The Effect of Sitagliptin on the Regression of Carotid Intima-Media Thickening in Patients with Type 2 Diabetes Mellitus: A Post Hoc Analysis of the Sitagliptin Preventive Study of Intima-Media Thickness Evaluation.

PubMed

Mita, Tomoya; Katakami, Naoto; Shiraiwa, Toshihiko; Yoshii, Hidenori; Gosho, Masahiko; Shimomura, Iichiro; Watada, Hirotaka

2017-01-01

Background. The effect of dipeptidyl peptidase-4 (DPP-4) inhibitors on the regression of carotid IMT remains largely unknown. The present study aimed to clarify whether sitagliptin, DPP-4 inhibitor, could regress carotid intima-media thickness (IMT) in insulin-treated patients with type 2 diabetes mellitus (T2DM). Methods . This is an exploratory analysis of a randomized trial in which we investigated the effect of sitagliptin on the progression of carotid IMT in insulin-treated patients with T2DM. Here, we compared the efficacy of sitagliptin treatment on the number of patients who showed regression of carotid IMT of ≥0.10 mm in a post hoc analysis. Results . The percentages of the number of the patients who showed regression of mean-IMT-CCA (28.9% in the sitagliptin group versus 16.4% in the conventional group, P  = 0.022) and left max-IMT-CCA (43.0% in the sitagliptin group versus 26.2% in the conventional group, P  = 0.007), but not right max-IMT-CCA, were higher in the sitagliptin treatment group compared with those in the non-DPP-4 inhibitor treatment group. In multiple logistic regression analysis, sitagliptin treatment significantly achieved higher target attainment of mean-IMT-CCA ≥0.10 mm and right and left max-IMT-CCA ≥0.10 mm compared to conventional treatment. Conclusions . Our data suggested that DPP-4 inhibitors were associated with the regression of carotid atherosclerosis in insulin-treated T2DM patients. This study has been registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN000007396).

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

PubMed Central

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

2017-01-01

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

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

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

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

PubMed

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

2003-08-20

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

Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Su, Edwin P; Grauer, Jonathan N

2018-03-01

Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2017-01-01

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

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis

PubMed Central

Kim, Seong-Gil

2018-01-01

Background The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. Material/Methods This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. Results In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). Conclusions Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement. PMID:29760375

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis.

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

BACKGROUND The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. MATERIAL AND METHODS This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. RESULTS In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). CONCLUSIONS Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement.

Cluster Analysis of Campylobacter jejuni Genotypes Isolated from Small and Medium-Sized Mammalian Wildlife and Bovine Livestock from Ontario Farms.

PubMed

Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S K; Jardine, C M

2017-05-01

Using data collected from a cross-sectional study of 25 farms (eight beef, eight swine and nine dairy) in 2010, we assessed clustering of molecular subtypes of C. jejuni based on a Campylobacter-specific 40 gene comparative genomic fingerprinting assay (CGF40) subtypes, using unweighted pair-group method with arithmetic mean (UPGMA) analysis, and multiple correspondence analysis. Exact logistic regression was used to determine which genes differentiate wildlife and livestock subtypes in our study population. A total of 33 bovine livestock (17 beef and 16 dairy), 26 wildlife (20 raccoon (Procyon lotor), five skunk (Mephitis mephitis) and one mouse (Peromyscus spp.) C. jejuni isolates were subtyped using CGF40. Dendrogram analysis, based on UPGMA, showed distinct branches separating bovine livestock and mammalian wildlife isolates. Furthermore, two-dimensional multiple correspondence analysis was highly concordant with dendrogram analysis showing clear differentiation between livestock and wildlife CGF40 subtypes. Based on multilevel logistic regression models with a random intercept for farm of origin, we found that isolates in general, and raccoons more specifically, were significantly more likely to be part of the wildlife branch. Exact logistic regression conducted gene by gene revealed 15 genes that were predictive of whether an isolate was of wildlife or bovine livestock isolate origin. Both multiple correspondence analysis and exact logistic regression revealed that in most cases, the presence of a particular gene (13 of 15) was associated with an isolate being of livestock rather than wildlife origin. In conclusion, the evidence gained from dendrogram analysis, multiple correspondence analysis and exact logistic regression indicates that mammalian wildlife carry CGF40 subtypes of C. jejuni distinct from those carried by bovine livestock. Future studies focused on source attribution of C. jejuni in human infections will help determine whether wildlife transmit Campylobacter jejuni directly to humans. © 2016 Blackwell Verlag GmbH.

Identification of Extremely Premature Infants at High Risk of Rehospitalization

PubMed Central

Carlo, Waldemar A.; McDonald, Scott A.; Yao, Qing; Das, Abhik; Higgins, Rosemary D.

2011-01-01

OBJECTIVE: Extremely low birth weight infants often require rehospitalization during infancy. Our objective was to identify at the time of discharge which extremely low birth weight infants are at higher risk for rehospitalization. METHODS: Data from extremely low birth weight infants in Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers from 2002–2005 were analyzed. The primary outcome was rehospitalization by the 18- to 22-month follow-up, and secondary outcome was rehospitalization for respiratory causes in the first year. Using variables and odds ratios identified by stepwise logistic regression, scoring systems were developed with scores proportional to odds ratios. Classification and regression-tree analysis was performed by recursive partitioning and automatic selection of optimal cutoff points of variables. RESULTS: A total of 3787 infants were evaluated (mean ± SD birth weight: 787 ± 136 g; gestational age: 26 ± 2 weeks; 48% male, 42% black). Forty-five percent of the infants were rehospitalized by 18 to 22 months; 14.7% were rehospitalized for respiratory causes in the first year. Both regression models (area under the curve: 0.63) and classification and regression-tree models (mean misclassification rate: 40%–42%) were moderately accurate. Predictors for the primary outcome by regression were shunt surgery for hydrocephalus, hospital stay of >120 days for pulmonary reasons, necrotizing enterocolitis stage II or higher or spontaneous gastrointestinal perforation, higher fraction of inspired oxygen at 36 weeks, and male gender. By classification and regression-tree analysis, infants with hospital stays of >120 days for pulmonary reasons had a 66% rehospitalization rate compared with 42% without such a stay. CONCLUSIONS: The scoring systems and classification and regression-tree analysis models identified infants at higher risk of rehospitalization and might assist planning for care after discharge. PMID:22007016

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

Discrimination of serum Raman spectroscopy between normal and colorectal cancer

NASA Astrophysics Data System (ADS)

Li, Xiaozhou; Yang, Tianyue; Yu, Ting; Li, Siqi

2011-07-01

Raman spectroscopy of tissues has been widely studied for the diagnosis of various cancers, but biofluids were seldom used as the analyte because of the low concentration. Herein, serum of 30 normal people, 46 colon cancer, and 44 rectum cancer patients were measured Raman spectra and analyzed. The information of Raman peaks (intensity and width) and that of the fluorescence background (baseline function coefficients) were selected as parameters for statistical analysis. Principal component regression (PCR) and partial least square regression (PLSR) were used on the selected parameters separately to see the performance of the parameters. PCR performed better than PLSR in our spectral data. Then linear discriminant analysis (LDA) was used on the principal components (PCs) of the two regression method on the selected parameters, and a diagnostic accuracy of 88% and 83% were obtained. The conclusion is that the selected features can maintain the information of original spectra well and Raman spectroscopy of serum has the potential for the diagnosis of colorectal cancer.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

a Comparison Between Two Ols-Based Approaches to Estimating Urban Multifractal Parameters

NASA Astrophysics Data System (ADS)

Huang, Lin-Shan; Chen, Yan-Guang

Multifractal theory provides a new spatial analytical tool for urban studies, but many basic problems remain to be solved. Among various pending issues, the most significant one is how to obtain proper multifractal dimension spectrums. If an algorithm is improperly used, the parameter spectrums will be abnormal. This paper is devoted to investigating two ordinary least squares (OLS)-based approaches for estimating urban multifractal parameters. Using empirical study and comparative analysis, we demonstrate how to utilize the adequate linear regression to calculate multifractal parameters. The OLS regression analysis has two different approaches. One is that the intercept is fixed to zero, and the other is that the intercept is not limited. The results of comparative study show that the zero-intercept regression yields proper multifractal parameter spectrums within certain scale range of moment order, while the common regression method often leads to abnormal multifractal parameter values. A conclusion can be reached that fixing the intercept to zero is a more advisable regression method for multifractal parameters estimation, and the shapes of spectral curves and value ranges of fractal parameters can be employed to diagnose urban problems. This research is helpful for scientists to understand multifractal models and apply a more reasonable technique to multifractal parameter calculations.

Detection of outliers in the response and explanatory variables of the simple circular regression model

NASA Astrophysics Data System (ADS)

Mahmood, Ehab A.; Rana, Sohel; Hussin, Abdul Ghapor; Midi, Habshah

2016-06-01

The circular regression model may contain one or more data points which appear to be peculiar or inconsistent with the main part of the model. This may be occur due to recording errors, sudden short events, sampling under abnormal conditions etc. The existence of these data points "outliers" in the data set cause lot of problems in the research results and the conclusions. Therefore, we should identify them before applying statistical analysis. In this article, we aim to propose a statistic to identify outliers in the both of the response and explanatory variables of the simple circular regression model. Our proposed statistic is robust circular distance RCDxy and it is justified by the three robust measurements such as proportion of detection outliers, masking and swamping rates.

Complexities and potential pitfalls of clinical study design and data analysis in assisted reproduction.

