oldroyd, Keith G.

2016-01-01

The natural history and pathophysiological significance of tissue remodeling in the myocardial remote zone after acute ST-elevation myocardial infarction (STEMI) is incompletely understood. Extracellular volume (ECV) in myocardial regions of interest can now be measured with cardiac magnetic resonance imaging. Patients who sustained an acute STEMI were enrolled in a cohort study (BHF MR-MI [British Heart Foundation Magnetic Resonance Imaging in Acute ST-Segment Elevation Myocardial Infarction study]). Cardiac magnetic resonance was performed at 1.5 Tesla at 2 days and 6 months post STEMI. T1 modified Look-Locker inversion recovery mapping was performed before and 15 minutes after contrast (0.15 mmol/kg gadoterate meglumine) in 140 patients at 2 days post STEMI (mean age: 59 years, 76% male) and in 131 patients at 6 months post STEMI. Remote zone ECV was lower than infarct zone ECV (25.6±2.8% versus 51.4±8.9%; P<0.001). In multivariable regression, left ventricular ejection fraction was inversely associated with remote zone ECV (P<0.001), and diabetes mellitus was positively associated with remote zone ECV (P=0.010). No ST-segment resolution (P=0.034) and extent of ischemic area at risk (P<0.001) were multivariable associates of the change in remote zone ECV at 6 months (ΔECV). ΔECV was a multivariable associate of the change in left ventricular end-diastolic volume at 6 months (regression coefficient [95% confidence interval]: 1.43 (0.10–2.76); P=0.036). ΔECV is implicated in the pathophysiology of left ventricular remodeling post STEMI, but because the effect size is small, ΔECV has limited use as a clinical biomarker of remodeling. Clinical Trial Registration— URL: https://www.clinicaltrials.gov. Unique identifier: NCT02072850. PMID:27354423

Time to antibiotics and outcomes in cancer patients with febrile neutropenia

PubMed Central

2014-01-01

Background Febrile neutropenia is an oncologic emergency. The timing of antibiotics administration in patients with febrile neutropenia may result in adverse outcomes. Our study aims to determine time-to- antibiotic administration in patients with febrile neutropenia, and its relationship with length of hospital stay, intensive care unit monitoring, and hospital mortality. Methods The study population was comprised of adult cancer patients with febrile neutropenia who were hospitalized, at a tertiary care hospital, between January 2010 and December 2011. Using Multination Association of Supportive Care in Cancer (MASCC) risk score, the study cohort was divided into high and low risk groups. A multivariate regression analysis was performed to assess relationship between time-to- antibiotic administration and various outcome variables. Results One hundred and five eligible patients with median age of 60 years (range: 18–89) and M:F of 43:62 were identified. Thirty-seven (35%) patients were in MASCC high risk group. Median time-to- antibiotic administration was 2.5 hrs (range: 0.03-50) and median length of hospital stay was 6 days (range: 1–57). In the multivariate analysis time-to- antibiotic administration (regression coefficient [RC]: 0.31 days [95% CI: 0.13-0.48]), known source of fever (RC: 4.1 days [95% CI: 0.76-7.5]), and MASCC high risk group (RC: 4 days [95% CI: 1.1-7.0]) were significantly correlated with longer hospital stay. Of 105 patients, 5 (4.7%) died & or required ICU monitoring. In multivariate analysis no variables significantly correlated with mortality or ICU monitoring. Conclusions Our study revealed that delay in antibiotics administration has been associated with a longer hospital stay. PMID:24716604

Successful Diabetic Control as Measured by Hemoglobin A1c is Associated with Lower Urine Risk Factors for Uric Acid Calculi.

PubMed

Maciolek, Kimberly A; Penniston, Kristina L; Jhagroo, R Allan; Best, Sara L

2018-06-13

To examine the association of glycemic control, including strict glycemic control, with 24-hour (24-h) urine risk factors for uric acid and calcium calculi. With IRB approval, we identified 183 stone formers (SFs) with 459 24-h urine collections. Hemoglobin A1c (HgbA1c) measures were obtained within 3 months of the urine collection. Collections were separated into normoglycemic (NG, HgbA1c<6.5) and hyperglycemic (HG, HgbA1c≥6.5) cohorts; 24-h urine parameters were compared. The NG cohort was further divided into patients with and without a history of diabetes type 2 (DM). Variables were analyzed using chi squared, Welch's t-test and multivariate linear regression to adjust for clustering, BMI, age, gender, thiazide and potassium citrate use. Patients in the HG group were older with higher BMI. Multivariate analysis of the total study population revealed that hyperglycemia correlated with lower pH, higher uric acid relative saturation (RS), lower brushite RS and higher citrate. NG SFs with and without a history of DM had similar risk factors for uric acid stone formation. Among NG SFs, those with DM had higher urine calcium (UCa) and calcium oxalate RS than those without DM. However, this difference may be related to other factors since neither parameter correlated with DM on multivariate regression (p>0.05). Successful glycemic control may be associated with reduced urinary risk factors for uric acid stone formation. Patients with well controlled DM had equivalent risk factors to those without DM. Glycemic control should be considered a target of the multidisciplinary medical management of stone disease.

Differences in temperament, character and psychopathology among subjects with different patterns of cannabis use.

PubMed

Spalletta, Gianfranco; Bria, Pietro; Caltagirone, Carlo

2007-01-01

Patients who use illicit drugs and suffer from comorbid psychiatric illnesses have worse outcomes than drug users without a dual diagnosis. For this reason we aimed at identifying predictors of cannabis use severity using a multivariate model in which different clinical and socio-demographic variables were included. We administered the Temperament and Character Inventory, SCID-P, SCID-II, the Beck Depression Inventory and the State-Trait Anxiety Inventory. Of the 84 subjects included, 25 were occasional users, 37 were abusers, and 22 were dependent on cannabis. A stepwise multiple regression analysis identified increased self-transcendence scores and state anxiety severity as the only predictors of a increased cannabis use severity (F = 6.635; d.f. = 2, 81; p = 0.0021). In particular, in a further multivariate analysis of variance, the transpersonal identification issue of self-transcendence was associated significantly (F = 4.267; d.f. = 2, 81; p = 0.017) with greater severity of cannabis use. Character dimension of self-transcendence and symptoms of state anxiety should be taken into consideration during the assessment procedure of patients with cannabis use as they may be helpful in the discrimination of cannabis use severity.

Exploring the facilitators and barriers to engagement in physical activity for people with multiple sclerosis.

PubMed

Kayes, Nicola M; McPherson, Kathryn M; Schluter, Philip; Taylor, Denise; Leete, Marta; Kolt, Gregory S

2011-01-01

To explore the relationship that cognitive behavioural and other previously identified variables have with physical activity engagement in people with multiple sclerosis (MS). This study adopted a cross-sectional questionnaire design. Participants were 282 individuals with MS. Outcome measures included the Physical Activity Disability Survey--Revised, Cognitive and Behavioural Responses to Symptoms Questionnaire, Barriers to Health Promoting Activities for Disabled Persons Scale, Multiple Sclerosis Self-efficacy Scale, Self-Efficacy for Chronic Diseases Scales and Chalder Fatigue Questionnaire. Multivariable stepwise regression analyses found that greater self-efficacy, greater reported mental fatigue and lower number of perceived barriers to physical activity accounted for a significant proportion of variance in physical activity behaviour, over that accounted for by illness-related variables. Although fear-avoidance beliefs accounted for a significant proportion of variance in the initial analyses, its effect was explained by other factors in the final multivariable analyses. Self-efficacy, mental fatigue and perceived barriers to physical activity are potentially modifiable variables which could be incorporated into interventions designed to improve physical activity engagement. Future research should explore whether a measurement tool tailored to capture beliefs about physical activity identified by people with MS would better predict participation in physical activity.

Predictors of readmission after successful electroconvulsive therapy for depression: a chart review study.

PubMed

Uchida, Takahito; Kishimoto, Taishiro; Koreki, Akihiro; Nakao, Shigetsugu; Owada, Ai; Koizumi, Teruki; Saito, Atsuyuki; Sato, Minako; Sawada, Shinya; Matsuzaki, Ryuta; Petrides, Georgios; Mimura, Masaru

2016-11-01

The study aimed to identify the predictors for readmission after a successful electroconvulsive therapy (ECT) course. Medical charts of patients who received ECT for major depressive episodes were reviewed. Patients' demographic characteristics and treatment parameters, such as ECT charge, seizure duration, the number of ECT sessions and pharmacotherapy, were extracted. We compared differences between those who were readmitted after successful ECT within 6 and 12 months, versus those not readmitted. We also conducted a multivariate logistic regression analysis to identify the predictors for readmission. Out of 51 patients who were discharged after ECT, 27 patients met the inclusion criteria and were included in the analysis. Eight patients were readmitted within 6 months after discharge, and four more patients were readmitted during the next 6-month follow up. Comparing patients who were and were not readmitted, we found no significant differences between groups, including ECT parameters such as the number of ECT sessions, average charge and final charge. No predictors for readmission were found through multivariate analysis. Although patients who require higher ECT charge and more sessions seem to be prone to readmission, our dataset suggested that none of these types of ECT parameters were risk factors for readmission.

Diagnosis of pernicious anemia and the risk of pancreatic cancer.

PubMed

Shah, Pari; Rhim, Andrew D; Haynes, Kevin; Hwang, Wei-Ting; Yang, Yu-Xiao

2014-04-01

A number of studies have demonstrated a trophic effect of gastrin on pancreatic cancer cells in vitro. Pernicious anemia (PA) is a clinical condition characterized by chronic hypergastrinemia. The aim of this study was to determine if PA is a risk factor for pancreatic cancer. This study is a retrospective cohort study using The Health Improvement Network database, which contains comprehensive health information on 7.5 million patients in the United Kingdom from 1993 to 2009. All patients with PA in the study cohort were identified and composed of the exposed group. Each exposed patient was matched on practice site, sex, and age with up to 4 unexposed patients without PA. The outcome was incident pancreatic cancer. The hazard ratio and 95% confidence intervals were estimated using multivariable Cox regression analysis. We identified 15,324 patients with PA and 55,094 unexposed patients. Mean follow-up time was similar between groups (exposed 4.31 [SD, 3.38] years, unexposed 4.63 [SD, 3.44] years). The multivariable adjusted hazard ratio for pancreatic cancer associated with PA was 1.16 (95% confidence interval, 0.77-1.76; P = 0.47). There is no significant association between PA and the risk of pancreatic cancer.

Computation of nonlinear least squares estimator and maximum likelihood using principles in matrix calculus

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi; Balasiddamuni, P.

2017-11-01

This paper uses matrix calculus techniques to obtain Nonlinear Least Squares Estimator (NLSE), Maximum Likelihood Estimator (MLE) and Linear Pseudo model for nonlinear regression model. David Pollard and Peter Radchenko [1] explained analytic techniques to compute the NLSE. However the present research paper introduces an innovative method to compute the NLSE using principles in multivariate calculus. This study is concerned with very new optimization techniques used to compute MLE and NLSE. Anh [2] derived NLSE and MLE of a heteroscedatistic regression model. Lemcoff [3] discussed a procedure to get linear pseudo model for nonlinear regression model. In this research article a new technique is developed to get the linear pseudo model for nonlinear regression model using multivariate calculus. The linear pseudo model of Edmond Malinvaud [4] has been explained in a very different way in this paper. David Pollard et.al used empirical process techniques to study the asymptotic of the LSE (Least-squares estimation) for the fitting of nonlinear regression function in 2006. In Jae Myung [13] provided a go conceptual for Maximum likelihood estimation in his work “Tutorial on maximum likelihood estimation

Rex fortran 4 system for combinatorial screening or conventional analysis of multivariate regressions

Treesearch

L.R. Grosenbaugh

1967-01-01

Describes an expansible computerized system that provides data needed in regression or covariance analysis of as many as 50 variables, 8 of which may be dependent. Alternatively, it can screen variously generated combinations of independent variables to find the regression with the smallest mean-squared-residual, which will be fitted if desired. The user can easily...

Knowledge of neonatal danger signs among mothers attending well baby clinic in Nakuru Central District, Kenya: cross sectional descriptive study.

PubMed

Kibaru, Elizabeth Gathoni; Otara, Amos Magembe

2016-10-25

Neonatal mortality has remained high in Kenya despite various efforts being applied to reduce this negative trend. Early detection of neonatal illness is an important step towards improving new born survival. Toward this end there is need for the mothers to be able to identify signs in neonates that signifies severe neonatal illnesses. The objective of the study was to determine the level of knowledge of mothers attending well baby clinics on postnatal neonatal danger signs and determine the associated factors. Cross sectional descriptive study. Purposive sampling of Health care facilities that provide antenatal, delivery and postnatal services were identified. In each of the selected health facility structured questionnaires were administered to mothers with children aged six weeks to nine months attending well baby clinics. Frequencies, Chi square and multivariate logistic regression were determined using the SPSS software (version 20). During the period of study 414 mothers attending well baby clinics were interviewed. Information on neonatal dangers was not provided to 237 (57.2%) of the postnatal mothers during their antenatal clinic attendance by the health care providers. Majority of mothers 350 (84.5%) identified less than three neonatal danger signs. Hotness of the body (fever) was the commonly recognized danger sign by 310 (74.9%) postnatal mothers. Out of 414 mothers 193 (46.6%), 166 (40.1%), 146 (35.3%) and 24 (5.8%) identified difficulty in breathing, poor sucking, jaundice and lethargy/unconsciousness as new born danger signs respectively. Only 46 (11.1%) and 40 (9.7%) identified convulsion and hypothermia as new born danger signs respectively. Education Level, PNC accompaniment by Spouse, Danger signs information to Mother, Explanation of MCH booklet by Care provider during ANC and Mother read MCH Booklet were factors positively associated with improved knowledge of neonatal danger sign. In multivariate logistic regression none of the factors tested were statistically significant in relation to level of knowledge. Knowledge of neonatal danger signs was low among mothers attending well baby clinic despite the information being available in the MCH booklets provided to the mothers during antenatal clinics.

Optimal Timing for Elective Early Primary Repair of Tetralogy of Fallot: Analysis of Intermediate Term Outcomes.

PubMed

Cunningham, Michael E A; Donofrio, Mary T; Peer, Syed Murfad; Zurakowski, David; Jonas, Richard A; Sinha, Pranava

2017-03-01

We have previously demonstrated that early primary repair of tetralogy of Fallot with pulmonary stenosis (TOF) can be safely performed without increase in hospital resource utilization or compromise to surgical technical performance scores (TPS). We sought to identify the optimal timing for elective early primary repair of TOF with respect to intermediate-term reintervention. Retrospective review of all patients with TOF undergoing elective primary repair between September 2004 and December 2013 was performed. Patients were stratified into reintervention group or no reintervention group. Multivariable Cox regression analysis identified independent predictors of reintervention. Youden's J-index in receiver operating characteristic analysis identified optimal age cutoff predictive of reintervention. Kaplan-Meier analysis with the log-rank test compared reintervention rates stratified by age and TPS. A total of 129 patients with median (interquartile range) age and weight of 78 days (56 to 111) and 5 kg (4.1 to 5.7), respectively, underwent primary repair. After a median (interquartile range) follow-up of 2.3 years (0.1 to 4.6), 18 patients (14%) required a total of 22 reinterventions. Youden's J-index revealed significantly lower risk of intermediate-term reintervention when repaired after 55 days of age (8% for >55 days old versus 31% for ≤55 days of age). Multivariable Cox regression identified age 55 days and younger (hazard ratio [HR] 4.5, 95% confidence interval [CI] 1.6 to 12.8, p = 0.004), valve sparing repair (HR 15.3, 95% CI 1.8 to 128.5, p < 0.001), residual right ventricular outflow tract (RVOT) gradient (HR 1.11, 95% CI 1.1 to 1.2, p < 0.001), and inadequate TPS (HR 21.5, 95% CI 7.4 to 63, p < 0.001) as independent predictors of overall intermediate-term reintervention. Elective repair in patients greater than 55 days of age, irrespective of size of the patient, can be safely performed without any increase in reintervention rates. Both residual peak RVOT gradient and TPS are effective in identifying patients at increased risk of reintervention. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Risk analysis for occurrences of schistosomiasis in the coastal area of Porto de Galinhas, Pernambuco, Brazil

PubMed Central

2014-01-01

Background Manson’s schistosomiasis continues to be a severe public health problem in Brazil, where thousands of people live under the risk of contracting this parasitosis. In the Northeast of Brazil, schistosomiasis has expanded from rural areas to the coast of Pernambuco State, where the intermediate host is Biomphalaria glabrata snails. This study aims at presenting situational analyses on schistosomiasis at the coastal locality of Porto de Galinhas, Pernambuco, Brazil, by determining the risk factors relating to its occurrence from the epidemiological and spatial perspectives. Methods In order to gather prevalence data, a parasitological census surveys were conducted in 2010 in the light of the Kato-Katz technique. Furthermore, malacological surveys were also conducted in the same years so as to define the density and infection rates of the intermediate host. Lastly, socioeconomic-behavioral survey was also conducted to determine the odds ratio for infection by Schistosoma mansoni. Based on these data, spatial analyses were done, resulting in maps of the risk of disease transmission. To predict the risk of schistosomiasis occurrence, a multivariate logistic regression was performed using R 2.13 software. Results Based on prevalence, malacological and socioeconomic-behavioural surveys, it was identified a prevalence of 15.7% in the investigated population (2,757 individuals). Due to the malacological survey, 36 breeding sites were identified, of which 11 were classified as foci of schistosomiasis transmission since they pointed out snails which were infected by Schistosoma mansoni. Overall, 11,012 snails (Biomphalaria glabrata) were collected. The multivariate regression model identified six explanatory variables of environmental, socioeconomic and demographic nature. Spatial sweep analysis by means of the Bernoulli method identified one statistically significant cluster in Salinas (RR = 2.2; p-value < 0.000), the district with the highest occurrence of cases. Conclusions Based on the resulting information from this study, the epidemiological dimensions of this disease are significant and severe, within the scenario of schistosomiasis in Pernambuco state. The risk factors which were identified in the predictive model made it clear that the environmental and social conditions influence on the schistosomiasis occurrences. PMID:24559264

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

Factors related to clinical pregnancy after vitrified-warmed embryo transfer: a retrospective and multivariate logistic regression analysis of 2313 transfer cycles.

PubMed

Shi, Wenhao; Zhang, Silin; Zhao, Wanqiu; Xia, Xue; Wang, Min; Wang, Hui; Bai, Haiyan; Shi, Juanzi

2013-07-01

What factors does multivariate logistic regression show to be significantly associated with the likelihood of clinical pregnancy in vitrified-warmed embryo transfer (VET) cycles? Assisted hatching (AH) and if the reason to freeze embryos was to avoid the risk of ovarian hyperstimulation syndrome (OHSS) were significantly positively associated with a greater likelihood of clinical pregnancy. Single factor analysis has shown AH, number of embryos transferred and the reason of freezing for OHSS to be positively and damaged blastomere to be negatively significantly associated with the chance of clinical pregnancy after VET. It remains unclear what factors would be significant after multivariate analysis. The study was a retrospective analysis of 2313 VET cycles from 1481 patients performed between January 2008 and April 2012. A multivariate logistic regression analysis was performed to identify the factors to affect clinical pregnancy outcome of VET. There were 22 candidate variables selected based on clinical experiences and the literature. With the thresholds of α entry = α removal= 0.05 for both variable entry and variable removal, eight variables were chosen to contribute the multivariable model by the bootstrap stepwise variable selection algorithm (n = 1000). Eight variables were age at controlled ovarian hyperstimulation (COH), reason for freezing, AH, endometrial thickness, damaged blastomere, number of embryos transferred, number of good-quality embryos, and blood presence on transfer catheter. A descriptive comparison of the relative importance was accomplished by the proportion of explained variation (PEV). Among the reasons for freezing, the OHSS group showed a higher OR than the surplus embryo group when compared with other reasons for VET groups (OHSS versus Other, OR: 2.145; CI: 1.4-3.286; Surplus embryos versus Other, OR: 1.152; CI: 0.761-1.743) and high PEV (marginal 2.77%, P = 0.2911; partial 1.68%; CI of area under receptor operator characteristic curve (ROC): 0.5576-0.6000). AH also showed a high OR (OR: 2.105, CI: 1.554-2.85) and high PEV (marginal 1.97%; partial 1.02%; CI of area under ROC: 0.5344-0.5647). The number of good-quality embryos showed the highest marginal PEV and partial PEV (marginal 3.91%, partial 2.28%; CI of area under ROC: 0.5886-0.6343). This was a retrospective multivariate analysis of the data obtained in 5 years from a single IVF center. Repeated cycles in the same woman were treated as independent observations, which could introduce bias. Results are based on clinical pregnancy and not live births. Prospective analysis of a larger data set from a multicenter study based on live births is necessary to confirm the findings. Paying attention to the quality of embryos, the number of good embryos, AH and the reasons for freezing that are associated with clinical pregnancy after VET will assist the improvement of success rates.

Patient characteristics of smokers undergoing lumbar spine surgery: an analysis from the Quality Outcomes Database.

PubMed

Asher, Anthony L; Devin, Clinton J; McCutcheon, Brandon; Chotai, Silky; Archer, Kristin R; Nian, Hui; Harrell, Frank E; McGirt, Matthew; Mummaneni, Praveen V; Shaffrey, Christopher I; Foley, Kevin; Glassman, Steven D; Bydon, Mohamad

2017-12-01

OBJECTIVE In this analysis the authors compare the characteristics of smokers to nonsmokers using demographic, socioeconomic, and comorbidity variables. They also investigate which of these characteristics are most strongly associated with smoking status. Finally, the authors investigate whether the association between known patient risk factors and disability outcome is differentially modified by patient smoking status for those who have undergone surgery for lumbar degeneration. METHODS A total of 7547 patients undergoing degenerative lumbar surgery were entered into a prospective multicenter registry (Quality Outcomes Database [QOD]). A retrospective analysis of the prospectively collected data was conducted. Patients were dichotomized as smokers (current smokers) and nonsmokers. Multivariable logistic regression analysis fitted for patient smoking status and subsequent measurement of variable importance was performed to identify the strongest patient characteristics associated with smoking status. Multivariable linear regression models fitted for 12-month Oswestry Disability Index (ODI) scores in subsets of smokers and nonsmokers was performed to investigate whether differential effects of risk factors by smoking status might be present. RESULTS In total, 18% (n = 1365) of patients were smokers and 82% (n = 6182) were nonsmokers. In a multivariable logistic regression analysis, the factors significantly associated with patients' smoking status were sex (p < 0.0001), age (p < 0.0001), body mass index (p < 0.0001), educational status (p < 0.0001), insurance status (p < 0.001), and employment/occupation (p = 0.0024). Patients with diabetes had lowers odds of being a smoker (p = 0.0008), while patients with coronary artery disease had greater odds of being a smoker (p = 0.044). Patients' propensity for smoking was also significantly associated with higher American Society of Anesthesiologists (ASA) class (p < 0.0001), anterior-alone surgical approach (p = 0.018), greater number of levels (p = 0.0246), decompression only (p = 0.0001), and higher baseline ODI score (p < 0.0001). In a multivariable proportional odds logistic regression model, the adjusted odds ratio of risk factors and direction of improvement in 12-month ODI scores remained similar between the subsets of smokers and nonsmokers. CONCLUSIONS Using a large, national, multiinstitutional registry, the authors described the profile of patients who undergo lumbar spine surgery and its association with their smoking status. Compared with nonsmokers, smokers were younger, male, nondiabetic, nonobese patients presenting with leg pain more so than back pain, with higher ASA classes, higher disability, less education, more likely to be unemployed, and with Medicaid/uninsured insurance status. Smoking status did not affect the association between these risk factors and 12-month ODI outcome, suggesting that interventions for modifiable risk factors are equally efficacious between smokers and nonsmokers.

Clinical Trial Participation and Time to Treatment Among Adolescents and Young Adults With Cancer: Does Age at Diagnosis or Insurance Make a Difference?

PubMed Central

Parsons, Helen M.; Harlan, Linda C.; Seibel, Nita L.; Stevens, Jennifer L.; Keegan, Theresa H.M.

2011-01-01

Purpose Because adolescent and young adult (AYA) patients with cancer have experienced variable improvement in survival over the past two decades, enhancing the quality and timeliness of cancer care in this population has emerged as a priority area. To identify current trends in AYA care, we examined patterns of clinical trial participation, time to treatment, and provider characteristics in a population-based sample of AYA patients with cancer. Methods Using the National Cancer Institute Patterns of Care Study, we used multivariate logistic regression to evaluate demographic and provider characteristics associated with clinical trial enrollment and time to treatment among 1,358 AYA patients with cancer (age 15 to 39 years) identified through the Surveillance, Epidemiology, and End Results Program. Results In our study, 14% of patients age 15 to 39 years had enrolled onto a clinical trial; participation varied by type of cancer, with the highest participation in those diagnosed with acute lymphoblastic leukemia (37%) and sarcoma (32%). Multivariate analyses demonstrated that uninsured, older patients and those treated by nonpediatric oncologists were less likely to enroll onto clinical trials. Median time from pathologic confirmation to first treatment was 3 days, but this varied by race/ethnicity and cancer site. In multivariate analyses, advanced cancer stage and outpatient treatment alone were associated with longer time from pathologic confirmation to treatment. Conclusion Our study identified factors associated with low clinical trial participation in AYA patients with cancer. These findings support the continued need to improve access to clinical trials and innovative treatments for this population, which may ultimately translate into improved survival. PMID:21931022

Prediction of concurrent endometrial carcinoma in women with endometrial hyperplasia.

PubMed

Matsuo, Koji; Ramzan, Amin A; Gualtieri, Marc R; Mhawech-Fauceglia, Paulette; Machida, Hiroko; Moeini, Aida; Dancz, Christina E; Ueda, Yutaka; Roman, Lynda D

2015-11-01

Although a fraction of endometrial hyperplasia cases have concurrent endometrial carcinoma, patient characteristics associated with concurrent malignancy are not well described. The aim of our study was to identify predictive clinico-pathologic factors for concurrent endometrial carcinoma among patients with endometrial hyperplasia. A case-control study was conducted to compare endometrial hyperplasia in both preoperative endometrial biopsy and hysterectomy specimens (n=168) and endometrial carcinoma in hysterectomy specimen but endometrial hyperplasia in preoperative endometrial biopsy (n=43). Clinico-pathologic factors were examined to identify independent risk factors of concurrent endometrial carcinoma in a multivariate logistic regression model. The most common histologic subtype in preoperative endometrial biopsy was complex hyperplasia with atypia [CAH] (n=129) followed by complex hyperplasia without atypia (n=58) and simple hyperplasia with or without atypia (n=24). The majority of endometrial carcinomas were grade 1 (86.0%) and stage I (83.7%). In multivariate analysis, age 40-59 (odds ratio [OR] 3.07, p=0.021), age≥60 (OR 6.65, p=0.005), BMI≥35kg/m(2) (OR 2.32, p=0.029), diabetes mellitus (OR 2.51, p=0.019), and CAH (OR 9.01, p=0.042) were independent predictors of concurrent endometrial carcinoma. The risk of concurrent endometrial carcinoma rose dramatically with increasing number of risk factors identified in multivariate model (none 0%, 1 risk factor 7.0%, 2 risk factors 17.6%, 3 risk factors 35.8%, and 4 risk factors 45.5%, p<0.001). Hormonal treatment was associated with decreased risk of concurrent endometrial cancer in those with ≥3 risk factors. Older age, obesity, diabetes mellitus, and CAH are predictive of concurrent endometrial carcinoma in endometrial hyperplasia patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Dirichlet Component Regression and its Applications to Psychiatric Data.

PubMed

Gueorguieva, Ralitza; Rosenheck, Robert; Zelterman, Daniel

2008-08-15

We describe a Dirichlet multivariable regression method useful for modeling data representing components as a percentage of a total. This model is motivated by the unmet need in psychiatry and other areas to simultaneously assess the effects of covariates on the relative contributions of different components of a measure. The model is illustrated using the Positive and Negative Syndrome Scale (PANSS) for assessment of schizophrenia symptoms which, like many other metrics in psychiatry, is composed of a sum of scores on several components, each in turn, made up of sums of evaluations on several questions. We simultaneously examine the effects of baseline socio-demographic and co-morbid correlates on all of the components of the total PANSS score of patients from a schizophrenia clinical trial and identify variables associated with increasing or decreasing relative contributions of each component. Several definitions of residuals are provided. Diagnostics include measures of overdispersion, Cook's distance, and a local jackknife influence metric.

Enhanced ID Pit Sizing Using Multivariate Regression Algorithm

NASA Astrophysics Data System (ADS)

Krzywosz, Kenji

2007-03-01

EPRI is funding a program to enhance and improve the reliability of inside diameter (ID) pit sizing for balance-of plant heat exchangers, such as condensers and component cooling water heat exchangers. More traditional approaches to ID pit sizing involve the use of frequency-specific amplitude or phase angles. The enhanced multivariate regression algorithm for ID pit depth sizing incorporates three simultaneous input parameters of frequency, amplitude, and phase angle. A set of calibration data sets consisting of machined pits of various rounded and elongated shapes and depths was acquired in the frequency range of 100 kHz to 1 MHz for stainless steel tubing having nominal wall thickness of 0.028 inch. To add noise to the acquired data set, each test sample was rotated and test data acquired at 3, 6, 9, and 12 o'clock positions. The ID pit depths were estimated using a second order and fourth order regression functions by relying on normalized amplitude and phase angle information from multiple frequencies. Due to unique damage morphology associated with the microbiologically-influenced ID pits, it was necessary to modify the elongated calibration standard-based algorithms by relying on the algorithm developed solely from the destructive sectioning results. This paper presents the use of transformed multivariate regression algorithm to estimate ID pit depths and compare the results with the traditional univariate phase angle analysis. Both estimates were then compared with the destructive sectioning results.

Determination of boiling point of petrochemicals by gas chromatography-mass spectrometry and multivariate regression analysis of structural activity relationship.

PubMed

Fakayode, Sayo O; Mitchell, Breanna S; Pollard, David A

2014-08-01

Accurate understanding of analyte boiling points (BP) is of critical importance in gas chromatographic (GC) separation and crude oil refinery operation in petrochemical industries. This study reported the first combined use of GC separation and partial-least-square (PLS1) multivariate regression analysis of petrochemical structural activity relationship (SAR) for accurate BP determination of two commercially available (D3710 and MA VHP) calibration gas mix samples. The results of the BP determination using PLS1 multivariate regression were further compared with the results of traditional simulated distillation method of BP determination. The developed PLS1 regression was able to correctly predict analytes BP in D3710 and MA VHP calibration gas mix samples, with a root-mean-square-%-relative-error (RMS%RE) of 6.4%, and 10.8% respectively. In contrast, the overall RMS%RE of 32.9% and 40.4%, respectively obtained for BP determination in D3710 and MA VHP using a traditional simulated distillation method were approximately four times larger than the corresponding RMS%RE of BP prediction using MRA, demonstrating the better predictive ability of MRA. The reported method is rapid, robust, and promising, and can be potentially used routinely for fast analysis, pattern recognition, and analyte BP determination in petrochemical industries. Copyright © 2014 Elsevier B.V. All rights reserved.

Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

NASA Astrophysics Data System (ADS)

Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

2017-06-01

The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

Learning investment indicators through data extension

NASA Astrophysics Data System (ADS)

Dvořák, Marek

2017-07-01

Stock prices in the form of time series were analysed using single and multivariate statistical methods. After simple data preprocessing in the form of logarithmic differences, we augmented this single variate time series to a multivariate representation. This method makes use of sliding windows to calculate several dozen of new variables using simple statistic tools like first and second moments as well as more complicated statistic, like auto-regression coefficients and residual analysis, followed by an optional quadratic transformation that was further used for data extension. These were used as a explanatory variables in a regularized logistic LASSO regression which tried to estimate Buy-Sell Index (BSI) from real stock market data.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis.

PubMed

Liu, Fei; Ye, Lanhan; Peng, Jiyu; Song, Kunlin; Shen, Tingting; Zhang, Chu; He, Yong

2018-02-27

Fast detection of heavy metals is very important for ensuring the quality and safety of crops. Laser-induced breakdown spectroscopy (LIBS), coupled with uni- and multivariate analysis, was applied for quantitative analysis of copper in three kinds of rice (Jiangsu rice, regular rice, and Simiao rice). For univariate analysis, three pre-processing methods were applied to reduce fluctuations, including background normalization, the internal standard method, and the standard normal variate (SNV). Linear regression models showed a strong correlation between spectral intensity and Cu content, with an R 2 more than 0.97. The limit of detection (LOD) was around 5 ppm, lower than the tolerance limit of copper in foods. For multivariate analysis, partial least squares regression (PLSR) showed its advantage in extracting effective information for prediction, and its sensitivity reached 1.95 ppm, while support vector machine regression (SVMR) performed better in both calibration and prediction sets, where R c 2 and R p 2 reached 0.9979 and 0.9879, respectively. This study showed that LIBS could be considered as a constructive tool for the quantification of copper contamination in rice.

Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis

PubMed Central

Ye, Lanhan; Song, Kunlin; Shen, Tingting

2018-01-01

Fast detection of heavy metals is very important for ensuring the quality and safety of crops. Laser-induced breakdown spectroscopy (LIBS), coupled with uni- and multivariate analysis, was applied for quantitative analysis of copper in three kinds of rice (Jiangsu rice, regular rice, and Simiao rice). For univariate analysis, three pre-processing methods were applied to reduce fluctuations, including background normalization, the internal standard method, and the standard normal variate (SNV). Linear regression models showed a strong correlation between spectral intensity and Cu content, with an R2 more than 0.97. The limit of detection (LOD) was around 5 ppm, lower than the tolerance limit of copper in foods. For multivariate analysis, partial least squares regression (PLSR) showed its advantage in extracting effective information for prediction, and its sensitivity reached 1.95 ppm, while support vector machine regression (SVMR) performed better in both calibration and prediction sets, where Rc2 and Rp2 reached 0.9979 and 0.9879, respectively. This study showed that LIBS could be considered as a constructive tool for the quantification of copper contamination in rice. PMID:29495445

The microbiological profile and presence of bloodstream infection influence mortality rates in necrotizing fasciitis

PubMed Central

2011-01-01

Introduction Necrotizing fasciitis (NF) is a life threatening infectious disease with a high mortality rate. We carried out a microbiological characterization of the causative pathogens. We investigated the correlation of mortality in NF with bloodstream infection and with the presence of co-morbidities. Methods In this retrospective study, we analyzed 323 patients who presented with necrotizing fasciitis at two different institutions. Bloodstream infection (BSI) was defined as a positive blood culture result. The patients were categorized as survivors and non-survivors. Eleven clinically important variables which were statistically significant by univariate analysis were selected for multivariate regression analysis and a stepwise logistic regression model was developed to determine the association between BSI and mortality. Results Univariate logistic regression analysis showed that patients with hypotension, heart disease, liver disease, presence of Vibrio spp. in wound cultures, presence of fungus in wound cultures, and presence of Streptococcus group A, Aeromonas spp. or Vibrio spp. in blood cultures, had a significantly higher risk of in-hospital mortality. Our multivariate logistic regression analysis showed a higher risk of mortality in patients with pre-existing conditions like hypotension, heart disease, and liver disease. Multivariate logistic regression analysis also showed that presence of Vibrio spp in wound cultures, and presence of Streptococcus Group A in blood cultures were associated with a high risk of mortality while debridement > = 3 was associated with improved survival. Conclusions Mortality in patients with necrotizing fasciitis was significantly associated with the presence of Vibrio in wound cultures and Streptococcus group A in blood cultures. PMID:21693053

Primary fascial closure with mesh reinforcement is superior to bridged mesh repair for abdominal wall reconstruction.

PubMed

Booth, Justin H; Garvey, Patrick B; Baumann, Donald P; Selber, Jesse C; Nguyen, Alexander T; Clemens, Mark W; Liu, Jun; Butler, Charles E

2013-12-01

Many surgeons believe that primary fascial closure with mesh reinforcement should be the goal of abdominal wall reconstruction (AWR), yet others have reported acceptable outcomes when mesh is used to bridge the fascial edges. It has not been clearly shown how the outcomes for these techniques differ. We hypothesized that bridged repairs result in higher hernia recurrence rates than mesh-reinforced repairs that achieve fascial coaptation. We retrospectively reviewed prospectively collected data from consecutive patients with 1 year or more of follow-up, who underwent midline AWR between 2000 and 2011 at a single center. We compared surgical outcomes between patients with bridged and mesh-reinforced fascial repairs. The primary outcomes measure was hernia recurrence. Multivariate logistic regression analysis was used to identify factors predictive of or protective for complications. We included 222 patients (195 mesh-reinforced and 27 bridged repairs) with a mean follow-up of 31.1 ± 14.2 months. The bridged repairs were associated with a significantly higher risk of hernia recurrence (56% vs 8%; hazard ratio [HR] 9.5; p < 0.001) and a higher overall complication rate (74% vs 32%; odds ratio [OR] 3.9; p < 0.001). The interval to recurrence was more than 9 times shorter in the bridged group (HR 9.5; p < 0.001). Multivariate Cox proportional hazard regression analysis identified bridged repair and defect width > 15 cm to be independent predictors of hernia recurrence (HR 7.3; p < 0.001 and HR 2.5; p = 0.028, respectively). Mesh-reinforced AWRs with primary fascial coaptation resulted in fewer hernia recurrences and fewer overall complications than bridged repairs. Surgeons should make every effort to achieve primary fascial coaptation to reduce complications. Published by Elsevier Inc.

Clinical factors and the decision to transfuse chronic dialysis patients.

PubMed

Whitman, Cynthia B; Shreay, Sanatan; Gitlin, Matthew; van Oijen, Martijn G H; Spiegel, Brennan M R

2013-11-01

Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD. A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed. A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to 11.1). Adaptive choice-based conjoint analysis was useful in predicting influences on transfusion decisions. Hemoglobin level, functional status, and cardiovascular comorbidities most strongly influenced transfusion decision-making, but preference variations were observed among subgroups.

The globalization of whitening: prevalence of skin lighteners (or bleachers) use and its social correlates among university students in 26 countries.

PubMed

Peltzer, Karl; Pengpid, Supa; James, Caryl

2016-02-01

The aim of this study was to investigate the use of skin lighteners and its social correlates in university students from 26 low, middle income, and emerging economy countries. Using anonymous questionnaires, data were collected from 19,624 undergraduate university students (mean age 20.8, SD 2.8) from 27 universities in 26 countries across Asia, Africa, and the Americas. Multivariate logistic regression analysis was used to identify associations between sociodemographic, social, health risk, mental health and abuse, and the use of skin lighteners. Overall, the prevalence of previous 12-month skin lightener use was 24.5, and 16.7% in male and 30.0% in female students. The use of skin lighteners varied by country, ranging from 0% in Turkey to 83.8% in Thailand. In multivariate logistic regression analysis among both men and women, social variables (highly-organized religious activity and lack of personal mastery) and health variables (inconsistent condom use) were associated with skin lightening use. In addition, male students from a lower income country, having a lack of social support, and a history of childhood sexual abuse were more likely to use skin lighteners, and women aged 20-21 years old, residing on the university campus, being a student of health and welfare, and having a lack of personal control, inadequate physical activity, and depressive symptoms were more likely users of skin-lightening products. A high prevalence of skin lightener use was found in this large sample of university students, and social and health-related risk factors were identified. © 2015 The International Society of Dermatology.

The role of visual markers in police victimization among structurally vulnerable persons in Tijuana, Mexico.

PubMed

Pinedo, Miguel; Burgos, Jose Luis; Ojeda, Adriana Vargas; FitzGerald, David; Ojeda, Victoria D

2015-05-01

Law enforcement can shape HIV risk behaviours and undermine strategies aimed at curbing HIV infection. Little is known about factors that increase vulnerability to police victimization in Mexico. This study identifies correlates of police or army victimization (i.e., harassment or assault) in the past 6 months among patients seeking care at a free clinic in Tijuana, Mexico. From January to May 2013, 601 patients attending a binational student-run free clinic completed an interviewer-administered questionnaire. Eligible participants were: (1) ≥18 years old; (2) seeking care at the clinic; and (3) spoke Spanish or English. Multivariate logistic regression analyses identified factors associated with police/army victimization in the past 6 months. More than one-third (38%) of participants reported victimization by police/army officials in the past 6 months in Tijuana. In multivariate logistic regression analyses, males (adjusted odds ratio (AOR): 3.68; 95% CI: 2.19-6.19), tattooed persons (AOR: 1.56; 95% CI: 1.04-2.33) and those who injected drugs in the past 6 months (AOR: 2.11; 95% CI: 1.29-3.43) were significantly more likely to report past 6-month police/army victimization. Recent feelings of rejection (AOR: 3.80; 95% CI: 2.47-5.85) and being denied employment (AOR: 2.23; 95% CI: 1.50-3.32) were also independently associated with police/army victimization. Structural interventions aimed at reducing stigma against vulnerable populations and increasing social incorporation may aid in reducing victimization events by police/army in Tijuana. Police education and training to reduce abusive policing practices may be warranted. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

A no-reflow prediction model in patients with ST-elevation acute myocardial infarction and primary drug-eluting stenting.

PubMed

Wang, Chang-Hua; Chen, Yun-Dai; Yang, Xin-Chun; Wang, Le-Feng; Wang, Hong-Shi; Sun, Zhi-Jun; Liu, Hong-Bin

2011-04-01

This study was undertaken to assess independent no-reflow predictors in patients with ST-elevation acute myocardial infarction (STEMI) and primary drug-eluting stenting in the current interventional strategies. One thousand four hundred and thirteen patients with STEMI were successfully treated with primary drug-eluting stenting within 12 h after AMI. All clinical, angiographic and procedural data were collected. Univariate and multivariate logistic regression was used to identify independent no-reflow predictors. The no-reflow was found in 297 (21%) of 1413 patients. Univariate and multivariate logistic regression identified that age (>65 years, OR 1.47, 95% CI 1.46-1.49; p = 0.007), long time-to-reperfusion (>6 h, OR 1.27, 95% CI 1.16-1.40; p = 0.001), admission plasma glucose (>13.0 mmol/L, OR 1.27, 95% CI 1.16-1.40; p = 0.027), collateral circulation (0-1, OR 1.69, 95% CI 1.25-2.29; p = 0.001), pre-PCI thrombus score (≥4, OR 1.36, 95% CI 1.16-1.79; p = 0.011), and IABP use before PCI (OR 2.89, 95% CI 1.65-5.05; p < 0.0001) were independent no-reflow predictors. The no-reflow rate significantly increased as the number of independent predictors increased (0%, 6%, 15%, 25%, 40%, 50% and 100% in patients with 0, 1, 2, 3, 4, 5, and 6 independent predictors, respectively; p < 0.0001). The prediction model consisted of six no-reflow predictors in patients with STEMI and primary drug-eluting stenting and should be confirmed in large-scale prospective studies.

Efficacy of oral moxifloxacin for aerobic vaginitis.

PubMed

Wang, C; Han, C; Geng, N; Fan, A; Wang, Y; Yue, Y; Zhang, H; Xue, F

2016-01-01

The purpose of this study was to investigate the therapeutic efficacy of oral moxifloxacin for aerobic vaginitis (AV). We also identified factors that are associated with therapeutic efficacy. This prospective study enrolled general gynecological outpatients at Tianjin Medical University General Hospital between September 2012 and May 2014. Women diagnosed with AV (n = 102) were recruited. All enrolled women were treated with oral moxifloxacin, 400 mg once daily for 6 days (one course). Therapeutic efficacy was evaluated based on microscopic criteria, and cure rates were calculated. Women who were microscopically improved (but not cured) received a second course of therapy. Women classified with microscopic failure were treated using other strategies. Univariate and multivariate logistic regression analysis was used to identify factors that may be associated with a cure after one course of therapy. After one course of therapy, 65.7 % (67/102) of women were cured, 29.4 % (30/102) of women were improved (but not cured), 4.9 % (5/102) of women failed to respond to the therapy. After two courses of therapy, 85.3 % (87/102) of women were cured, 9.8 % (10/102) of women were improved, 4.9 % (5/102) of women failed to respond to the therapy, and clinical improvement was achieved in additional women. In the multivariate logistic regression analysis, women with a baseline vaginal pH value of <5.0 had a 3.5-times higher chance of being cured, compared with those with a baseline vaginal pH value of ≥5.0 (OR, 3.503; 95 % CI, 1.278-9.601). Moxifloxacin is an effective therapeutic option for patients with AV. Most women with AV were cured with one course of moxifloxacin. For those with a higher vaginal pH value of ≥5.0 before treatment, two courses of therapy should be considered.

Predicting critical care unit-level complications after long-segment fusion procedures for adult spinal deformity.

PubMed

De la Garza-Ramos, Rafael; Nakhla, Jonathan; Gelfand, Yaroslav; Echt, Murray; Scoco, Aleka N; Kinon, Merritt D; Yassari, Reza

2018-03-01

To identify predictive factors for critical care unit-level complications (CCU complication) after long-segment fusion procedures for adult spinal deformity (ASD). The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database [2010-2014] was reviewed. Only adult patients who underwent fusion of 7 or more spinal levels for ASD were included. CCU complications included intraoperative arrest/infarction, ventilation >48 hours, pulmonary embolism, renal failure requiring dialysis, cardiac arrest, myocardial infarction, unplanned intubation, septic shock, stroke, coma, or new neurological deficit. A stepwise multivariate regression was used to identify independent predictors of CCU complications. Among 826 patients, the rate of CCU complications was 6.4%. On multivariate regression analysis, dependent functional status (P=0.004), combined approach (P=0.023), age (P=0.044), diabetes (P=0.048), and surgery for over 8 hours (P=0.080) were significantly associated with complication development. A simple scoring system was developed to predict complications with 0 points for patients aged <50, 1 point for patients between 50-70, 2 points for patients 70 or over, 1 point for diabetes, 2 points dependent functional status, 1 point for combined approach, and 1 point for surgery over 8 hours. The rate of CCU complications was 0.7%, 3.2%, 9.0%, and 12.6% for patients with 0, 1, 2, and 3+ points, respectively (P<0.001). The findings in this study suggest that older patients, patients with diabetes, patients who depend on others for activities of daily living, and patients who undergo combined approaches or surgery for over 8 hours may be at a significantly increased risk of developing a CCU-level complication after ASD surgery.

Risk factors for the development of heterotopic ossification in seriously burned adults: A National Institute on Disability, Independent Living and Rehabilitation Research burn model system database analysis.

PubMed

Levi, Benjamin; Jayakumar, Prakash; Giladi, Avi; Jupiter, Jesse B; Ring, David C; Kowalske, Karen; Gibran, Nicole S; Herndon, David; Schneider, Jeffrey C; Ryan, Colleen M

2015-11-01

Heterotopic ossification (HO) is a debilitating complication of burn injury; however, incidence and risk factors are poorly understood. In this study, we use a multicenter database of adults with burn injuries to identify and analyze clinical factors that predict HO formation. Data from six high-volume burn centers, in the Burn Injury Model System Database, were analyzed. Univariate logistic regression models were used for model selection. Cluster-adjusted multivariate logistic regression was then used to evaluate the relationship between clinical and demographic data and the development of HO. Of 2,979 patients in the database with information on HO that addressed risk factors for development of HO, 98 (3.5%) developed HO. Of these 98 patients, 97 had arm burns, and 96 had arm grafts. When controlling for age and sex in a multivariate model, patients with greater than 30% total body surface area burn had 11.5 times higher odds of developing HO (p < 0.001), and those with arm burns that required skin grafting had 96.4 times higher odds of developing HO (p = 0.04). For each additional time a patient went to the operating room, odds of HO increased by 30% (odds ratio, 1.32; p < 0.001), and each additional ventilator day increased odds by 3.5% (odds ratio, 1.035; p < 0.001). Joint contracture, inhalation injury, and bone exposure did not significantly increase odds of HO. Risk factors for HO development include greater than 30% total body surface area burn, arm burns, arm grafts, ventilator days, and number of trips to the operating room. Future studies can use these results to identify highest-risk patients to guide deployment of prophylactic and experimental treatments. Prognostic study, level III.

Study for Updated Gout Classification Criteria (SUGAR): identification of features to classify gout

PubMed Central

Taylor, William J.; Fransen, Jaap; Jansen, Tim L.; Dalbeth, Nicola; Schumacher, H. Ralph; Brown, Melanie; Louthrenoo, Worawit; Vazquez-Mellado, Janitzia; Eliseev, Maxim; McCarthy, Geraldine; Stamp, Lisa K.; Perez-Ruiz, Fernando; Sivera, Francisca; Ea, Hang-Korng; Gerritsen, Martijn; Scire, Carlo; Cavagna, Lorenzo; Lin, Chingtsai; Chou, Yin-Yi; Tausche, Anne-Kathrin; Vargas-Santos, Ana Beatriz; Janssen, Matthijs; Chen, Jiunn-Horng; Slot, Ole; Cimmino, Marco A.; Uhlig, Till; Neogi, Tuhina

2015-01-01

Objective To determine which clinical, laboratory and imaging features most accurately distinguished gout from non-gout. Methods A cross-sectional study of consecutive rheumatology clinic patients with at least one swollen joint or subcutaneous tophus. Gout was defined by synovial fluid or tophus aspirate microscopy by certified examiners in all patients. The sample was randomly divided into a model development (2/3) and test sample (1/3). Univariate and multivariate association between clinical features and MSU-defined gout was determined using logistic regression modelling. Shrinkage of regression weights was performed to prevent over-fitting of the final model. Latent class analysis was conducted to identify patterns of joint involvement. Results In total, 983 patients were included. Gout was present in 509 (52%). In the development sample (n=653), these features were selected for the final model (multivariate OR) joint erythema (2.13), difficulty walking (7.34), time to maximal pain < 24 hours (1.32), resolution by 2 weeks (3.58), tophus (7.29), MTP1 ever involved (2.30), location of currently tender joints: Other foot/ankle (2.28), MTP1 (2.82), serum urate level > 6 mg/dl (0.36 mmol/l) (3.35), ultrasound double contour sign (7.23), Xray erosion or cyst (2.49). The final model performed adequately in the test set with no evidence of misfit, high discrimination and predictive ability. MTP1 involvement was the most common joint pattern (39.4%) in gout cases. Conclusion Ten key discriminating features have been identified for further evaluation for new gout classification criteria. Ultrasound findings and degree of uricemia add discriminating value, and will significantly contribute to more accurate classification criteria. PMID:25777045

Epidemiologic Characteristics of Injured School-age Patients Transported via Emergency Medical Services in Korea.

PubMed

Park, Hang A; Ahn, Ki Ok; Park, Ju Ok; Kim, Jungeun; Jeong, Seungmin; Kim, Meesook

2018-03-05

The purpose of this study was to identify the characteristics of injuries of school-aged children transported via emergency medical services (EMS) that occurred in schools by comparing with injuries that occurred outside of school. Data from the 119 EMS from 2012 to 2014 were analyzed. School and non-school injuries were analyzed in children 6 to 17 years of age. The epidemiologic characteristics were assessed according to school-age groups; low-grade primary (6-8 years), high-grade primary (9-13 years), middle (13-15 years) and high (15-17 years) school. Gender-stratified multivariable logistic regression analysis was conducted to estimate the risks of school injury in each age group. During the study period, a total of 167,104 children with injury were transported via 119 ambulances. Of these injuries, 13.3% occurred at schools. Boys accounted for 76.9% of school injuries and middle school children accounted for a significantly greater proportion (39.6%) of school injuries (P < 0.001). The most frequent mechanisms of injury at school were falls (43.8%). The peak times for school injury occurrence were lunch time (13:00-13:59) in all age groups. Multivariate regression identified the risky age groups as high-grade primary (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.09-1.20) and middle school-aged boys (OR, 1.82; 95% CI, 1.74-1.90) and middle school-aged girls (OR, 1.30; 95% CI, 1.21-1.40). Notable epidemiologic differences exist between in- and out-of-school injuries. The age groups at risk for school injuries differ by gender. © 2018 The Korean Academy of Medical Sciences.

Neighborhood socioeconomic status is associated with violent reinjury.

PubMed

Chong, Vincent E; Lee, Wayne S; Victorino, Gregory P

2015-11-01

Measures of individual socioeconomic status correlate with recurrent violent injury; however, neighborhood socioeconomic status may also matter. We conducted a review of victims of interpersonal violence treated at our trauma center, hypothesizing that the percent of the population living under the poverty level in their neighborhood is associated with recurrent violent victimization. We identified victims of interpersonal violence, ages 12-24, in our trauma registry from 2005-2010. Recurrent episodes of violent injury were identified through 2012. The percentage of the population living under the poverty level for the patient's zip code of residence was derived from United States census estimates and divided into quartiles. Multivariable logistic regression was conducted to evaluate predictors of violent injury recidivism. Our cohort consisted of 1890 patients. Multivariable logistic regression confirmed the following factors as independent predictors of violent injury recidivism: male sex (odds ratio [OR] = 2 [1.06-3.80]; P = 0.03), black race (OR = 2.1 [1.44-3.06]; P < 0.001), injury due to firearms (OR = 1.67 [1.12-2.50]; P = 0.01), and living in the lowest zip code socioeconomic quartile (OR = 1.59 [1.12-2.25]; P = 0.01). For young patients injured by violence, the socioeconomic position of their neighborhood of residence is independently correlated with their risk of violent reinjury. Low neighborhood socioeconomic status may be associated with a disrupted sense of safety after injury and also may alter a person's likelihood of engaging in behaviors correlated with recurrent violent injury. Programs aimed at reducing violent injury recidivism should address needs at the individual and neighborhood level. Copyright © 2015 Elsevier Inc. All rights reserved.

Police Victimization Among Persons Who Inject Drugs Along the U.S.–Mexico Border

PubMed Central

Pinedo, Miguel; Burgos, José Luis; Zúñiga, María Luisa; Perez, Ramona; Macera, Caroline A.; Ojeda, Victoria D.

2015-01-01

Objective: Problematic policing practices are an important driver of HIV infection among persons who inject drugs (PWID) in the U.S.–Mexico border region. This study identifies factors associated with recent (i.e., past 6 months) police victimization (e.g., extortion, physical and sexual violence) in the border city of Tijuana, Mexico. Method: From 2011 to 2013, 733 PWID (62% male) were recruited in Tijuana and completed a structured questionnaire. Eligible participants were age 18 years or older, injected illicit drugs within the past month, and spoke Spanish or English. Multivariable logistic regression analyses identified correlates of recent experiences of police victimization (e.g., bribes, unlawful confiscation, physical and sexual violence). Results: Overall, 56% of PWID reported a recent police victimization experience in Tijuana. In multivariable logistic regression analyses, factors independently associated with recent police victimization included recent injection of methamphetamine (adjusted odds ratio [AOR] = 1.62; 95% CI [1.18, 2.21]) and recently received injection assistance by a “hit doctor” (AOR = 1.56; 95% CI [1.03, 2.36]). Increased years lived in Tijuana (AOR = 0.98 per year; 95% CI [0.97, 0.99]) and initiating drug use at a later age (AOR = 0.96 per year; 95% CI [0.92, 0.99]) were inversely associated with recent police victimization. Conclusions: Physical drugusing markers may increase PWID susceptibility to police targeting and contribute to experiences of victimization. Interventions aimed at reducing police victimization events in the U.S.–Mexico border region should consider PWID’s drug-using behaviors. Reducing problematic policing practices may be a crucial public health strategy to reduce HIV risk among PWID in this region. PMID:26402356

Primary caregivers of in-home oxygen-dependent children: predictors of stress based on characteristics, needs and social support.

PubMed

Wang, Kai-Wei K; Lin, Hung-Ching; Lee, Chin-Ting; Lee, Kuo-Sheng

2016-07-01

To identify the predictors of primary caregivers' stress in caring for in-home oxygen-dependent children by examining the association between their levels of stress, caregiver needs and social support. Increasing numbers of primary caregivers of oxygen-dependent children experience caregiving stress that warrants investigation. The study used a cross-sectional design with three psychometric scales - Modified-Parenting Stress Index, Caregiver Needs Scale and Social Support Index. The data collected during 2010-2011 were from participants who were responsible for their child's care that included oxygen therapy for ≧6 hours/day; the children's ages ranged from 3 months-16 years. Descriptive statistics and multivariable linear regression were used. A total of 104 participants (M = 34, F = 70) were recruited, with an average age of 39·7 years. The average age of the oxygen-dependent children was 6·68 years and their daily use of oxygen averaged 11·39 hours. The caregivers' overall levels of stress were scored as high and information needs were scored as the highest. The most available support from family and friends was emotional support. Informational support was mostly received from health professionals, but both instrumental and emotional support were important. Levels of stress and caregiver needs were significantly correlated. Multivariable linear regression analyses identified three risk factors predicting stress, namely, the caregiver's poor health status, the child's male gender and the caregiver's greater financial need. To support these caregivers, health professionals can maintain their health status and provide instrumental, emotional, informational and financial support. © 2016 John Wiley & Sons Ltd.

Poor Long-Term Blood Pressure Control after Intracerebral Hemorrhage

PubMed Central

Zahuranec, Darin B.; Wing, Jeffrey J.; Edwards, Dorothy F.; Menon, Ravi S.; Fernandez, Stephen J.; Burgess, Richard E.; Sobotka, Ian A.; German, Laura; Trouth, Anna J.; Shara, Nawar M.; Gibbons, M. Chris; Boden-Albala, Bernadette; Kidwell, Chelsea S.

2012-01-01

Background and Purpose Hypertension is the most important risk factor associated with intracerebral hemorrhage (ICH). We explored racial differences in blood pressure (BP) control after ICH and assessed predictors of BP control at presentation, 30 days, and 1 year in a prospective cohort study. Methods Subjects with spontaneous ICH were identified from the DiffErenCes in the Imaging of Primary Hemorrhage based on Ethnicity or Race (DECIPHER) Project. Blood pressure was compared by race at each time point. Multivariable linear regression was used to determine predictors of presenting mean arterial pressure (MAP), and longitudinal linear regression was used to assess predictors of MAP at follow-up. Results A total of 162 patients were included (mean age 59, 53% male, 77% black). MAP at presentation was 9.6 mmHg higher in blacks than whites despite adjustment for confounders (p=0.065). Fewer than 20% of patients had normal blood pressure (<120/80 mmHg) at 30 days or 1 year. While there was no difference at 30 days (p=0.331), blacks were more likely than whites to have Stage I/II hypertension at one year (p=0.036). Factors associated with lower MAP at follow-up in multivariable analysis were being married at baseline (p=0.032) and living in a facility (versus personal residence) at the time of BP measurement (p=0.023). Conclusions Long-term blood pressure control is inadequate in patients following ICH, particularly in blacks. Further studies are needed to understand the role of social support and barriers to control to identify optimal approaches to improve blood pressure in this high-risk population. PMID:22903494

Impact of preoperative calculation of nephron volume loss on future of partial nephrectomy techniques; planning a strategic roadmap for improving functional preservation and securing oncological safety.

PubMed

Rha, Koon H; Abdel Raheem, Ali; Park, Sung Y; Kim, Kwang H; Kim, Hyung J; Koo, Kyo C; Choi, Young D; Jung, Byung H; Lee, Sang K; Lee, Won K; Krishnan, Jayram; Shin, Tae Y; Cho, Jin-Seon

2017-11-01

To assess the correlation of the resected and ischaemic volume (RAIV), which is a preoperatively calculated volume of nephron loss, with the amount of postoperative renal function (PRF) decline after minimally invasive partial nephrectomy (PN) in a multi-institutional dataset. We identified 348 patients from March 2005 to December 2013 at six institutions. Data on all cases of laparoscopic (n = 85) and robot-assisted PN (n = 263) performed were retrospectively gathered. Univariable and multivariable linear regression analyses were used to identify the associations between various time points of PRF and the RAIV, as a continuous variable. The mean (sd) RAIV was 24.2 (29.2) cm 3 . The mean preoperative estimated glomerular filtration rate (eGFR) and the eGFRs at postoperative day 1, 6 and 36 months after PN were 91.0 and 76.8, 80.2 and 87.7 mL/min/1.73 m 2 , respectively. In multivariable linear regression analysis, the amount of decline in PRF at follow-up was significantly correlated with the RAIV (β 0.261, 0.165, 0.260 at postoperative day 1, 6 and 36 months after PN, respectively). This study has the limitation of its retrospective nature. Preoperatively calculated RAIV significantly correlates with the amount of decline in PRF during long-term follow-up. The RAIV could lead our research to the level of prediction of the amount of PRF decline after PN and thus would be appropriate for assessing the technical advantages of emerging techniques. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Risk factors for mortality before age 18 years in cystic fibrosis.

PubMed

McColley, Susanna A; Schechter, Michael S; Morgan, Wayne J; Pasta, David J; Craib, Marcia L; Konstan, Michael W

2017-07-01

Understanding early-life risk factors for childhood death in cystic fibrosis (CF) is important for clinical care, including the identification of effective interventions. Data from the Epidemiologic Study of Cystic Fibrosis (ESCF) collected 1994-2005 were linked with the Cystic Fibrosis Foundation Patient Registry (CFFPR) demographic and mortality data from 2013. Inclusion criteria were ≥1 visit annually at age 3-5 years and ≥1 FEV 1 measurement at age 6-8 years. Demographic data, nutritional parameters, pulmonary signs and symptoms, microbiology, and FEV 1 were evaluated as risk factors for death before age 18 years. Multivariable Cox proportional hazards regression was used to model the simultaneous effects of risk factors associated with death before age 18 years. Among 5365 patients enrolled in ESCF who met inclusion criteria, 3880 (72%) were linked to the CFFPR. Among these, 191 (5.7%) died before age 18 years; median age at death was 13.4 ± 3.1 years. Multivariable regression showed clubbing, crackles, female sex, unknown CFTR genotype, minority race or ethnicity, Medicaid insurance (a proxy of low socioeconomic status), Pseudomonas aeruginosa on 2 or more cultures, and weight-for-age <50th percentile were significant risk factors for death regardless of inclusion of FEV 1 at age 6-8 years in the model. We identified multiple risk factors for childhood death of patients with CF, all of which remained important after incorporating FEV 1 at age 6-8 years. Among the factors identified were the presence of clubbing or crackles at age 3-5 years, signs which are not routinely collected in registries. © 2017 Wiley Periodicals, Inc.

Ratio of serum levels of AGEs to soluble form of RAGE is a predictor of endothelial function.

PubMed

Kajikawa, Masato; Nakashima, Ayumu; Fujimura, Noritaka; Maruhashi, Tatsuya; Iwamoto, Yumiko; Iwamoto, Akimichi; Matsumoto, Takeshi; Oda, Nozomu; Hidaka, Takayuki; Kihara, Yasuki; Chayama, Kazuaki; Goto, Chikara; Aibara, Yoshiki; Noma, Kensuke; Takeuchi, Masayoshi; Matsui, Takanori; Yamagishi, Sho-Ichi; Higashi, Yukihito

2015-01-01

Advanced glycation end products (AGEs) and their specific receptor, the receptor for AGEs (RAGE), play an important role in atherosclerosis. Recently, a soluble form of RAGE (sRAGE) has been identified in human serum. However, the role of sRAGE in cardiovascular disease is still controversial. There is no information on the association between simultaneous measurements of AGEs and sRAGE and vascular function. In this study, we evaluated the associations between serum levels of AGEs and sRAGE, ratio of AGEs to sRAGE, and vascular function. We measured serum levels of AGEs and sRAGE and assessed vascular function by measurement of flow-mediated vasodilation (FMD) and nitroglycerine-induced vasodilation in 110 subjects who underwent health examinations. Multivariate regression analyses were performed to identify factors associated with vascular function. Univariate regression analysis revealed that FMD correlated with age, BMI, systolic blood pressure, diastolic blood pressure, heart rate, triglycerides, HDL cholesterol, glucose, smoking pack-years, nitroglycerine-induced vasodilation, serum levels of AGEs and sRAGE, and ratio of AGEs to sRAGE. Multivariate analysis revealed that the ratio of AGEs to sRAGE remained an independent predictor of FMD, while serum level of AGEs alone or sRAGE alone was not associated with FMD. These findings suggest that sRAGE may have a counterregulatory mechanism that is activated to counteract the vasotoxic effect of the AGE-RAGE axis. The ratio of AGEs to sRAGE may be a new chemical biomarker of endothelial function. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Gender Disparities in Osteoarthritis-Related Health Care Utilization Before Total Knee Arthroplasty.

PubMed

Bawa, Harpreet S; Weick, Jack W; Dirschl, Douglas R

2016-10-01

Women older than 50 years have higher prevalence of knee osteoarthritis (OA) and experience greater functional disability than men. No studies have examined large populations to identify knee OA-related health care utilization differences. The purpose of this investigation was to evaluate gender differences in the utilization of OA-related health care resources in the 12 months preceding total knee arthroplasty (TKA). Truven Health MarketScan Commercial Claims and Encounters and Medicare Supplemental and Coordination of Benefit databases were reviewed from 2005 to 2012. Subjects were included if they underwent TKA, had associated diagnosis of lower leg OA, and were continuously in the database for 12 months preceding TKA. Patient-specific OA-related health care utilization was identified. Multivariate logistic regression analysis controlling for age, region, and Charlson Comorbidity Index was performed to isolate the influence of gender. A total of 244,059 patients with a mean age of 64.8 years consisting of 61.2% women were included. Multivariate logistic regression adjusted odds ratios showed that when compared to men, women were 30%, 20%, 31%, 18%, 19%, 29%, and 39%, more likely to receive a narcotic analgesic, nonnarcotic analgesics, corticosteroid injection, hyaluronic acid injection, knee magnetic resonance imaging, a physical therapy evaluation, and occupational therapy evaluation in the 12 months preceding TKA, respectively. Women have a significantly higher utilization of knee OA-related health care in the 12 months preceding TKA. Although the precise cause for this discrepancy in care cannot be determined from this study, it highlights a potential bias in management of advanced knee OA and directions for further investigation. Copyright © 2016 Elsevier Inc. All rights reserved.

Coastal Fish Assemblages Reflect Geological and Oceanographic Gradients Within An Australian Zootone

PubMed Central

Harvey, Euan S.; Cappo, Mike; Kendrick, Gary A.; McLean, Dianne L.