PubMed

Patounakis, George; Hill, Micah J

2018-06-01

The purpose of the current review is to describe the common pitfalls in design and statistical analysis of reproductive medicine studies. It serves to guide both authors and reviewers toward reducing the incidence of spurious statistical results and erroneous conclusions. The large amount of data gathered in IVF cycles leads to problems with multiplicity, multicollinearity, and over fitting of regression models. Furthermore, the use of the word 'trend' to describe nonsignificant results has increased in recent years. Finally, methods to accurately account for female age in infertility research models are becoming more common and necessary. The pitfalls of study design and analysis reviewed provide a framework for authors and reviewers to approach clinical research in the field of reproductive medicine. By providing a more rigorous approach to study design and analysis, the literature in reproductive medicine will have more reliable conclusions that can stand the test of time.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

PubMed Central

Huang, Desheng; Guan, Peng; Guo, Junqiao; Wang, Ping; Zhou, Baosen

2008-01-01

Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations. PMID:18816415

Hybrid ICA-Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals.

PubMed

Mannan, Malik M Naeem; Jeong, Myung Y; Kamran, Muhammad A

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG.

Hybrid ICA—Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals

PubMed Central

Mannan, Malik M. Naeem; Jeong, Myung Y.; Kamran, Muhammad A.

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG. PMID:27199714

Evaluating the utility of companion animal tick surveillance practices for monitoring spread and occurrence of human Lyme disease in West Virginia, 2014-2016.

PubMed

Hendricks, Brian; Mark-Carew, Miguella; Conley, Jamison

2017-11-13

Domestic dogs and cats are potentially effective sentinel populations for monitoring occurrence and spread of Lyme disease. Few studies have evaluated the public health utility of sentinel programmes using geo-analytic approaches. Confirmed Lyme disease cases diagnosed by physicians and ticks submitted by veterinarians to the West Virginia State Health Department were obtained for 2014-2016. Ticks were identified to species, and only Ixodes scapularis were incorporated in the analysis. Separate ordinary least squares (OLS) and spatial lag regression models were conducted to estimate the association between average numbers of Ix. scapularis collected on pets and human Lyme disease incidence. Regression residuals were visualised using Local Moran's I as a diagnostic tool to identify spatial dependence. Statistically significant associations were identified between average numbers of Ix. scapularis collected from dogs and human Lyme disease in the OLS (β=20.7, P<0.001) and spatial lag (β=12.0, P=0.002) regression. No significant associations were identified for cats in either regression model. Statistically significant (P≤0.05) spatial dependence was identified in all regression models. Local Moran's I maps produced for spatial lag regression residuals indicated a decrease in model over- and under-estimation, but identified a higher number of statistically significant outliers than OLS regression. Results support previous conclusions that dogs are effective sentinel populations for monitoring risk of human exposure to Lyme disease. Findings reinforce the utility of spatial analysis of surveillance data, and highlight West Virginia's unique position within the eastern United States in regards to Lyme disease occurrence.

A study of home deaths in Japan from 1951 to 2002

PubMed Central

Yang, Limin; Sakamoto, Naoko; Marui, Eiji

2006-01-01

Background Several surveys in Japan have indicated that most terminally ill Japanese patients would prefer to die at home or in a homelike setting. However, there is a great disparity between this stated preference and the reality, since most Japanese die in hospital. We report here national changes in home deaths in Japan over the last 5 decades. Using prefecture data, we also examined the factors in the medical service associated with home death in Japan. Methods Published data on place of death was obtained from the vital statistics compiled by the Ministry of Health, Labor and Welfare of Japan. We analyzed trends of home deaths from 1951 to 2002, and describe the changes in the proportion of home deaths by region, sex, age, and cause of death. Joinpoint regression analysis was used for trend analysis. Logistic regression analysis was performed to identify secular trends in home deaths, and the impact of age, sex, year of deaths and cause of deaths on home death. We also examined the association between home death and medical service factors by multiple regression analysis, using home death rate by prefectures in 2002 as a dependent variable. Results A significant decrease in the percentage of patients dying at home was observed in the results of joinpoint regression analysis. Older patients and males were more likely to die at home. Patients who died from cancer were less likely to die at home. The results of multiple regression analysis indicated that home death was related to the number of beds in hospital, ratio of daily occupied beds in general hospital, the number of families in which the elderly were living alone, and dwelling rooms. Conclusion The pattern of the place of death has not only been determined by social and demographic characteristics of the decedent, but also associated with the medical service in the community. PMID:16524485

Comparing nouns and verbs in a lexical task.

PubMed

Cordier, Françoise; Croizet, Jean-Claude; Rigalleau, François

2013-02-01

We analyzed the differential processing of nouns and verbs in a lexical decision task. Moderate and high-frequency nouns and verbs were compared. The characteristics of our material were specified at the formal level (number of letters and syllables, number of homographs, orthographic neighbors, frequency and age of acquisition), and at the semantic level (imagery, number and strength of associations, number of meanings, context dependency). A regression analysis indicated a classical frequency effect and a word-type effect, with latencies for verbs being slower than for nouns. The regression analysis did not permit the conclusion that semantic effects were involved (particularly imageability). Nevertheless, the semantic opposition between nouns as prototypical representations of objects, and verbs as prototypical representation of actions was not tested in this experiment and remains a good candidate explanation of the response time discrepancies between verbs and nouns.

Effective psychological and psychosocial approaches to reduce repetition of self-harm: a systematic review, meta-analysis and meta-regression

PubMed Central

Robinson, Jo; Spittal, Matthew J; Carter, Greg

2016-01-01

Objective To examine the efficacy of psychological and psychosocial interventions for reductions in repeated self-harm. Design We conducted a systematic review, meta-analysis and meta-regression to examine the efficacy of psychological and psychosocial interventions to reduce repeat self-harm in adults. We included a sensitivity analysis of studies with a low risk of bias for the meta-analysis. For the meta-regression, we examined whether the type, intensity (primary analyses) and other components of intervention or methodology (secondary analyses) modified the overall intervention effect. Data sources A comprehensive search of MEDLINE, PsycInfo and EMBASE (from 1999 to June 2016) was performed. Eligibility criteria for selecting studies Randomised controlled trials of psychological and psychosocial interventions for adult self-harm patients. Results Forty-five trials were included with data available from 36 (7354 participants) for the primary analysis. Meta-analysis showed a significant benefit of all psychological and psychosocial interventions combined (risk ratio 0.84; 95% CI 0.74 to 0.96; number needed to treat=33); however, sensitivity analyses showed that this benefit was non-significant when restricted to a limited number of high-quality studies. Meta-regression showed that the type of intervention did not modify the treatment effects. Conclusions Consideration of a psychological or psychosocial intervention over and above treatment as usual is worthwhile; with the public health benefits of ensuring that this practice is widely adopted potentially worth the investment. However, the specific type and nature of the intervention that should be delivered is not yet clear. Cognitive–behavioural therapy or interventions with an interpersonal focus and targeted on the precipitants to self-harm may be the best candidates on the current evidence. Further research is required. PMID:27660314

Kernel machine SNP set analysis provides new insight into the association between obesity and polymorphisms located on the chromosomal 16q.12.2 region: Tehran Lipid and Glucose Study.

PubMed

Javanrouh, Niloufar; Daneshpour, Maryam S; Soltanian, Ali Reza; Tapak, Leili

2018-06-05

Obesity is a serious health problem that leads to low quality of life and early mortality. To the purpose of prevention and gene therapy for such a worldwide disease, genome wide association study is a powerful tool for finding SNPs associated with increased risk of obesity. To conduct an association analysis, kernel machine regression is a generalized regression method, has an advantage of considering the epistasis effects as well as the correlation between individuals due to unknown factors. In this study, information of the people who participated in Tehran cardio-metabolic genetic study was used. They were genotyped for the chromosomal region, evaluation 986 variations located at 16q12.2; build 38hg. Kernel machine regression and single SNP analysis were used to assess the association between obesity and SNPs genotyped data. We found that associated SNP sets with obesity, were almost in the FTO (P = 0.01), AIKTIP (P = 0.02) and MMP2 (P = 0.02) genes. Moreover, two SNPs, i.e., rs10521296 and rs11647470, showed significant association with obesity using kernel regression (P = 0.02). In conclusion, significant sets were randomly distributed throughout the region with more density around the FTO, AIKTIP and MMP2 genes. Furthermore, two intergenic SNPs showed significant association after using kernel machine regression. Therefore, more studies have to be conducted to assess their functionality or precise mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.

Eye regression in blind Astyanax cavefish may facilitate the evolution of an adaptive behavior and its sensory receptors.

PubMed

Borowsky, Richard

2013-07-11

The forces driving the evolutionary loss or simplification of traits such as vision and pigmentation in cave animals are still debated. Three alternative hypotheses are direct selection against the trait, genetic drift, and indirect selection due to antagonistic pleiotropy. Recent work establishes that Astyanax cavefish exhibit vibration attraction behavior (VAB), a presumed behavioral adaptation to finding food in the dark not exhibited by surface fish. Genetic analysis revealed two regions in the genome with quantitative trait loci (QTL) for both VAB and eye size. These observations were interpreted as genetic evidence that selection for VAB indirectly drove eye regression through antagonistic pleiotropy and, further, that this is a general mechanism to account for regressive evolution. These conclusions are unsupported by the data; the analysis fails to establish pleiotropy and ignores the numerous other QTL that map to, and potentially interact, in the same regions. It is likely that all three forces drive evolutionary change. We will be able to distinguish among them in individual cases only when we have identified the causative alleles and characterized their effects.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea

PubMed Central

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-01-01

Objectives The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Methods Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. Results GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD – negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. Conclusions The results suggest that psychological and medical approaches should be combined in GERD assessment. PMID:27691373

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

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

PubMed Central

2013-01-01

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

Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies.

PubMed

Shardell, Michelle; Harris, Anthony D; El-Kamary, Samer S; Furuno, Jon P; Miller, Ram R; Perencevich, Eli N

2007-10-01

Quasi-experimental study designs are frequently used to assess interventions that aim to limit the emergence of antimicrobial-resistant pathogens. However, previous studies using these designs have often used suboptimal statistical methods, which may result in researchers making spurious conclusions. Methods used to analyze quasi-experimental data include 2-group tests, regression analysis, and time-series analysis, and they all have specific assumptions, data requirements, strengths, and limitations. An example of a hospital-based intervention to reduce methicillin-resistant Staphylococcus aureus infection rates and reduce overall length of stay is used to explore these methods.

Fall-related self-efficacy, not balance and mobility performance, is related to accidental falls in chronic stroke survivors with low bone mineral density

PubMed Central

Pang, Marco Y.C.; Eng, Janice J.

2011-01-01

Introduction Chronic stroke survivors with low bone mineral density (BMD) are particularly prone to fragility fractures. The purpose of this study was to identify the determinants of balance, mobility and falls in this sub-group of stroke patients. Methods Thirty nine chronic stroke survivors with low hip BMD (T-score <-1.0) were studied. Each subject was evaluated for: balance, mobility, leg muscle strength, spasticity, and falls-related self-efficacy. Any falls in the past 12 months were also recorded. Multiple regression analysis was used to identify the determinants of balance and mobility performance whereas logistic regression was used to identify the determinants of falls. Results Multiple regression analysis revealed that after adjusting for basic demographics, falls-related self-efficacy remained independently associated with balance/mobility performance (R2=0.494, P<0.001). Logistic regression showed that falls-related self-efficacy, but not balance and mobility performance, was a significant determinant of falls (odds ratio: 0.18, P=0.04). Conclusions Falls-related self-efficacy, but not mobility and balance performance, was the most important determinant of accidental falls. This psychological factor should not be overlooked in the prevention of fragility fractures among chronic stroke survivors with low hip BMD. PMID:18097709

Vascular Disease, ESRD, and Death: Interpreting Competing Risk Analyses

PubMed Central

Coresh, Josef; Segev, Dorry L.; Kucirka, Lauren M.; Tighiouart, Hocine; Sarnak, Mark J.

2012-01-01

Summary Background and objectives Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. Design, setting, participants, & measurements This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989–1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. Results The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20–2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15–2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. Conclusions When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors. PMID:22859747

Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis

PubMed Central

Hill, Andrew; Loh, Po-Ru; Bharadwaj, Ragu B.; Pons, Pascal; Shang, Jingbo; Guinan, Eva; Lakhani, Karim; Kilty, Iain

2017-01-01

Abstract Background: The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Results: Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Conclusions: Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics. PMID:28327993

Ethical climate as a moderator between organizational trust and whistle-blowing among nurses and secretaries

PubMed Central

Aydan, Seda; Kaya, Sidika

2018-01-01

Objectives: To reveal the effect of perception of ethical climate by nurses and secretaries and their level of organizational trust on their whistleblowing intention. Methods: Nurses and secretaries working in a University Hospital in Ankara, Turkey, were enrolled in the study conducted in 2016. Responses were received from 369 nurses and secretaries working at Clinics and Polyclinics. Path analysis, investigation of structural equation models used while multi-regression analysis was also applied. Results: According to the regression model, ethical climate dimensions, profession, gender, and work place had significant impact on the whistleblowing intention. According to Path analysis, ethical climate had direct impact of 69% on whistleblowing intention. It was seen that organizational trust had an indirect impact of 27% on the whistleblowing score when ethical climate had a moderator role. Conclusion: In order to promote whistleblowing in organizations, it is important to keep the ethical climate perception of employees and the level of their organizational trust at high levels. PMID:29805421

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

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

How is the weather? Forecasting inpatient glycemic control

PubMed Central

Saulnier, George E; Castro, Janna C; Cook, Curtiss B; Thompson, Bithika M

2017-01-01

Aim: Apply methods of damped trend analysis to forecast inpatient glycemic control. Method: Observed and calculated point-of-care blood glucose data trends were determined over 62 weeks. Mean absolute percent error was used to calculate differences between observed and forecasted values. Comparisons were drawn between model results and linear regression forecasting. Results: The forecasted mean glucose trends observed during the first 24 and 48 weeks of projections compared favorably to the results provided by linear regression forecasting. However, in some scenarios, the damped trend method changed inferences compared with linear regression. In all scenarios, mean absolute percent error values remained below the 10% accepted by demand industries. Conclusion: Results indicate that forecasting methods historically applied within demand industries can project future inpatient glycemic control. Additional study is needed to determine if forecasting is useful in the analyses of other glucometric parameters and, if so, how to apply the techniques to quality improvement. PMID:29134125

Regressive research: The pitfalls of post hoc data selection in the study of unconscious mental processes.

PubMed

Shanks, David R

2017-06-01

Many studies of unconscious processing involve comparing a performance measure (e.g., some assessment of perception or memory) with an awareness measure (such as a verbal report or a forced-choice response) taken either concurrently or separately. Unconscious processing is inferred when above-chance performance is combined with null awareness. Often, however, aggregate awareness is better than chance, and data analysis therefore employs a form of extreme group analysis focusing post hoc on participants, trials, or items where awareness is absent or at chance. The pitfalls of this analytic approach are described with particular reference to recent research on implicit learning and subliminal perception. Because of regression to the mean, the approach can mislead researchers into erroneous conclusions concerning unconscious influences on behavior. Recommendations are made about future use of post hoc selection in research on unconscious cognition.

Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593

The reproductive outcome of female patients with myotonic dystrophy type 1 (DM1) undergoing PGD is not affected by the size of the expanded CTG repeat tract

PubMed Central

Seneca, Sara; De Rademaeker, Marjan; Sermon, Karen; De Rycke, Martine; De Vos, Michel; Haentjens, Patrick; Devroey, Paul; Liebaers, Ingeborg

2010-01-01

Purpose This study aims to analyze the relationship between trinucleotide repeat length and reproductive outcome in a large cohort of DM1 patients undergoing ICSI and PGD. Methods Prospective cohort study. The effect of trinucleotide repeat length on reproductive outcome per patient was analyzed using bivariate analysis (T-test) and multivariate analysis using Kaplan-Meier and Cox regression analysis. Results Between 1995 and 2005, 205 cycles of ICSI and PGD were carried out for DM1 in 78 couples. The number of trinucleotide repeats does not have an influence on reproductive outcome when adjusted for age, BMI, basal FSH values, parity, infertility status and male or female affected. Cox regression analysis indicates that cumulative live birth rate is not influenced by the number of trinucleotide repeats. The only factor with a significant effect is age (p < 0.05). Conclusion There is no evidence of an effect of trinucleotide repeat length on reproductive outcome in patients undergoing ICSI and PGD. PMID:20221684

Application of Regression-Discontinuity Analysis in Pharmaceutical Health Services Research

PubMed Central

Zuckerman, Ilene H; Lee, Euni; Wutoh, Anthony K; Xue, Zhenyi; Stuart, Bruce

2006-01-01

Objective To demonstrate how a relatively underused design, regression-discontinuity (RD), can provide robust estimates of intervention effects when stronger designs are impossible to implement. Data Sources/Study Setting Administrative claims from a Mid-Atlantic state Medicaid program were used to evaluate the effectiveness of an educational drug utilization review intervention. Study Design Quasi-experimental design. Data Collection/Extraction Methods A drug utilization review study was conducted to evaluate a letter intervention to physicians treating Medicaid children with potentially excessive use of short-acting β2-agonist inhalers (SAB). The outcome measure is change in seasonally-adjusted SAB use 5 months pre- and postintervention. To determine if the intervention reduced monthly SAB utilization, results from an RD analysis are compared to findings from a pretest–posttest design using repeated-measure ANOVA. Principal Findings Both analyses indicated that the intervention significantly reduced SAB use among the high users. Average monthly SAB use declined by 0.9 canisters per month (p<.001) according to the repeated-measure ANOVA and by 0.2 canisters per month (p<.001) from RD analysis. Conclusions Regression-discontinuity design is a useful quasi-experimental methodology that has significant advantages in internal validity compared to other pre–post designs when assessing interventions in which subjects' assignment is based on cutoff scores for a critical variable. PMID:16584464

Analyzing the Impact of Ambient Temperature Indicators on Transformer Life in Different Regions of Chinese Mainland

PubMed Central

Bai, Cui-fen; Gao, Wen-Sheng; Liu, Tong

2013-01-01

Regression analysis is applied to quantitatively analyze the impact of different ambient temperature characteristics on the transformer life at different locations of Chinese mainland. 200 typical locations in Chinese mainland are selected for the study. They are specially divided into six regions so that the subsequent analysis can be done in a regional context. For each region, the local historical ambient temperature and load data are provided as inputs variables of the life consumption model in IEEE Std. C57.91-1995 to estimate the transformer life at every location. Five ambient temperature indicators related to the transformer life are involved into the partial least squares regression to describe their impact on the transformer life. According to a contribution measurement criterion of partial least squares regression, three indicators are conclusively found to be the most important factors influencing the transformer life, and an explicit expression is provided to describe the relationship between the indicators and the transformer life for every region. The analysis result is applicable to the area where the temperature characteristics are similar to Chinese mainland, and the expressions obtained can be applied to the other locations that are not included in this paper if these three indicators are known. PMID:23843729

Analyzing the impact of ambient temperature indicators on transformer life in different regions of Chinese mainland.