2013-01-01

Distributions of mobile animals have been shown to be heavily influenced by habitat and climate. We address the historical and contemporary context of fish habitats within a major zootone: the Recherche Archipelago, southern western Australia. Baited remote underwater video systems were set in nine habitat types within three regions to determine the species diversity and relative abundance of bony fishes, sharks and rays. Constrained ordinations and multivariate prediction and regression trees were used to examine the effects of gradients in longitude, depth, distance from islands and coast, and epibenthic habitat on fish assemblage composition. A total of 90 species from 43 families were recorded from a wide range of functional groups. Ordination accounted for 19% of the variation in the assemblage composition when constrained by spatial and epibenthic covariates, and identified redundancy in the use of distance from the nearest emergent island as a predictor. A spatial hierarchy of fourteen fish assemblages was identified using multivariate prediction and regression trees, with the primary split between assemblages on macroalgal reefs, and those on bare or sandy habitats supporting seagrass beds. The characterisation of indicator species for assemblages within the hierarchy revealed important faunal break in fish assemblages at 122.30 East at Cape Le Grand and subtle niche partitioning amongst species within the labrids and monacanthids. For example, some species of monacanthids were habitat specialists and predominantly found on seagrass (Acanthaluteres vittiger, Scobinichthys granulatus), reef (Meuschenia galii, Meuschenia hippocrepis) or sand habitats (Nelusetta ayraudi). Predatory fish that consume molluscs, crustaceans and cephalopods were dominant with evidence of habitat generalisation in reef species to cope with local disturbances by wave action. Niche separation within major genera, and a sub-regional faunal break, indicate future zootone mapping should recognise both cross-shelf and longshore environmental gradients. PMID:24278353

The prevalence and characteristics of low back pain among sitting workers in a Japanese manufacturing company.

PubMed

Inoue, Gen; Miyagi, Masayuki; Uchida, Kentaro; Ishikawa, Tetsuhiro; Kamoda, Hiroto; Eguchi, Yawara; Orita, Sumihisa; Yamauchi, Kazuyo; Takaso, Masashi; Tsuchiya, Kei-Ichi; Takahashi, Kazuhisa; Ohtori, Seiji

2015-01-01

Low back pain (LBP) is a major public health problem and the most common cause of workers' disability, resulting in substantial economic burden in terms of workers' compensation and medical costs. Sitting is a recognized potential risk factor for developing LBP. Therefore, eliminating risk factors associated with working conditions and individual work capacity may be beneficial in preventing LBP in sitting workers. The purpose of this prospective cross-sectional study is to investigate the prevalence of LBP and examine risk factors that contribute to the development of LBP in sitting workers at an electronics manufacturing company. A cross-sectional survey was administered to all subjects to assess the prevalence of LBP persisting for at least 48 h during the recent week. Data on demographic characteristics and potential risk factors for LBP were collected at routine annual check-ups. Patients with LBP completed the Roland-Morris Disability Questionnaire (RDQ), which provided information on the attributes of LBP. Univariate and multivariate regression analyses examined the association between LBP and potential risk factors. Of the 1,329 sitting workers, 201 (15.1 %) acknowledged experiencing LBP during the recent week. In female workers, weight and body mass index were significantly correlated with the RDQ score. Univariate analyses identified male sex, prior history of LBP, height ≥170 cm, and weight ≥70 kg as significant risk factors of LBP. Multivariate logistic regression analyses identified prior history of LBP and past history of lumbar spine surgery as significant risk factors of LBP. This study characterized the prevalence and attributes of LBP in Japanese sitting workers and provided information about potential risk factors contributing to occurrence of LBP in the workplace.

Prevalence of Diabetes and Associated Factors in the Uyghur and Han Population in Xinjiang, China.

PubMed

Gong, Haiying; Pa, Lize; Wang, Ke; Mu, Hebuli; Dong, Fen; Ya, Shengjiang; Xu, Guodong; Tao, Ning; Pan, Li; Wang, Bin; Shan, Guangliang

2015-10-14

To estimate the prevalence of diabetes and identify risk factors in the Uyghur and Han population in Xinjiang, China. A cross-sectional study in urban and rural areas in Xinjiang, including 2863 members of the Uyghur population and 3060 of the Han population aged 20 to 80 years, was conducted from June 2013 to August 2013. Data on fasting plasma glucose (FPG) and personal history of diabetes were used to estimate the prevalence of diabetes. Data on demographic characteristics, lifestyle risk factors, and lipid profiles were collected to identify risks factors using the multivariate logistic regression model. In urban areas, the age- and gender-standardized prevalence of diabetes was 8.21%, and the age- and gender-standardized prevalence of diabetes was higher in the Uyghur population (10.47%) than in the Han population (7.36%). In rural areas, the age- and gender-standardized prevalence of diabetes was 6.08%, and it did not differ significantly between the Uyghur population (5.71%) and the Han population (6.59%). The results of the multivariate logistic regression analysis showed that older age, obesity, high triglycerides (TG), and hypertension were all associated with an increased risk of diabetes in the Uyghur and Han population. Urban residence and low high-density lipoprotein cholesterol (HDL-C) were associated with an increased risk of diabetes in the Uyghur population. Being an ex-drinker was associated with an increased risk of diabetes and heavy physical activity was associated with a decreased risk of diabetes in the Han population. Our study indicates that diabetes is more prevalent in the Uyghur population compared with the Han population in urban areas. Strategies aimed at the prevention of diabetes require ethnic targeting.

The role of visual markers in police victimization among structurally vulnerable persons in Tijuana, Mexico

PubMed Central

Pinedo, Miguel; Burgos, Jose Luis; Ojeda, Adriana Vargas; FitzGerald, David; Ojeda, Victoria D.

2015-01-01

Background Law enforcement can shape HIV risk behaviours and undermine strategies aimed at curbing HIV infection. Little is known about factors that increase vulnerability to police victimization in Mexico. This study identifies correlates of police or army victimization (i.e., harassment or assault) in the past 6 months among patients seeking care at a free clinic in Tijuana, Mexico. Methods From January to May 2013, 601 patients attending a binational student-run free clinic completed an interviewer-administered questionnaire. Eligible participants were: (1) ≥18 years old; (2) seeking care at the clinic; and (3) spoke Spanish or English. Multivariate logistic regression analyses identified factors associated with police/army victimization in the past 6 months. Results More than one-third (38%) of participants reported victimization by police/army officials in the past 6 months in Tijuana. In multivariate logistic regression analyses, males (Adjusted Odds Ratio (AOR): 3.68; 95% CI: 2.19–6.19), tattooed persons (AOR: 1.56; 95% CI: 1.04–2.33) and those who injected drugs in the past 6 months (AOR: 2.11; 95% CI: 1.29–3.43) were significantly more likely to report past 6-month police/army victimization. Recent feelings of rejection (AOR: 3.80; 95% CI: 2.47–5.85) and being denied employment (AOR: 2.23; 95% CI: 1.50–3.32) were also independently associated with police/army victimization. Conclusion Structural interventions aimed at reducing stigma against vulnerable populations and increasing social incorporation may aid in reducing victimization events by police/army in Tijuana. Police education and training to reduce abusive policing practices may be warranted. PMID:25281235

Factors associated with physicians' choice of a career in research: a retrospective report 15 years after medical school graduation.

PubMed

Krupat, Edward; Camargo, Carlos A; Strewler, Gordon J; Espinola, Janice A; Fleenor, Thomas J; Dienstag, Jules L

2017-03-01

Relatively little is known regarding factors associated with the choice of a research career among practicing physicians, and most investigations of this issue have been conducted in the absence of a theoretical/conceptual model. Therefore we designed a survey to identify the determinants of decisions to pursue a biomedical research career based upon the Theory of Planned Behavior and the concept of stereotype threat. From October 2012 through January 2014 electronic surveys were sent to four consecutive Harvard Medical School graduating classes, 1996-1999. Respondents provided demographic information, indicated their current research involvement, and provided retrospective reports of their experiences and attitudes when they were making career choices as they completed medical school. Multivariable ordinal regression was used to identify factors independently associated with current research involvement. Completed questionnaires were received from 358 respondents (response rate 65 %). In unadjusted analyses, variables associated with more extensive research involvement included non-minority status, male gender, lower debt at graduation, strong attitudes toward research at time of graduation, and greater social pressures to pursue research (all P < .001). These associations remained significant in multivariable regression analysis (all P < 0.01). However, an interaction between sex and prior research publications was also detected, indicating that more extensive research involvement during medical school doubled the likelihood of a research career for women (OR 2.53, 95 % CI 1.00-6.40; P = 0.05). Most of the factors predicting research career choice involve factors that are potentially modifiable, suggesting that appropriately designed behavioral interventions may help to expand the size and diversity of the biomedical research community.

Surveillance and Radiation Therapy for Stage I Seminoma—Have We Learned From the Evidence?

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

Glaser, Scott M.; Vargo, John A.; Balasubramani, Goundappa K.

2016-01-01

Purpose: To analyze, in the setting of stage I seminoma, the factors affecting adjuvant treatment decisions and resulting survival outcomes, using a national dataset. Methods and Materials: We identified 33,094 stage I seminoma patients after orchiectomy from 1998 to 2012 from the National Cancer Data Base. Factors affecting treatment selection (active surveillance [AS] vs adjuvant treatment [AT]) were identified using a parsimonious multivariate logistic regression model. Propensity scores for treatment decision were generated and incorporated into a multivariate Cox regression analysis of overall survival. This process was then repeated within the AT cohort for factors predictive for chemotherapy [CT] versus radiationmore » therapy [RT]. Results: Only 33% of patients received AS, and 65% received AT (89% RT and 11% CT). From 1998 to 2012 the proportion receiving AS increased from 23% to 60%, whereas RT utilization decreased from 73% to 21%, and CT utilization increased from 2% to 17%. Utilization of low-dose RT increased from 1.5% in 1999 to 34% in 2012. There was a small absolute overall survival advantage to AT over AS at 10 years (95.0% vs 93.4%, propensity adjusted hazard ratio 0.58, P<.0005). Conclusions: There has been a significant increase in use of AS for stage I seminoma, influenced by both sociodemogrpahic and clinicopathologic factors. Between AT options, there has been significant increase in use of CT, mirrored by a decline in use of RT. Although overall survival remains high for all 3 treatment strategies, AT seems to be associated with a small absolute survival advantage over AS up to 10 years out from diagnosis.« less

Revascularization Treatment of Emergency Patients with Acute ST-Segment Elevation Myocardial Infarction in Switzerland: Results from a Nationwide, Cross-Sectional Study in Switzerland for 2010-2011.

PubMed

Berlin, Claudia; Jüni, Peter; Endrich, Olga; Zwahlen, Marcel

2016-01-01

Cardiovascular diseases are the leading cause of death worldwide and in Switzerland. When applied, treatment guidelines for patients with acute ST-segment elevation myocardial infarction (STEMI) improve the clinical outcome and should eliminate treatment differences by sex and age for patients whose clinical situations are identical. In Switzerland, the rate at which STEMI patients receive revascularization may vary by patient and hospital characteristics. To examine all hospitalizations in Switzerland from 2010-2011 to determine if patient or hospital characteristics affected the rate of revascularization (receiving either a percutaneous coronary intervention or a coronary artery bypass grafting) in acute STEMI patients. We used national data sets on hospital stays, and on hospital infrastructure and operating characteristics, for the years 2010 and 2011, to identify all emergency patients admitted with the main diagnosis of acute STEMI. We then calculated the proportion of patients who were treated with revascularization. We used multivariable multilevel Poisson regression to determine if receipt of revascularization varied by patient and hospital characteristics. Of the 9,696 cases we identified, 71.6% received revascularization. Patients were less likely to receive revascularization if they were female, and 80 years or older. In the multivariable multilevel Poisson regression analysis, there was a trend for small-volume hospitals performing fewer revascularizations but this was not statistically significant while being female (Relative Proportion = 0.91, 95% CI: 0.86 to 0.97) and being older than 80 years was still associated with less frequent revascularization. Female and older patients were less likely to receive revascularization. Further research needs to clarify whether this reflects differential application of treatment guidelines or limitations in this kind of routine data.

Epidemiologic Characteristics of Injured School-age Patients Transported via Emergency Medical Services in Korea

PubMed Central

2018-01-01

Background The purpose of this study was to identify the characteristics of injuries of school-aged children transported via emergency medical services (EMS) that occurred in schools by comparing with injuries that occurred outside of school. Methods Data from the 119 EMS from 2012 to 2014 were analyzed. School and non-school injuries were analyzed in children 6 to 17 years of age. The epidemiologic characteristics were assessed according to school-age groups; low-grade primary (6–8 years), high-grade primary (9–13 years), middle (13–15 years) and high (15–17 years) school. Gender-stratified multivariable logistic regression analysis was conducted to estimate the risks of school injury in each age group. Results During the study period, a total of 167,104 children with injury were transported via 119 ambulances. Of these injuries, 13.3% occurred at schools. Boys accounted for 76.9% of school injuries and middle school children accounted for a significantly greater proportion (39.6%) of school injuries (P < 0.001). The most frequent mechanisms of injury at school were falls (43.8%). The peak times for school injury occurrence were lunch time (13:00–13:59) in all age groups. Multivariate regression identified the risky age groups as high-grade primary (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.09–1.20) and middle school-aged boys (OR, 1.82; 95% CI, 1.74–1.90) and middle school-aged girls (OR, 1.30; 95% CI, 1.21–1.40). Conclusion Notable epidemiologic differences exist between in- and out-of-school injuries. The age groups at risk for school injuries differ by gender. PMID:29495140

Expert Involvement Predicts mHealth App Downloads: Multivariate Regression Analysis of Urology Apps

PubMed Central

Osório, Luís; Cavadas, Vitor; Fraga, Avelino; Carrasquinho, Eduardo; Cardoso de Oliveira, Eduardo; Castelo-Branco, Miguel; Roobol, Monique J

2016-01-01

Background Urological mobile medical (mHealth) apps are gaining popularity with both clinicians and patients. mHealth is a rapidly evolving and heterogeneous field, with some urology apps being downloaded over 10,000 times and others not at all. The factors that contribute to medical app downloads have yet to be identified, including the hypothetical influence of expert involvement in app development. Objective The objective of our study was to identify predictors of the number of urology app downloads. Methods We reviewed urology apps available in the Google Play Store and collected publicly available data. Multivariate ordinal logistic regression evaluated the effect of publicly available app variables on the number of apps being downloaded. Results Of 129 urology apps eligible for study, only 2 (1.6%) had >10,000 downloads, with half having ≤100 downloads and 4 (3.1%) having none at all. Apps developed with expert urologist involvement (P=.003), optional in-app purchases (P=.01), higher user rating (P<.001), and more user reviews (P<.001) were more likely to be installed. App cost was inversely related to the number of downloads (P<.001). Only data from the Google Play Store and the developers’ websites, but not other platforms, were publicly available for analysis, and the level and nature of expert involvement was not documented. Conclusions The explicit participation of urologists in app development is likely to enhance its chances to have a higher number of downloads. This finding should help in the design of better apps and further promote urologist involvement in mHealth. Official certification processes are required to ensure app quality and user safety. PMID:27421338

Factors associated with physicians’ choice of a career in research: A retrospective report 15 years after medical school graduation

PubMed Central

Krupat, Edward; Camargo, Carlos A.; Strewler, Gordon J.; Espinola, Janice A.; Fleenor, Thomas J.; Dienstag, Jules L.

2016-01-01

Relatively little is known regarding factors associated with the choice of a research career among practicing physicians, and most investigations of this issue have been conducted in the absence of a theoretical/conceptual model. Therefore we designed a survey to identify the determinants of decisions to pursue a biomedical research career based upon the Theory of Planned Behavior and the concept of stereotype threat. From October 2012 through January 2014 electronic surveys were sent to four consecutive Harvard Medical School graduating classes, 1996-1999. Respondents provided demographic information, indicated their current research involvement, and provided retrospective reports of their experiences and attitudes when they were making career choices as they completed medical school. Multivariable ordinal regression was used to identify factors independently associated with current research involvement. Completed questionnaires were received from 358 respondents (response rate 65%). In unadjusted analyses, variables associated with more extensive research involvement included non-minority status, male gender, lower debt at graduation, strong attitudes toward research at time of graduation, and greater social pressures to pursue research (all P<.001). These associations remained significant in multivariable regression analysis (all P<0.01). However, an interaction between sex and prior research publications was also detected, indicating that more extensive research involvement during medical school doubled the likelihood of a research career for women (OR 2.53, 95%CI 1.00-6.40; P=0.05). Most of the factors predicting research career choice involve factors that are potentially modifiable, suggesting that appropriately designed behavioral interventions may help to expand the size and diversity of the biomedical research community. PMID:27112959

Prognostic factors in Acanthamoeba keratitis.

PubMed

Kaiserman, Igor; Bahar, Irit; McAllum, Penny; Srinivasan, Sathish; Elbaz, Uri; Slomovic, Allan R; Rootman, David S

2012-06-01

To assess the prognostic factors influencing visual prognosis and length of treatment after acanthamoeba keratitis (AK). Forty-two AK eyes of 41 patients treated between 1999 and 2006 were included. A diagnosis of AK was made on the basis of culture results with a corresponding clinical presentation. We calculated the prognostic effect of the various factors on final visual acuity and the length of treatment. Multivariate regression analysis was used to adjust for the simultaneous effects of the various prognostic factors. Mean follow-up was 19.7 ± 21.0 months. Sixty-four percent of cases had > 1 identified risk factor for AK, the most common risk factor being contact lens wear (92.9% of eyes). At presentation, median best spectacle corrected visual acuity (BCVA) was 20/200 (20/30 to Hand Motion [HM]) that improved after treatment to 20/50 (20/20 to Counting Fingers [CF]). Infection acquired by swimming or related to contact lenses had significantly better final BCVA (p = 0.03 and p = 0.007, respectively). Neuritis and pseudodendrites were also associated with better final BCVA (p = 0.04 and p = 0.05, respectively). Having had an epithelial defect on presentation and having been treated with topical steroid were associated with worse final best spectacle corrected visual acuity (BSCVA) (p = 0.0006 and p = 0.04). Multivariate regression analysis found a good initial visual acuity (p = 0.002), infections related to swimming (p = 0.01), the absence of an epithelial defect (p = 0.03), having been treated with chlorhexidine (p = 0.05), and not having receive steroids (p = 0.003) to significantly forecast a good final BCVA. We identified several prognostic factors that can help clinicians evaluate the expected visual damage of the AK infection and thus tailor treatment accordingly. Copyright © 2012 Canadian Ophthalmological Society. All rights reserved.

The use of and adherence to CTCAE v3.0 in cancer clinical trial publications.

PubMed

Zhang, Sheng; Chen, Qiang; Wang, Qing

2016-10-04

The Common Terminology Criteria for Adverse Events, Version 3.0 (CTCAE v3.0) was released in 2003, and has been widely used as the predominant set of toxicity criteria for cancer clinical trials and scientific meetings. However, the degree to which the elements of CTCAE v3.0 are followed in oncology publications has not been comprehensively evaluated. We reviewed phase III randomized clinical trials evaluating systemic cancer therapies, published between Jan 1, 2012 and December 31, 2013, to identify eligible studies that explicitly mentioned using CTCAE v3.0 as the toxicity criteria. A 10-point score based on adherence to CTCAE v3.0 was used to assess the studies. Multivariate linear regression was used to identify features associated with improved adherence. In total, 104 publications reporting data on 86,957 patients were included in this analysis. The mean total score for adherence to all four elements of CTCAE v3.0 was 4.03 on a 10-point scale (range, 1 to 9), with 16 publications (15%) having total scores ≤2. Highly heterogeneous and unstandardized adverse event terms were frequently used. In addition, Supra-ordinate terms, terms using 'Other, specify', and Grades were often used incorrectly. The multivariate regression model revealed that the absence of a placebo (P=0.003) and a higher total number of AE terms in the table (P<0.001) were independent predictors of a lower total score. Given the importance of understanding the toxicity of new treatments, better adherence to CTCAE v3.0 should be encouraged to ensure the consistency and comparability of toxicity data across different studies.

Predictors of hospital re-admissions among Hispanics with hepatitis C-related cirrhosis.

PubMed

Atla, Pradeep R; Sheikh, Muhammad Y; Gill, Firdose; Kundu, Rabindra; Choudhury, Jayanta

2016-01-01

Hospital re-admissions in decompensated cirrhosis are associated with worse patient outcomes. Hispanics have a disproportionately high prevalence of hepatitis C virus (HCV)-related morbidity and mortality. The goal of this study was to evaluate the factors affecting re-admission rates among Hispanics with HCV-related cirrhosis. A total of 292 consecutive HCV-related cirrhosis admissions (Hispanics 189, non-Hispanics 103) from January 2009 to December 2012 were retrospectively reviewed; 132 were cirrhosis-related re-admissions. The statistical analysis was performed using STATA version 11.1. Chi-square/Fisher's exact and Student's t-tests were used to compare categorical and continuous variables, respectively. Multivariate logistic regression analysis was performed to identify predictors for hospital readmissions. Among the 132 cirrhosis-related readmissions, 71% were Hispanics while 29% were non-Hispanics (P=0.035). Hepatic encephalopathy (HE) and esophageal variceal hemorrhage were the most frequent causes of the first and subsequent readmissions. Hispanics with readmissions had a higher Child-Turcotte-Pugh (CTP) class (B and C) and higher model for end-stage liver disease (MELD) scores (≥15), as well as a higher incidence of alcohol use, HE, spontaneous bacterial peritonitis, hepatocellular carcinoma, and varices (P<0.05). The majority of the study patients (81%) had MELD scores <15. Multivariate regression analysis identified alcohol use (OR 2.63; 95%CI 1.1-6.4), HE (OR 5.5; 95%CI 2-15.3), varices (OR 3.2; 95%CI 1.3-8.2), and CTP class (OR 3.3; 95%CI 1.4-8.1) as predictors for readmissions among Hispanics. CTP classes B and C, among other factors, were the major predictors for hospital readmissions in Hispanics with HCV-related cirrhosis. The majority of these readmissions were due to HE and variceal hemorrhage.

Risk Factors for the Development of Heterotopic Ossification in Seriously Burned Adults: A NIDRR Burn Model System Database Analysis

PubMed Central

Levi, Benjamin; Jayakumar, Prakash; Giladi, Avi; Jupiter, Jesse B.; Ring, David C.; Kowalske, Karen; Gibran, Nicole S.; Herndon, David; Schneider, Jeffrey C.; Ryan, Colleen M.

2015-01-01

Purpose Heterotopic ossification (HO) is a debilitating complication of burn injury; however, incidence and risk factors are poorly understood. In this study we utilize a multicenter database of adults with burn injuries to identify and analyze clinical factors that predict HO formation. Methods Data from 6 high-volume burn centers, in the Burn Injury Model System Database, were analyzed. Univariate logistic regression models were used for model selection. Cluster-adjusted multivariate logistic regression was then used to evaluate the relationship between clinical and demographic data and the development of HO. Results Of 2,979 patients in the database with information on HO that addressed risk factors for development of HO, 98 (3.5%) developed HO. Of these 98 patients, 97 had arm burns, and 96 had arm grafts. Controlling for age and sex in a multivariate model, patients with >30% total body surface area (TBSA) burn had 11.5x higher odds of developing HO (p<0.001), and those with arm burns that required skin grafting had 96.4x higher odds of developing HO (p=0.04). For each additional time a patient went to the operating room, odds of HO increased 30% (OR 1.32, p<0.001), and each additional ventilator day increase odds 3.5% (OR 1.035, p<0.001). Joint contracture, inhalation injury, and bone exposure did not significantly increase odds of HO. Conclusion Risk factors for HO development include >30% TBSA burn, arm burns, arm grafts, ventilator days, and number of trips to the operating room. Future studies can use these results to identify highest-risk patients to guide deployment of prophylactic and experimental treatments. PMID:26496115

Marginal analysis in assessing factors contributing time to physician in the Emergency Department using operations data.

PubMed

Pathan, Sameer A; Bhutta, Zain A; Moinudheen, Jibin; Jenkins, Dominic; Silva, Ashwin D; Sharma, Yogdutt; Saleh, Warda A; Khudabakhsh, Zeenat; Irfan, Furqan B; Thomas, Stephen H

2016-01-01

Background: Standard Emergency Department (ED) operations goals include minimization of the time interval (tMD) between patients' initial ED presentation and initial physician evaluation. This study assessed factors known (or suspected) to influence tMD with a two-step goal. The first step was generation of a multivariate model identifying parameters associated with prolongation of tMD at a single study center. The second step was the use of a study center-specific multivariate tMD model as a basis for predictive marginal probability analysis; the marginal model allowed for prediction of the degree of ED operations benefit that would be affected with specific ED operations improvements. Methods: The study was conducted using one month (May 2015) of data obtained from an ED administrative database (EDAD) in an urban academic tertiary ED with an annual census of approximately 500,000; during the study month, the ED saw 39,593 cases. The EDAD data were used to generate a multivariate linear regression model assessing the various demographic and operational covariates' effects on the dependent variable tMD. Predictive marginal probability analysis was used to calculate the relative contributions of key covariates as well as demonstrate the likely tMD impact on modifying those covariates with operational improvements. Analyses were conducted with Stata 14MP, with significance defined at p  < 0.05 and confidence intervals (CIs) reported at the 95% level. Results: In an acceptable linear regression model that accounted for just over half of the overall variance in tMD (adjusted r 2 0.51), important contributors to tMD included shift census ( p  = 0.008), shift time of day ( p  = 0.002), and physician coverage n ( p  = 0.004). These strong associations remained even after adjusting for each other and other covariates. Marginal predictive probability analysis was used to predict the overall tMD impact (improvement from 50 to 43 minutes, p  < 0.001) of consistent staffing with 22 physicians. Conclusions: The analysis identified expected variables contributing to tMD with regression demonstrating significance and effect magnitude of alterations in covariates including patient census, shift time of day, and number of physicians. Marginal analysis provided operationally useful demonstration of the need to adjust physician coverage numbers, prompting changes at the study ED. The methods used in this analysis may prove useful in other EDs wishing to analyze operations information with the goal of predicting which interventions may have the most benefit.

Risk factors for hospital readmission of elderly patients.

PubMed

Franchi, Carlotta; Nobili, Alessandro; Mari, Daniela; Tettamanti, Mauro; Djade, Codjo D; Pasina, Luca; Salerno, Francesco; Corrao, Salvatore; Marengoni, Alessandra; Iorio, Alfonso; Marcucci, Maura; Mannucci, Pier Mannuccio

2013-01-01

The aim of this study was to identify which factors were associated with a risk of hospital readmission within 3 months after discharge of a sample of elderly patients admitted to internal medicine and geriatric wards. Of the 1178 patients aged 65 years or more and discharged from one of the 66 wards of the 'Registry Politerapie SIMI (REPOSI)' during 2010, 766 were followed up by phone interview 3 months after discharge and were included in this analysis. Univariate and multivariate logistic regression models were used to evaluate the association of several variables with rehospitalization within 3 months from discharge. Nineteen percent of patients were readmitted at least once within 3 months after discharge. By univariate analysis in-hospital clinical adverse events (AEs), a previous hospital admission, number of diagnoses and drugs, comorbidity and severity index (according to Cumulative Illness Rating Scale-CIRS), vascular and liver diseases with a level of impairment at discharge of 3 or more at CIRS were significantly associated with risk of readmission. Multivariate logistic regression analysis showed that only AEs during hospitalization, previous hospital admission, and vascular and liver diseases were significantly associated with the likelihood of readmission. The results demonstrate the need for increased medical attention towards elderly patients discharged from hospital with characteristics such as AEs during the hospitalization, previous admission, vascular and liver diseases. Copyright © 2012 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration

PubMed Central

Goovaerts, P.; Albuquerque, Teresa; Antunes, Margarida

2015-01-01

This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R2=0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold’s paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization. PMID:27777638

Household Food Waste: Multivariate Regression and Principal Components Analyses of Awareness and Attitudes among U.S. Consumers

PubMed Central

2016-01-01

We estimate models of consumer food waste awareness and attitudes using responses from a national survey of U.S. residents. Our models are interpreted through the lens of several theories that describe how pro-social behaviors relate to awareness, attitudes and opinions. Our analysis of patterns among respondents’ food waste attitudes yields a model with three principal components: one that represents perceived practical benefits households may lose if food waste were reduced, one that represents the guilt associated with food waste, and one that represents whether households feel they could be doing more to reduce food waste. We find our respondents express significant agreement that some perceived practical benefits are ascribed to throwing away uneaten food, e.g., nearly 70% of respondents agree that throwing away food after the package date has passed reduces the odds of foodborne illness, while nearly 60% agree that some food waste is necessary to ensure meals taste fresh. We identify that these attitudinal responses significantly load onto a single principal component that may represent a key attitudinal construct useful for policy guidance. Further, multivariate regression analysis reveals a significant positive association between the strength of this component and household income, suggesting that higher income households most strongly agree with statements that link throwing away uneaten food to perceived private benefits. PMID:27441687

Association between chronic viral hepatitis infection and breast cancer risk: a nationwide population-based case-control study

PubMed Central

2011-01-01

Background In Taiwan, there is a high incidence of breast cancer and a high prevalence of viral hepatitis. In this case-control study, we used a population-based insurance dataset to evaluate whether breast cancer in women is associated with chronic viral hepatitis infection. Methods From the claims data, we identified 1,958 patients with newly diagnosed breast cancer during the period 2000-2008. A randomly selected, age-matched cohort of 7,832 subjects without cancer was selected for comparison. Multivariable logistic regression models were constructed to calculate odds ratios of breast cancer associated with viral hepatitis after adjustment for age, residential area, occupation, urbanization, and income. The age-specific (<50 years and ≥50 years) risk of breast cancer was also evaluated. Results There were no significant differences in the prevalence of hepatitis C virus (HCV) infection, hepatitis B virus (HBV), or the prevalence of combined HBC/HBV infection between breast cancer patients and control subjects (p = 0.48). Multivariable logistic regression analysis, however, revealed that age <50 years was associated with a 2-fold greater risk of developing breast cancer (OR = 2.03, 95% CI = 1.23-3.34). Conclusions HCV infection, but not HBV infection, appears to be associated with early onset risk of breast cancer in areas endemic for HCV and HBV. This finding needs to be replicated in further studies. PMID:22115285

A cross-sectional evaluation of the prevalence and associations of HIV among female sex workers in the Gambia.

PubMed

Peitzmeier, Sarah; Mason, Krystal; Ceesay, Nuha; Diouf, Daouda; Drame, Fatou; Loum, Jaegan; Baral, Stefan

2014-03-01

To determine HIV prevalence among female sex workers in the Gambia and HIV risk factors, we accrued participants (n = 251) through peer-referral and venue-based recruitment. Blood samples were screened for HIV and participants were administered a questionnaire. Bivariate and multivariate logistic regression identified factors associated with HIV status. Forty respondents (15.9%) were HIV-positive: 20 (8.0%) were infected with HIV-1 only, 10 (4.0%) with HIV-2 only, and 10 (4.0%) with both HIV-1 and HIV-2; 12.5% (n = 5/40) knew their status. Condom usage at last sex was 97.1% (n = 170/175) with new clients and 44.2% (n = 53/120) with non-paying partners. Having a non-paying partner, living with relatives or friends, having felt scared to walk in public, selling sex in multiple locations, and recent depressive symptoms were positively associated with HIV under multivariate regression. Female sex workers have a higher prevalence of HIV compared to the general Gambian population. Interventions should be rights-based, promote safer sex practices and regular testing for female sex workers and linkage to HIV treatment and care with adherence support for those living with HIV. In addition, service providers should consider non-paying partners of female sex workers, improve knowledge and availability of condoms and lubricant, and address safety and mental health needs.

Predictors of parent-adolescent communication in post-apartheid South Africa: a protective factor in adolescent sexual and reproductive health.

PubMed

Coetzee, Jenny; Dietrich, Janan; Otwombe, Kennedy; Nkala, Busi; Khunwane, Mamakiri; van der Watt, Martin; Sikkema, Kathleen J; Gray, Glenda E

2014-04-01

In the HIV context, risky sexual behaviours can be reduced through effective parent-adolescent communication. This study used the Parent Adolescent Communication Scale to determine parent-adolescent communication by ethnicity and identify predictors of high parent-adolescent communication amongst South African adolescents post-apartheid. A cross-sectional interviewer-administered survey was administered to 822 adolescents from Johannesburg, South Africa. Backward stepwise multivariate regressions were performed. The sample was predominantly Black African (62%, n = 506) and female (57%, n = 469). Of the participants, 57% (n = 471) reported high parent-adolescent communication. Multivariate regression showed that gender was a significant predictor of high parent-adolescent communication (Black African OR:1.47, CI: 1.0-2.17, Indian OR: 2.67, CI: 1.05-6.77, White OR: 2.96, CI: 1.21-7.18). Female-headed households were predictors of high parent-adolescent communication amongst Black Africans (OR:1.49, CI: 1.01-2.20), but of low parent-adolescent communication amongst Whites (OR:0.36, CI: 0.15-0.89). Overall levels of parent-adolescent communication in South Africa are low. HIV prevention programmes for South African adolescents should include information and skills regarding effective parent-adolescent communication. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Analysis of association of clinical aspects and IL1B tagSNPs with severe preeclampsia.

PubMed

Leme Galvão, Larissa Paes; Menezes, Filipe Emanuel; Mendonca, Caio; Barreto, Ikaro; Alvim-Pereira, Claudia; Alvim-Pereira, Fabiano; Gurgel, Ricardo

2016-01-01

This study investigates the association between IL1B genotypes using a tag SNP (single polymorphism) approach, maternal and environmental factors in Brazilian women with severe preeclampsia. A case-control study with a total of 456 patients (169 preeclamptic women and 287 controls) was conducted in the two reference maternity hospitals of Sergipe state, Northeast Brazil. A questionnaire was administered and DNA was extracted to genotype the population for four tag SNPs of the IL1Beta: rs 1143643, rs 1143633, rs 1143634 and rs 1143630. Haplotype association analysis and p-values were calculated using the THESIAS test. Odds ratio (OR) estimation, confidence interval (CI) and multivariate logistic regression were performed. High pregestational body mass index (pre-BMI), first gestation, cesarean section, more than six medical visits, low level of consciousness on admission and TC and TT genotype in rs1143630 of IL1Beta showed association with the preeclamptic group in univariate analysis. After multivariate logistic regression pre-BMI, first gestation and low level of consciousness on admission remained associated. We identified an association between clinical variables and preeclampsia. Univariate analysis suggested that inflammatory process-related genes, such as IL1B, may be involved and should be targeted in further studies. The identification of the genetic background involved in preeclampsia host response modulation is mandatory in order to understand the preeclampsia process.