PubMed

Bai, Cui-fen; Gao, Wen-Sheng; Liu, Tong

2013-01-01

Regression analysis is applied to quantitatively analyze the impact of different ambient temperature characteristics on the transformer life at different locations of Chinese mainland. 200 typical locations in Chinese mainland are selected for the study. They are specially divided into six regions so that the subsequent analysis can be done in a regional context. For each region, the local historical ambient temperature and load data are provided as inputs variables of the life consumption model in IEEE Std. C57.91-1995 to estimate the transformer life at every location. Five ambient temperature indicators related to the transformer life are involved into the partial least squares regression to describe their impact on the transformer life. According to a contribution measurement criterion of partial least squares regression, three indicators are conclusively found to be the most important factors influencing the transformer life, and an explicit expression is provided to describe the relationship between the indicators and the transformer life for every region. The analysis result is applicable to the area where the temperature characteristics are similar to Chinese mainland, and the expressions obtained can be applied to the other locations that are not included in this paper if these three indicators are known.

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Practical aspects of estimating energy components in rodents

PubMed Central

van Klinken, Jan B.; van den Berg, Sjoerd A. A.; van Dijk, Ko Willems

2013-01-01

Recently there has been an increasing interest in exploiting computational and statistical techniques for the purpose of component analysis of indirect calorimetry data. Using these methods it becomes possible to dissect daily energy expenditure into its components and to assess the dynamic response of the resting metabolic rate (RMR) to nutritional and pharmacological manipulations. To perform robust component analysis, however, is not straightforward and typically requires the tuning of parameters and the preprocessing of data. Moreover the degree of accuracy that can be attained by these methods depends on the configuration of the system, which must be properly taken into account when setting up experimental studies. Here, we review the methods of Kalman filtering, linear, and penalized spline regression, and minimal energy expenditure estimation in the context of component analysis and discuss their results on high resolution datasets from mice and rats. In addition, we investigate the effect of the sample time, the accuracy of the activity sensor, and the washout time of the chamber on the estimation accuracy. We found that on the high resolution data there was a strong correlation between the results of Kalman filtering and penalized spline (P-spline) regression, except for the activity respiratory quotient (RQ). For low resolution data the basal metabolic rate (BMR) and resting RQ could still be estimated accurately with P-spline regression, having a strong correlation with the high resolution estimate (R2 > 0.997; sample time of 9 min). In contrast, the thermic effect of food (TEF) and activity related energy expenditure (AEE) were more sensitive to a reduction in the sample rate (R2 > 0.97). In conclusion, for component analysis on data generated by single channel systems with continuous data acquisition both Kalman filtering and P-spline regression can be used, while for low resolution data from multichannel systems P-spline regression gives more robust results. PMID:23641217

Test anxiety and academic performance in chiropractic students.

PubMed

Zhang, Niu; Henderson, Charles N R

2014-01-01

Objective : We assessed the level of students' test anxiety, and the relationship between test anxiety and academic performance. Methods : We recruited 166 third-quarter students. The Test Anxiety Inventory (TAI) was administered to all participants. Total scores from written examinations and objective structured clinical examinations (OSCEs) were used as response variables. Results : Multiple regression analysis shows that there was a modest, but statistically significant negative correlation between TAI scores and written exam scores, but not OSCE scores. Worry and emotionality were the best predictive models for written exam scores. Mean total anxiety and emotionality scores for females were significantly higher than those for males, but not worry scores. Conclusion : Moderate-to-high test anxiety was observed in 85% of the chiropractic students examined. However, total test anxiety, as measured by the TAI score, was a very weak predictive model for written exam performance. Multiple regression analysis demonstrated that replacing total anxiety (TAI) with worry and emotionality (TAI subscales) produces a much more effective predictive model of written exam performance. Sex, age, highest current academic degree, and ethnicity contributed little additional predictive power in either regression model. Moreover, TAI scores were not found to be statistically significant predictors of physical exam skill performance, as measured by OSCEs.

Serum Folate Shows an Inverse Association with Blood Pressure in a Cohort of Chinese Women of Childbearing Age: A Cross-Sectional Study

PubMed Central

Shen, Minxue; Tan, Hongzhuan; Zhou, Shujin; Retnakaran, Ravi; Smith, Graeme N.; Davidge, Sandra T.; Trasler, Jacquetta; Walker, Mark C.; Wen, Shi Wu

2016-01-01

Background It has been reported that higher folate intake from food and supplementation is associated with decreased blood pressure (BP). The association between serum folate concentration and BP has been examined in few studies. We aim to examine the association between serum folate and BP levels in a cohort of young Chinese women. Methods We used the baseline data from a pre-conception cohort of women of childbearing age in Liuyang, China, for this study. Demographic data were collected by structured interview. Serum folate concentration was measured by immunoassay, and homocysteine, blood glucose, triglyceride and total cholesterol were measured through standardized clinical procedures. Multiple linear regression and principal component regression model were applied in the analysis. Results A total of 1,532 healthy normotensive non-pregnant women were included in the final analysis. The mean concentration of serum folate was 7.5 ± 5.4 nmol/L and 55% of the women presented with folate deficiency (< 6.8 nmol/L). Multiple linear regression and principal component regression showed that serum folate levels were inversely associated with systolic and diastolic BP, after adjusting for demographic, anthropometric, and biochemical factors. Conclusions Serum folate is inversely associated with BP in non-pregnant women of childbearing age with high prevalence of folate deficiency. PMID:27182603

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

The relationship between quality of work life and turnover intention of primary health care nurses in Saudi Arabia

PubMed Central

2012-01-01

Background Quality of work life (QWL) has been found to influence the commitment of health professionals, including nurses. However, reliable information on QWL and turnover intention of primary health care (PHC) nurses is limited. The aim of this study was to examine the relationship between QWL and turnover intention of PHC nurses in Saudi Arabia. Methods A cross-sectional survey was used in this study. Data were collected using Brooks’ survey of Quality of Nursing Work Life, the Anticipated Turnover Scale and demographic data questions. A total of 508 PHC nurses in the Jazan Region, Saudi Arabia, completed the questionnaire (RR = 87%). Descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression, and hierarchical multiple regression were applied for analysis using SPSS v17 for Windows. Results Findings suggested that the respondents were dissatisfied with their work life, with almost 40% indicating a turnover intention from their current PHC centres. Turnover intention was significantly related to QWL. Using standard multiple regression, 26% of the variance in turnover intention was explained by QWL, p < 0.001, with R2 = .263. Further analysis using hierarchical multiple regression found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, p < 0.001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables. Conclusions Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes. PMID:22970764

A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011

PubMed Central

Otwombe, Kennedy N.; Petzold, Max; Martinson, Neil; Chirwa, Tobias

2014-01-01

Background Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used. Objectives We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002–2006 and 2007–2011. Time-to-event analysis techniques were considered appropriate. Data Sources Pubmed/Medline. Study Eligibility Criteria Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded. Results A total of 189 studies were identified (n = 91 in 2002–2006 and n = 98 in 2007–2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003). Conclusion Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods. PMID:24498313

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

PubMed Central

2011-01-01

Background Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. Results We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. Conclusions An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies. PMID:21247440

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran

PubMed Central

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-01-01

Background Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people’s general health. Aim To determine marital satisfaction and its relationship with job stress and general health of nurses. Methods This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). Results The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Conclusions Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses. PMID:28607660

Uncovering the Power of Personality to Shape Income

PubMed Central

Denissen, Jaap J. A.; Bleidorn, Wiebke; Hennecke, Marie; Luhmann, Maike; Orth, Ulrich; Specht, Jule; Zimmermann, Julia

2017-01-01

The notion of person-environment fit implies that personal and contextual factors interact in influencing important life outcomes. Using data from 8,458 employed individuals, we examined the combined effects of individuals’ actual personality traits and jobs’ expert-rated personality demands on earnings. Results from a response surface analysis indicated that the fit between individuals’ actual personality and the personality demands of their jobs is a predictor of income. Conclusions of this combined analysis were partly opposite to conclusions reached in previous studies using conventional regression methods. Individuals can earn additional income of more than their monthly salary per year if they hold a job that fits their personality. Thus, at least for some traits, economic success depends not only on having a “successful personality” but also, in part, on finding the best niche for one’s personality. We discuss the findings with regard to labor-market policies and individuals’ job-selection strategies. PMID:29155616

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari

2018-01-01

Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134

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

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding

PubMed Central

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-01-01

AIM: To distinguish upper from lower gastrointestinal (GI) bleeding. METHODS: Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. RESULTS: Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. CONCLUSION: The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL. PMID:26034359

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

The Necessity-Concerns-Framework: A Multidimensional Theory Benefits from Multidimensional Analysis

PubMed Central

Phillips, L. Alison; Diefenbach, Michael; Kronish, Ian M.; Negron, Rennie M.; Horowitz, Carol R.

2014-01-01

Background Patients’ medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). Purpose We use polynomial regression to assess the multidimensional effect of stroke-event survivors’ medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication. Methods Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. Results As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Conclusions Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites. PMID:24500078

Quantifying prosthetic gait deviation using simple outcome measures

PubMed Central

Kark, Lauren; Odell, Ross; McIntosh, Andrew S; Simmons, Anne

2016-01-01

AIM: To develop a subset of simple outcome measures to quantify prosthetic gait deviation without needing three-dimensional gait analysis (3DGA). METHODS: Eight unilateral, transfemoral amputees and 12 unilateral, transtibial amputees were recruited. Twenty-eight able-bodied controls were recruited. All participants underwent 3DGA, the timed-up-and-go test and the six-minute walk test (6MWT). The lower-limb amputees also completed the Prosthesis Evaluation Questionnaire. Results from 3DGA were summarised using the gait deviation index (GDI), which was subsequently regressed, using stepwise regression, against the other measures. RESULTS: Step-length (SL), self-selected walking speed (SSWS) and the distance walked during the 6MWT (6MWD) were significantly correlated with GDI. The 6MWD was the strongest, single predictor of the GDI, followed by SL and SSWS. The predictive ability of the regression equations were improved following inclusion of self-report data related to mobility and prosthetic utility. CONCLUSION: This study offers a practicable alternative to quantifying kinematic deviation without the need to conduct complete 3DGA. PMID:27335814

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis

PubMed Central

Gong, Xiajing; Hu, Meng

2018-01-01

Abstract Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high‐dimensional data featured by a large number of predictor variables. Our results showed that ML‐based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high‐dimensional data. The prediction performances of ML‐based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML‐based methods provide a powerful tool for time‐to‐event analysis, with a built‐in capacity for high‐dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. PMID:29536640

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

Regression and Sentinel Lymph Node Status in Melanoma Progression

PubMed Central

Letca, Alina Florentina; Ungureanu, Loredana; Şenilă, Simona Corina; Grigore, Lavinia Elena; Pop, Ştefan; Fechete, Oana; Vesa, Ştefan Cristian

2018-01-01

Background The purpose of this study was to assess the role of regression and other clinical and histological features for the prognosis and the progression of cutaneous melanoma. Material/Methods Between 2005 and 2016, 403 patients with melanoma were treated and followed at our Department of Dermatology. Of the 403 patients, 173 patients had cutaneous melanoma and underwent sentinel lymph node (SLN) biopsy and thus were included in this study. Results Histological regression was found in 37 cases of melanoma (21.3%). It was significantly associated with marked and moderate tumor-infiltrating lymphocyte (TIL) and with negative SLN. Progression of the disease occurred in 42 patients (24.2%). On multivariate analysis, we found that a positive lymph node and a Breslow index higher than 2 mm were independent variables associated with disease free survival (DFS). These variables together with a mild TIL were significantly correlated with overall survival (OS). The presence of regression was not associated with DFS or OS. Conclusions We could not demonstrate an association between regression and the outcome of patients with cutaneous melanoma. Tumor thickness greater than 2 mm and a positive SLN were associated with recurrence. Survival was influenced by a Breslow thickness >2 mm, the presence of a mild TIL and a positive SLN status. PMID:29507279

Efficacy of Statin Therapy in Inducing Coronary Plaque Regression in Patients with Low Baseline Cholesterol Levels

PubMed Central

Nozue, Tsuyoshi; Yamamoto, Shingo; Tohyama, Shinichi; Fukui, Kazuki; Umezawa, Shigeo; Onishi, Yuko; Kunishima, Tomoyuki; Sato, Akira; Miyake, Shogo; Morino, Yoshihiro; Yamauchi, Takao; Muramatsu, Toshiya; Hibi, Kiyoshi; Terashima, Mitsuyasu; Suzuki, Hiroshi; Michishita, Ichiro

2016-01-01

Aim: The efficacy of statin therapy in inducing coronary plaque regression may depend on baseline cholesterol levels. We aimed to determine the efficacy of statin therapy in inducing coronary plaque regression in statin-naïve patients with low cholesterol levels using serial intravascular ultrasound (IVUS) data from the treatment with statin on atheroma regression evaluated by virtual histology IVUS (TRUTH) study. Methods: The TRUTH study is a prospective, multicenter trial, comparing the efficacies of pitavastatin and pravastatin in coronary plaque regression in 164 patients. All patients were statin-naïve and received statin therapy only after study enrollment. The primary endpoint was the observation of coronary plaque progression, despite statin therapy. Results: Serial IVUS data, at baseline and after an 8-month follow-up, were available for 119 patients. The patients were divided into three groups based on non-high-density lipoprotein cholesterol (HDL-C) levels—low: ≤ 140 mg/dl, n = 38; moderate: 141–169 mg/dl, n = 42; and high: ≥ 170 mg/dl, n = 39. Coronary plaque progression was noted in the low cholesterol group, whereas plaque regression was noted in the moderate and high cholesterol groups [%Δplaque volume: 2.3 ± 7.4 vs. − 2.7 ± 10.7 vs. − 3.2 ± 7.5, p = 0.004 (analysis of variance)]. After adjusting for all variables, a low non-HDLC level (≤ 140 mg/dl) was identified as an independent predictor of coronary plaque progression [odds ratio, 3.7; 95% confidence interval, 1.5–9.1, p = 0.004]. Conclusion: Serial IVUS data analysis indicated that statin therapy was less effective in inducing coronary plaque regression in patients with low cholesterol levels but more effective in those with high cholesterol levels at baseline. University Hospital Medical Information Network (UMIN) (UMIN ID: C000000311). PMID:27040362

Sample entropy analysis for the estimating depth of anaesthesia through human EEG signal at different levels of unconsciousness during surgeries.

PubMed

Liu, Quan; Ma, Li; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing

2018-01-01

Estimating the depth of anaesthesia (DoA) in operations has always been a challenging issue due to the underlying complexity of the brain mechanisms. Electroencephalogram (EEG) signals are undoubtedly the most widely used signals for measuring DoA. In this paper, a novel EEG-based index is proposed to evaluate DoA for 24 patients receiving general anaesthesia with different levels of unconsciousness. Sample Entropy (SampEn) algorithm was utilised in order to acquire the chaotic features of the signals. After calculating the SampEn from the EEG signals, Random Forest was utilised for developing learning regression models with Bispectral index (BIS) as the target. Correlation coefficient, mean absolute error, and area under the curve (AUC) were used to verify the perioperative performance of the proposed method. Validation comparisons with typical nonstationary signal analysis methods (i.e., recurrence analysis and permutation entropy) and regression methods (i.e., neural network and support vector machine) were conducted. To further verify the accuracy and validity of the proposed methodology, the data is divided into four unconsciousness-level groups on the basis of BIS levels. Subsequently, analysis of variance (ANOVA) was applied to the corresponding index (i.e., regression output). Results indicate that the correlation coefficient improved to 0.72 ± 0.09 after filtering and to 0.90 ± 0.05 after regression from the initial values of 0.51 ± 0.17. Similarly, the final mean absolute error dramatically declined to 5.22 ± 2.12. In addition, the ultimate AUC increased to 0.98 ± 0.02, and the ANOVA analysis indicates that each of the four groups of different anaesthetic levels demonstrated significant difference from the nearest levels. Furthermore, the Random Forest output was extensively linear in relation to BIS, thus with better DoA prediction accuracy. In conclusion, the proposed method provides a concrete basis for monitoring patients' anaesthetic level during surgeries.

Statistical approach to the analysis of olive long-term pollen season trends in southern Spain.

PubMed

García-Mozo, H; Yaezel, L; Oteros, J; Galán, C

2014-03-01

Analysis of long-term airborne pollen counts makes it possible not only to chart pollen-season trends but also to track changing patterns in flowering phenology. Changes in higher plant response over a long interval are considered among the most valuable bioindicators of climate change impact. Phenological-trend models can also provide information regarding crop production and pollen-allergen emission. The interest of this information makes essential the election of the statistical analysis for time series study. We analysed trends and variations in the olive flowering season over a 30-year period (1982-2011) in southern Europe (Córdoba, Spain), focussing on: annual Pollen Index (PI); Pollen Season Start (PSS), Peak Date (PD), Pollen Season End (PSE) and Pollen Season Duration (PSD). Apart from the traditional Linear Regression analysis, a Seasonal-Trend Decomposition procedure based on Loess (STL) and an ARIMA model were performed. Linear regression results indicated a trend toward delayed PSE and earlier PSS and PD, probably influenced by the rise in temperature. These changes are provoking longer flowering periods in the study area. The use of the STL technique provided a clearer picture of phenological behaviour. Data decomposition on pollination dynamics enabled the trend toward an alternate bearing cycle to be distinguished from the influence of other stochastic fluctuations. Results pointed to show a rising trend in pollen production. With a view toward forecasting future phenological trends, ARIMA models were constructed to predict PSD, PSS and PI until 2016. Projections displayed a better goodness of fit than those derived from linear regression. Findings suggest that olive reproductive cycle is changing considerably over the last 30years due to climate change. Further conclusions are that STL improves the effectiveness of traditional linear regression in trend analysis, and ARIMA models can provide reliable trend projections for future years taking into account the internal fluctuations in time series. Copyright © 2013 Elsevier B.V. All rights reserved.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Transportation assimilation revisited: New evidence from repeated cross-sectional survey data

PubMed Central

2018-01-01

Background Based on single cross-sectional data, prior research finds evidence of “transportation assimilation” among U.S. immigrants: the length of stay in the U.S. is negatively correlated with public transit use. This paper revisits this question by using repeated cross-sectional data, and examines the trend of transportation assimilation over time. Methods and results Using 1980, 1990, 2000 1% census and 2010 (1%) American Community Survey, I examine the relationship between the length of stay in the U.S. and public transit ridership among immigrants. I first run regressions separately in four data sets: I regress public transit ridership on the length of stay, controlling for other individual and geographic variables. I then compare the magnitudes of the relationship in four regressions. To study how the rate of transportation assimilation changes over time, I pool the data set and regress public transit ridership on the length of stay and its interactions with year dummies to compare the coefficients across surveys. Results confirm the conclusion of transportation assimilation: as the length of stay in the U.S. increases, an immigrant’s public transit use decreases. However, the repeated cross-section analysis suggests the assimilation rate has been decreasing in the past few decades. Conclusions This paper finds evidence of transportation assimilation: immigrants become less likely to ride public transit as the length of stay in the U.S. increases. The assimilation rate, however, has been decreasing over time. This paper finds that the rate of public transit ridership among new immigrants upon arrival, the geographic distribution of immigrants, and the changing demographics of the U.S. immigrants play roles in affecting the trend of transportation assimilation. PMID:29668676

Imaging Analysis of Hepatoblastoma Resectability Across Neoadjuvant Chemotherapy

PubMed Central

Murphy, Andrew J.; Ayers, Gregory D.; Hilmes, Melissa A.; Mukherjee, Kaushik; Wilson, Kevin J.; Allen, Wade M.; Fernandez-Pineda, Israel; Shinall, Myrick C.; Zhao, Zhiguo; Furman, Wayne L.; McCarville, Mary Beth; Davidoff, Andrew M.; Lovvorn, Harold N.