Risk factors for refractive errors in primary school children (6-12 years old) in Nakhon Pathom Province.

PubMed

Yingyong, Penpimol

2010-11-01

Refractive error is one of the leading causes of visual impairment in children. An analysis of risk factors for refractive error is required to reduce and prevent this common eye disease. To identify the risk factors associated with refractive errors in primary school children (6-12 year old) in Nakhon Pathom province. A population-based cross-sectional analytic study was conducted between October 2008 and September 2009 in Nakhon Pathom. Refractive error, parental refractive status, and hours per week of near activities (studying, reading books, watching television, playing with video games, or working on the computer) were assessed in 377 children who participated in this study. The most common type of refractive error in primary school children was myopia. Myopic children were more likely to have parents with myopia. Children with myopia spend more time at near activities. The multivariate odds ratio (95% confidence interval)for two myopic parents was 6.37 (2.26-17.78) and for each diopter-hour per week of near work was 1.019 (1.005-1.033). Multivariate logistic regression models show no confounding effects between parental myopia and near work suggesting that each factor has an independent association with myopia. Statistical analysis by logistic regression revealed that family history of refractive error and hours of near-work were significantly associated with refractive error in primary school children.

Incidence and risk factors of axial symptoms after cervical disc arthroplasty: a minimum 5-year follow-up study.

PubMed

Chen, Jing; Li, Jia; Qiu, Gang; Wei, Jingchao; Qiu, Yanfen; An, Yonghui; Shen, Yong

2016-09-20

The purpose of this study was to investigate whether uncovertebral joint ossification was a risk factor for axial symptoms (AS) after cervical disc arthroplasty (CDA). This retrospective study included 52 consecutive patients who underwent CDA for single-level cervical disc disease. To examine possible risk factors for AS after CDA, univariate and multivariate logistic regression analyses were conducted to compare data from the patients with and without AS (the AS and no-AS groups, respectively). Among the 52 patients examined, AS were observed in 24 patients (46.2 %), including a stiff neck (n = 11), neck pain and dullness (n = 10), and shoulder pain (n = 3). Uncovertebral joint ossification was detected in 22 (42.3 %) patients, including 17 patients in the AS group and 5 patients in the no-AS group. Clinical outcome improved during the follow-up period for the AS group. According to multivariate logistic regression analysis, uncovertebral joint ossification, cervical kyphosis, and range of motion (ROM) at the index level were identified as significant risk factors for AS after CDA. Satisfactory clinical outcomes were observed following CDA for the treatment of single-level cervical disc disease in the present cohort. In addition, uncovertebral joint ossification, cervical kyphosis, and ROM at the index level were found to affect the incidence of AS after CDA.

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.

Prediction of adherent placenta in pregnancy with placenta previa using ultrasonography and magnetic resonance imaging.

PubMed

Tanimura, Kenji; Yamasaki, Yui; Ebina, Yasuhiko; Deguchi, Masashi; Ueno, Yoshiko; Kitajima, Kazuhiro; Yamada, Hideto

2015-04-01

Adherent placenta is a life-threatening condition in pregnancy, and is often complicated by placenta previa. The aim of this prospective study was to determine prenatal imaging findings that predict the presence of adherent placenta in pregnancies with placenta previa. The study included 58 consecutive pregnant women with placenta previa who underwent both ultrasonography and magnetic resonance imaging prenatally. Ultrasonographic findings of anterior placental location, grade 2 or higher placental lacunae (PL≥G2), loss of retroplacental hypoechoic clear zone (LCZ) and the presence of turbulent blood flow in the arteries were evaluated, in addition to MRI findings. Forty-three women underwent cesarean section alone; 15 women with adherent placenta underwent cesarean section followed by hysterectomy with pathological examination. To determine imaging findings that predict adherent placenta, univariate and multivariate logistic regression analyses were performed. Univariate logistic regression analyses demonstrated that anterior placental location, PL≥G2, LCZ, and MRI were associated with the presence of adherent placenta. Multivariate analyses revealed that LCZ (p<0.01, odds ratio 15.6, 95%CI 2.1-114.6) was a single significant predictor of adherent placenta in women with placenta previa. This prospective study demonstrated for the first time that US findings, especially LCZ, might be useful for identifying patients at high risk for adherent placenta among pregnant women with placenta previa. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Factors associated with abnormal eating attitudes among Greek adolescents.

PubMed

Bilali, Aggeliki; Galanis, Petros; Velonakis, Emmanuel; Katostaras, Theofanis

2010-01-01

To estimate the prevalence of abnormal eating attitudes among Greek adolescents and identify possible risk factors associated with these attitudes. Cross-sectional, school-based study. Six randomly selected schools in Patras, southern Greece. The study population consisted of 540 Greek students aged 13-18 years, and the response rate was 97%. The dependent variable was scores on the Eating Attitudes Test-26, with scores > or = 20 indicating abnormal eating attitudes. Bivariate analysis included independent Student t test, chi-square test, and Fisher's exact test. Multivariate logistic regression analysis was applied for the identification of the predictive factors, which were associated independently with abnormal eating attitudes. A 2-sided P value of less than .05 was considered statistically significant. The prevalence of abnormal eating attitudes was 16.7%. Multivariate logistic regression analysis demonstrated that females, urban residents, and those with a body mass index outside normal range, a perception of being overweight, body dissatisfaction, and a family member on a diet were independently related to abnormal eating attitudes. The results indicate that a proportion of Greek adolescents report abnormal eating attitudes and suggest that multiple factors contribute to the development of these attitudes. These findings are useful for further research into this topic and would be valuable in designing preventive interventions. Copyright 2010 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

Refusal of Recommended Chemotherapy for Ovarian Cancer: Risk Factors and Outcomes; a National Cancer Data Base Study.

PubMed

Wallace, Sumer K; Lin, Jeff F; Cliby, William A; Leiserowitz, Gary S; Tergas, Ana I; Bristow, Robert E

2016-05-01

To identify risk factors associated with refusal of recommended chemotherapy and its impact on patients with epithelial ovarian cancer (EOC). We identified patients in the National Cancer Data Base diagnosed with EOC from January 1998 to December 2011. Patients who refused chemotherapy were identified and compared with those who received recommended, multiagent chemotherapy. Univariate and multivariable analyses were performed using chi-square test with Bonferroni correction, binary logistic regression, log-rank test, and Cox proportional hazards modeling. The threshold for statistical significance was set at a P value of less than 0.05. From a cohort of 147,713 eligible patients, 2,707 refused chemotherapy. These patients were compared with 92,212 patients who received recommended multiagent chemotherapy. Older age, more medical comorbidities, not having insurance, and later year of diagnosis were directly and significantly associated with chemotherapy refusal when analyzed using multivariable logistic regression. In addition, lower-than-expected facility adherence to NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Ovarian Cancer, treatment at low-volume center, lower grade, and higher stage were all significantly and independently associated with chemotherapy refusal. Median overall survival of patients who received multiagent chemotherapy was significantly longer than that of those who refused chemotherapy (43 vs 4.8 months; P<.0005). After controlling for known patient, facility, and disease prognostic factors, chemotherapy refusal is significantly associated with increased risk of death. Refusal of recommended chemotherapy carries significant risk of early death from ovarian cancer. Our data demonstrate that the decision to refuse chemotherapy is multifactorial and, in addition to unalterable factors (eg, stage/grade, age), involves factors that can be changed, including facility type and payor. Efforts at addressing these discrepancies in care can improve compliance with chemotherapy recommendations in the NCCN Guidelines for Ovarian Cancer and outcomes. Copyright © 2016 by the National Comprehensive Cancer Network.

Exercise oscillatory breathing and increased ventilation to carbon dioxide production slope in heart failure: an unfavorable combination with high prognostic value.

PubMed

Guazzi, Marco; Arena, Ross; Ascione, Aniello; Piepoli, Massimo; Guazzi, Maurizio D

2007-05-01

Increased slope of exercise ventilation to carbon dioxide production (VE/VCO2) is an established prognosticator in patients with heart failure. Recently, the occurrence of exercise oscillatory breathing (EOB) has emerged as an additional strong indicator of survival. The aim of this study is to define the respective prognostic significance of these variables and whether excess risk may be identified when either respiratory disorder is present. In 288 stable chronic HF patients (average left ventricular ejection fraction, 33 +/- 13%) who underwent cardiopulmonary exercise testing, the prognostic relevance of VE/VCO2 slope, EOB, and peak VO2 was evaluated by multivariate Cox regression. During a mean interval of 28 +/- 13 months, 62 patients died of cardiac reasons. Thirty-five percent presented with EOB. Among patients exhibiting EOB, 54% had an elevated VE/VCO2 slope. The optimal threshold value for the VE/VCO2 slope identified by receiver operating characteristic analysis was < 36.2 or > or = 36.2 (sensitivity, 77%; specificity, 64%; P < .001). Univariate predictors of death included low left ventricular ejection fraction, low peak VO2, high VE/VCO2 slope, and EOB presence. Multivariate analysis selected EOB as the strongest predictor (chi2, 46.5; P < .001). The VE/VCO2 slope (threshold, < 36.2 or > or = 36.2) was the only other exercise test variable retained in the regression (residual chi2, 5.9; P = .02). The hazard ratio for subjects with EOB and a VE/VCO2 slope > or = 36.2 was 11.4 (95% confidence interval, 4.9-26.5; P < .001). These findings identify EOB as a strong survival predictor even more powerful than VE/VCO2 slope. Exercise oscillatory breathing presence does not necessarily imply an elevated VE/VCO2 slope, but combination of either both yields to a burden of risk remarkably high.

Healthcare Resource Use and Direct Costs in Patients with Ankylosing Spondylitis and Psoriatic Arthritis in a Large US Cohort.

PubMed

Greenberg, Jeffrey D; Palmer, Jacqueline B; Li, Yunfeng; Herrera, Vivian; Tsang, Yuen; Liao, Minlei

2016-01-01

Direct costs of ankylosing spondylitis (AS) and psoriatic arthritis (PsA) have not been well characterized in the United States. This study assessed healthcare resource use and direct cost of AS and PsA, and identified predictors of all-cause medical and pharmacy costs. Adults aged ≥ 18 with a diagnosis of AS and PsA were identified in the MarketScan databases between October 1, 2011, and September 30, 2012. Patients were continuously enrolled with medical and pharmacy benefits for 12 months before and after the index date (first diagnosis). Baseline demographics and comorbidities were identified. Direct costs included hospitalizations, emergency room and office visits, and pharmacy costs. Multivariable regression was used to determine whether baseline covariates were associated with direct costs. Patients with AS were younger and mostly men compared with patients with PsA. Hypertension and hyperlipidemia were the most common comorbidities in both cohorts. A higher percentage of patients with PsA used biologics and nonbiologic disease-modifying drugs (61.1% and 52.4%, respectively) compared with patients with AS (52.5% and 21.8%, respectively). Office visits were the most commonly used resource by patients with AS and PsA (∼11 visits). Annual direct medical costs [all US dollars, mean (SD)] for patients with AS and PsA were $6514 ($32,982) and $5108 ($22,258), respectively. Prescription drug costs were higher for patients with PsA [$14,174 ($15,821)] compared with patients with AS [$11,214 ($14,249)]. Multivariable regression analysis showed higher all-cause direct costs were associated with biologic use, age, and increased comorbidities in patients with AS or PsA (all p < 0.05). Biologic use, age, and comorbidities were major determinants of all-cause direct costs in patients with AS and PsA.

Psychoactive substances use and associated factors among middle and high school students in the North Center of Morocco: a cross-sectional questionnaire survey.

PubMed

Zarrouq, B; Bendaou, B; El Asri, A; Achour, S; Rammouz, I; Aalouane, R; Lyoussi, B; Khelafa, S; Bout, A; Berhili, N; Hlal, H; Najdi, A; Nejjari, C; El Rhazi, K

2016-06-04

Data on psychoactive substance (PAS) consumption among adolescents in the North Center of Morocco are not at all available. Therefore, the current study aimed at investigating the prevalence and the determinants of psychoactive substances use among middle and high school students in this region. A cross-sectional study was conducted from April 2012 to November 2013 in public middle and high schools in the North Central Region of Morocco. An anonymous self-administered questionnaire was used to assess psychoactive substances use among a representative sample of school students from the 7th to the 12th grade, aged 11-23 years, selected by stratified cluster random sampling. Factors associated with psychoactive substance use were identified using multivariate stepwise logistic regression analyses. A total of 3020 school students completed the questionnaires, 53.0 % of which were males. The overall lifetime smoking prevalence was 16.1 %. The lifetime, annual and past month rates of any psychoactive substance use among the study subjects were 9.3, 7.5, and 6.3 % respectively. Cannabis recorded the highest lifetime prevalence of 8.1 %, followed by alcohol 4.3 %, inhalants 1.7 %, psychotropic substances without medical prescription 1.0, cocaine 0.7, heroine 0.3, and amphetamine with only 0.2 %. Psychoactive substance use was associated with males more than females. The risk factors identified by multivariate stepwise logistic regression analyses were being male, studying in secondary school level, smoking tobacco, living with a family member who uses tobacco, and feeling insecure within the family. The prevalence among all school students reported by the current study was comparable to the national prevalence. Efforts to initiate psychoactive substance prevention programs among school students should be made by designing such programs based on the significant factors associated with psychoactive substance use identified in this study.

Blend Sign on Computed Tomography: Novel and Reliable Predictor for Early Hematoma Growth in Patients With Intracerebral Hemorrhage.

PubMed

Li, Qi; Zhang, Gang; Huang, Yuan-Jun; Dong, Mei-Xue; Lv, Fa-Jin; Wei, Xiao; Chen, Jian-Jun; Zhang, Li-Juan; Qin, Xin-Yue; Xie, Peng

2015-08-01

Early hematoma growth is not uncommon in patients with intracerebral hemorrhage and is an independent predictor of poor functional outcome. The purpose of our study was to report and validate the use of our newly identified computed tomographic (CT) blend sign in predicting early hematoma growth. Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours after onset of symptoms were included. The follow-up CT scan was performed within 24 hours after the baseline CT scan. Significant hematoma growth was defined as an increase in hematoma volume of >33% or an absolute increase of hematoma volume of >12.5 mL. The blend sign on admission nonenhanced CT was defined as blending of hypoattenuating area and hyperattenuating region with a well-defined margin. Univariate and multivariable logistic regression analyses were performed to assess the relationship between the presence of the blend sign on nonenhanced admission CT and early hematoma growth. A total of 172 patients were included in our study. Blend sign was observed in 29 of 172 (16.9%) patients with intracerebral hemorrhage on baseline nonenhanced CT scan. Of the 61 patients with hematoma growth, 24 (39.3%) had blend sign on admission CT scan. Interobserver agreement for identifying blend sign was excellent between the 2 readers (κ=0.957). The multivariate logistic regression analysis demonstrated that the time to baseline CT scan, initial hematoma volume, and presence of blend sign on baseline CT scan to be independent predictors of early hematoma growth. The sensitivity, specificity, positive and negative predictive values of blend sign for predicting hematoma growth were 39.3%, 95.5%, 82.7%, and 74.1%, respectively. The CT blend sign could be easily identified on regular nonenhanced CT and is highly specific for predicting hematoma growth. © 2015 American Heart Association, Inc.

The use of inferior vena cava filters in spine trauma: A nationwide study using the National Trauma Data Bank.

PubMed

Sabharwal, Samir; Fox, Adam D; Vives, Michael J

2018-05-07

Objective To determine the prevalence and variation of inferior vena cava filter (IVCF) use in the spine trauma population and evaluate patient and facility level factors associated with their use. Study Design Retrospective cohort. Participants/Outcome Measures Patients with spinal injuries were identified by ICD-9 codes from the National Trauma Data Bank (NTDB), the best validated national trauma database. Patients whose spine injuries were operatively treated and those who received IVCF were identified from procedure description fields. Additional information compiled included patient demographics, injury severity score (ISS), time until surgery, concomitant fractures, and facility level information. Multivariate logistic regression analyses were conducted to examine the relationship of associated factors for IVCF use. Results Of the 120,920 patients identified with spinal injuries, 2.4% received prophylactic IVCF. Of the 13,273 patients with operatively treated spinal injuries, 8.2% received prophylactic IVCF. Of the 7,770 patients with spinal cord injury (SCI), 10.8% received prophylactic IVCF. The interquartile ranges of placement rates among centers demonstrated greater than 10 fold variation. Based on multivariate logistic regression, ISS score >12 demonstrated the strongest association with prophylactic IVCF (adjusted OR = 4.908). Concomitant pelvic and lower extremity fractures (adj OR 2.573 and 2.522) were also associated with their use. Conclusions Currently the only data regarding existing IVCF use in the spine trauma population amounts to surveys. The present study provides the most detailed and objective information regarding their use in this setting. Even in the operatively treated and SCI subgroups, prophylactic filters were used in only a small percentage of cases but placement rates varied widely among centers. More severely injured patients (ISS >12) had highest odds of receiving prophylactic IVCF. Further study is needed to clarify their role in this vulnerable population.

Ketorolac use may increase risk of postoperative pancreatic fistula after pancreaticoduodenectomy.

PubMed

Kowalsky, Stacy J; Zenati, Mazen S; Steve, Jennifer; Lee, Kenneth K; Hogg, Melissa E; Zeh, Herbert J; Zureikat, Amer H

2018-01-01

Ketorolac (Toradol), a commonly used nonselective nonsteroidal anti-inflammatory drug (NSAID) in the postoperative period, has been associated with increased risk of anastomotic leak after colon resection. The effect of postoperative NSAID and ketorolac use on postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy (PD) is unknown. Retrospective review of consecutive PDs at a high-volume pancreas center from 2012 to 2015. POPF was identified and graded using International Study Group on Pancreatic Fistula criteria. Demographics, operative variables and 30-d postoperative NSAID use, dosage, and timing (early = postoperative day [POD] 0-5, late > POD 5) were collected. Univariate and multivariate logistic regressions were used to identify predictors of POPF. Four hundred twenty-three PDs were analyzed (mean age 66 y, 47% female), and 60% received NSAIDs postoperatively. Ketorolac (median POD 0-5 cumulative dose = 90 mg, interquartile range 60-165) was used in 35.7% (n = 151). POPF occurred in 90 patients (21.3%). Early (POD 0-5) ketorolac use was associated with increased POPF, especially grade A (odds ratio [OR] 2.16, P = 0.036). Each 25 mg incremental increase in ketorolac use was associated with a 10% increase in the incidence of POPF (OR 1.10, P = 0.021), whereas a cumulative dose of >150 mg was associated with a 44% increased risk of POPF (OR 1.44, 95% confidence interval 1.03-2.01, P = 0.035). A multivariate regression model identified estimated blood loss, soft gland, pancreatic duct diameter, body mass index, and cumulative ketorolac dose >150 mg as independent predictors of POPF (P < 0.0001, pseudo R 2  = 0.149). Increasing doses of ketorolac in the early postoperative period are associated with increased risk of POPF, whereas a cumulative dose of >150 mg is an independent predictor of POPF after PD. Copyright © 2017 Elsevier Inc. All rights reserved.

Influence of systemic bone mineral density on atlantoaxial subluxation in patients with rheumatoid arthritis.

PubMed

Han, M H; Ryu, J I; Kim, C H; Kim, J M; Cheong, J H; Bak, K H; Chun, H J

2017-06-01

Osteopenia and osteoporosis were independent predictive factors for higher atlantoaxial subluxation occurrence in patients with lower body mass index. Our findings suggest that patients with rheumatoid arthritis with osteopenia or osteoporosis, particularly those with lower body mass index (BMI), should be screened regularly to determine the status of their cervical spines. Cervical spine involvement in rheumatoid arthritis (RA) patients may cause serious adverse effects on quality of life and overall health. This study aimed to evaluate the association between atlantodental interval (ADI), atlantoaxial subluxation (AAS), and systemic bone mineral density (BMD) based on BMI variations among established patients with RA. The ADI was transformed to the natural log scale to normalize distributions for all analyses. Multivariable linear regression analyses were used to identify independent predictive factors for ADI based on each BMD classification. Multivariate Cox regression analyses were also performed to identify independent predictive factors for the risk of AAS, which were classified by tertile groups of BMI. A total of 1220 patients with RA who had undergone at least one or more cervical radiography and BMD assessments were identified and enrolled. We found that the association between BMD and ADI (β, -0.029; 95% CI, -0.059 to 0.002; p = 0.070) fell short of achieving statistical significance. However, the ADI showed a 3.6% decrease per 1 BMI increase in the osteoporosis group (β, -0.036; 95% CI, -0.061 to -0.011; p = 0.004). The osteopenia and osteoporosis groups showed about a 1.5-fold and a 1.8-fold increased risk of AAS occurrence among the first tertile of the BMI group. Our study showed a possible association between lower BMD and AAS occurrence in patients with RA with lower BMI. Further studies are needed to confirm our findings.

Cigarette smoking and male sex are independent and age concomitant risk factors for the development of ocular sarcoidosis in a new orleans sarcoidosis population

PubMed Central

Janot, Adam C.; Huscher, Dörte; Walker, McCall; Grewal, Harmanjot K.; Yu, Mary; Lammi, Matthew R.; Saketkoo, Lesley Ann

2016-01-01

Introduction Sarcoidosis is a multi-organ system granulomatous disease of unknown origin with an incidence of 1–40/100,000. Though pulmonary manifestations are predominant, ocular sarcoidosis (OS) affects 25–50% of patients with sarcoidosis and can lead to blindness. Methods A retrospective, single-center chart review of sarcoidosis cases investigated variables associated with the development of OS. Inclusion criteria were biopsy-proven sarcoidosis, disease duration greater than 1 year, documented smoking status on chart review and documentation of sarcoid-related eye disease. Multivariate analysis identified independent risk factors for OS. Results Of 269 charts reviewed, 109 patients met inclusion criteria. The OS group had a significantly higher proportion of smokers (71.4%) than without OS (42.0%, p=0.027) with no difference (p=0.61) in median number of pack years. Male sex was significantly higher in the OS group (57.1% versus 26.1%, p=0.009). Median duration of sarcoidosis was higher in the OS group (10 versus 4 years, p=0.031). Multivariate regression identified tobacco exposure (OR=5.25, p=0.007, 95% CI 1.58–17.41), male sex (OR=7.48, p=0.002, 95% CI 2.15–26.01), and age (OR=1.114, p=0.002, 95% CI 1.04–1.19) as concomitant risk factors for the development of OS. Conclusion To date, there are few dedicated investigations of risk factors for OS, especially smoking. This investigation identified male sex, age, and tobacco exposure as independent risk factors for OS. Though disease duration did not withstand regression analysis in this moderately sized group, age at chart review suggests screening for OS should not remit but rather intensify in aging patients with sarcoidosis. PMID:26278693

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.

Factors associated with utilization of long-acting and permanent contraceptive methods among women who have decided not to have more children in Gondar city.

PubMed

Zenebe, Chernet Baye; Adefris, Mulat; Yenit, Melaku Kindie; Gelaw, Yalemzewod Assefa

2017-09-06

Despite the fact that long acting family planning methods reduce population growth and improve maternal health, their utilization remains poor. Therefore, this study assessed the prevalence of long acting and permanent family planning method utilization and associated factors among women in reproductive age groups who have decided not to have more children in Gondar city, northwest Ethiopia. An institution based cross-sectional study was conducted from August to October, 2015. Three hundred seventeen women who have decided not to have more children were selected consecutively into the study. A structured and pretested questionnaire was used to collect data. Both bivariate and multi-variable logistic regressions analyses were used to identify factors associated with utilization of long acting and permanent family planning methods. The multi-variable logistic regression analysis was used to investigate factors associated with the utilization of long acting and permanent family planning methods. The Adjusted Odds Ratio (AOR) with the corresponding 95% Confidence Interval (CI) was used to show the strength of associations, and variables with a P-value of <0.05 were considered statistically significant. In this study, the overall prevalence of long acting and permanent contraceptive (LAPCM) method utilization was 34.7% (95% CI: 29.5-39.9). According to the multi-variable logistic regression analysis, utilization of long acting and permanent contraceptive methods was significantly associated with women who had secondary school, (AOR: 2279, 95% CI: 1.17, 4.44), college, and above education (AOR: 2.91, 95% CI: 1.36, 6.24), history of previous utilization (AOR: 3.02, 95% CI: 1.69, 5.38), and information about LAPCM (AOR: 8.85, 95% CI: 2.04, 38.41). In this study the prevalence of long acting and permanent family planning method utilization among women who have decided not to have more children was high compared with previous studies conducted elsewhere. Advanced educational status, previous utilization of LAPCM, and information on LAPCM were significantly associated with the utilization of LAPCM. As a result, strengthening behavioral change communication channels to make information accessible is highly recommended.

Barriers and benefits of a healthy diet in spain: comparison with other European member states.

PubMed

Holgado, B; de Irala-Estévez, J; Martínez-González, M A; Gibney, M; Kearney, J; Martínez, J A

2000-06-01

Our purpose was to identify the main barriers and benefits perceived by the European citizens in regard to following a healthy diet and to assess the differences in expected benefits and difficulties between Spain and the remaining countries of the European Union. A cross-sectional study in which quota-controlled, nationally representative samples of approximately 1000 adults from each country completed a questionnaire. The survey was carried out between October 1995 and February 1996 in the 15 member states of the European Union. Participants (aged 15 y and older) were selected and interviewed in their homes about their attitudes towards healthy diets. They were asked to select two options from a list of 22 potential barriers to achieve a healthy diet and the benefits derived from a healthy diet. The associations of the perceived benefits of barriers with the sociodemographic variables within Spain and the rest of the European Union were compared with the Pearson chi-squared test and the chi-squared linear trend test. Two multivariate logistic regression models were also fitted to assess the characteristics independently related to the selection of 'Resistance to change' among the main barriers and to the selection of 'Prevent disease/stay healthy' as the main perceived benefits. The barrier most frequently mentioned in Spain was 'Irregular work hours' (29.7%) in contrast with the rest of the European Union where 'Giving up foods that I like' was the barrier most often chosen (26.2%). In the multivariate logistic regression model studying resistance to change, Spaniards were less resistant to change than the rest of the European Union. The benefit more frequently mentioned across Europe was 'Prevent disease/stay healthy'. In the multivariate logistic regression model women, older individuals, and people with a higher educational level were more likely to choose this benefit. It is apparent that there are many barriers to achieve healthy eating, mostly lack of time. For this reason a higher availability of food in line with the nutrition guidelines could be helpful. The population could have a better knowledge of the benefits derived from a healthy diet.

Suicidal ideation among Italian and Spanish young adults: the role of sexual orientation.

PubMed

Baiocco, Roberto; Ioverno, Salvatore; Lonigro, Antonia; Baumgartner, Emma; Laghi, Fiorenzo

2015-01-01

The purpose of the current study was to identify demographic, social, and psychological variables associated with suicidal ideation in an Italian sample and a Spanish sample, taking into account the relevance of sexual orientation as a risk factor for suicide. Three hundred twenty gay and bisexual men, 396 heterosexual men, 281 lesbians and bisexual women, and 835 heterosexual women were recruited. In chi-square and multivariable logistic regression analyses we identified several consistent cross-national risk factors for suicidal ideation: having lower education, not being religious, being homosexual or bisexual, not being engaged in a stable relationship, having lower level of peer and parental attachment, and having depressive symptoms. Interestingly, the strongest risk factor in both samples, after depression symptoms, was sexual orientation.

The effect of dental overbite on eustachian tube dysfunction in Iranian children.

PubMed

Azadani, Peyman Nejatbakhsh; Jafarimehr, Elnaz; Shokatbakhsh, Abdorahman; Pourhoseingholi, Mohamad Amin; Ghougeghi, Aman

2007-02-01

To investigate the association between deep dental overbite and eustachian tube dysfunction. It was designed as a case-control study. Among hospitalized patients in otolaryngology department at Taleghani Hospital in Tehran, Iran, from January to December 2005, 132 patients between the ages of 2 and 6 years were recruited. Dental overbite, overjet, and occlusal relationships were measured by one observer. Eustachian tube dysfunction was defined as having ventilation tubes with an abnormal tympanometry. In addition, demographic information, medical and social histories were prospectively recorded. Univariate and multivariate logistic regression model were used. In a multivariate model, children with deep bites were 10.6 times more likely to have eustachian tube dysfunction than those without deep bites (P<0.05). Other independent risk factors for eustachian tube dysfunction identified in this model were family history of otitis media, daycare exposure, and non-breast-feeding. Children with deep dental overbites are at a significantly increased risk for developing eustachian tube dysfunction.

B-mode sonographic criteria for differential diagnosis of cervicofacial lymphadenopathy in cat-scratch disease and toxoplasmosis.

PubMed

Ridder, Gerd Jürgen; Boedeker, Carsten Christof; Lee, Tao-Kwang Kevin; Sander, Anna

2003-04-01

Our purpose was to evaluate different sonographic parameters of cervicofacial lymphadenopathy caused by cat-scratch disease (CSD) and toxoplasmosis. By use of high-resolution B-mode sonography a total of 552 lymph nodes in the head and neck were detected between January 1997 and December 2001. There were 71 patients (422 lymph nodes) with CSD and 19 patients (130 lymph nodes) with toxoplasmosis. Sonographic variables, including 20 sonomorphologic features along with age and gender, were analyzed with multivariate logistic regression. Heterogenous lymph nodes were more often found in CSD (p =.003), and nonsharp nodal borders showed a significant association with CSD (p =.0005). Multivariate analysis identified sharpness of borders (p =.0001), S/L ratio (p =.0006), and type of lymphadenopathy (acute, abscessed, chronic) (p =.0006) as most significant for differentiating between CSD and toxoplasmosis. These results provide significant and useful criteria for ultrasonographic differentiation between CSD and toxoplasmosis. Copyright 2003 Wiley Periodicals, Inc.

Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networks.

PubMed

Faes, Luca; Nollo, Giandomenico; Krohova, Jana; Czippelova, Barbora; Turianikova, Zuzana; Javorka, Michal

2017-07-01

To fully elucidate the complex physiological mechanisms underlying the short-term autonomic regulation of heart period (H), systolic and diastolic arterial pressure (S, D) and respiratory (R) variability, the joint dynamics of these variables need to be explored using multivariate time series analysis. This study proposes the utilization of information-theoretic measures to measure causal interactions between nodes of the cardiovascular/cardiorespiratory network and to assess the nature (synergistic or redundant) of these directed interactions. Indexes of information transfer and information modification are extracted from the H, S, D and R series measured from healthy subjects in a resting state and during postural stress. Computations are performed in the framework of multivariate linear regression, using bootstrap techniques to assess on a single-subject basis the statistical significance of each measure and of its transitions across conditions. We find patterns of information transfer and modification which are related to specific cardiovascular and cardiorespiratory mechanisms in resting conditions and to their modification induced by the orthostatic stress.

Pediatric anemia in rural Ghana: a cross-sectional study of prevalence and risk factors.

PubMed

VanBuskirk, Kelley M; Ofosu, Anthony; Kennedy, Amy; Denno, Donna M

2014-08-01

To assess anemia prevalence and identify associated parameters in children <3 years of age in a rural area of Ghana. Univariate and multivariate logistic regression of cross-sectional survey results from 861 children aged <3 years attending routine immunization services in Berekum district. Anemia prevalence was 73.1%; most were either mildly (31.2%) or moderately (38.7%) affected. Risk factors for anemia (hemoglobin < 11.0 g/dl) in multivariate analysis were malaria parasitemia and male sex; these factors and younger age were associated with anemia severity. A partial defect in glucose-6-phosphate dehydrogenase was associated with decreased severity. Height-for-age, but not weight-for-age, was associated with anemia and its severity. Malaria parasitemia was strongly associated with anemia and its severity, suggesting that malaria control may be the most effective way to reduce the burden of anemia in rural Ghanaian children. © The Author [2014]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Awareness and Acceptability of Pre-exposure HIV Prophylaxis Among Men Who have Sex with Men in Baltimore.

PubMed

Fallon, Susan A; Park, Ju Nyeong; Ogbue, Christine Powell; Flynn, Colin; German, Danielle

2017-05-01

This paper assessed characteristics associated with awareness of and willingness to take pre-exposure prophylaxis (PrEP) among Baltimore men who have sex with men (MSM). We used data from BESURE-MSM3, a venue-based cross-sectional HIV surveillance study conducted among MSM in 2011. Multivariate regression was used to identify characteristics associated with PrEP knowledge and acceptability among 399 participants. Eleven percent had heard of PrEP, 48% would be willing to use PrEP, and none had previously used it. In multivariable analysis, black race and perceived discrimination against those with HIV were significantly associated with decreased awareness, and those who perceived higher HIV discrimination reported higher acceptability of PrEP. Our findings indicate a need for further education about the potential utility of PrEP in addition to other prevention methods among MSM. HIV prevention efforts should address the link between discrimination and potential PrEP use, especially among men of color.