2013-01-01

Purpose Hepatoblastomas often require neoadjuvant chemotherapy to facilitate partial hepatectomy, which necessitates freedom of tumor borders from the confluence of hepatic veins (COHV), portal vein bifurcation (PVB), and retrohepatic inferior vena cava (IVC). This study aimed to clarify the effect of incremental neoadjuvant cycles on the AHEP0731 protocol criteria of hepatoblastoma resectability. Methods Hepatoblastoma responses to neoadjuvant chemotherapy were analyzed among patients (n=23) treated at two children’s hospitals between 1996 and 2010. Using digital imaging data, ellipsoid and point-based models were created to measure tumor volume regression and respective distances from tumor borders nearest to the COHV, PVB, and IVC. Results Hepatoblastoma volumes regressed with incremental neoadjuvant chemotherapy cycles (p<0.001). Although tumor borders regressed away from the COHV (p=0.008), on average only 1.1mm was gained. No change from tumor borders to the PVB was detected (p=0.102). Distances from tumor borders to the IVC remained stable at one hospital (p=0.612), but increased only 0.15mm every 10 days of therapy at the other (p=0.002). Neoadjuvant chemotherapy induced slightly more tumors to meet the threshold vascular margin of 1cm (baseline to completion): COHV, 11 (47.8%) to 17 (73.9%; p=0.058); PVB, 11 (47.8%) to 15 (65.2%; p=0.157); IVC, 4 (17.4%) to 10 (43.5%; p=0.034). No differences were detected in demographic or disease-specific characteristics between patients who did or did not achieve this 1cm margin after conclusion of chemotherapy. Conclusion Hepatoblastoma volumes regress significantly with increasing neoadjuvant chemotherapy cycles. However, tumors often remain anchored to the major hepatic vasculature, showing marginal improvement in resectability criteria. PMID:23845613

Comparison of Cox’s Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000–2012

PubMed Central

Adelian, R.; Jamali, J.; Zare, N.; Ayatollahi, S. M. T.; Pooladfar, G. R.; Roustaei, N.

2015-01-01

Background: Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. Objective: To compare Cox’s regression model with parametric models for determining the independent factors for predicting adults’ and pediatrics’ survival after liver transplantation. Method: This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Result: Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Conclusion: Parametric regression model is a good alternative for the Cox’s regression model. PMID:26306158

Trend analysis of salt load and evaluation of the frequency of water-quality measurements for the Gunnison, the Colorado, and the Dolores rivers in Colorado and Utah

USGS Publications Warehouse

Kircher, J.E.; Dinicola, Richard S.; Middelburg, R.F.

1984-01-01

Monthly values were computed for water-quality constituents at four streamflow gaging stations in the Upper Colorado River basin for the determination of trends. Seasonal regression and seasonal Kendall trend analysis techniques were applied to two monthly data sets at each station site for four different time periods. A recently developed method for determining optimal water-discharge data-collection frequency was also applied to the monthly water-quality data. Trend analysis results varied with each monthly load computational method, period of record, and trend detection model used. No conclusions could be reached regarding which computational method was best to use in trend analysis. Time-period selection for analysis was found to be important with regard to intended use of the results. Seasonal Kendall procedures were found to be applicable to most data sets. Seasonal regression models were more difficult to apply and were sometimes of questionable validity; however, those results were more informative than seasonal Kendall results. The best model to use depends upon the characteristics of the data and the amount of trend information needed. The measurement-frequency optimization method had potential for application to water-quality data, but refinements are needed. (USGS)

A Study of the Effect of the Front-End Styling of Sport Utility Vehicles on Pedestrian Head Injuries

PubMed Central

Qin, Qin; Chen, Zheng; Bai, Zhonghao; Cao, Libo

2018-01-01

Background The number of sport utility vehicles (SUVs) on China market is continuously increasing. It is necessary to investigate the relationships between the front-end styling features of SUVs and head injuries at the styling design stage for improving the pedestrian protection performance and product development efficiency. Methods Styling feature parameters were extracted from the SUV side contour line. And simplified finite element models were established based on the 78 SUV side contour lines. Pedestrian headform impact simulations were performed and validated. The head injury criterion of 15 ms (HIC15) at four wrap-around distances was obtained. A multiple linear regression analysis method was employed to describe the relationships between the styling feature parameters and the HIC15 at each impact point. Results The relationship between the selected styling features and the HIC15 showed reasonable correlations, and the regression models and the selected independent variables showed statistical significance. Conclusions The regression equations obtained by multiple linear regression can be used to assess the performance of SUV styling in protecting pedestrians' heads and provide styling designers with technical guidance regarding their artistic creations.

The effectiveness of manual and mechanical instrumentation for the retreatment of three different root canal filling materials.

PubMed

Somma, Francesco; Cammarota, Giuseppe; Plotino, Gianluca; Grande, Nicola M; Pameijer, Cornelis H

2008-04-01

The aim of this study was to compare the effectiveness of the Mtwo R (Sweden & Martina, Padova, Italy), ProTaper retreatment files (Dentsply-Maillefer, Ballaigues, Switzerland), and a Hedström manual technique in the removal of three different filling materials (gutta-percha, Resilon [Resilon Research LLC, Madison, CT], and EndoRez [Ultradent Products Inc, South Jordan, UT]) during retreatment. Ninety single-rooted straight premolars were instrumented and randomly divided into 9 groups of 10 teeth each (n = 10) with regards to filling material and instrument used. For all roots, the following data were recorded: procedural errors, time of retreatment, apically extruded material, canal wall cleanliness through optical stereomicroscopy (OSM), and scanning electron microscopy (SEM). A linear regression analysis and three logistic regression analyses were performed to assess the level of significance set at p = 0.05. The results indicated that the overall regression models were statistically significant. The Mtwo R, ProTaper retreatment files, and Resilon filling material had a positive impact in reducing the time for retreatment. Both ProTaper retreatment files and Mtwo R showed a greater extrusion of debris. For both OSM and SEM logistic regression models, the root canal apical third had the greatest impact on the score values. EndoRez filling material resulted in cleaner root canal walls using OSM analysis, whereas Resilon filling material and both engine-driven NiTi rotary techniques resulted in less clean root canal walls according to SEM analysis. In conclusion, all instruments left remnants of filling material and debris on the root canal walls irrespective of the root filling material used. Both the engine-driven NiTi rotary systems proved to be safe and fast devices for the removal of endodontic filling material.

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

Mapping the Structure-Function Relationship in Glaucoma and Healthy Patients Measured with Spectralis OCT and Humphrey Perimetry

PubMed Central

Muñoz–Negrete, Francisco J.; Oblanca, Noelia; Rebolleda, Gema

2018-01-01

Purpose To study the structure-function relationship in glaucoma and healthy patients assessed with Spectralis OCT and Humphrey perimetry using new statistical approaches. Materials and Methods Eighty-five eyes were prospectively selected and divided into 2 groups: glaucoma (44) and healthy patients (41). Three different statistical approaches were carried out: (1) factor analysis of the threshold sensitivities (dB) (automated perimetry) and the macular thickness (μm) (Spectralis OCT), subsequently applying Pearson's correlation to the obtained regions, (2) nonparametric regression analysis relating the values in each pair of regions that showed significant correlation, and (3) nonparametric spatial regressions using three models designed for the purpose of this study. Results In the glaucoma group, a map that relates structural and functional damage was drawn. The strongest correlation with visual fields was observed in the peripheral nasal region of both superior and inferior hemigrids (r = 0.602 and r = 0.458, resp.). The estimated functions obtained with the nonparametric regressions provided the mean sensitivity that corresponds to each given macular thickness. These functions allowed for accurate characterization of the structure-function relationship. Conclusions Both maps and point-to-point functions obtained linking structure and function damage contribute to a better understanding of this relationship and may help in the future to improve glaucoma diagnosis. PMID:29850196

Sensitivity Analysis of Mechanical Parameters of Different Rock Layers to the Stability of Coal Roadway in Soft Rock Strata

PubMed Central

Zhao, Zeng-hui; Wang, Wei-ming; Gao, Xin; Yan, Ji-xing

2013-01-01

According to the geological characteristics of Xinjiang Ili mine in western area of China, a physical model of interstratified strata composed of soft rock and hard coal seam was established. Selecting the tunnel position, deformation modulus, and strength parameters of each layer as influencing factors, the sensitivity coefficient of roadway deformation to each parameter was firstly analyzed based on a Mohr-Columb strain softening model and nonlinear elastic-plastic finite element analysis. Then the effect laws of influencing factors which showed high sensitivity were further discussed. Finally, a regression model for the relationship between roadway displacements and multifactors was obtained by equivalent linear regression under multiple factors. The results show that the roadway deformation is highly sensitive to the depth of coal seam under the floor which should be considered in the layout of coal roadway; deformation modulus and strength of coal seam and floor have a great influence on the global stability of tunnel; on the contrary, roadway deformation is not sensitive to the mechanical parameters of soft roof; roadway deformation under random combinations of multi-factors can be deduced by the regression model. These conclusions provide theoretical significance to the arrangement and stability maintenance of coal roadway. PMID:24459447

Network Approach to Understanding Emotion Dynamics in Relation to Childhood Trauma and Genetic Liability to Psychopathology: Replication of a Prospective Experience Sampling Analysis

PubMed Central

Hasmi, Laila; Drukker, Marjan; Guloksuz, Sinan; Menne-Lothmann, Claudia; Decoster, Jeroen; van Winkel, Ruud; Collip, Dina; Delespaul, Philippe; De Hert, Marc; Derom, Catherine; Thiery, Evert; Jacobs, Nele; Rutten, Bart P. F.; Wichers, Marieke; van Os, Jim

2017-01-01

Background: The network analysis of intensive time series data collected using the Experience Sampling Method (ESM) may provide vital information in gaining insight into the link between emotion regulation and vulnerability to psychopathology. The aim of this study was to apply the network approach to investigate whether genetic liability (GL) to psychopathology and childhood trauma (CT) are associated with the network structure of the emotions “cheerful,” “insecure,” “relaxed,” “anxious,” “irritated,” and “down”—collected using the ESM method. Methods: Using data from a population-based sample of twin pairs and siblings (704 individuals), we examined whether momentary emotion network structures differed across strata of CT and GL. GL was determined empirically using the level of psychopathology in monozygotic and dizygotic co-twins. Network models were generated using multilevel time-lagged regression analysis and were compared across three strata (low, medium, and high) of CT and GL, respectively. Permutations were utilized to calculate p values and compare regressions coefficients, density, and centrality indices. Regression coefficients were presented as connections, while variables represented the nodes in the network. Results: In comparison to the low GL stratum, the high GL stratum had significantly denser overall (p = 0.018) and negative affect network density (p < 0.001). The medium GL stratum also showed a directionally similar (in-between high and low GL strata) but statistically inconclusive association with network density. In contrast to GL, the results of the CT analysis were less conclusive, with increased positive affect density (p = 0.021) and overall density (p = 0.042) in the high CT stratum compared to the medium CT stratum but not to the low CT stratum. The individual node comparisons across strata of GL and CT yielded only very few significant results, after adjusting for multiple testing. Conclusions: The present findings demonstrate that the network approach may have some value in understanding the relation between established risk factors for mental disorders (particularly GL) and the dynamic interplay between emotions. The present finding partially replicates an earlier analysis, suggesting it may be instructive to model negative emotional dynamics as a function of genetic influence. PMID:29163289

Can Predictive Modeling Identify Head and Neck Oncology Patients at Risk for Readmission?

PubMed

Manning, Amy M; Casper, Keith A; Peter, Kay St; Wilson, Keith M; Mark, Jonathan R; Collar, Ryan M

2018-05-01

Objective Unplanned readmission within 30 days is a contributor to health care costs in the United States. The use of predictive modeling during hospitalization to identify patients at risk for readmission offers a novel approach to quality improvement and cost reduction. Study Design Two-phase study including retrospective analysis of prospectively collected data followed by prospective longitudinal study. Setting Tertiary academic medical center. Subjects and Methods Prospectively collected data for patients undergoing surgical treatment for head and neck cancer from January 2013 to January 2015 were used to build predictive models for readmission within 30 days of discharge using logistic regression, classification and regression tree (CART) analysis, and random forests. One model (logistic regression) was then placed prospectively into the discharge workflow from March 2016 to May 2016 to determine the model's ability to predict which patients would be readmitted within 30 days. Results In total, 174 admissions had descriptive data. Thirty-two were excluded due to incomplete data. Logistic regression, CART, and random forest predictive models were constructed using the remaining 142 admissions. When applied to 106 consecutive prospective head and neck oncology patients at the time of discharge, the logistic regression model predicted readmissions with a specificity of 94%, a sensitivity of 47%, a negative predictive value of 90%, and a positive predictive value of 62% (odds ratio, 14.9; 95% confidence interval, 4.02-55.45). Conclusion Prospectively collected head and neck cancer databases can be used to develop predictive models that can accurately predict which patients will be readmitted. This offers valuable support for quality improvement initiatives and readmission-related cost reduction in head and neck cancer care.

Regression Rates Following the Treatment of Aggressive Posterior Retinopathy of Prematurity with Bevacizumab Versus Laser: 8-Year Retrospective Analysis

PubMed Central

Nicoară, Simona D.; Ştefănuţ, Anne C.; Nascutzy, Constanta; Zaharie, Gabriela C.; Toader, Laura E.; Drugan, Tudor C.

2016-01-01

Background Retinopathy is a serious complication related to prematurity and a leading cause of childhood blindness. The aggressive posterior form of retinopathy of prematurity (APROP) has a worse anatomical and functional outcome following laser therapy, as compared with the classic form of the disease. The main outcome measures are the APROP regression rate, structural outcomes, and complications associated with intravitreal bevacizumab (IVB) versus laser photocoagulation in APROP. Material/Methods This is a retrospective case series that includes infants with APROP who received either IVB or laser photocoagulation and had a follow-up of at least 60 weeks (for the laser photocoagulation group) and 80 weeks (for the IVB group). In the first group, laser photocoagulation of the retina was carried out and in the second group, 1 bevacizumab injection was administered intravitreally. The following parameters were analyzed in each group: sex, gestational age, birth weight, postnatal age and postmenstrual age at treatment, APROP regression, sequelae, and complications. Statistical analysis was performed using Microsoft Excel and IBM SPSS (version 23.0). Results The laser photocoagulation group consisted of 6 premature infants (12 eyes) and the IVB group consisted of 17 premature infants (34 eyes). Within the laser photocoagulation group, the evolution was favorable in 9 eyes (75%) and unfavorable in 3 eyes (25%). Within the IVB group, APROP regressed in 29 eyes (85.29%) and failed to regress in 5 eyes (14.71%). These differences are statistically significant, as proved by the McNemar test (P<0.001). Conclusions The IVB group had a statistically significant better outcome compared with the laser photocoagulation group, in APROP in our series. PMID:27062023

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Resection of complex pancreatic injuries: Benchmarking postoperative complications using the Accordion classification

PubMed Central

Krige, Jake E; Jonas, Eduard; Thomson, Sandie R; Kotze, Urda K; Setshedi, Mashiko; Navsaria, Pradeep H; Nicol, Andrew J

2017-01-01

AIM To benchmark severity of complications using the Accordion Severity Grading System (ASGS) in patients undergoing operation for severe pancreatic injuries. METHODS A prospective institutional database of 461 patients with pancreatic injuries treated from 1990 to 2015 was reviewed. One hundred and thirty patients with AAST grade 3, 4 or 5 pancreatic injuries underwent resection (pancreatoduodenectomy, n = 20, distal pancreatectomy, n = 110), including 30 who had an initial damage control laparotomy (DCL) and later definitive surgery. AAST injury grades, type of pancreatic resection, need for DCL and incidence and ASGS severity of complications were assessed. Uni- and multivariate logistic regression analysis was applied. RESULTS Overall 238 complications occurred in 95 (73%) patients of which 73% were ASGS grades 3-6. Nineteen patients (14.6%) died. Patients more likely to have complications after pancreatic resection were older, had a revised trauma score (RTS) < 7.8, were shocked on admission, had grade 5 injuries of the head and neck of the pancreas with associated vascular and duodenal injuries, required a DCL, received a larger blood transfusion, had a pancreatoduodenectomy (PD) and repeat laparotomies. Applying univariate logistic regression analysis, mechanism of injury, RTS < 7.8, shock on admission, DCL, increasing AAST grade and type of pancreatic resection were significant variables for complications. Multivariate logistic regression analysis however showed that only age and type of pancreatic resection (PD) were significant. CONCLUSION This ASGS-based study benchmarked postoperative morbidity after pancreatic resection for trauma. The detailed outcome analysis provided may serve as a reference for future institutional comparisons. PMID:28396721

Periodic limb movements of sleep: empirical and theoretical evidence supporting objective at-home monitoring

PubMed Central

Moro, Marilyn; Goparaju, Balaji; Castillo, Jelina; Alameddine, Yvonne; Bianchi, Matt T

2016-01-01

Introduction Periodic limb movements of sleep (PLMS) may increase cardiovascular and cerebrovascular morbidity. However, most people with PLMS are either asymptomatic or have nonspecific symptoms. Therefore, predicting elevated PLMS in the absence of restless legs syndrome remains an important clinical challenge. Methods We undertook a retrospective analysis of demographic data, subjective symptoms, and objective polysomnography (PSG) findings in a clinical cohort with or without obstructive sleep apnea (OSA) from our laboratory (n=443 with OSA, n=209 without OSA). Correlation analysis and regression modeling were performed to determine predictors of periodic limb movement index (PLMI). Markov decision analysis with TreeAge software compared strategies to detect PLMS: in-laboratory PSG, at-home testing, and a clinical prediction tool based on the regression analysis. Results Elevated PLMI values (>15 per hour) were observed in >25% of patients. PLMI values in No-OSA patients correlated with age, sex, self-reported nocturnal leg jerks, restless legs syndrome symptoms, and hypertension. In OSA patients, PLMI correlated only with age and self-reported psychiatric medications. Regression models indicated only a modest predictive value of demographics, symptoms, and clinical history. Decision modeling suggests that at-home testing is favored as the pretest probability of PLMS increases, given plausible assumptions regarding PLMS morbidity, costs, and assumed benefits of pharmacological therapy. Conclusion Although elevated PLMI values were commonly observed, routinely acquired clinical information had only weak predictive utility. As the clinical importance of elevated PLMI continues to evolve, it is likely that objective measures such as PSG or at-home PLMS monitors will prove increasingly important for clinical and research endeavors. PMID:27540316

Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy

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

Dean, Jamie A., E-mail: jamie.dean@icr.ac.uk; Wong, Kee H.; Gay, Hiram

Purpose: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue–sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. Methods and Materials: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogrammore » data. The reduced dose data were input into functional logistic regression models (functional partial least squares–logistic regression [FPLS-LR] and functional principal component–logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate–response associations, assessed using bootstrapping. Results: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/−0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/−0.96, 0.79/−0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. Conclusions: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling.« less