Tobacco Smoking and Its Association with Illicit Drug Use among Young Men Aged 15-24 Years Living in Urban Slums of Bangladesh

PubMed Central

Kabir, Mohammad Alamgir; Goh, Kim-Leng; Kamal, Sunny Mohammad Mostafa; Khan, Md. Mobarak Hossain

2013-01-01

Background Tobacco smoking (TS) and illicit drug use (IDU) are of public health concerns especially in developing countries, including Bangladesh. This paper aims to (i) identify the determinants of TS and IDU, and (ii) examine the association of TS with IDU among young slum dwellers in Bangladesh. Methodology/Principal Findings Data on a total of 1,576 young slum dwellers aged 15–24 years were extracted for analysis from the 2006 Urban Health Survey (UHS), which covered a nationally representative sample of 13,819 adult men aged 15–59 years from slums, non-slums and district municipalities of six administrative regions in Bangladesh. Methods used include frequency run, Chi-square test of association and multivariable logistic regression. The overall prevalence of TS in the target group was 42.3%, of which 41.4% smoked cigarettes and 3.1% smoked bidis. The regression model for TS showed that age, marital status, education, duration of living in slums, and those with sexually transmitted infections were significantly (p<0.001 to p<0.05) associated with TS. The overall prevalence of IDU was 9.1%, dominated by those who had drug injections (3.2%), and smoked ganja (2.8%) and tari (1.6%). In the regression model for IDU, the significant (p<0.01 to p<0.10) predictors were education, duration of living in slums, and whether infected by sexually transmitted diseases. The multivariable logistic regression (controlling for other variables) revealed significantly (p<0.001) higher likelihood of IDU (OR = 9.59, 95% CI = 5.81–15.82) among users of any form of TS. The likelihood of IDU increased significantly (p<0.001) with increased use of cigarettes. Conclusions/Significance Certain groups of youth are more vulnerable to TS and IDU. Therefore, tobacco and drug control efforts should target these groups to reduce the consequences of risky lifestyles through information, education and communication (IEC) programs. PMID:23935885

The influence of sarcopenia on survival and surgical complications in ovarian cancer patients undergoing primary debulking surgery.

PubMed

Rutten, I J G; Ubachs, J; Kruitwagen, R F P M; van Dijk, D P J; Beets-Tan, R G H; Massuger, L F A G; Olde Damink, S W M; Van Gorp, T

2017-04-01

Sarcopenia, severe skeletal muscle loss, has been identified as a prognostic factor in various malignancies. This study aims to investigate whether sarcopenia is associated with overall survival (OS) and surgical complications in patients with advanced ovarian cancer undergoing primary debulking surgery (PDS). Ovarian cancer patients (n = 216) treated with PDS were enrolled retrospectively. Total skeletal muscle surface area was measured on axial computed tomography at the level of the third lumbar vertebra. Optimum stratification was used to find the optimal skeletal muscle index cut-off to define sarcopenia (≤38.73 cm 2 /m 2 ). Cox-regression and Kaplan-Meier analysis were used to analyse the relationship between sarcopenia and OS. The effect of sarcopenia on the development of major surgical complications was studied with logistic regression. Kaplan-Meier analysis showed a significant survival disadvantage for patients with sarcopenia compared to patients without sarcopenia (p = 0.010). Sarcopenia univariably predicted OS (HR 1.536 (95% CI 1.105-2.134), p = 0.011) but was not significant in multivariable Cox-regression analysis (HR 1.362 (95% CI 0.968-1.916), p = 0.076). Significant predictors for OS in multivariable Cox-regression analysis were complete PDS, treatment in a specialised centre and the development of major complications. Sarcopenia was not predictive of major complications. Sarcopenia was not predictive of OS or major complications in ovarian cancer patients undergoing primary debulking surgery. However a strong trend towards a survival disadvantage for patients with sarcopenia was seen. Future prospective studies should focus on interventions to prevent or reverse sarcopenia and possibly increase ovarian cancer survival. Complete cytoreduction remains the strongest predictor of ovarian cancer survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

Risk for Health Care-Associated Bloodstream Infections in Pediatric Oncology Patients With Various Malignancies.

PubMed

Thurman, Cara B; Abbott, Maura; Liu, Jinfang; Larson, Elaine

This was a retrospective cohort study to identify the rates, predictors, and outcomes of health care-associated bloodstream infections (HA-BSI) among children with solid tumors, lymphoma, lymphoid leukemia, and myeloid leukemia. The study population included 4500 children ≤18 years old at a pediatric hospital in New York City from 2006 to 2014. A total of 147 HA-BSI cases were identified; using multivariable logistic regression modeling, children with a hematologic diagnosis (lymphoma, lymphoid leukemia, myeloid leukemia) were at greater risk for HA-BSI than those with a solid tumor diagnosis (all P values <.0001). The odds of mortality for patients with HA-BSI were 6.98 (95% confidence interval 3.02-16.10) times that of those without HA-BSI. Although malignancy type was identified as risk factor for HA-BSI, there was no significant difference in overall mortality from HA-BSI by tumor type ( P = .51).

Determinants of Sunburn and Sun Protection of Agricultural Workers During Occupational and Recreational Activities.

PubMed

Backes, Claudine; Milon, Antoine; Koechlin, Alice; Vernez, David; Bulliard, Jean-Luc

2017-11-01

The aim of this study was to identify determinants of occupational sunburn in agricultural workers and assess their occupational and recreational sun protection habits. Specific surveys of agricultural workers in Switzerland and France were conducted (N = 1538). Multivariate logistic regressions identified occupational sunburn determinants. Occupational and recreational sun protection habits were estimated and correlated. One-year occupational and recreational sunburn prevalences were 19.8% and 11.5%, respectively. Occupational sunburn increased with having a recent recreational sunburn, highly sensitive skin, young age, high perceived skin cancer risk, using sunscreen, and not wearing a hat. Correlation between protection habits during work and leisure was substantial (rs 0.5 to 0.7). Skin health knowledge was high and pro-tanning attitude moderate. Potentially modifiable sunburn determinants and suboptimal recreational and occupational sun protection practices were identified in agricultural workers. Refining and tailoring sun protection messages targeting the agricultural sector are needed.

Improved estimation of PM2.5 using Lagrangian satellite-measured aerosol optical depth

NASA Astrophysics Data System (ADS)

Olivas Saunders, Rolando

Suspended particulate matter (aerosols) with aerodynamic diameters less than 2.5 mum (PM2.5) has negative effects on human health, plays an important role in climate change and also causes the corrosion of structures by acid deposition. Accurate estimates of PM2.5 concentrations are thus relevant in air quality, epidemiology, cloud microphysics and climate forcing studies. Aerosol optical depth (AOD) retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument has been used as an empirical predictor to estimate ground-level concentrations of PM2.5 . These estimates usually have large uncertainties and errors. The main objective of this work is to assess the value of using upwind (Lagrangian) MODIS-AOD as predictors in empirical models of PM2.5. The upwind locations of the Lagrangian AOD were estimated using modeled backward air trajectories. Since the specification of an arrival elevation is somewhat arbitrary, trajectories were calculated to arrive at four different elevations at ten measurement sites within the continental United States. A systematic examination revealed trajectory model calculations to be sensitive to starting elevation. With a 500 m difference in starting elevation, the 48-hr mean horizontal separation of trajectory endpoints was 326 km. When the difference in starting elevation was doubled and tripled to 1000 m and 1500m, the mean horizontal separation of trajectory endpoints approximately doubled and tripled to 627 km and 886 km, respectively. A seasonal dependence of this sensitivity was also found: the smallest mean horizontal separation of trajectory endpoints was exhibited during the summer and the largest separations during the winter. A daily average AOD product was generated and coupled to the trajectory model in order to determine AOD values upwind of the measurement sites during the period 2003-2007. Empirical models that included in situ AOD and upwind AOD as predictors of PM2.5 were generated by multivariate linear regressions using the least squares method. The multivariate models showed improved performance over the single variable regression (PM2.5 and in situ AOD) models. The statistical significance of the improvement of the multivariate models over the single variable regression models was tested using the extra sum of squares principle. In many cases, even when the R-squared was high for the multivariate models, the improvement over the single models was not statistically significant. The R-squared of these multivariate models varied with respect to seasons, with the best performance occurring during the summer months. A set of seasonal categorical variables was included in the regressions to exploit this variability. The multivariate regression models that included these categorical seasonal variables performed better than the models that didn't account for seasonal variability. Furthermore, 71% of these regressions exhibited improvement over the single variable models that was statistically significant at a 95% confidence level.

Multivariate regression model for partitioning tree volume of white oak into round-product classes

Treesearch

Daniel A. Yaussy; David L. Sonderman

1984-01-01

Describes the development of multivariate equations that predict the expected cubic volume of four round-product classes from independent variables composed of individual tree-quality characteristics. Although the model has limited application at this time, it does demonstrate the feasibility of partitioning total tree cubic volume into round-product classes based on...

Multivariate decoding of brain images using ordinal regression.

PubMed

Doyle, O M; Ashburner, J; Zelaya, F O; Williams, S C R; Mehta, M A; Marquand, A F

2013-11-01

Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found that ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine data set, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection. Copyright © 2013. Published by Elsevier Inc.

A prognostic mutation panel for predicting cancer recurrence in stages II and III colorectal cancer.

PubMed

Sho, Shonan; Court, Colin M; Winograd, Paul; Russell, Marcia M; Tomlinson, James S

2017-12-01

Approximately 20-40% of stage II/III colorectal cancer (CRC) patients develop relapse. Clinicopathological factors alone are limited in detecting these patients, resulting in potential under/over-treatment. We sought to identify a prognostic tumor mutational profile that could predict CRC recurrence. Whole-exome sequencing data were obtained for 207 patients with stage II/III CRC from The Cancer Genome Atlas. Mutational landscape in relapse-free versus relapsed cohort was compared using Fisher's exact test, followed by multivariate Cox regression to identify genes associated with cancer recurrence. Bootstrap-validation was used to examine internal/external validity. We identified five prognostic genes (APAF1, DIAPH2, NTNG1, USP7, and VAV2), which were combined to form a prognostic mutation panel. Patients with ≥1 mutation(s) within this five-gene panel had worse prognosis (3-yr relapse-free survival [RFS]: 53.0%), compared to patients with no mutation (3-yr RFS: 84.3%). In multivariate analysis, the five-gene panel remained prognostic for cancer recurrence independent of stage and high-risk features (hazard ratio 3.63, 95%CI [1.93-6.83], P < 0.0001). Furthermore, its prognostic accuracy was superior to the American Joint Commission on Cancer classification (concordance-index: 0.70 vs 0.54). Our proposed mutation panel identifies CRC patients at high-risk for recurrence, which may help guide adjuvant therapy and post-operative surveillance protocols. © 2017 Wiley Periodicals, Inc.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody–peptide fusion

PubMed Central

Goldrick, Stephen; Holmes, William; Bond, Nicholas J.; Lewis, Gareth; Kuiper, Marcel; Turner, Richard

2017-01-01

ABSTRACT Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. PMID:28500668

Venous thromboembolism in women undergoing pelvic reconstructive surgery with mechanical prophylaxis alone.

PubMed

Montoya, T Ignacio; Leclaire, Edgar L; Oakley, Susan H; Crane, Andrea K; Mcpencow, Alexandra; Cichowski, Sara; Rahn, David D

2014-07-01

The objective of this study was determine the frequency of symptomatic perioperative venous thromboembolism (VTE) and risk factor(s) associated with VTE occurrence in women undergoing elective pelvic reconstructive surgery using only intermittent pneumatic compression (IPC) for VTE prophylaxis. A multi-center case-cohort retrospective review was conducted at six clinical sites over a 66-month period. All sites utilize IPC as standard VTE prophylaxis for urogynecological surgery. VTE cases occurring during the same hospitalization and up to 6 weeks postoperatively were identified by ICD9 code query. Four controls were temporally matched to each case. Information collected included demographics, medical history, route of surgery, operative time, and intraoperative characteristics. Univariate and multivariate backward stepwise logistic regression analyses were performed to identify potential risk factors for VTE. Symptomatic perioperative VTE was diagnosed in 27 subjects from a cohort of 10,627 women who underwent elective urogynecological surgery (0.25 %). Univariate analysis identified surgical route (laparotomy vs others), type of surgery ("major" vs "minor"), history of gynecological cancer, surgery time, and patient age as risk factors for VTE (P < 0.05). Multivariate analysis identified increased frequency of VTE with laparotomy, age ≥ 70, and surgery duration ≥ 5 h. In our study cohort, the frequency of symptomatic perioperative VTE was low. Laparotomy, age ≥ 70 years, and surgery duration ≥ 5 h were associated with VTE occurrence.

Identification of the compositional changes in Orthosiphon stamineus leaves triggered by different drying techniques using 1 H NMR metabolomics.

PubMed

Pariyani, Raghunath; Ismail, Intan Safinar; Ahmad Azam, Amalina; Abas, Faridah; Shaari, Khozirah

2017-09-01

Java tea is a well-known herbal infusion prepared from the leaves of Orthosiphon stamineus (OS). The biological properties of tea are in direct correlation with the primary and secondary metabolite composition, which in turn largely depends on the choice of drying method. Herein, the impact of three commonly used drying methods, i.e. shade, microwave and freeze drying, on the metabolite composition and antioxidant activity of OS leaves was investigated using proton nuclear magnetic resonance ( 1 H NMR) spectroscopy combined with multivariate classification and regression analysis tools. A total of 31 constituents comprising primary and secondary metabolites belonging to the chemical classes of fatty acids, amino acids, sugars, terpenoids and phenolic compounds were identified. Shade-dried leaves were identified to possess the highest concentrations of bioactive secondary metabolites such as chlorogenic acid, caffeic acid, luteolin, orthosiphol and apigenin, followed by microwave-dried samples. Freeze-dried leaves had higher concentrations of choline, amino acids leucine, alanine and glutamine and sugars such as fructose and α-glucose, but contained the lowest levels of secondary metabolites. Metabolite profiling coupled with multivariate analysis identified shade drying as the best method to prepare OS leaves as Java tea or to include in traditional medicine preparation. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Clinically Identified Postpartum Depression in Asian American Mothers

PubMed Central

Goyal, Deepika; Wang, Elsie J.; Shen, Jeremy; Wong, Eric C.; Palaniappan, Latha P.

2015-01-01

Objective To identify the clinical diagnosis rate of postpartum depression (PPD) in Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese) compared to non-Hispanic Whites. Design Cross-sectional study using electronic health records (EHR). Setting A large, outpatient, multiservice clinic in Northern California. Participants A diverse clinical population of non-Hispanic White (N = 4582), Asian Indian (N = 1264), Chinese (N = 1160), Filipino (N = 347), Japanese (N = 124), Korean (N = 183), and Vietnamese (N = 147) mothers. Methods Cases of PPD were identified from EHRs using physician diagnosis codes, medication usage, and age standardized for comparison. The relationship between PPD and other demographic variables (race/ethnicity, maternal age, delivery type, marital status, and infant gender) were examined in a multivariate logistic regression model. Results The PPD diagnosis rate for all Asian American mothers in aggregate was significantly lower than the diagnosis rate in non-Hispanic White mothers. Moreover, of the six Asian American subgroups, PPD diagnosis rates for Asian Indian, Chinese, and Filipino mothers were significantly lower than non-Hispanic White mothers. In multivariate analyses, race/ethnicity, age, and cesarean were significant predictors of PPD. Conclusion In this insured population, PPD diagnosis rates were lower among Asian Americans, with variability in rates across the individual Asian American subgroups. It is unclear whether these lower rates are due to underreporting, underdiagnosis, or underutilization of mental health care in this setting. PMID:22536783

Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome

PubMed Central

Jamme, Matthieu; Raimbourg, Quentin; Chauveau, Dominique; Seguin, Amélie; Presne, Claire; Perez, Pierre; Gobert, Pierre; Wynckel, Alain; Provôt, François; Delmas, Yahsou; Mousson, Christiane; Servais, Aude; Vrigneaud, Laurence; Veyradier, Agnès

2017-01-01

Chronic kidney disease (CKD) is a frequent and serious complication of atypical haemolytic uremic syndrome (aHUS). We aimed to develop a simple accurate model to predict the risk of renal dysfunction in aHUS based on clinical and biological features available at hospital admission. Renal function at 1-year follow-up, based on an estimated glomerular filtration rate < 60mL/min/1.73m2 as assessed by the Modification of Diet in Renal Disease equation, was used as an indicator of significant CKD. Prospectively collected data from a cohort of 156 aHUS patients who did not receive eculizumab were used to identify predictors of CKD. Covariates associated with renal impairment were identified by multivariate analysis. The model performance was assessed and a scoring system for clinical practice was constructed from the regression coefficient. Multivariate analyses identified three predictors of CKD: a high serum creatinine level, a high mean arterial pressure and a mildly decreased platelet count. The prognostic model had a good discriminative ability (area under the curve = .84). The scoring system ranged from 0 to 5, with corresponding risks of CKD ranging from 18% to 100%. This model accurately predicts development of 1-year CKD in patients with aHUS using clinical and biological features available on admission. After further validation, this model may assist in clinical decision making. PMID:28542627

Clinically identified postpartum depression in Asian American mothers.

PubMed

Goyal, Deepika; Wang, Elsie J; Shen, Jeremy; Wong, Eric C; Palaniappan, Latha P

2012-01-01

To identify the clinical diagnosis rate of postpartum depression (PPD) in Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese) compared to non-Hispanic Whites. Cross-sectional study using electronic health records (EHR). A large, outpatient, multiservice clinic in Northern California. A diverse clinical population of non-Hispanic White (N = 4582), Asian Indian (N = 1264), Chinese (N = 1160), Filipino (N = 347), Japanese (N = 124), Korean (N = 183), and Vietnamese (N = 147) mothers. Cases of PPD were identified from EHRs using physician diagnosis codes, medication usage, and age standardized for comparison. The relationship between PPD and other demographic variables (race/ethnicity, maternal age, delivery type, marital status, and infant gender) were examined in a multivariate logistic regression model. The PPD diagnosis rate for all Asian American mothers in aggregate was significantly lower than the diagnosis rate in non-Hispanic White mothers. Moreover, of the six Asian American subgroups, PPD diagnosis rates for Asian Indian, Chinese, and Filipino mothers were significantly lower than non-Hispanic White mothers. In multivariate analyses, race/ethnicity, age, and cesarean were significant predictors of PPD. In this insured population, PPD diagnosis rates were lower among Asian Americans, with variability in rates across the individual Asian American subgroups. It is unclear whether these lower rates are due to underreporting, underdiagnosis, or underutilization of mental health care in this setting. © 2012 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.

Association of intimate partner violence and health-care provider-identified obesity.

PubMed

Davies, Rhian; Lehman, Erik; Perry, Amanda; McCall-Hosenfeld, Jennifer S

2016-07-01

The association of physical and nonphysical intimate partner violence (IPV) with obesity was examined. Women (N = 1,179) were surveyed regarding demographics, obesity, and IPV exposure using humiliate-afraid-rape-kick (HARK), an IPV screening tool. A three-level lifetime IPV exposure variable measured physical, nonphysical or no IPV. Health-care provider-identified obesity was defined if participants were told by a medical provider within the past 5 years that they were obese. Bivariate analyses examined obesity by IPV and demographics. Multivariable logistic regression assessed odds of obesity by IPV type, adjusting for age, race/ethnicity, education, and marital status. Among participants, 44% reported lifetime IPV (25% physical, 19% nonphysical), and 24% reported health-care provider-identified obesity. In unadjusted analyses, obesity was more prevalent among women exposed to physical IPV (30%) and nonphysical IPV (27%), compared to women without IPV (20%, p = .002). In multivariable models, women reporting physical IPV had 1.67 times greater odds of obesity (95% confidence interval [CI] 1.20, 2.33), and women reporting nonphysical IPV had 1.46 times greater odds of obesity (95% CI 1.01, 2.10), compared to women reporting no exposure. This study extends prior data by showing, not only an association between physical IPV and obesity, but also an association between obesity and nonphysical IPV.

Obesity Increases Operative Time in Children Undergoing Laparoscopic Cholecystectomy.

PubMed

Pandian, T K; Ubl, Daniel S; Habermann, Elizabeth B; Moir, Christopher R; Ishitani, Michael B

2017-03-01

Few studies have assessed the impact of obesity on laparoscopic cholecystectomy (LC) in pediatric patients. Children who underwent LC were identified from the 2012 to 2013 American College of Surgeons' National Surgical Quality Improvement Program Pediatrics data. Patient characteristics, operative details, and outcomes were compared. Multivariable logistic regression was utilized to identify predictors of increased operative time (OT) and duration of anesthesia (DOAn). In total, 1757 patients were identified. Due to low rates of obesity in children <9 years old, analyses were limited to those 9-17 (n = 1611, 43% obese). Among obese children, 80.6% were girls. A higher proportion of obese patients had diabetes (3.0% versus 1.0%, P < .01) and contaminated or dirty/infected wounds (15.1% versus 9.4%, P < .01). Complication rates were low. The most frequent indications for surgery were cholelithiasis/biliary colic (34.3%), chronic cholecystitis (26.9%), and biliary dyskinesia (18.2%). On multivariable analysis, obesity was an independent predictor of OT >90 (odds ratio [OR] 2.02; 95% confidence interval [95% CI] 1.55-2.63), and DOAn >140 minutes (OR 1.86; 95% CI 1.42-2.43). Obesity is an independent risk factor for increased OT in children undergoing LC. Pediatric surgeons and anesthesiologists should be prepared for the technical and physiological challenges that obesity may pose in this patient population.

Multivariate outcome prediction in traumatic brain injury with focus on laboratory values.

PubMed

Nelson, David W; Rudehill, Anders; MacCallum, Robert M; Holst, Anders; Wanecek, Michael; Weitzberg, Eddie; Bellander, Bo-Michael

2012-11-20

Traumatic brain injury (TBI) is a major cause of morbidity and mortality. Identifying factors relevant to outcome can provide a better understanding of TBI pathophysiology, in addition to aiding prognostication. Many common laboratory variables have been related to outcome but may not be independent predictors in a multivariate setting. In this study, 757 patients were identified in the Karolinska TBI database who had retrievable early laboratory variables. These were analyzed towards a dichotomized Glasgow Outcome Scale (GOS) with logistic regression and relevance vector machines, a non-linear machine learning method, univariately and controlled for the known important predictors in TBI outcome: age, Glasgow Coma Score (GCS), pupil response, and computed tomography (CT) score. Accuracy was assessed with Nagelkerke's pseudo R². Of the 18 investigated laboratory variables, 15 were found significant (p<0.05) towards outcome in univariate analyses. In contrast, when adjusting for other predictors, few remained significant. Creatinine was found an independent predictor of TBI outcome. Glucose, albumin, and osmolarity levels were also identified as predictors, depending on analysis method. A worse outcome related to increasing osmolarity may warrant further study. Importantly, hemoglobin was not found significant when adjusted for post-resuscitation GCS as opposed to an admission GCS, and timing of GCS can thus have a major impact on conclusions. In total, laboratory variables added an additional 1.3-4.4% to pseudo R².

Prevalence of difficult venous access and associated risk factors in highly complex hospitalised patients.

PubMed

Armenteros-Yeguas, Victoria; Gárate-Echenique, Lucía; Tomás-López, Maria Aranzazu; Cristóbal-Domínguez, Estíbaliz; Moreno-de Gusmão, Breno; Miranda-Serrano, Erika; Moraza-Dulanto, Maria Inmaculada

2017-12-01

To estimate the prevalence of difficult venous access in complex patients with multimorbidity and to identify associated risk factors. In highly complex patients, factors like ageing, the need for frequent use of irritant medication and multiple venous catheterisations to complete treatment could contribute to exhaustion of venous access. A cross-sectional study was conducted. 'Highly complex' patients (n = 135) were recruited from March 2013-November 2013. The main study variable was the prevalence of difficult venous access, assessed using one of the following criteria: (1) a history of difficulties obtaining venous access based on more than two attempts to insert an intravenous line and (2) no visible or palpable veins. Other factors potentially associated with the risk of difficult access were also measured (age, gender and chronic illnesses). Univariate analysis was performed for each potential risk factor. Factors with p < 0·2 were then included in multivariable logistic regression analysis. Odds ratios were also calculated. The prevalence of difficult venous access was 59·3%. The univariate logistic regression analysis indicated that gender, a history of vascular access complications and osteoarticular disease were significantly associated with difficult venous access. The multivariable logistic regression showed that only gender was an independent risk factor and the odds ratios was 2·85. The prevalence of difficult venous access is high in this population. Gender (female) is the only independent risk factor associated with this. Previous history of several attempts at catheter insertion is an important criterion in the assessment of difficult venous access. The prevalence of difficult venous access in complex patients is 59·3%. Significant risk factors include being female and a history of complications related to vascular access. © 2017 John Wiley & Sons Ltd.

Intraoperative factors associated with delayed recovery of liver function after hepatectomy: analysis of 1969 living donors.

PubMed

Choi, S-S; Cho, S-S; Ha, T-Y; Hwang, S; Lee, S-G; Kim, Y-K

2016-02-01

The safety of healthy living donors who are undergoing hepatic resection is a primary concern. We aimed to identify intraoperative anaesthetic and surgical factors associated with delayed recovery of liver function after hepatectomy in living donors. We retrospectively analysed 1969 living donors who underwent hepatectomy for living donor liver transplantation. Delayed recovery of hepatic function was defined by increases in international normalised ratio of prothrombin time and concomitant hyperbilirubinaemia on or after post-operative day 5. Univariate and multivariate logistic regression analyses were performed to determine the factors associated with delayed recovery of hepatic function after living donor hepatectomy. Delayed recovery of liver function after donor hepatectomy was observed in 213 (10.8%) donors. Univariate logistic regression analysis showed that sevoflurane anaesthesia, synthetic colloid, donor age, body mass index, fatty change and remnant liver volume were significant factors for prediction of delayed recovery of hepatic function. Multivariate logistic regression analysis showed that independent factors significantly associated with delayed recovery of liver function after donor hepatectomy were sevoflurane anaesthesia (odds ratio = 3.514, P < 0.001), synthetic colloid (odds ratio = 1.045, P = 0.033), donor age (odds ratio = 0.970, P = 0.003), female gender (odds ratio = 1.512, P = 0.014) and remnant liver volume (odds ratio = 0.963, P < 0.001). Anaesthesia with sevoflurane was an independent factor in predicting delayed recovery of hepatic function after donor hepatectomy. Although synthetic colloid may be associated with delayed recovery of hepatic function after donor hepatectomy, further study is required. These results can provide useful information on perioperative management of living liver donors. © 2015 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

p53 predictive value for pT1-2 N0 disease at radical cystectomy.

PubMed

Shariat, Shahrokh F; Lotan, Yair; Karakiewicz, Pierre I; Ashfaq, Raheela; Isbarn, Hendrik; Fradet, Yves; Bastian, Patrick J; Nielsen, Matthew E; Capitanio, Umberto; Jeldres, Claudio; Montorsi, Francesco; Müller, Stefan C; Karam, Jose A; Heukamp, Lukas C; Netto, George; Lerner, Seth P; Sagalowsky, Arthur I; Cote, Richard J

2009-09-01

Approximately 15% to 30% of patients with pT1-2N0M0 urothelial carcinoma of the bladder experience disease progression despite radical cystectomy with curative intent. We determined whether p53 expression would improve the prediction of disease progression after radical cystectomy for pT1-2N0M0 UCB. In a multi-institutional retrospective cohort we identified 324 patients with pT1-2N0M0 urothelial carcinoma of the bladder who underwent radical cystectomy. Analysis focused on a testing cohort of 272 patients and an external validation of 52. Competing risks regression models were used to test the association of variables with cancer specific mortality after accounting for nonbladder cancer caused mortality. In the testing cohort 91 patients (33.5%) had altered p53 expression (p53alt). On multivariate competing risks regression analysis altered p53 achieved independent status for predicting disease recurrence and cancer specific mortality (each p <0.001). Adding p53 increased the accuracy of multivariate competing risks regression models predicting recurrence and cancer specific mortality by 5.7% (62.0% vs 67.7%) and 5.4% (61.6% vs 67.0%), respectively. Alterations in p53 represent a highly promising marker of disease recurrence and cancer specific mortality after radical cystectomy for urothelial carcinoma of the bladder. Analysis confirmed previous findings and showed that considering p53 can result in substantial accuracy gains relative to the use of standard predictors. The value and the level of the current evidence clearly exceed previous proof of the independent predictor status of p53 for predicting recurrence and cancer specific mortality.

A retrospective study: Multivariate logistic regression analysis of the outcomes after pressure sores reconstruction with fasciocutaneous, myocutaneous, and perforator flaps.

PubMed

Chiu, Yu-Jen; Liao, Wen-Chieh; Wang, Tien-Hsiang; Shih, Yu-Chung; Ma, Hsu; Lin, Chih-Hsun; Wu, Szu-Hsien; Perng, Cherng-Kang

2017-08-01

Despite significant advances in medical care and surgical techniques, pressure sore reconstruction is still prone to elevated rates of complication and recurrence. We conducted a retrospective study to investigate not only complication and recurrence rates following pressure sore reconstruction but also preoperative risk stratification. This study included 181 ulcers underwent flap operations between January 2002 and December 2013 were included in the study. We performed a multivariable logistic regression model, which offers a regression-based method accounting for the within-patient correlation of the success or failure of each flap. The overall complication and recurrence rates for all flaps were 46.4% and 16.0%, respectively, with a mean follow-up period of 55.4 ± 38.0 months. No statistically significant differences of complication and recurrence rates were observed among three different reconstruction methods. In subsequent analysis, albumin ≤3.0 g/dl and paraplegia were significantly associated with higher postoperative complication. The anatomic factor, ischial wound location, significantly trended toward the development of ulcer recurrence. In the fasciocutaneous group, paraplegia had significant correlation to higher complication and recurrence rates. In the musculocutaneous flap group, variables had no significant correlation to complication and recurrence rates. In the free-style perforator group, ischial wound location and malnourished status correlated with significantly higher complication rates; ischial wound location also correlated with significantly higher recurrence rate. Ultimately, our review of a noteworthy cohort with lengthy follow-up helped identify and confirm certain risk factors that can facilitate a more informed and thoughtful pre- and postoperative decision-making process for patients with pressure ulcers. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Suspicion of respiratory tract infection with multidrug-resistant Enterobacteriaceae: epidemiology and risk factors from a Paediatric Intensive Care Unit.

PubMed

Renk, Hanna; Stoll, Lenja; Neunhoeffer, Felix; Hölzl, Florian; Kumpf, Matthias; Hofbeck, Michael; Hartl, Dominik

2017-02-21

Multidrug-resistant (MDR) infections are a serious concern for children admitted to the Paediatric Intensive Care Unit (PICU). Tracheal colonization with MDR Enterobacteriaceae predisposes to respiratory infection, but underlying risk factors are poorly understood. This study aims to determine the incidence of children with suspected infection during mechanical ventilation and analyses risk factors for the finding of MDR Enterobacteriaceae in tracheal aspirates. A retrospective single-centre analysis of Enterobacteriaceae isolates from the lower respiratory tract of ventilated PICU patients from 2005 to 2014 was performed. Resistance status was determined and clinical records were reviewed for potential risk factors. A classification and regression tree (CRT) to predict risk factors for infection with MDR Enterobacteriaceae was employed. The model was validated by simple and multivariable logistic regression. One hundred sixty-seven Enterobacteriaceae isolates in 123 children were identified. The most frequent isolates were Enterobacter spp., Klebsiella spp. and E.coli. Among these, 116 (69%) isolates were susceptible and 51 (31%) were MDR. In the CRT analysis, antibiotic exposure for ≥ 7 days and presence of gastrointestinal comorbidity were the most relevant predictors for an MDR isolate. Antibiotic exposure for ≥ 7 days was confirmed as a significant risk factor for infection with MDR Enterobacteriaceae by a multivariable logistic regression model. This study shows that critically-ill children with tracheal Enterobacteriaceae infection are at risk of carrying MDR isolates. Prior use of antibiotics for ≥ 7 days significantly increased the risk of finding MDR organisms in ventilated PICU patients with suspected infection. Our results imply that early identification of patients at risk, rapid microbiological diagnostics and tailored antibiotic therapy are essential to improve management of critically ill children infected with Enterobacteriaceae.

Characteristics of aggression in a German psychiatric hospital and predictors of patients at risk.

PubMed

Ketelsen, R; Zechert, C; Driessen, M; Schulz, M

2007-02-01

This study investigated the aggressive behaviour of all mentally ill patients within a whole psychiatric hospital with a catchment area of 325 000 inhabitants over a 1-year period (i) to assess the 1-year prevalence and characteristics of aggressive episodes and index inpatients, and (ii) to identify predictors of patients at risk by a multivariate approach. Staff Observation of Aggression Scale was used to assess aggressive behaviour. Characteristics of index inpatients were compared with those of non-index inpatients. Logistic regression analysis was applied to identify risk factors. A total of 171 out of 2210 admitted patients (7.7%) exhibited 441 aggressive incidents (1.7 incidents per bed per year). Logistic regression analyses revealed as major risk factors of aggression: diagnoses (organic brain syndromes OR = 3.6, schizophrenia OR = 2.9), poor psychosocial living conditions (OR = 2.2), and critical behaviour leading to involuntary admission (OR = 3.3). Predictors of aggressive behaviour can be useful to identify inpatients at risk. Nevertheless, additional situational determinants have to be recognized. Training for professionals should include preventive and de-escalating strategies to reduce the incidence of aggressive behaviour in psychiatric hospitals. The application of de-escalating interventions prior to admission might be effective in preventing aggressive behaviour during inpatient treatment especially for patients with severe mental disorders.

Community-Based Management of Child Malnutrition in Zambia: HIV/AIDS Infection and Other Risk Factors on Child Survival.

PubMed

Moramarco, Stefania; Amerio, Giulia; Ciarlantini, Clarice; Chipoma, Jean Kasengele; Simpungwe, Matilda Kakungu; Nielsen-Saines, Karin; Palombi, Leonardo; Buonomo, Ersilia

2016-07-01

(1) BACKGROUND: Supplementary feeding programs (SFPs) are effective in the community-based treatment of moderate acute malnutrition (MAM) and prevention of severe acute malnutrition (SAM); (2) METHODS: A retrospective study was conducted on a sample of 1266 Zambian malnourished children assisted from 2012 to 2014 in the Rainbow Project SFPs. Nutritional status was evaluated according to WHO/Unicef methodology. We performed univariate and multivariate Cox proportional risk regression to identify the main predictors of mortality. In addition, a time-to event analysis was performed to identify predictors of failure and time to cure events; (3) RESULTS: The analysis included 858 malnourished children (19 months ± 9.4; 49.9% males). Program outcomes met international standards with a better performance for MAM compared to SAM. Cox regression identified SAM (3.8; 2.1-6.8), HIV infection (3.1; 1.7-5.5), and WAZ <-3 (3.1; 1.6-5.7) as predictors of death. Time to event showed 80% of children recovered by SAM/MAM at 24 weeks. (4) CONCLUSIONS: Preventing deterioration of malnutrition, coupled to early detection of HIV/AIDS with adequate antiretroviral treatment, and extending the duration of feeding supplementation, could be crucial elements for ensuring full recovery and improve child survival in malnourished Zambian children.

Combinations of Multiple Neuroimaging Markers using Logistic Regression for Auxiliary Diagnosis of Alzheimer Disease and Mild Cognitive Impairment.

PubMed

Mao, Nini; Liu, Yunting; Chen, Kewei; Yao, Li; Wu, Xia

2018-06-05

Multiple neuroimaging modalities have been developed providing various aspects of information on the human brain. Used together and properly, these complementary multimodal neuroimaging data integrate multisource information which can facilitate a diagnosis and improve the diagnostic accuracy. In this study, 3 types of brain imaging data (sMRI, FDG-PET, and florbetapir-PET) were fused in the hope to improve diagnostic accuracy, and multivariate methods (logistic regression) were applied to these trimodal neuroimaging indices. Then, the receiver-operating characteristic (ROC) method was used to analyze the outcomes of the logistic classifier, with either each index, multiples from each modality, or all indices from all 3 modalities, to investigate their differential abilities to identify the disease. With increasing numbers of indices within each modality and across modalities, the accuracy of identifying Alzheimer disease (AD) increases to varying degrees. For example, the area under the ROC curve is above 0.98 when all the indices from the 3 imaging data types are combined. Using a combination of different indices, the results confirmed the initial hypothesis that different biomarkers were potentially complementary, and thus the conjoint analysis of multiple information from multiple sources would improve the capability to identify diseases such as AD and mild cognitive impairment. © 2018 S. Karger AG, Basel.

Association between Nurse Staffing and In-Hospital Bone Fractures: A Retrospective Cohort Study.

PubMed

Morita, Kojiro; Matsui, Hiroki; Fushimi, Kiyohide; Yasunaga, Hideo

2017-06-01

To determine if sufficient nurse staffing reduced in-hospital fractures in acute care hospitals. The Japanese Diagnosis Procedure Combination inpatient (DPC) database from July 2010 to March 2014 linked with the Surveys for Medical Institutions. We conducted a retrospective cohort study to examine the association of inpatient nurse-to-occupied bed ratio (NBR) with in-hospital fractures. Multivariable logistic regression with generalized estimating equations was performed, adjusting for patient characteristics and hospital characteristics. We identified 770,373 patients aged 50 years or older who underwent planned major surgery for some forms of cancer or cardiovascular diseases. We used ICD-10 codes and postoperative procedure codes to identify patients with in-hospital fractures. Hospital characteristics were obtained from the "Survey of Medical Institutions and Hospital Report" and "Annual Report for Functions of Medical Institutions." Overall, 662 (0.09 percent) in-hospital fractures were identified. Logistic regression analysis showed that the proportion of in-hospital fractures in the group with the highest NBR was significantly lower than that in the group with the lowest NBR (adjusted odd ratios, 0.67; 95 percent confidence interval, 0.44-0.99; p = .048). Sufficient nurse staffing may be important to reduce postsurgical in-hospital fractures in acute care hospitals. © Health Research and Educational Trust.

[Regression analysis to select native-like structures from decoys of antigen-antibody docking].

PubMed

Chen, Zhengshan; Chi, Xiangyang; Fan, Pengfei; Zhang, Guanying; Wang, Meirong; Yu, Changming; Chen, Wei

2018-06-25

Given the increasing exploitation of antibodies in different contexts such as molecular diagnostics and therapeutics, it would be beneficial to unravel properties of antigen-antibody interaction with modeling of computational protein-protein docking, especially, in the absence of a cocrystal structure. However, obtaining a native-like antigen-antibody structure remains challenging due in part to failing to reliably discriminate accurate from inaccurate structures among tens of thousands of decoys after computational docking with existing scoring function. We hypothesized that some important physicochemical and energetic features could be used to describe antigen-antibody interfaces and identify native-like antigen-antibody structure. We prepared a dataset, a subset of Protein-Protein Docking Benchmark Version 4.0, comprising 37 nonredundant 3D structures of antigen-antibody complexes, and used it to train and test multivariate logistic regression equation which took several important physicochemical and energetic features of decoys as dependent variables. Our results indicate that the ability to identify native-like structures of our method is superior to ZRANK and ZDOCK score for the subset of antigen-antibody complexes. And then, we use our method in workflow of predicting epitope of anti-Ebola glycoprotein monoclonal antibody-4G7 and identify three accurate residues in its epitope.

"Take the Volume Pledge" may result in disparity in access to care.

PubMed

Blanco, Barbara A; Kothari, Anai N; Blackwell, Robert H; Brownlee, Sarah A; Yau, Ryan M; Attisha, John P; Ezure, Yoshiki; Pappas, Sam; Kuo, Paul C; Abood, Gerard J

2017-03-01

"Take the Volume Pledge" proposes restricting pancreatectomies to hospitals that perform ≥20 per year. Our purpose was to identify those factors that characterize patients at risk for loss of access to pancreatic cancer care with enforcement of volume standards. Using the Healthcare Cost and Utilization Project State Inpatient Database from Florida, we identified patients who underwent pancreatectomy for pancreatic malignancy from 2007-2011. American Hospital Association and United States Census Bureau data were linked to patient-level data. High-volume hospitals were defined as performing ≥20 pancreatic resections per year. Univariable and multivariable statistics compared patient characteristics and utilization of high-volume hospitals. Classification and Regression Tree modeling was used to predict patients at risk for losing access to care. Our study included 1,663 patients. Five high-volume hospitals were identified, and they treated 1,056 (63.5%) patients. Patients residing far from high-volume hospitals, in areas with the highest population density, non-Caucasian ethnicity, and greater income had decreased odds of obtaining care at high-volume hospitals. Using these factors, we developed a Classification and Regression Tree-based predictive tool to identify these patients. Implementation of "Take the Volume Pledge" is an important step toward improving pancreatectomy outcomes; however, policymakers must consider the potential impact on limiting access and possible health disparities that may arise. Copyright © 2016 Elsevier Inc. All rights reserved.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert M.

2013-01-01

A new regression model search algorithm was developed that may be applied to both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The algorithm is a simplified version of a more complex algorithm that was originally developed for the NASA Ames Balance Calibration Laboratory. The new algorithm performs regression model term reduction to prevent overfitting of data. It has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a regression model search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression model. Therefore, the simplified algorithm is not intended to replace the original algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new search algorithm.

Performances on the CogState and Standard Neuropsychological Batteries Among HIV Patients Without Dementia

PubMed Central

Overton, Edgar Turner; Kauwe, John S.K.; Paul, Rob; Tashima, Karen; Tate, David F.; Patel, Pragna; Carpenter, Chuck; Patty, David; Brooks, John T.; Clifford, David B

2013-01-01

HIV-associated neurocognitive disorders (HAND) remain prevalent but challenging to diagnose particularly among non-demented individuals. To determine whether a brief computerized battery correlates with formal neurocognitive testing, we identified 46 HIV-infected persons who had undergone both formal neurocognitive testing and a brief computerized battery. Simple detection tests correlated best with formal neuropsychological testing. By multivariable regression model, 53% of the variance in the composite Global Deficit Score was accounted for by elements from the brief computerized tool (p<0.01). These data confirm previous correlation data with the computerized battery, yet illustrate remaining challenges for neurocognitive screening. PMID:21877204

Impact of immunotherapy among patients with melanoma brain metastases managed with radiotherapy.

PubMed

Stokes, William A; Binder, David C; Jones, Bernard L; Oweida, Ayman J; Liu, Arthur K; Rusthoven, Chad G; Karam, Sana D

2017-12-15

Patients with melanoma brain metastases (MBM) have been excluded from trials evaluating immunotherapy in melanoma. As such, immunotherapy's role in MBM is poorly understood, particularly in combination with radiotherapy. The National Cancer Database was queried for patients with MBM receiving brain radiotherapy. They were classified according to immunotherapy receipt. Multivariate Cox regression was performed to identify factors associated with survival. Among 1287 patients, 185 received immunotherapy. Factors associated with improved survival included younger age, academic facility, lower extracranial disease burden, stereotactic radiotherapy, chemotherapy, and immunotherapy. Adding immunotherapy to radiotherapy for MBM is associated with improved survival. Copyright © 2017 Elsevier B.V. All rights reserved.

Carbon financial markets: A time-frequency analysis of CO2 prices

NASA Astrophysics Data System (ADS)

Sousa, Rita; Aguiar-Conraria, Luís; Soares, Maria Joana

2014-11-01

We characterize the interrelation of CO2 prices with energy prices (electricity, gas and coal), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.

A spline-based regression parameter set for creating customized DARTEL MRI brain templates from infancy to old age.

PubMed

Wilke, Marko

2018-02-01

This dataset contains the regression parameters derived by analyzing segmented brain MRI images (gray matter and white matter) from a large population of healthy subjects, using a multivariate adaptive regression splines approach. A total of 1919 MRI datasets ranging in age from 1-75 years from four publicly available datasets (NIH, C-MIND, fCONN, and IXI) were segmented using the CAT12 segmentation framework, writing out gray matter and white matter images normalized using an affine-only spatial normalization approach. These images were then subjected to a six-step DARTEL procedure, employing an iterative non-linear registration approach and yielding increasingly crisp intermediate images. The resulting six datasets per tissue class were then analyzed using multivariate adaptive regression splines, using the CerebroMatic toolbox. This approach allows for flexibly modelling smoothly varying trajectories while taking into account demographic (age, gender) as well as technical (field strength, data quality) predictors. The resulting regression parameters described here can be used to generate matched DARTEL or SHOOT templates for a given population under study, from infancy to old age. The dataset and the algorithm used to generate it are publicly available at https://irc.cchmc.org/software/cerebromatic.php.

[Influences of environmental factors and interaction of several chemokines gene-environmental on systemic lupus erythematosus].

PubMed

Ye, Dong-qing; Hu, Yi-song; Li, Xiang-pei; Huang, Fen; Yang, Shi-gui; Hao, Jia-hu; Yin, Jing; Zhang, Guo-qing; Liu, Hui-hui

2004-11-01

To explore the impact of environmental factors, daily lifestyle, psycho-social factors and the interactions between environmental factors and chemokines genes on systemic lupus erythematosus (SLE). Case-control study was carried out and environmental factors for SLE were analyzed by univariate and multivariate unconditional logistic regression. Interactions between environmental factors and chemokines polymorphism contributing to systemic lupus erythematosus were also analyzed by logistic regression model. There were nineteen factors associated with SLE when univariate unconditional logistic regression was used. However, when multivariate unconditional logistic regression was used, only five factors showed having impacts on the disease, in which drinking well water (OR=0.099) was protective factor for SLE, and multiple drug allergy (OR=8.174), over-exposure to sunshine (OR=18.339), taking antibiotics (OR=9.630) and oral contraceptives were risk factors for SLE. When unconditional logistic regression model was used, results showed that there was interaction between eating irritable food and -2518MCP-1G/G genotype (OR=4.387). No interaction between environmental factors was found that contributing to SLE in this study. Many environmental factors were related to SLE, and there was an interaction between -2518MCP-1G/G genotype and eating irritable food.

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data.

PubMed

Abram, Samantha V; Helwig, Nathaniel E; Moodie, Craig A; DeYoung, Colin G; MacDonald, Angus W; Waller, Niels G

2016-01-01

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks.

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data

PubMed Central

Abram, Samantha V.; Helwig, Nathaniel E.; Moodie, Craig A.; DeYoung, Colin G.; MacDonald, Angus W.; Waller, Niels G.

2016-01-01

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks. PMID:27516732

Behaviour patterns preceding a railway suicide: Explorative study of German Federal Police officers' experiences

PubMed Central

2011-01-01

Background Constant high-level numbers of railway suicides indicate that prevention strategies against railway suicides are urgently needed. The main question of the present study was whether pre-crash railway suicide behaviour can be identified, using German Federal Police officers experience with suicidal events in railway related environments. Methods To collect information on pre-crash railway suicide behaviour, a questionnaire was used and made available on the German Federal Police intranet. A total of 202 subjects (mean age: 41 years, sex: 84.9% male) were included in the analysis. Multivariate logistic regression analyses were performed to predict the prevention of suicide (first model) or demand for counselling (second model) as outcomes. Sex, age, years of service, number of experienced suicides, suicides personally observed, information on suicides obtained from witnesses and finally either counselling/debriefing (first model) or whether officers had prevented a suicide (second model) were used as predictors. Results A considerable proportion of police officers reported behavioural patterns preceding a suicide. Half of them observed the dropping or leaving behind of personal belongings or the avoidance of eye contact, more than a third erratic gesture, mimic or movement. Erratic communication patterns and general confusion were each reported by about one quarter. One fifth indicated the influence of alcohol. Less frequently observed behaviour was aimlessly wandering (14.3%) and out of the ordinary clothing (4%). About one third of all railway suicide victims committed suicide in stations. Of those, 70% had chosen an eminent spot. The multivariate logistic regression model using prevented suicides as the outcome identified the number of suicides experienced, counselling/debriefing and having personally observed a suicide as variables with significant impact. The model using counselling/debriefing as the outcome identified age and having prevented a suicide as variables with a significant association. Conclusions Our results provide evidence that railway suicides are preceded by identifiable behavioural patterns. This emphasizes the importance of educational efforts, taking into account the knowledge and skills of experienced police officers. PMID:21816069

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

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

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

Predictive equations for the estimation of body size in seals and sea lions (Carnivora: Pinnipedia)

PubMed Central

Churchill, Morgan; Clementz, Mark T; Kohno, Naoki

2014-01-01

Body size plays an important role in pinniped ecology and life history. However, body size data is often absent for historical, archaeological, and fossil specimens. To estimate the body size of pinnipeds (seals, sea lions, and walruses) for today and the past, we used 14 commonly preserved cranial measurements to develop sets of single variable and multivariate predictive equations for pinniped body mass and total length. Principal components analysis (PCA) was used to test whether separate family specific regressions were more appropriate than single predictive equations for Pinnipedia. The influence of phylogeny was tested with phylogenetic independent contrasts (PIC). The accuracy of these regressions was then assessed using a combination of coefficient of determination, percent prediction error, and standard error of estimation. Three different methods of multivariate analysis were examined: bidirectional stepwise model selection using Akaike information criteria; all-subsets model selection using Bayesian information criteria (BIC); and partial least squares regression. The PCA showed clear discrimination between Otariidae (fur seals and sea lions) and Phocidae (earless seals) for the 14 measurements, indicating the need for family-specific regression equations. The PIC analysis found that phylogeny had a minor influence on relationship between morphological variables and body size. The regressions for total length were more accurate than those for body mass, and equations specific to Otariidae were more accurate than those for Phocidae. Of the three multivariate methods, the all-subsets approach required the fewest number of variables to estimate body size accurately. We then used the single variable predictive equations and the all-subsets approach to estimate the body size of two recently extinct pinniped taxa, the Caribbean monk seal (Monachus tropicalis) and the Japanese sea lion (Zalophus japonicus). Body size estimates using single variable regressions generally under or over-estimated body size; however, the all-subset regression produced body size estimates that were close to historically recorded body length for these two species. This indicates that the all-subset regression equations developed in this study can estimate body size accurately. PMID:24916814

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

PubMed

Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P; Gonzalez-Zacarias, Clio; Zhao, Lu; D'Arcy, Mike; Kesselman, Carl; Herting, Megan M; Dinov, Ivo D; Toga, Arthur W; Clark, Kristi A

2018-05-15

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases). Copyright © 2018 Elsevier Inc. All rights reserved.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

PubMed Central

Pei, Ling-Ling; Li, Qin

2018-01-01

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. PMID:29517985

[Correlation between gaseous exchange rate, body temperature, and mitochondrial protein content in the liver of mice].

PubMed

Muradian, Kh K; Utko, N O; Mozzhukhina, T H; Pishel', I M; Litoshenko, O Ia; Bezrukov, V V; Fraĭfel'd, V E

2002-01-01

Correlative and regressive relations between the gaseous exchange, thermoregulation and mitochondrial protein content were analyzed by two- and three-dimensional statistics in mice. It has been shown that the pair wise linear methods of analysis did not reveal any significant correlation between the parameters under exploration. However, it became evident at three-dimensional and non-linear plotting for which the coefficients of multivariable correlation reached and even exceeded 0.7-0.8. The calculations based on partial differentiation of the multivariable regression equations allow to conclude that at certain values of VO2, VCO2 and body temperature negative relations between the systems of gaseous exchange and thermoregulation become dominating.

A multiplexed analysis approach identifies new association of inflammatory proteins in patients with overactive bladder

PubMed Central

Ma, Emily; Vetter, Joel; Bliss, Laura; Lai, H. Henry; Mysorekar, Indira U.

2016-01-01

Overactive bladder (OAB) is a common debilitating bladder condition with unknown etiology and limited diagnostic modalities. Here, we explored a novel high-throughput and unbiased multiplex approach with cellular and molecular components in a well-characterized patient cohort to identify biomarkers that could be reliably used to distinguish OAB from controls or provide insights into underlying etiology. As a secondary analysis, we determined whether this method could discriminate between OAB and other chronic bladder conditions. We analyzed plasma samples from healthy volunteers (n = 19) and patients diagnosed with OAB, interstitial cystitis/bladder pain syndrome (IC/BPS), or urinary tract infections (UTI; n = 51) for proinflammatory, chemokine, cytokine, angiogenesis, and vascular injury factors using Meso Scale Discovery (MSD) analysis and urinary cytological analysis. Wilcoxon rank-sum tests were used to perform univariate and multivariate comparisons between patient groups (controls, OAB, IC/BPS, and UTI). Multivariate logistic regression models were fit for each MSD analyte on 1) OAB patients and controls, 2) OAB and IC/BPS patients, and 3) OAB and UTI patients. Age, race, and sex were included as independent variables in all multivariate analysis. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic potential of a given analyte. Our findings demonstrate that five analytes, i.e., interleukin 4, TNF-α, macrophage inflammatory protein-1β, serum amyloid A, and Tie2 can reliably differentiate OAB relative to controls and can be used to distinguish OAB from the other conditions. Together, our pilot study suggests a molecular imbalance in inflammatory proteins may contribute to OAB pathogenesis. PMID:27029431

Factors associated with seasonal influenza vaccination in pregnant women.

PubMed

Henninger, Michelle L; Irving, Stephanie A; Thompson, Mark; Avalos, Lyndsay Ammon; Ball, Sarah W; Shifflett, Pat; Naleway, Allison L

2015-05-01

This observational study followed a cohort of pregnant women during the 2010-2011 influenza season to determine factors associated with vaccination. Participants were 1105 pregnant women who completed a survey assessing health beliefs related to vaccination upon enrollment and were then followed to determine vaccination status by the end of the 2010-2011 influenza season. We conducted univariate and multivariate analyses to explore factors associated with vaccination status and a factor analysis of survey items to identify health beliefs associated with vaccination. Sixty-three percent (n=701) of the participants were vaccinated. In the univariate analyses, multiple factors were associated with vaccination status, including maternal age, race, marital status, educational level, and gravidity. Factor analysis identified two health belief factors associated with vaccination: participant's positive views (factor 1) and negative views (factor 2) of influenza vaccination. In a multivariate logistic regression model, factor 1 was associated with increased likelihood of vaccination (adjusted odds ratio [aOR]=2.18; 95% confidence interval [CI]=1.72-2.78), whereas factor 2 was associated with decreased likelihood of vaccination (aOR=0.36; 95% CI=0.28-0.46). After controlling for the two health belief factors in multivariate analyses, demographic factors significant in univariate analyses were no longer significant. Women who received a provider recommendation were about three times more likely to be vaccinated (aOR=3.14; 95% CI=1.99-4.96). Pregnant women's health beliefs about vaccination appear to be more important than demographic and maternal factors previously associated with vaccination status. Provider recommendation remains one of the most critical factors influencing vaccination during pregnancy.

Factors Associated with the Emergence of Highly Pathogenic Avian Influenza A (H5N1) Poultry Outbreaks in China: Evidence from an Epidemiological Investigation in Ningxia, 2012.

PubMed

Liu, H; Zhou, X; Zhao, Y; Zheng, D; Wang, J; Wang, X; Castellan, D; Huang, B; Wang, Z; Soares Magalhães, R J

2017-06-01

In April 2012, highly pathogenic avian influenza virus of the H5N1 subtype (HPAIV H5N1) emerged in poultry layers in Ningxia. A retrospective case-control study was conducted to identify possible risk factors associated with the emergence of H5N1 infection and describe and quantify the spatial variation in H5N1 infection. A multivariable logistic regression model was used to identify risk factors significantly associated with the presence of infection; residual spatial variation in H5N1 risk unaccounted by the factors included in the multivariable model was investigated using a semivariogram. Our results indicate that HPAIV H5N1-infected farms were three times more likely to improperly dispose farm waste [adjusted OR = 0.37; 95% CI: 0.12-0.82] and five times more likely to have had visitors in their farm within the past month [adjusted OR = 5.47; 95% CI: 1.97-15.64] compared to H5N1-non-infected farms. The variables included in the final multivariable model accounted only 20% for the spatial clustering of H5N1 infection. The average size of a H5N1 cluster was 660 m. Bio-exclusion practices should be strengthened on poultry farms to prevent further emergence of H5N1 infection. For future poultry depopulation, operations should consider H5N1 disease clusters to be as large as 700 m. © 2015 Blackwell Verlag GmbH.

Correlates of Incident Cognitive Impairment in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study

PubMed Central

Gillett, Sarah R.; Thacker, Evan L.; Letter, Abraham J.; McClure, Leslie A.; Wadley, Virginia G.; Unverzagt, Frederick W.; Kissela, Brett M.; Kennedy, Richard E.; Glasser, Stephen P.; Levine, Deborah A.; Cushman, Mary

2015-01-01

Objective To identify approximately 500 cases of incident cognitive impairment (ICI) in a large, national sample adapting an existing cognitive test-based case definition and to examine relationships of vascular risk factors with ICI. Method Participants were from the REGARDS study, a national sample of 30,239 African-American and white Americans. Participants included in this analysis had normal cognitive screening and no history of stroke at baseline, and at least one follow-up cognitive assessment with a three test battery (TTB). Regression-based norms were applied to TTB scores to identify cases of ICI. Logistic regression was used to model associations with baseline vascular risk factors. Results We identified 495 participants with ICI out of 17,630 eligible participants. In multivariable modeling, income (OR 1.83 CI 1.27,2.62), stroke belt residence (OR 1.45 CI 1.18,1.78), history of transient ischemic attack (OR 1.90 CI 1.29,2.81), coronary artery disease(OR 1.32 CI 1.02,1.70), diabetes (OR 1.48 CI 1.17,1.87), obesity (OR 1.40 CI 1.05,1.86), and incident stroke (OR 2.73 CI 1.52,4.90) were associated with ICI. Conclusions We adapted a previously validated cognitive test-based case definition to identify cases of ICI. Many previously identified risk factors were associated with ICI, supporting the criterion-related validity of our definition. PMID:25978342

A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies

Treesearch

Xuan Chi; Barry Goodwin

2012-01-01

Spatial and temporal relationships among agricultural prices have been an important topic of applied research for many years. Such research is used to investigate the performance of markets and to examine linkages up and down the marketing chain. This research has empirically evaluated price linkages by using correlation and regression models and, later, linear and...

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

The analyses of risk factors for COPD in the Li ethnic group in Hainan, People's Republic of China.

PubMed

Ding, Yipeng; Xu, Junxu; Yao, Jinjian; Chen, Yu; He, Ping; Ouyang, Yanhong; Niu, Huan; Tian, Zhongjie; Sun, Pei

2015-01-01

To study the risk factors for chronic obstructive pulmonary disease (COPD) in Li population in Hainan province, People's Republic of China. Li people above 40 years of age from Hainan were chosen by stratified random cluster sampling between 2012 and 2014. All participants were interviewed with a home-visiting questionnaire, and spirometry was performed on all eligible participants. Patients with airflow limitation (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] <0.70) were further examined by postbronchodilator spirometry, and those with a postbronchodilator FEV1/FVC <0.70 was diagnosed with COPD. The information of physical condition and history, smoking intensity, smoking duration, second-hand smoking, education, job category, monthly household income, working years, residential environment, primary fuel for cooking and heating (biomass fuel including wood, crop residues, dung, and charcoal, or modern fuel such as natural gas, liquefied petroleum gas, electricity, and solar energy), ventilated kitchen, heating methods, air pollution, recurrent respiratory infections, family history of respiratory diseases, cough incentives, and allergies of COPD and non-COPD subjects was analyzed by univariate and multivariate logistic regression models to identify correlated risk factors for COPD. Out of the 5,463 Li participants, a total of 277 COPD cases were identified by spirometry, and 307 healthy subjects were randomly selected as controls. Univariate logistic regression analyses showed that older people (65 years and above), low body mass index (BMI), biomass smoke, 11-20 and >20 cigarettes/day, smoking for 40 years or more, second-hand smoking, recurrent respiratory infections, and induced cough were risk factors for COPD, whereas high BMI, high education level, and presence of ventilated kitchen were protective factors. Subsequent multivariate logistic regression model further demonstrated that aging, low BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory tract infections were high-risk factors for COPD in the Li population. The incidence of COPD has a strong correlation with age, BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory infections, suggesting they were high-risk factors for COPD in Li population.

The analyses of risk factors for COPD in the Li ethnic group in Hainan, People’s Republic of China

PubMed Central

Ding, Yipeng; Xu, Junxu; Yao, Jinjian; Chen, Yu; He, Ping; Ouyang, Yanhong; Niu, Huan; Tian, Zhongjie; Sun, Pei

2015-01-01

Objective To study the risk factors for chronic obstructive pulmonary disease (COPD) in Li population in Hainan province, People’s Republic of China. Methods Li people above 40 years of age from Hainan were chosen by stratified random cluster sampling between 2012 and 2014. All participants were interviewed with a home-visiting questionnaire, and spirometry was performed on all eligible participants. Patients with airflow limitation (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] <0.70) were further examined by postbronchodilator spirometry, and those with a postbronchodilator FEV1/FVC <0.70 was diagnosed with COPD. The information of physical condition and history, smoking intensity, smoking duration, second-hand smoking, education, job category, monthly household income, working years, residential environment, primary fuel for cooking and heating (biomass fuel including wood, crop residues, dung, and charcoal, or modern fuel such as natural gas, liquefied petroleum gas, electricity, and solar energy), ventilated kitchen, heating methods, air pollution, recurrent respiratory infections, family history of respiratory diseases, cough incentives, and allergies of COPD and non-COPD subjects was analyzed by univariate and multivariate logistic regression models to identify correlated risk factors for COPD. Results Out of the 5,463 Li participants, a total of 277 COPD cases were identified by spirometry, and 307 healthy subjects were randomly selected as controls. Univariate logistic regression analyses showed that older people (65 years and above), low body mass index (BMI), biomass smoke, 11–20 and >20 cigarettes/day, smoking for 40 years or more, second-hand smoking, recurrent respiratory infections, and induced cough were risk factors for COPD, whereas high BMI, high education level, and presence of ventilated kitchen were protective factors. Subsequent multivariate logistic regression model further demonstrated that aging, low BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory tract infections were high-risk factors for COPD in the Li population. Conclusion The incidence of COPD has a strong correlation with age, BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory infections, suggesting they were high-risk factors for COPD in Li population. PMID:26664107

Effect of latitude on the rate of change in incidence of Lyme disease in the United States

PubMed Central

Tuite, Ashleigh R.; Greer, Amy L.

2013-01-01

Background Tick-borne illnesses represent an important class of emerging zoonoses, with climate change projected to increase the geographic range within which tick-borne zoonoses might become endemic. We evaluated the impact of latitude on the rate of change in the incidence of Lyme disease in the United States, using publicly available data. Methods We estimated state-level year-on-year incidence rate ratios (IRRs) for Lyme disease for the period 1993 to 2007 using Poisson regression methods. We evaluated between-state heterogeneity in IRRs using a random-effects meta-analytic approach. We identified state-level characteristics associated with increasing incidence using random-effects meta-regression. Results The incidence of Lyme disease in the US increased by about 80% between 1993 and 2007 (IRR per year 1.049, 95% CI [confidence interval] 1.048 to 1.050). There was marked between-state heterogeneity in the average incidence of Lyme disease, ranging from 0.008 per 100 000 person-years in Colorado to 75 per 100 000 in Connecticut, and significant between-state heterogeneity in temporal trends (p < 0.001). In multivariable meta-regression models, increasing incidence showed a linear association with state latitude and population density. These 2 factors explained 27% of the between-state variation in IRRs. No independent association was identified for other state-level characteristics. Interpretation Lyme disease incidence increased in the US as a whole during the study period, but the changes were not uniform. Marked increases were identified in northern-most states, whereas southern states experienced stable or declining rates of Lyme disease. PMID:25077101

Intake of Fiber and Nuts during Adolescence and Incidence of Proliferative Benign Breast Disease

PubMed Central

Su, Xuefen; Tamimi, Rulla M.; Collins, Laura C.; Baer, Heather J.; Cho, Eunyoung; Sampson, Laura; Willett, Walter C.; Schnitt, Stuart J.; Connolly, James L.; Rosner, Bernard A.; Colditz, Graham A.

2011-01-01

Objective We examined the association between adolescent fiber intake and proliferative BBD, a marker of increased breast cancer risk, in the Nurses’ Health Study II. Methods Among 29,480 women who completed a high school diet questionnaire in 1998, 682 proliferative BBD cases were identified and confirmed by centralized pathology review between 1991 and 2001. Multivariate-adjusted Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results Women in the highest quintile of adolescent fiber intake had a 25% lower risk of proliferative BBD (multivariate HR (95% CI): 0.75 (0.59, 0.96), p-trend = 0.01) than women in the lowest quintile. High school intake of nuts and apples was also related to significantly reduced BBD risk. Women consuming ≥2 servings of nuts/week had a 36% lower risk (multivariate HR (95% CI): 0.64 (0.48, 0.85), p-trend < 0.01) than women consuming <1 serving/month. Results were essentially the same when the analysis was restricted to prospective cases (n = 142) diagnosed after return of the high school diet questionnaire. Conclusions These findings support the hypothesis that dietary intake of fiber and nuts during adolescence influence subsequent risk of breast disease and may suggest a viable means for breast cancer prevention. PMID:20229245

The impact of moderate wine consumption on the risk of developing prostate cancer

PubMed Central

Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

Objective To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. Design This study was a meta-analysis that includes data from case–control and cohort studies. Materials and methods A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane’s Q test and I2 statistics. Publication bias was assessed using Egger’s regression test. Results A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92–1.05, p=0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10–1.43, p=0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78–0.999, p=0.047) in the multivariable analysis that comprised 222,447 subjects. Conclusions In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk. PMID:29713200

Experimental variability and data pre-processing as factors affecting the discrimination power of some chemometric approaches (PCA, CA and a new algorithm based on linear regression) applied to (+/-)ESI/MS and RPLC/UV data: Application on green tea extracts.

PubMed

Iorgulescu, E; Voicu, V A; Sârbu, C; Tache, F; Albu, F; Medvedovici, A

2016-08-01

The influence of the experimental variability (instrumental repeatability, instrumental intermediate precision and sample preparation variability) and data pre-processing (normalization, peak alignment, background subtraction) on the discrimination power of multivariate data analysis methods (Principal Component Analysis -PCA- and Cluster Analysis -CA-) as well as a new algorithm based on linear regression was studied. Data used in the study were obtained through positive or negative ion monitoring electrospray mass spectrometry (+/-ESI/MS) and reversed phase liquid chromatography/UV spectrometric detection (RPLC/UV) applied to green tea extracts. Extractions in ethanol and heated water infusion were used as sample preparation procedures. The multivariate methods were directly applied to mass spectra and chromatograms, involving strictly a holistic comparison of shapes, without assignment of any structural identity to compounds. An alternative data interpretation based on linear regression analysis mutually applied to data series is also discussed. Slopes, intercepts and correlation coefficients produced by the linear regression analysis applied on pairs of very large experimental data series successfully retain information resulting from high frequency instrumental acquisition rates, obviously better defining the profiles being compared. Consequently, each type of sample or comparison between samples produces in the Cartesian space an ellipsoidal volume defined by the normal variation intervals of the slope, intercept and correlation coefficient. Distances between volumes graphically illustrates (dis)similarities between compared data. The instrumental intermediate precision had the major effect on the discrimination power of the multivariate data analysis methods. Mass spectra produced through ionization from liquid state in atmospheric pressure conditions of bulk complex mixtures resulting from extracted materials of natural origins provided an excellent data basis for multivariate analysis methods, equivalent to data resulting from chromatographic separations. The alternative evaluation of very large data series based on linear regression analysis produced information equivalent to results obtained through application of PCA an CA. Copyright © 2016 Elsevier B.V. All rights reserved.

A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending.

ERIC Educational Resources Information Center

Baker, Bruce D.; Richards, Craig E.

1999-01-01

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

"Let Me Count the Ways:" Fostering Reasons for Living among Low-Income, Suicidal, African American Women

ERIC Educational Resources Information Center

West, Lindsey M.; Davis, Telsie A.; Thompson, Martie P.; Kaslow, Nadine J.

2011-01-01

Protective factors for fostering reasons for living were examined among low-income, suicidal, African American women. Bivariate logistic regressions revealed that higher levels of optimism, spiritual well-being, and family social support predicted reasons for living. Multivariate logistic regressions indicated that spiritual well-being showed…

Fresh Biomass Estimation in Heterogeneous Grassland Using Hyperspectral Measurements and Multivariate Statistical Analysis

NASA Astrophysics Data System (ADS)

Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.

2014-12-01

Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.

Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities.

PubMed

Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

2016-01-01

Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. Copyright © 2015 Elsevier Ltd. All rights reserved.

Barriers to health-care and psychological distress among mothers living with HIV in Quebec (Canada).

PubMed

Blais, Martin; Fernet, Mylène; Proulx-Boucher, Karène; Lebouché, Bertrand; Rodrigue, Carl; Lapointe, Normand; Otis, Joanne; Samson, Johanne

2015-01-01

Health-care providers play a major role in providing good quality care and in preventing psychological distress among mothers living with HIV (MLHIV). The objectives of this study are to explore the impact of health-care services and satisfaction with care providers on psychological distress in MLHIV. One hundred MLHIV were recruited from community and clinical settings in the province of Quebec (Canada). Prevalence estimation of clinical psychological distress and univariate and multivariable logistic regression models were performed to predict clinical psychological distress. Forty-five percent of the participants reported clinical psychological distress. In the multivariable regression, the following variables were significantly associated with psychological distress while controlling for sociodemographic variables: resilience, quality of communication with the care providers, resources, and HIV disclosure concerns. The multivariate results support the key role of personal, structural, and medical resources in understanding psychological distress among MLHIV. Interventions that can support the psychological health of MLHIV are discussed.

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

PHI and PCA3 improve the prognostic performance of PRIAS and Epstein criteria in predicting insignificant prostate cancer in men eligible for active surveillance.

PubMed

Cantiello, Francesco; Russo, Giorgio Ivan; Cicione, Antonio; Ferro, Matteo; Cimino, Sebastiano; Favilla, Vincenzo; Perdonà, Sisto; De Cobelli, Ottavio; Magno, Carlo; Morgia, Giuseppe; Damiano, Rocco

2016-04-01

To assess the performance of prostate health index (PHI) and prostate cancer antigen 3 (PCA3) when added to the PRIAS or Epstein criteria in predicting the presence of pathologically insignificant prostate cancer (IPCa) in patients who underwent radical prostatectomy (RP) but eligible for active surveillance (AS). An observational retrospective study was performed in 188 PCa patients treated with laparoscopic or robot-assisted RP but eligible for AS according to Epstein or PRIAS criteria. Blood and urinary specimens were collected before initial prostate biopsy for PHI and PCA3 measurements. Multivariate logistic regression analyses and decision curve analysis were carried out to identify predictors of IPCa using the updated ERSPC definition. At the multivariate analyses, the inclusion of both PCA3 and PHI significantly increased the accuracy of the Epstein multivariate model in predicting IPCa with an increase of 17 % (AUC = 0.77) and of 32 % (AUC = 0.92), respectively. The inclusion of both PCA3 and PHI also increased the predictive accuracy of the PRIAS multivariate model with an increase of 29 % (AUC = 0.87) and of 39 % (AUC = 0.97), respectively. DCA revealed that the multivariable models with the addition of PHI or PCA3 showed a greater net benefit and performed better than the reference models. In a direct comparison, PHI outperformed PCA3 performance resulting in higher net benefit. In a same cohort of patients eligible for AS, the addition of PHI and PCA3 to Epstein or PRIAS models improved their prognostic performance. PHI resulted in greater net benefit in predicting IPCa compared to PCA3.

Gun orientation in self-inflicted craniomaxillofacial gunshot wounds: risk factors associated with fatality.

PubMed

Johnson, J; Markiewicz, M R; Bell, R B; Potter, B E; Dierks, E J

2012-08-01

The purpose of this study was to evaluate whether orientation of a firearm predicts survival, and to identify risk factors associated with fatality in subjects with self-inflicted craniomaxillofacial gunshot wounds. A retrospective cohort study design was used. The primary predictor variable was orientation of the weapon, defined as in the coronal (lateral) or sagittal (anterior-posterior) trajectory pattern. The primary outcome variable was death for subjects on arrival or during their hospital stay. Other covariates measured include demographic, firearm-related, and psychosocial variables. Risk factors for fatality were identified using multivariate logistic regression. Of the 92 subjects that met study inclusion criteria, 47 (67.2) held the firearm in the coronal position. In the full multivariate model, coronal gun orientation (OR=7.7, 95% CI: 2.0, 30.1, p=0.003) and the absence of a psychiatric diagnosis were associated with an increased risk of fatality (OR=0.1, 95% CI: 0.04, 0.5, p=0.002). Coronal firearm orientation was associated with an increased risk of fatality following self-inflicted craniomaxillofacial gunshot injuries. A patient with a documented psychiatric disorder was not found to be more likely to succumb to this type of injury. Copyright © 2012 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Factors associated with intimate partner violence against women in a mega city of South-Asia: multi-centre cross-sectional study.

PubMed

Ali, Niloufer S; Ali, Farzana N; Khuwaja, Ali K; Nanji, Kashmira

2014-08-01

OBJECTIVES. To assess the proportion of women subjected to intimate partner violence and the associated factors, and to identify the attitudes of women towards the use of violence by their husbands. DESIGN. Cross-sectional study. SETTING. Family practice clinics at a teaching hospital in Karachi, Pakistan. PARTICIPANTS. A total of 520 women aged between 16 and 60 years were consecutively approached to participate in the study and interviewed by trained data collectors. Overall, 401 completed questionnaires were available for analysis. Multivariate logistic regression analysis was used to identify the association of various factors of interest. RESULTS. In all, 35% of the women reported being physically abused by their husbands in the last 12 months. Multivariate analysis showed that experiences of violence were independently associated with women's illiteracy (adjusted odds ratio=5.9; 95% confidence interval, 1.8-19.6), husband's illiteracy (3.9; 1.4-10.7), smoking habit of husbands (3.3; 1.9-5.8), and substance use (3.1; 1.7-5.7). CONCLUSION. It is imperative that intimate partner violence be considered a major public health concern. It can be prevented through comprehensive, multifaceted, and integrated approaches. The role of education is greatly emphasised in changing the perspectives of individuals and societies against intimate partner violence.

Application of quality by design concepts in the development of fluidized bed granulation and tableting processes.

PubMed

Djuris, Jelena; Medarevic, Djordje; Krstic, Marko; Djuric, Zorica; Ibric, Svetlana

2013-06-01

This study illustrates the application of experimental design and multivariate data analysis in defining design space for granulation and tableting processes. According to the quality by design concepts, critical quality attributes (CQAs) of granules and tablets, as well as critical parameters of granulation and tableting processes, were identified and evaluated. Acetaminophen was used as the model drug, and one of the study aims was to investigate the possibility of the development of immediate- or extended-release acetaminophen tablets. Granulation experiments were performed in the fluid bed processor using polyethylene oxide polymer as a binder in the direct granulation method. Tablets were compressed in the laboratory excenter tablet press. The first set of experiments was organized according to Plackett-Burman design, followed by the full factorial experimental design. Principal component analysis and partial least squares regression were applied as the multivariate analysis techniques. By using these different methods, CQAs and process parameters were identified and quantified. Furthermore, an in-line method was developed to monitor the temperature during the fluidized bed granulation process, to foresee possible defects in granules CQAs. Various control strategies that are based on the process understanding and assure desired quality attributes of the product are proposed. Copyright © 2013 Wiley Periodicals, Inc.

Characterizing Durations of Heroin Abstinence in the California Civil Addict Program: Results From a 33-Year Observational Cohort Study

PubMed Central

Nosyk, Bohdan; Anglin, M. Douglas; Brecht, Mary-Lynn; Lima, Viviane Dias; Hser, Yih-Ing

2013-01-01

In accordance with the chronic disease model of opioid dependence, cessation is often observed as a longitudinal process rather than a discrete endpoint. We aimed to characterize and identify predictors of periods of heroin abstinence in the natural history of recovery from opioid dependence. Data were collected on participants from California who were enrolled in the Civil Addict Program from 1962 onward by use of a natural history interview. Multivariate regression using proportional hazards frailty models was applied to identify independent predictors and correlates of repeated abstinence episode durations. Among 471 heroin-dependent males, 387 (82.2%) reported 932 abstinence episodes, 60.3% of which lasted at least 1 year. Multivariate analysis revealed several important findings. First, demographic factors such as age and ethnicity did not explain variation in durations of abstinence episodes. However, employment and lower drug use severity predicted longer episodes. Second, abstinence durations were longer following sustained treatment versus incarceration. Third, individuals with multiple abstinence episodes remained abstinent for longer durations in successive episodes. Finally, abstinence episodes initiated >10 and ≤20 years after first use lasted longer than others. Public policy facilitating engagement of opioid-dependent individuals in maintenance-oriented drug treatment and employment is recommended to achieve and sustain opioid abstinence. PMID:23445901

Factors Predictive Of Alcohol Consumption Among Elderly People In A Rural Community: A Case Study In Phayao Province Thailand.

PubMed

Hongthong, Donnapa; Somrongthong, Ratana; Wongchaiya, Pimpimon; Kumar, Ramesh

2016-01-01

Alcohol consumption is recognized as a public health issue. Study objectives were to identify factors predictive of alcohol consumption among elderly people in Phayao province Thailand, where there was high prevalence of alcohol consumption. This was a cross-sectional study. Four hundred elderly people participated in a survey. Data was collected by face-to-face interviews. Chi-square and multivariate logistic regression were used to determine the factors predictive of alcohol consumption among the study subjects. One thirds of elderly (31.7%) had consumed alcohol in their lifetime, and (15.7%) of them were current drinkers. Following univariate analysis, seven factors included gender, working, sickness, smoking, quality of life (QOL), daily activities and economic recession - were identified as being significantly associated with drinking (p<0.05). Multivariate analysis revealed four factors to be predictive of alcohol among elderly people: gender (OR=6.02, 95% CI=3.58-10.13), smoking (OR=4.34, 95% CI=2.57-7.34), economic recession (OR=2.79, 95%, CI=1.66-4.71), and QOL (OR=1.86, 95%, CI=1.09-3.16). Gender (male) and smoking were strongly predictive factors of elderly alcohol consumption. Hence, an effort to reduce alcohol consumption should be placed on male elderly and those who smoke.

Using Time Series Analysis to Predict Cardiac Arrest in a PICU.

PubMed

Kennedy, Curtis E; Aoki, Noriaki; Mariscalco, Michele; Turley, James P

2015-11-01

To build and test cardiac arrest prediction models in a PICU, using time series analysis as input, and to measure changes in prediction accuracy attributable to different classes of time series data. Retrospective cohort study. Thirty-one bed academic PICU that provides care for medical and general surgical (not congenital heart surgery) patients. Patients experiencing a cardiac arrest in the PICU and requiring external cardiac massage for at least 2 minutes. None. One hundred three cases of cardiac arrest and 109 control cases were used to prepare a baseline dataset that consisted of 1,025 variables in four data classes: multivariate, raw time series, clinical calculations, and time series trend analysis. We trained 20 arrest prediction models using a matrix of five feature sets (combinations of data classes) with four modeling algorithms: linear regression, decision tree, neural network, and support vector machine. The reference model (multivariate data with regression algorithm) had an accuracy of 78% and 87% area under the receiver operating characteristic curve. The best model (multivariate + trend analysis data with support vector machine algorithm) had an accuracy of 94% and 98% area under the receiver operating characteristic curve. Cardiac arrest predictions based on a traditional model built with multivariate data and a regression algorithm misclassified cases 3.7 times more frequently than predictions that included time series trend analysis and built with a support vector machine algorithm. Although the final model lacks the specificity necessary for clinical application, we have demonstrated how information from time series data can be used to increase the accuracy of clinical prediction models.

Physical Function in Older Men With Hyperkyphosis

PubMed Central

Harrison, Stephanie L.; Fink, Howard A.; Marshall, Lynn M.; Orwoll, Eric; Barrett-Connor, Elizabeth; Cawthon, Peggy M.; Kado, Deborah M.

2015-01-01

Background. Age-related hyperkyphosis has been associated with poor physical function and is a well-established predictor of adverse health outcomes in older women, but its impact on health in older men is less well understood. Methods. We conducted a cross-sectional study to evaluate the association of hyperkyphosis and physical function in 2,363 men, aged 71–98 (M = 79) from the Osteoporotic Fractures in Men Study. Kyphosis was measured using the Rancho Bernardo Study block method. Measurements of grip strength and lower extremity function, including gait speed over 6 m, narrow walk (measure of dynamic balance), repeated chair stands ability and time, and lower extremity power (Nottingham Power Rig) were included separately as primary outcomes. We investigated associations of kyphosis and each outcome in age-adjusted and multivariable linear or logistic regression models, controlling for age, clinic, education, race, bone mineral density, height, weight, diabetes, and physical activity. Results. In multivariate linear regression, we observed a dose-related response of worse scores on each lower extremity physical function test as number of blocks increased, p for trend ≤.001. Using a cutoff of ≥4 blocks, 20% (N = 469) of men were characterized with hyperkyphosis. In multivariate logistic regression, men with hyperkyphosis had increased odds (range 1.5–1.8) of being in the worst quartile of performing lower extremity physical function tasks (p < .001 for each outcome). Kyphosis was not associated with grip strength in any multivariate analysis. Conclusions. Hyperkyphosis is associated with impaired lower extremity physical function in older men. Further studies are needed to determine the direction of causality. PMID:25431353

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

PubMed Central

Nickerson, Lisa D.; Smith, Stephen M.; Öngür, Döst; Beckmann, Christian F.

2017-01-01

Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia. PMID:28348512

Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

PubMed

Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

2013-03-01

Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birth.

PubMed

Menon, Ramkumar; Bhat, Geeta; Saade, George R; Spratt, Heidi

2014-04-01

To develop classification models of demographic/clinical factors and biomarker data from spontaneous preterm birth in African Americans and Caucasians. Secondary analysis of biomarker data using multivariate adaptive regression splines (MARS), a supervised machine learning algorithm method. Analysis of data on 36 biomarkers from 191 women was reduced by MARS to develop predictive models for preterm birth in African Americans and Caucasians. Maternal plasma, cord plasma collected at admission for preterm or term labor and amniotic fluid at delivery. Data were partitioned into training and testing sets. Variable importance, a relative indicator (0-100%) and area under the receiver operating characteristic curve (AUC) characterized results. Multivariate adaptive regression splines generated models for combined and racially stratified biomarker data. Clinical and demographic data did not contribute to the model. Racial stratification of data produced distinct models in all three compartments. In African Americans maternal plasma samples IL-1RA, TNF-α, angiopoietin 2, TNFRI, IL-5, MIP1α, IL-1β and TGF-α modeled preterm birth (AUC train: 0.98, AUC test: 0.86). In Caucasians TNFR1, ICAM-1 and IL-1RA contributed to the model (AUC train: 0.84, AUC test: 0.68). African Americans cord plasma samples produced IL-12P70, IL-8 (AUC train: 0.82, AUC test: 0.66). Cord plasma in Caucasians modeled IGFII, PDGFBB, TGF-β1 , IL-12P70, and TIMP1 (AUC train: 0.99, AUC test: 0.82). Amniotic fluid in African Americans modeled FasL, TNFRII, RANTES, KGF, IGFI (AUC train: 0.95, AUC test: 0.89) and in Caucasians, TNF-α, MCP3, TGF-β3 , TNFR1 and angiopoietin 2 (AUC train: 0.94 AUC test: 0.79). Multivariate adaptive regression splines models multiple biomarkers associated with preterm birth and demonstrated racial disparity. © 2014 Nordic Federation of Societies of Obstetrics and Gynecology.

Quality of Care for Work-associated Carpal Tunnel Syndrome

PubMed Central

Nuckols, Teryl; Conlon, Craig; Robbins, Michael; Dworsky, Michael; Lai, Julie; Roth, Carol P.; Levitan, Barbara; Seabury, Seth; Seelam, Rachana; Asch, Steven M.

2017-01-01

Objective To evaluate the quality of care provided to individuals with workers’ compensation claims related to CTS and identify patient characteristics associated with receiving better care. Methods We recruited subjects with new claims for CTS from 30 occupational clinics affiliated with Kaiser Permanente Northern California. We applied 45 process-oriented quality measures to 477 subjects’ medical records, and performed multivariate logistic regression to identify patient characteristics associated with quality. Results Overall, 81.6% of care adhered to recommended standards. Certain tasks related to assessing and managing activity were underused. Patients with classic/probable Katz diagrams, positive electrodiagnostic tests, and higher incomes received better care. However, age, gender, and race/ethnicity were not associated with quality. Conclusions Care processes for work-associated CTS frequently adhered to quality measures. Clinical factors were more strongly associated with quality than demographic and socioeconomic ones. PMID:28045797

Predictors of Membership in Alcoholics Anonymous in a Sample of Successfully Remitted Alcoholics

PubMed Central

Krentzman, Amy R.; Robinson, Elizabeth A. R.; Perron, Brian E.; Cranford, James A.

2012-01-01

This study identifies factors associated with Alcoholics Anonymous (AA) membership in a sample of 81 persons who have achieved at least one year of total abstinence from drugs and alcohol. Forty-four were AA members, 37 were not. Logistic regression was used to test the cross-sectional associations of baseline demographic, substance-related, spiritual and religious, and personality variables with AA membership. Significant variables from the bivariate analyses were included in a multivariate model controlling for previous AA involvement. Having more positive views of God and more negative consequences of drinking were significantly associated with AA membership. This information can be used by clinicians to identify clients for whom AA might be a good fit, and can help others overcome obstacles to AA or explore alternative forms of abstinence support. PMID:21615004

Is use of homeopathy associated with poor prescribing in English primary care? A cross-sectional study.

PubMed

Walker, Alex J; Croker, Richard; Bacon, Seb; Ernst, Edzard; Curtis, Helen J; Goldacre, Ben

2018-05-01

Objectives Prescribing of homeopathy still occurs in a small minority of English general practices. We hypothesised that practices that prescribe any homeopathic preparations might differ in their prescribing of other drugs. Design Cross-sectional analysis. Setting English primary care. Participants English general practices. Main outcome measures We identified practices that made any homeopathy prescriptions over six months of data. We measured associations with four prescribing and two practice quality indicators using multivariable logistic regression. Results Only 8.5% of practices (644) prescribed homeopathy between December 2016 and May 2017. Practices in the worst-scoring quartile for a composite measure of prescribing quality (>51.4 mean percentile) were 2.1 times more likely to prescribe homeopathy than those in the best category (<40.3) (95% confidence interval: 1.6-2.8). Aggregate savings from the subset of these measures where a cost saving could be calculated were also strongly associated (highest vs. lowest quartile multivariable odds ratio: 2.9, confidence interval: 2.1-4.1). Of practices spending the most on medicines identified as 'low value' by NHS England, 12.8% prescribed homeopathy, compared to 3.9% for lowest spenders (multivariable odds ratio: 2.6, confidence interval: 1.9-3.6). Of practices in the worst category for aggregated price-per-unit cost savings, 12.7% prescribed homeopathy, compared to 3.5% in the best category (multivariable odds ratio: 2.7, confidence interval: 1.9-3.9). Practice quality outcomes framework scores and patient recommendation rates were not associated with prescribing homeopathy (odds ratio range: 0.9-1.2). Conclusions Even infrequent homeopathy prescribing is strongly associated with poor performance on a range of prescribing quality measures, but not with overall patient recommendation or quality outcomes framework score. The association is unlikely to be a direct causal relationship, but may reflect underlying practice features, such as the extent of respect for evidence-based practice, or poorer stewardship of the prescribing budget.

A novel approach to identify genes that determine grain protein deviation in cereals.

PubMed

Mosleth, Ellen F; Wan, Yongfang; Lysenko, Artem; Chope, Gemma A; Penson, Simon P; Shewry, Peter R; Hawkesford, Malcolm J

2015-06-01

Grain yield and protein content were determined for six wheat cultivars grown over 3 years at multiple sites and at multiple nitrogen (N) fertilizer inputs. Although grain protein content was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to identify gene transcripts significantly related to GPD across environments. The yield and protein content were initially adjusted for nitrogen fertilizer inputs and then adjusted for yield (to remove the negative correlation with protein content), resulting in a parameter termed corrected GPD. Significant genetic variation in corrected GPD was observed for six cultivars grown over a range of environmental conditions (a total of 584 samples). Gene transcript profiles were determined in a subset of 161 samples of developing grain to identify transcripts contributing to GPD. Principal component analysis (PCA), analysis of variance (ANOVA) and means of scores regression (MSR) were used to identify individual principal components (PCs) correlating with GPD alone. Scores of the selected PCs, which were significantly related to GPD and protein content but not to the yield and significantly affected by cultivar, were identified as reflecting a multivariate pattern of gene expression related to genetic variation in GPD. Transcripts with consistent variation along the selected PCs were identified by an approach hereby called one-block means of scores regression (one-block MSR). © 2014 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

An Investigation of Multivariate Adaptive Regression Splines for Modeling and Analysis of Univariate and Semi-Multivariate Time Series Systems

DTIC Science & Technology

1991-09-01

However, there is no guarantee that this would work; for instance if the data were generated by an ARCH model (Tong, 1990 pp. 116-117) then a simple...Hill, R., Griffiths, W., Lutkepohl, H., and Lee, T., Introduction to the Theory and Practice of Econometrics , 2th ed., Wiley, 1985. Kendall, M., Stuart

A Novel MiRNA-Based Predictive Model for Biochemical Failure Following Post-Prostatectomy Salvage Radiation Therapy

PubMed Central

Stegmaier, Petra; Drendel, Vanessa; Mo, Xiaokui; Ling, Stella; Fabian, Denise; Manring, Isabel; Jilg, Cordula A.; Schultze-Seemann, Wolfgang; McNulty, Maureen; Zynger, Debra L.; Martin, Douglas; White, Julia; Werner, Martin; Grosu, Anca L.; Chakravarti, Arnab

2015-01-01

Purpose To develop a microRNA (miRNA)-based predictive model for prostate cancer patients of 1) time to biochemical recurrence after radical prostatectomy and 2) biochemical recurrence after salvage radiation therapy following documented biochemical disease progression post-radical prostatectomy. Methods Forty three patients who had undergone salvage radiation therapy following biochemical failure after radical prostatectomy with greater than 4 years of follow-up data were identified. Formalin-fixed, paraffin-embedded tissue blocks were collected for all patients and total RNA was isolated from 1mm cores enriched for tumor (>70%). Eight hundred miRNAs were analyzed simultaneously using the nCounter human miRNA v2 assay (NanoString Technologies; Seattle, WA). Univariate and multivariate Cox proportion hazards regression models as well as receiver operating characteristics were used to identify statistically significant miRNAs that were predictive of biochemical recurrence. Results Eighty eight miRNAs were identified to be significantly (p<0.05) associated with biochemical failure post-prostatectomy by multivariate analysis and clustered into two groups that correlated with early (≤ 36 months) versus late recurrence (>36 months). Nine miRNAs were identified to be significantly (p<0.05) associated by multivariate analysis with biochemical failure after salvage radiation therapy. A new predictive model for biochemical recurrence after salvage radiation therapy was developed; this model consisted of miR-4516 and miR-601 together with, Gleason score, and lymph node status. The area under the ROC curve (AUC) was improved to 0.83 compared to that of 0.66 for Gleason score and lymph node status alone. Conclusion miRNA signatures can distinguish patients who fail soon after radical prostatectomy versus late failures, giving insight into which patients may need adjuvant therapy. Notably, two novel miRNAs (miR-4516 and miR-601) were identified that significantly improve prediction of biochemical failure post-salvage radiation therapy compared to clinico-histopathological factors, supporting the use of miRNAs within clinically used predictive models. Both findings warrant further validation studies. PMID:25760964

Poor methodological quality and reporting standards of systematic reviews in burn care management.

PubMed

Wasiak, Jason; Tyack, Zephanie; Ware, Robert; Goodwin, Nicholas; Faggion, Clovis M

2017-10-01

The methodological and reporting quality of burn-specific systematic reviews has not been established. The aim of this study was to evaluate the methodological quality of systematic reviews in burn care management. Computerised searches were performed in Ovid MEDLINE, Ovid EMBASE and The Cochrane Library through to February 2016 for systematic reviews relevant to burn care using medical subject and free-text terms such as 'burn', 'systematic review' or 'meta-analysis'. Additional studies were identified by hand-searching five discipline-specific journals. Two authors independently screened papers, extracted and evaluated methodological quality using the 11-item A Measurement Tool to Assess Systematic Reviews (AMSTAR) tool and reporting quality using the 27-item Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Characteristics of systematic reviews associated with methodological and reporting quality were identified. Descriptive statistics and linear regression identified features associated with improved methodological quality. A total of 60 systematic reviews met the inclusion criteria. Six of the 11 AMSTAR items reporting on 'a priori' design, duplicate study selection, grey literature, included/excluded studies, publication bias and conflict of interest were reported in less than 50% of the systematic reviews. Of the 27 items listed for PRISMA, 13 items reporting on introduction, methods, results and the discussion were addressed in less than 50% of systematic reviews. Multivariable analyses showed that systematic reviews associated with higher methodological or reporting quality incorporated a meta-analysis (AMSTAR regression coefficient 2.1; 95% CI: 1.1, 3.1; PRISMA regression coefficient 6·3; 95% CI: 3·8, 8·7) were published in the Cochrane library (AMSTAR regression coefficient 2·9; 95% CI: 1·6, 4·2; PRISMA regression coefficient 6·1; 95% CI: 3·1, 9·2) and included a randomised control trial (AMSTAR regression coefficient 1·4; 95%CI: 0·4, 2·4; PRISMA regression coefficient 3·4; 95% CI: 0·9, 5·8). The methodological and reporting quality of systematic reviews in burn care requires further improvement with stricter adherence by authors to the PRISMA checklist and AMSTAR tool. © 2016 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Red Blood Cell Transfusion Need for Elective Primary Posterior Lumbar Fusion in A High-Volume Center for Spine Surgery

PubMed Central

Ristagno, Giuseppe; Beluffi, Simonetta; Tanzi, Dario; Belloli, Federica; Carmagnini, Paola; Croci, Massimo; D’Aviri, Giuseppe; Menasce, Guido; Pastore, Juan C.; Pellanda, Armando; Pollini, Alberto; Savoia, Giorgio

2018-01-01

(1) Background: This study evaluated the perioperative red blood cell (RBC) transfusion need and determined predictors for transfusion in patients undergoing elective primary lumbar posterior spine fusion in a high-volume center for spine surgery. (2) Methods: Data from all patients undergoing spine surgery between 1 January 2014 and 31 December 2016 were reviewed. Patients’ demographics and comorbidities, perioperative laboratory results, and operative time were analyzed in relation to RBC transfusion. Multivariate logistic regression analysis was performed to identify the predictors of transfusion. (3) Results: A total of 874 elective surgeries for primary spine fusion were performed over the three years. Only 54 cases (6%) required RBC transfusion. Compared to the non-transfused patients, transfused patients were mainly female (p = 0.0008), significantly older, with a higher ASA grade (p = 0.0002), and with lower pre-surgery hemoglobin (HB) level and hematocrit (p < 0.0001). In the multivariate logistic regression, a lower pre-surgery HB (OR (95% CI) 2.84 (2.11–3.82)), a higher ASA class (1.77 (1.03–3.05)) and a longer operative time (1.02 (1.01–1.02)) were independently associated with RBC transfusion. (4) Conclusions: In the instance of elective surgery for primary posterior lumbar fusion in a high-volume center for spine surgery, the need for RBC transfusion is low. Factors anticipating transfusion should be taken into consideration in the patient’s pre-surgery preparation. PMID:29385760

Meningococcal vaccination in primary care amongst adolescents in North West England: an ecological study investigating associations with general practice characteristics.

PubMed

Blagden, Sarah; Hungerford, Daniel; Limmer, Mark

2018-01-27

In 2015 the meningococcal ACWY (MenACWY) vaccination was introduced amongst adolescents in England following increased incidence and mortality associated with meningococcal group W. MenACWY vaccination uptake data for 17-18 years old and students delivered in primary care were obtained for 20 National Health Service clinical commissioning groups (CCGs) via the ImmForm vaccination system. Data on general practice characteristics, encompassing demographics and patient satisfaction variables, were extracted from the National General Practice Profiles resource. Univariable analysis of the associations between practice characteristics and vaccination was performed, followed by multivariable negative binomial regression. Data were utilized from 587 general practices, accounting for ~8% of all general practices in England. MenACWY vaccination uptake varied from 20.8% to 46.8% across the CCGs evaluated. Upon multivariable regression, vaccination uptake increased with increasing percentage of patients from ethnic minorities, increasing percentage of patients aged 15-24 years, increasing percentage of patients that would recommend their practice and total Quality and Outcomes Framework achievement for the practice. Conversely, vaccination uptake decreased with increasing deprivation. This study has identified several factors independently associated with MenACWY vaccination in primary care. These findings will enable a targeted approach to improve general practice-level vaccination uptake. © The Author(s) 2018. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Pharmacodynamics and effectiveness of topical nitroglycerin at lowering blood pressure during autonomic dysreflexia.

PubMed

Solinsky, R; Bunnell, A E; Linsenmeyer, T A; Svircev, J N; Engle, A; Burns, S P

2017-10-01

Secondary analysis of prospectively collected observational data assessing the safety of an autonomic dysreflexia (AD) management protocol. To estimate the time to onset of action, time to full clinical effect (sustained systolic blood pressure (SBP) <160 mm Hg) and effectiveness of nitroglycerin ointment at lowering blood pressure for patients with spinal cord injuries experiencing AD. US Veterans Affairs inpatient spinal cord injury (SCI) unit. Episodes of AD recalcitrant to nonpharmacologic interventions that were given one to two inches of 2% topical nitroglycerin ointment were recorded. Pharmacodynamics as above and predictive characteristics (through a mixed multivariate logistic regression model) were calculated. A total of 260 episodes of pharmacologically managed AD were recorded in 56 individuals. Time to onset of action for nitroglycerin ointment was 9-11 min. Time to full clinical effect was 14-20 min. Topical nitroglycerin controlled SBP <160 mm Hg in 77.3% of pharmacologically treated AD episodes with the remainder requiring additional antihypertensive medications. A multivariate logistic regression model was unable to identify statistically significant factors to predict which patients would respond to nitroglycerin ointment (odds ratios 95% confidence intervals 0.29-4.93). The adverse event rate, entirely attributed to hypotension, was 3.6% with seven of the eight events resolving with close observation alone and one episode requiring normal saline. Nitroglycerin ointment has a rapid onset of action and time to full clinical effect with high efficacy and relatively low adverse event rate for patients with SCI experiencing AD.

Association between Furosemide Exposure and Patent Ductus Arteriosus in Hospitalized Infants of Very Low Birth Weight.

PubMed

Thompson, Elizabeth J; Greenberg, Rachel G; Kumar, Karan; Laughon, Matthew; Smith, P Brian; Clark, Reese H; Crowell, Andromeda; Shaw, Layla; Harrison, Louis; Scales, Gabrielle; Bell, Nicole; Hornik, Christoph P

2018-05-08

To evaluate the association between furosemide exposure and patent ductus arteriosus (PDA) in a large, contemporary cohort of hospitalized infants with very low birth weight (VLBW). Using the Pediatrix Medical Group Clinical Data Warehouse, we identified all inborn infants of VLBW <37 weeks of gestation discharged from the neonatal intensive care unit after the first postnatal week from 2011 to 2015. We defined PDA as any medical (ibuprofen or indomethacin) or surgical PDA therapy. We collected data up to the day of PDA treatment or postnatal day 18 for infants not diagnosed with PDA. We performed multivariable logistic regression to evaluate the association between PDA and exposure to furosemide. We included 43 576 infants from 337 neonatal intensive care units, of whom 6675 (15%) underwent PDA treatment. Infants with PDA were more premature and more often exposed to mechanical ventilation and inotropes. Furosemide was prescribed to 4055 (9%) infants. On multivariable regression, exposure to furosemide was associated with decreased odds of PDA treatment (OR 0.72; 95% CI 0.65-0.79). Increasing percentage of days with furosemide exposure was not associated with PDA treatment (OR 1.01; 95% CI 0.97-1.06). Furosemide exposure was not associated with increased odds of PDA treatment in hospitalized infants of VLBW. Further studies are needed to characterize the efficacy and safety of furosemide in premature infants. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of third-degree and fourth-degree laceration rates as quality indicators.

PubMed

Friedman, Alexander M; Ananth, Cande V; Prendergast, Eri; D'Alton, Mary E; Wright, Jason D

2015-04-01

To examine the patterns and predictors of third-degree and fourth-degree laceration in women undergoing vaginal delivery. We identified a population-based cohort of women in the United States who underwent a vaginal delivery between 1998 and 2010 using the Nationwide Inpatient Sample. Multivariable log-linear regression models were developed to account for patient, obstetric, and hospital factors related to lacerations. Between-hospital variability of laceration rates was calculated using generalized log-linear mixed models. Among 7,096,056 women who underwent vaginal delivery in 3,070 hospitals, 3.3% (n=232,762) had a third-degree laceration and 1.1% (n=76,347) had a fourth-degree laceration. In an adjusted model for fourth-degree lacerations, important risk factors included shoulder dystocia and forceps and vacuum deliveries with and without episiotomy. Other demographic, obstetric, medical, and hospital variables, although statistically significant, were not major determinants of lacerations. Risk factors in a multivariable model for third-degree lacerations were similar to those in the fourth-degree model. Regression analysis of hospital rates (n=3,070) of lacerations demonstrated limited between-hospital variation. Risk of third-degree and fourth-degree laceration was most strongly related to operative delivery and shoulder dystocia. Between-hospital variation was limited. Given these findings and that the most modifiable practice related to lacerations would be reduction in operative vaginal deliveries (and a possible increase in cesarean delivery), third-degree and fourth-degree laceration rates may be a quality metric of limited utility.

Neurological Manifestations of Mycoplasma pneumoniae Infection in Hospitalized Children and Their Long-Term Follow-Up.

PubMed

Kammer, Jessica; Ziesing, Stefan; Davila, Lukas Aguirre; Bültmann, Eva; Illsinger, Sabine; Das, Anibh M; Haffner, Dieter; Hartmann, Hans

2016-10-01

Objective In this retrospective study, we aimed to assess frequency, types, and long-term outcome of neurological disease during acute Mycoplasma pneumoniae (M. pneumoniae) infection in pediatric patients. Materials and Methods Medical records of patients hospitalized with acute M. pneumoniae infection were reviewed. Possible risk factors were analyzed by uni- and multivariate regression. Patients with neurological symptoms were followed up by expanded disability status score (EDSS) and the cognitive problems in children and adolescents (KOPKJ) scale. Results Out of 89 patients, 22 suffered from neurological symptoms and signs. Neurological disorders were diagnosed in 11 patients: (meningo-) encephalitis (n = 6), aseptic meningitis (n = 3), transverse myelitis (n = 1), and vestibular neuritis (n = 1), 11 patients had nonspecific neurological symptoms and signs. Multivariate logistic regression identified lower respiratory tract symptoms as a negative predictor (odds ratio [OR] = 0.1, p < 0.001), a preexisting immune deficit was associated with a trend for a decreased risk (OR = 0.12, p = 0.058). Long-term follow-up after a median of 5.1 years (range, 0.6-13 years) showed ongoing neurological deficits in the EDSS in 8/18, and in the KOPKJ in 7/17. Conclusion Neurological symptoms occurred in 25% of hospitalized pediatric patients with M. pneumoniae infection. Outcome was often favorable, but significant sequels were reported by 45%. Georg Thieme Verlag KG Stuttgart · New York.

Associations Between Physician Empathy, Physician Characteristics, and Standardized Measures of Patient Experience.

PubMed

Chaitoff, Alexander; Sun, Bob; Windover, Amy; Bokar, Daniel; Featherall, Joseph; Rothberg, Michael B; Misra-Hebert, Anita D

2017-10-01

To identify correlates of physician empathy and determine whether physician empathy is related to standardized measures of patient experience. Demographic, professional, and empathy data were collected during 2013-2015 from Cleveland Clinic Health System physicians prior to participation in mandatory communication skills training. Empathy was assessed using the Jefferson Scale of Empathy. Data were also collected for seven measures (six provider communication items and overall provider rating) from the visit-specific and 12-month Consumer Assessment of Healthcare Providers and Systems Clinician and Group (CG-CAHPS) surveys. Associations between empathy and provider characteristics were assessed by linear regression, ANOVA, or a nonparametric equivalent. Significant predictors were included in a multivariable linear regression model. Correlations between empathy and CG-CAHPS scores were assessed using Spearman rank correlation coefficients. In bivariable analysis (n = 847 physicians), female sex (P < .001), specialty (P < .01), outpatient practice setting (P < .05), and DO degree (P < .05) were associated with higher empathy scores. In multivariable analysis, female sex (P < .001) and four specialties (obstetrics-gynecology, pediatrics, psychiatry, and thoracic surgery; all P < .05) were significantly associated with higher empathy scores. Of the seven CG-CAHPS measures, scores on five for the 583 physicians with visit-specific data and on three for the 277 physicians with 12-month data were positively correlated with empathy. Specialty and sex were independently associated with physician empathy. Empathy was correlated with higher scores on multiple CG-CAHPS items, suggesting improving physician empathy might play a role in improving patient experience.

Predictors of health of pre-registration nursing and midwifery students: Findings from a cross-sectional survey.

PubMed

Deasy, Christine; Coughlan, Barry; Pironom, Julie; Jourdan, Didier; Mannix-McNamara, Patricia

2016-01-01

Student nurses/midwives evidence less than exemplary lifestyle habits and poor emotional health, despite exposure to health education/promotion during their educational preparation. Knowledge of the factors that predict nursing/midwifery students' health could inform strategies to enhance their health and increase their credibility as future health promoters/educators. To establish the predictors of nursing/midwifery student emotional health. Cross-sectional survey. The research took place at a university in Ireland. We involved a total sample (n=473) student nurses/midwives. Participants completed the General Health Questionnaire, Lifestyle Behaviour Questionnaire and Ways of Coping Questionnaire to determine their self-reported emotional health, lifestyle behaviour and coping processes. Multivariate regression was performed to identify the predictors of student emotional health (dependent variable). The independent variables were demographics, coping, lifestyle behaviour and students' perceptions of determinants of their health. Many respondents reported significant emotional distress (48.71%) and unhealthy lifestyle behaviours including smoking (27.94%), physical inactivity (34.29%), alcohol consumption (91.7%) and unhealthy diet (28.05%). Multivariate regressions indicated that the predictors of emotional distress included gender, year of study, smoking, passive coping and beliefs that their student life was stressful or/and that worry stress and boredom adversely impacted their diet. Targeting student's beliefs regarding influences upon their health, promotion of positive lifestyles and adaptive coping is necessary to facilitate health gain of future health professionals. Copyright © 2015 Elsevier Ltd. All rights reserved.

Can a simple test of functional capacity add to the clinical assessment of diabetes?

PubMed

Stewart, T; Caffrey, D G; Gilman, R H; Mathai, S C; Lerner, A; Hernandez, A; Pinto, M E; Huaylinos, Y; Cabrera, L; Wise, R A; Miranda, J J; Checkley, W

2016-08-01

To identify impairment in functional capacity associated with complicated and non-complicated diabetes using the 6-min walk distance test. We enrolled 111 adults, aged ≥40 years, with Type 2 diabetes from a hospital facility and 150 healthy control subjects of similar age and sex from a community site in Lima, Peru. All participants completed a 6-min walk test. The mean age of the 261 participants was 58.3 years, and 43.3% were male. Among those with diabetes, 67 (60%) had non-complicated diabetes and 44 (40%) had complications such as peripheral neuropathy, retinopathy or nephropathy. The mean unadjusted 6-min walk distances were 376 m and 394 m in adults with and without diabetes complications, respectively, vs 469 m in control subjects (P<0.001). In multivariable regression, the subjects with diabetes complications walked 84 m less far (95% CI -104 to -63 m) and those without complications walked 60 m less far (-77 to -42 m) than did control subjects. When using HbA1c level as a covariate in multivariable regression, participants walked 13 m less far (-16.9 to -9.9 m) for each % increase in HbA1c . The subjects with diabetes had lower functional capacity compared with healthy control subjects with similar characteristics. Differences in 6-min walk distance were even apparent in the subjects without diabetes complications. Potential mechanisms that could explain this finding are early cardiovascular disease or deconditioning. © 2015 Diabetes UK.

Can a simple test of functional capacity add to the clinical assessment of diabetes?

PubMed Central

Stewart, T.; Caffrey, D. G.; Gilman, R. H.; Mathai, S. C.; Lerner, A.; Hernandez, A.; Pinto, M. E.; Huaylinos, Y.; Cabrera, L.; Wise, R. A.; Miranda, J. J.; Checkley, W.

2016-01-01

Aim To identify impairment in functional capacity associated with complicated and non-complicated diabetes using the 6-min walk distance test. Methods We enrolled 111 adults, aged ≥40 years, with Type 2 diabetes from a hospital facility and 150 healthy control subjects of similar age and sex from a community site in Lima, Peru. All participants completed a 6-min walk test. Results The mean age of the 261 participants was 58.3 years, and 43.3% were male. Among those with diabetes, 67 (60%) had non-complicated diabetes and 44 (40%) had complications such as peripheral neuropathy, retinopathy or nephropathy. The mean unadjusted 6-min walk distances were 376 m and 394 m in adults with and without diabetes complications, respectively, vs 469 m in control subjects (P<0.001). In multivariable regression, the subjects with diabetes complications walked 84 m less far (95% CI -104 to -63 m) and those without complications walked 60 m less far (-77 to -42 m) than did control subjects. When using HbA1c level as a covariate in multivariable regression, participants walked 13 m less far (-16.9 to -9.9 m) for each % increase in HbA1c. Conclusions The subjects with diabetes had lower functional capacity compared with healthy control subjects with similar characteristics. Differences in 6-min walk distance were even apparent in the subjects without diabetes complications. Potential mechanisms that could explain this finding are early cardiovascular disease or deconditioning. PMID:26599981

The prognosis analysis of different metastasis pattern in patients with different breast cancer subtypes: a SEER based study.

PubMed

Wang, Haiyong; Zhang, Chenyue; Zhang, Jingze; Kong, Li; Zhu, Hui; Yu, Jinming

2017-04-18

Studies on prognosis of different metastasis patterns in patients with different breast cancer subtypes (BCS) are limited. Therefore, we identified 7862 breast cancer patients with distant metastasis from 2010 to 2013 using Surveillance, Epidemiology, wand End Results (SEER) population-based data. The results showed that bone was the most common metastatic site and brain was the least common metastatic site, and the patients with HR+/HER2- occupied the highest metastasis proportion, the lowest metastasis proportion were found in HR-/HER2+ patients. Univariate and multivariate logistic regression analysis were used to analyze the association, and it was found that there were significant differences of distant metastasis patterns in patients with different BCS(different P value). Importantly, univariate and multivariate Cox regression analysis were used to analyze the prognosis. It was proven that only bone metastasis was not a prognostic factor in the HR+/HER2-, HR+/HER2+ and HR-/HER2+ subgroup (all, P > 0.05), and patients with brain metastasis had the worst cancer specific survival (CSS) in all the subgroups of BCS (all, P<0.01). Interestingly, for patients with two metastatic sites, those with bone and lung metastasis had best CSS in the HR+/HER2- (P<0.001) and HR+/HER2+ subgroups (P=0.009) However, for patients with three and four metastatic sites, there was no statistical difference in their CSS (all, P>0.05).

The prognosis analysis of different metastasis pattern in patients with different breast cancer subtypes: a SEER based study

PubMed Central

Wang, Haiyong; Zhang, Chenyue; Zhang, Jingze; Kong, Li; Zhu, Hui; Yu, Jinming

2017-01-01

Studies on prognosis of different metastasis patterns in patients with different breast cancer subtypes (BCS) are limited. Therefore, we identified 7862 breast cancer patients with distant metastasis from 2010 to 2013 using Surveillance, Epidemiology, wand End Results (SEER) population-based data. The results showed that bone was the most common metastatic site and brain was the least common metastatic site, and the patients with HR+/HER2− occupied the highest metastasis proportion, the lowest metastasis proportion were found in HR-/HER2+ patients. Univariate and multivariate logistic regression analysis were used to analyze the association, and it was found that there were significant differences of distant metastasis patterns in patients with different BCS(different P value). Importantly, univariate and multivariate Cox regression analysis were used to analyze the prognosis. It was proven that only bone metastasis was not a prognostic factor in the HR+/HER2-, HR+/HER2+ and HR-/HER2+ subgroup (all, P > 0.05), and patients with brain metastasis had the worst cancer specific survival (CSS) in all the subgroups of BCS (all, P<0.01). Interestingly, for patients with two metastatic sites, those with bone and lung metastasis had best CSS in the HR+/HER2- (P<0.001) and HR+/HER2+ subgroups (P=0.009) However, for patients with three and four metastatic sites, there was no statistical difference in their CSS (all, P>0.05). PMID:28038448

Risk of Peripheral Artery Occlusive Disease in Patients with Vertigo, Tinnitus, or Sudden Deafness: A Secondary Case-Control Analysis of a Nationwide, Population-Based Health Claims Database.

PubMed

Koo, Malcolm; Chen, Jin-Cherng; Hwang, Juen-Haur

2016-01-01

Cochleovestibular symptoms, such as vertigo, tinnitus, and sudden deafness, are common manifestations of microvascular diseases. However, it is unclear whether these symptoms occurred preceding the diagnosis of peripheral artery occlusive disease (PAOD). Therefore, the aim of this case-control study was to investigate the risk of PAOD among patients with vertigo, tinnitus, and sudden deafness using a nationwide, population-based health claim database in Taiwan. We identified 5,340 adult patients with PAOD diagnosed between January 1, 2006 and December 31, 2010 and 16,020 controls, frequency matched on age interval, sex, and year of index date, from the Taiwan National Health Insurance Research Database. Risks of PAOD in patients with vertigo, tinnitus, or sudden deafness were separately evaluated with multivariate logistic regression analyses. Of the 5,340 patients with PAOD, 12.7%, 6.7%, and 0.3% were diagnosed with vertigo, tinnitus, and sudden deafness, respectively. In the controls, 10.6%, 6.1%, and 0.3% were diagnosed with vertigo (P < 0.001), tinnitus (P = 0.161), and sudden deafness (P = 0.774), respectively. Results from the multivariate logistic regression analyses showed that the risk of PAOD was significantly increased in patients with vertigo (adjusted odds ratio = 1.12, P = 0.027) but not in those with tinnitus or sudden deafness. A modest increase in the risk of PAOD was observed among Taiwanese patients with vertigo, after adjustment for comorbidities.

Varicocele is associated with hypogonadism and impaired erectile function: a prospective comparative study.

PubMed

Ji, B; Jin, X-B

2017-08-01

We conducted this prospective comparative study to examine the hypothesis that varicocele was associated with hypogonadism and impaired erectile function as reflected in International Index of Erectile Function-5 (IIEF-5) scores as well as nocturnal penile tumescence and rigidity (NPTR) parameters. From December 2014 to December 2015, a total of 130 males with varicocele complaining of infertility or scrotal discomfort and 130 age-matched healthy males chosen from volunteer healthy hospital staff as controls were recruited in this study. Serum testosterone (TT) levels and IIEF-5 scores as well as NPTR parameters were evaluated and compared between varicocele and control subjects. All participants were further grouped into hypogonadism based on the cut-off value 300 ng/dL. A total of 45 of 130 patients were identified as hypogonadism, while it was not found in control subjects. A multivariate logistic regression with likelihood ratio test revealed that TT levels as well as grade III and II varicocele posed significant indicators for hypogonadism occurrence (chi-square of likelihood ratio = 12.40, df = 3, p < .01). Furthermore, TT levels and infertility duration were associated with IIEF-5 scores in a multivariate linear regression analysis (adjusted R 2  = 0.545). In conclusion, the correlation of grade III and II varicocele with an increased risk of hypogonadism was confirmed in this study and an impaired erectile function correlated with TT levels and infertility duration was also observed. © 2016 Blackwell Verlag GmbH.

Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

NASA Astrophysics Data System (ADS)

Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

2017-12-01

The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

Effects of Social Class and School Conditions on Educational Enrollment and Achievement of Boys and Girls in Rural Viet Nam

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

This study examines the effects of parental SES, school quality, and community factors on children's enrollment and achievement in rural areas in Viet Nam, using logistic regression and ordered logistic regression. Multivariate analysis reveals significant differences in educational enrollment and outcomes by level of household expenditures and…

Procedures for using signals from one sensor as substitutes for signals of another

NASA Technical Reports Server (NTRS)

Suits, G.; Malila, W.; Weller, T.

1988-01-01

Long-term monitoring of surface conditions may require a transfer from using data from one satellite sensor to data from a different sensor having different spectral characteristics. Two general procedures for spectral signal substitution are described in this paper, a principal-components procedure and a complete multivariate regression procedure. They are evaluated through a simulation study of five satellite sensors (MSS, TM, AVHRR, CZCS, and HRV). For illustration, they are compared to another recently described procedure for relating AVHRR and MSS signals. The multivariate regression procedure is shown to be best. TM can accurately emulate the other sensors, but they, on the other hand, have difficulty in accurately emulating its shortwave infrared bands (TM5 and TM7).

Multivariate Analysis of Seismic Field Data

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

Alam, M. Kathleen

1999-06-01

This report includes the details of the model building procedure and prediction of seismic field data. Principal Components Regression, a multivariate analysis technique, was used to model seismic data collected as two pieces of equipment were cycled on and off. Models built that included only the two pieces of equipment of interest had trouble predicting data containing signals not included in the model. Evidence for poor predictions came from the prediction curves as well as spectral F-ratio plots. Once the extraneous signals were included in the model, predictions improved dramatically. While Principal Components Regression performed well for the present datamore » sets, the present data analysis suggests further work will be needed to develop more robust modeling methods as the data become more complex.« less

Non-proportional odds multivariate logistic regression of ordinal family data.

PubMed

Zaloumis, Sophie G; Scurrah, Katrina J; Harrap, Stephen B; Ellis, Justine A; Gurrin, Lyle C

2015-03-01

Methods to examine whether genetic and/or environmental sources can account for the residual variation in ordinal family data usually assume proportional odds. However, standard software to fit the non-proportional odds model to ordinal family data is limited because the correlation structure of family data is more complex than for other types of clustered data. To perform these analyses we propose the non-proportional odds multivariate logistic regression model and take a simulation-based approach to model fitting using Markov chain Monte Carlo methods, such as partially collapsed Gibbs sampling and the Metropolis algorithm. We applied the proposed methodology to male pattern baldness data from the Victorian Family Heart Study. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Plasma neutrophil gelatinase-associated lipocalin: a marker of acute pyelonephritis in children.

PubMed

Kim, Byung Kwan; Yim, Hyung Eun; Yoo, Kee Hwan

2017-03-01

This study was designed to compare the diagnostic accuracy of plasma neutrophil gelatinase-associated lipocalin (NGAL) with procalcitonin (PCT), C-reactive protein (CRP), and white blood cells (WBCs) for predicting acute pyelonephritis (APN) in children with febrile urinary tract infections (UTIs). In total, 138 children with febrile UTIs (APN 59, lower UTI 79) were reviewed retrospectively. Levels of NGAL, PCT, CRP, and WBCs in blood were measured on admission. The diagnostic accuracy of the biomarkers was investigated. Independent predictors of APN were identified by multivariate logistic regression analysis. Receiver operating curve (ROC) analyses showed good diagnostic profiles of NGAL, PCT, CRP, and WBCs for identifying APN [area under the curve (AUC) 0.893, 0.855, 0.879, and 0.654, respectively]. However, multivariate analysis revealed only plasma NGAL level was an independent predictor of APN (P = 0.006). At the best cutoff values of all examined biomarkers for identifying APN, sensitivity (86 %), specificity (85 %), positive predictive value (81 %), and negative predictive value (89 %) of plasma NGAL levels were the highest. The optimal NGAL cutoff value was 117 ng/ml. The positive likelihood ratio [odds ratio (OR) 5.69, 95 % confidence interval (CI) 3.56-8.78], and negative likelihood ratio (OR 0.16, 95 % CI 0.08-0.29) of plasma NGAL for APN diagnosis also showed it seemed to be more accurate than serum PCT, CRP, and WBCs. Plasma NGAL can be more useful than serum PCT, CRP, and WBC levels for identifying APN in children with febrile UTIs.

Retrospective Analysis of 255 Papillary Thyroid Carcinomas ≤2 cm: Clinicohistological Features and Prognostic Factors.

PubMed

Marques, Pedro; Leite, Valeriano; Bugalho, Maria João

2014-12-01

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. The widespread use of neck ultrasound (US) and US-guided fine-needle aspiration cytology is triggering an overdiagnosis of PTC. To evaluate clinical behavior and outcomes of patients with PTCs ≤2 cm, seeking for possible prognostic factors. Clinical records of cases with histological diagnosis of PTC ≤2 cm followed at the Endocrine Department of Instituto Português de Oncologia, Lisbon between 2002 and 2006 were analyzed retrospectively. We identified 255 PTCs, 111 were microcarcinomas. Most patients underwent near-total thyroidectomy, with lymph node dissections in 55 cases (21.6%). Radioiodine therapy was administered in 184 patients. At the last evaluation, 38 (14.9%) had evidence of disease. Two deaths were attributed to PTC. Median (±SD) follow-up was 74 (±23) months. Multivariate analysis identified vascular invasion, lymph node and systemic metastases significantly associated with recurrence/persistence of disease. In addition, lymph node involvement was significantly associated with extrathyroidal extension and angioinvasion. Median (±SD) disease-free survival (DFS) was estimated as 106 (±3) months and the 5-year DFS rate was 87.5%. Univariate Cox analysis identified some relevant parameters for DFS, but multivariate regression only identified lymph node and systemic metastases as significant independent factors. The median DFS estimated for lymph node and systemic metastases was 75 and 0 months, respectively. In the setting of small PTCs, vascular invasion, extrathyroidal extension and lymph node and/or systemic metastases may confer worse prognosis, perhaps justifying more aggressive therapeutic and follow-up approaches in such cases.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion.

PubMed

Goldrick, Stephen; Holmes, William; Bond, Nicholas J; Lewis, Gareth; Kuiper, Marcel; Turner, Richard; Farid, Suzanne S

2017-10-01

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (Ambr TM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on-line and off-line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale-up. Biotechnol. Bioeng. 2017;114: 2222-2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

Risk factors for early failure after peripheral endovascular intervention: application of a reliability engineering approach.

PubMed

Meltzer, Andrew J; Graham, Ashley; Connolly, Peter H; Karwowski, John K; Bush, Harry L; Frazier, Peter I; Schneider, Darren B

2013-01-01

We apply an innovative and novel analytic approach, based on reliability engineering (RE) principles frequently used to characterize the behavior of manufactured products, to examine outcomes after peripheral endovascular intervention. We hypothesized that this would allow for improved prediction of outcome after peripheral endovascular intervention, specifically with regard to identification of risk factors for early failure. Patients undergoing infrainguinal endovascular intervention for chronic lower-extremity ischemia from 2005 to 2010 were identified in a prospectively maintained database. The primary outcome of failure was defined as patency loss detected by duplex ultrasonography, with or without clinical failure. Analysis included univariate and multivariate Cox regression models, as well as RE-based analysis including product life-cycle models and Weibull failure plots. Early failures were distinguished using the RE principle of "basic rating life," and multivariate models identified independent risk factors for early failure. From 2005 to 2010, 434 primary endovascular peripheral interventions were performed for claudication (51.8%), rest pain (16.8%), or tissue loss (31.3%). Fifty-five percent of patients were aged ≥75 years; 57% were men. Failure was noted after 159 (36.6%) interventions during a mean follow-up of 18 months (range, 0-71 months). Using multivariate (Cox) regression analysis, rest pain and tissue loss were independent predictors of patency loss, with hazard ratios of 2.5 (95% confidence interval, 1.6-4.1; P < 0.001) and 3.2 (95% confidence interval, 2.0-5.2, P < 0.001), respectively. The distribution of failure times for both claudication and critical limb ischemia fit distinct Weibull plots, with different characteristics: interventions for claudication demonstrated an increasing failure rate (β = 1.22, θ = 13.46, mean time to failure = 12.603 months, index of fit = 0.99037, R(2) = 0.98084), whereas interventions for critical limb ischemia demonstrated a decreasing failure rate, suggesting the predominance of early failures (β = 0.7395, θ = 6.8, mean time to failure = 8.2, index of fit = 0.99391, R(2) = 0.98786). By 3.1 months, 10% of interventions failed. This point (90% reliability) was identified as the basic rating life. Using multivariate analysis of failure data, independent predictors of early failure (before 3.1 months) included tissue loss, long lesion length, chronic total occlusions, heart failure, and end-stage renal disease. Application of a RE framework to the assessment of clinical outcomes after peripheral interventions is feasible, and potentially more informative than traditional techniques. Conceptualization of interventions as "products" permits application of product life-cycle models that allow for empiric definition of "early failure" may facilitate comparative effectiveness analysis and enable the development of individualized surveillance programs after endovascular interventions. Copyright © 2013 Annals of Vascular Surgery Inc. Published by Elsevier Inc. All rights reserved.

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2013-01-01

A new regression model search algorithm was developed in 2011 that may be used to analyze both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The new algorithm is a simplified version of a more complex search algorithm that was originally developed at the NASA Ames Balance Calibration Laboratory. The new algorithm has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression models. Therefore, the simplified search algorithm is not intended to replace the original search algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm either fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new regression model search algorithm.

Comprehensive ripeness-index for prediction of ripening level in mangoes by multivariate modelling of ripening behaviour

NASA Astrophysics Data System (ADS)

Eyarkai Nambi, Vijayaram; Thangavel, Kuladaisamy; Manickavasagan, Annamalai; Shahir, Sultan

2017-01-01

Prediction of ripeness level in climacteric fruits is essential for post-harvest handling. An index capable of predicting ripening level with minimum inputs would be highly beneficial to the handlers, processors and researchers in fruit industry. A study was conducted with Indian mango cultivars to develop a ripeness index and associated model. Changes in physicochemical, colour and textural properties were measured throughout the ripening period and the period was classified into five stages (unripe, early ripe, partially ripe, ripe and over ripe). Multivariate regression techniques like partial least square regression, principal component regression and multi linear regression were compared and evaluated for its prediction. Multi linear regression model with 12 parameters was found more suitable in ripening prediction. Scientific variable reduction method was adopted to simplify the developed model. Better prediction was achieved with either 2 or 3 variables (total soluble solids, colour and acidity). Cross validation was done to increase the robustness and it was found that proposed ripening index was more effective in prediction of ripening stages. Three-variable model would be suitable for commercial applications where reasonable accuracies are sufficient. However, 12-variable model can be used to obtain more precise results in research and development applications.

Gambling disorder-related illegal acts: Regression model of associated factors

PubMed Central

Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; JEU Group; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie

2017-01-01

Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions. PMID:28198636

Gambling disorder-related illegal acts: Regression model of associated factors.

PubMed

Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie

2017-03-01

Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions.

A population study of the contribution of medical comorbidity to the risk of prematurity in blacks.

PubMed

Ehrenthal, Deborah B; Jurkovitz, Claudine; Hoffman, Matthew; Kroelinger, Charlan; Weintraub, William

2007-10-01

The purpose of this study was to test the hypothesis that the higher prevalence of medical comorbidities among black women accounts for their increased risk of prematurity. A population-based regional cohort of women receiving obstetric care for singleton pregnancies at a large community hospital between 2003 and 2006 were analyzed using univariate and multivariable logistic regression. Data for 18,624 consecutive births found increased odds of adverse outcomes for black compared to white women: prematurity OR = 1.6 (1.4-1.8), extreme prematurity OR = 2.5 (2.0-3.2). Logistic regression modeling identified black race, age < 20, preconception diabetes and hypertension, smoking, underweight, and gestational hypertension as the greatest risks for adverse outcomes. Controlling for these risks did not attenuate the higher risk for prematurity among blacks. Though there is a greater burden of health risk among black women, this did not account for the higher rates of low birthweight and prematurity.

Dirichlet Component Regression and its Applications to Psychiatric Data

PubMed Central

Gueorguieva, Ralitza; Rosenheck, Robert; Zelterman, Daniel

2011-01-01

Summary We describe a Dirichlet multivariable regression method useful for modeling data representing components as a percentage of a total. This model is motivated by the unmet need in psychiatry and other areas to simultaneously assess the effects of covariates on the relative contributions of different components of a measure. The model is illustrated using the Positive and Negative Syndrome Scale (PANSS) for assessment of schizophrenia symptoms which, like many other metrics in psychiatry, is composed of a sum of scores on several components, each in turn, made up of sums of evaluations on several questions. We simultaneously examine the effects of baseline socio-demographic and co-morbid correlates on all of the components of the total PANSS score of patients from a schizophrenia clinical trial and identify variables associated with increasing or decreasing relative contributions of each component. Several definitions of residuals are provided. Diagnostics include measures of overdispersion, Cook’s distance, and a local jackknife influence metric. PMID:22058582

Polycyclic aromatic hydrocarbons in ambient air, surface soil and wheat grain near a large steel-smelting manufacturer in northern China.

PubMed

Liu, Weijian; Wang, Yilong; Chen, Yuanchen; Tao, Shu; Liu, Wenxin

2017-07-01

The total concentrations and component profiles of polycyclic aromatic hydrocarbons (PAHs) in ambient air, surface soil and wheat grain collected from wheat fields near a large steel-smelting manufacturer in Northern China were determined. Based on the specific isomeric ratios of paired species in ambient air, principle component analysis and multivariate linear regression, the main emission source of local PAHs was identified as a mixture of industrial and domestic coal combustion, biomass burning and traffic exhaust. The total organic carbon (TOC) fraction was considerably correlated with the total and individual PAH concentrations in surface soil. The total concentrations of PAHs in wheat grain were relatively low, with dominant low molecular weight constituents, and the compositional profile was more similar to that in ambient air than in topsoil. Combined with more significant results from partial correlation and linear regression models, the contribution from air PAHs to grain PAHs may be greater than that from soil PAHs. Copyright © 2016. Published by Elsevier B.V.

Contextual predictive factors of child sexual abuse: the role of parent-child interaction.

PubMed

Ramírez, Clemencia; Pinzón-Rondón, Angela María; Botero, Juan Carlos

2011-12-01

To determine the prevalence of child sexual abuse in the Colombian coasts, as well as to assess the role of parent-child interactions on its occurrence and to identify factors from different environmental levels that predict it. This cross-sectional study explores the results of 1,089 household interviews responded by mothers. Descriptive analyses and multivariate logistic regressions were conducted, with child sexual abuse regressed on parent-child interactions, children's characteristics, maternal characteristics, family characteristics, and community characteristics. 1.2% of the mothers reported that their children had been sexually abused. Families that communicated with their children were less likely to report child sexual abuse, each additional standard deviation of communication reduced child sexual abuse 3.5 times. Affection and negative treatment to the children were not associated with child sexual abuse. Families who experienced intimate partner violence and violent communities were more likely to experience child sexual abuse. Interventions are needed to address the problem of child sexual abuse. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Pilot Study of Reasons and Risk Factors for "No-Shows" in a Pediatric Neurology Clinic.

PubMed

Guzek, Lindsay M; Fadel, William F; Golomb, Meredith R

2015-09-01

Missed clinic appointments lead to decreased patient access, worse patient outcomes, and increased healthcare costs. The goal of this pilot study was to identify reasons for and risk factors associated with missed pediatric neurology outpatient appointments ("no-shows"). This was a prospective cohort study of patients scheduled for 1 week of clinic. Data on patient clinical and demographic information were collected by record review; data on reasons for missed appointments were collected by phone interviews. Univariate and multivariate analyses were conducted using chi-square tests and multiple logistic regression to assess risk factors for missed appointments. Fifty-nine (25%) of 236 scheduled patients were no-shows. Scheduling conflicts (25.9%) and forgetting (20.4%) were the most common reasons for missed appointments. When controlling for confounding factors in the logistic regression, Medicaid (odds ratio 2.36), distance from clinic, and time since appointment was scheduled were associated with missed appointments. Further work in this area is needed. © The Author(s) 2014.

Prediction of all-cause death in hemodialysis patients using elevated postdialysis pulse wave velocity.

PubMed

Fu, Xiaohong; Yang, Jihong; Fan, Zhaoxin; Chen, Xianguang; Wu, Jie; Li, Jie; Wu, Hua

2016-02-01

To identify the relationship between predialysis pulse wave velocity (PWV), postdialysis PWV during 1 hemodialysis (HD) session, and deaths in maintenance HD patients. 43 patients were recruited. PWV was measured before and after one HD session and dialysis- related data were recorded. Clinical data such as blood pressure, blood lipids, and blood glucose, were carefully observed and managed in a 5-year follow-up. The association between all-cause death, predialysis PWV, postdialysis PWV, change of PWV (ΔPWV), and other related variables were analyzed. After 5 years, 17 patients (39.5%) died. Univariate Cox regression analysis showed that all-cause death of the patients significantly correlated with age, postdialysis PWV, and ΔPWV. Multivariate Cox regression analysis revealed that postdialysis PWV was an independent predictor for all-cause death in these patients (HR: 1.377, 95% CI: 1.146 - 1.656, p = 0.001). Elevated postdialysis PWV significantly correlated with and was an independent predictor for all-cause death in maintenance HD patients.