Frontier-based techniques in measuring hospital efficiency in Iran: a systematic review and meta-regression analysis

PubMed Central

2013-01-01

Background In recent years, there has been growing interest in measuring the efficiency of hospitals in Iran and several studies have been conducted on the topic. The main objective of this paper was to review studies in the field of hospital efficiency and examine the estimated technical efficiency (TE) of Iranian hospitals. Methods Persian and English databases were searched for studies related to measuring hospital efficiency in Iran. Ordinary least squares (OLS) regression models were applied for statistical analysis. The PRISMA guidelines were followed in the search process. Results A total of 43 efficiency scores from 29 studies were retrieved and used to approach the research question. Data envelopment analysis was the principal frontier efficiency method in the estimation of efficiency scores. The pooled estimate of mean TE was 0.846 (±0.134). There was a considerable variation in the efficiency scores between the different studies performed in Iran. There were no differences in efficiency scores between data envelopment analysis (DEA) and stochastic frontier analysis (SFA) techniques. The reviewed studies are generally similar and suffer from similar methodological deficiencies, such as no adjustment for case mix and quality of care differences. The results of OLS regression revealed that studies that included more variables and more heterogeneous hospitals generally reported higher TE. Larger sample size was associated with reporting lower TE. Conclusions The features of frontier-based techniques had a profound impact on the efficiency scores among Iranian hospital studies. These studies suffer from major methodological deficiencies and were of sub-optimal quality, limiting their validity and reliability. It is suggested that improving data collection and processing in Iranian hospital databases may have a substantial impact on promoting the quality of research in this field. PMID:23945011

Multidimensional analysis of the effect of occupational exposure to organic solvents on lung cancer risk: the ICARE study

PubMed Central

Mattei, Francesca; Liverani, Silvia; Guida, Florence; Matrat, Mireille; Cenée, Sylvie; Azizi, Lamiae; Menvielle, Gwenn; Sanchez, Marie; Pilorget, Corinne; Lapôtre-Ledoux, Bénédicte; Luce, Danièle; Richardson, Sylvia; Stücker, Isabelle

2016-01-01

Background The association between lung cancer and occupational exposure to organic solvents is discussed. Since different solvents are often used simultaneously, it is difficult to assess the role of individual substances. Objectives The present study is focused on an in-depth investigation of the potential association between lung cancer risk and occupational exposure to a large group of organic solvents, taking into account the well-known risk factors for lung cancer, tobacco smoking and occupational exposure to asbestos. Methods We analysed data from the Investigation of occupational and environmental causes of respiratory cancers (ICARE) study, a large French population-based case–control study, set up between 2001 and 2007. A total of 2276 male cases and 2780 male controls were interviewed, and long-life occupational history was collected. In order to overcome the analytical difficulties created by multiple correlated exposures, we carried out a novel type of analysis based on Bayesian profile regression. Results After analysis with conventional logistic regression methods, none of the 11 solvents examined were associated with lung cancer risk. Through a profile regression approach, we did not observe any significant association between solvent exposure and lung cancer. However, we identified clusters at high risk that are related to occupations known to be at risk of developing lung cancer, such as painters. Conclusions Organic solvents do not appear to be substantial contributors to the occupational risk of lung cancer for the occupations known to be at risk. PMID:26911986

Principal component regression analysis with SPSS.

PubMed

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

A secure distributed logistic regression protocol for the detection of rare adverse drug events

PubMed Central

El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

2013-01-01

Background There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. Objective To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. Methods We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. Results The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. Conclusion The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for correlations among patients within sites through generalized estimating equations, and to accommodate other link functions by extending it to generalized linear models. PMID:22871397

p.Q192R SNP of PON1 seems not to be Associated with Carotid Atherosclerosis Risk Factors in an Asymptomatic and Normolipidemic Brazilian Population Sample

PubMed Central

Scherrer, Daniel Zanetti; Zago, Vanessa Helena de Souza; Vieira, Isabela Calanca; Parra, Eliane Soler; Panzoldo, Natália Baratella; Alexandre, Fernanda; Secolin, Rodrigo; Baracat, Jamal; Quintão, Eder Carlos Rocha; de Faria, Eliana Cotta

2015-01-01

Background Evidences suggest that paraoxonase 1 (PON1) confers important antioxidant and anti-inflammatory properties when associated with high-density lipoprotein (HDL). Objective To investigate the relationships between p.Q192R SNP of PON1, biochemical parameters and carotid atherosclerosis in an asymptomatic, normolipidemic Brazilian population sample. Methods We studied 584 volunteers (females n = 326, males n = 258; 19-75 years of age). Total genomic DNA was extracted and SNP was detected in the TaqMan® SNP OpenArray® genotyping platform (Applied Biosystems, Foster City, CA). Plasma lipoproteins and apolipoproteins were determined and PON1 activity was measured using paraoxon as a substrate. High-resolution β-mode ultrasonography was used to measure cIMT and the presence of carotid atherosclerotic plaques in a subgroup of individuals (n = 317). Results The presence of p.192Q was associated with a significant increase in PON1 activity (RR = 12.30 (11.38); RQ = 46.96 (22.35); QQ = 85.35 (24.83) μmol/min; p < 0.0001), HDL-C (RR= 45 (37); RQ = 62 (39); QQ = 69 (29) mg/dL; p < 0.001) and apo A-I (RR = 140.76 ± 36.39; RQ = 147.62 ± 36.92; QQ = 147.49 ± 36.65 mg/dL; p = 0.019). Stepwise regression analysis revealed that heterozygous and p.192Q carriers influenced by 58% PON1 activity towards paraoxon. The univariate linear regression analysis demonstrated that p.Q192R SNP was not associated with mean cIMT; as a result, in the multiple regression analysis, no variables were selected with 5% significance. In logistic regression analysis, the studied parameters were not associated with the presence of carotid plaques. Conclusion In low-risk individuals, the presence of the p.192Q variant of PON1 is associated with a beneficial plasma lipid profile but not with carotid atherosclerosis. PMID:26039660

Study of relationship between clinical factors and velopharyngeal closure in cleft palate patients

PubMed Central

Chen, Qi; Zheng, Qian; Shi, Bing; Yin, Heng; Meng, Tian; Zheng, Guang-ning

2011-01-01

BACKGROUND: This study was carried out to analyze the relationship between clinical factors and velopharyngeal closure (VPC) in cleft palate patients. METHODS: Chi-square test was used to compare the postoperative velopharyngeal closure rate. Logistic regression model was used to analyze independent variables associated with velopharyngeal closure. RESULTS: Difference of postoperative VPC rate in different cleft types, operative ages and surgical techniques was significant (P=0.000). Results of logistic regression analysis suggested that when operative age was beyond deciduous dentition stage, or cleft palate type was complete, or just had undergone a simple palatoplasty without levator veli palatini retropositioning, patients would suffer a higher velopharyngeal insufficiency rate after primary palatal repair. CONCLUSIONS: Cleft type, operative age and surgical technique were the contributing factors influencing VPC rate after primary palatal repair of cleft palate patients. PMID:22279464

The effect of cigarette taxes on cigarette consumption.

PubMed Central

Showalter, M H

1998-01-01

OBJECTIVES: This paper reexamines the work of Meier and Licari in a previous issue of the Journal. METHODS: The impact of excise taxes on cigarette consumption and sales was measured via standard regression analysis. RESULTS: The 1983 federal tax increase is shown to have an anomalous effect on the regression results. When those data are excluded, there is no significant difference between state and federal tax increases. Further investigation suggests that firms raised cigarette prices substantially in the years surrounding the 1983 federal tax increase, which accounts for the relatively large decrease in consumption during this period. CONCLUSIONS: Federal excise taxes per se do not appear to be more effective than state excise taxes in terms of reducing cigarette consumption. The reaction of cigarette firms to government policies appears to be an important determinant of the success of antismoking initiatives. PMID:9663167

Regression models for analyzing costs and their determinants in health care: an introductory review.

PubMed

Gregori, Dario; Petrinco, Michele; Bo, Simona; Desideri, Alessandro; Merletti, Franco; Pagano, Eva

2011-06-01

This article aims to describe the various approaches in multivariable modelling of healthcare costs data and to synthesize the respective criticisms as proposed in the literature. We present regression methods suitable for the analysis of healthcare costs and then apply them to an experimental setting in cardiovascular treatment (COSTAMI study) and an observational setting in diabetes hospital care. We show how methods can produce different results depending on the degree of matching between the underlying assumptions of each method and the specific characteristics of the healthcare problem. The matching of healthcare cost models to the analytic objectives and characteristics of the data available to a study requires caution. The study results and interpretation can be heavily dependent on the choice of model with a real risk of spurious results and conclusions.

The Relationships between Weather-Related Factors and Daily Outdoor Physical Activity Counts on an Urban Greenway

PubMed Central

Wolff, Dana; Fitzhugh, Eugene C.

2011-01-01

The purpose of this study was to examine relationships between weather and outdoor physical activity (PA). An online weather source was used to obtain daily max temperature [DMT], precipitation, and wind speed. An infra-red trail counter provided data on daily trail use along a greenway, over a 2-year period. Multiple regression analysis was used to examine associations between PA and weather, while controlling for day of the week and month of the year. The overall regression model explained 77.0% of the variance in daily PA (p < 0.001). DMT (b = 10.5), max temp-squared (b = −4.0), precipitation (b = −70.0), and max wind speed (b = 1.9) contributed significantly. Conclusion: Aggregated daily data can detect relationships between weather and outdoor PA. PMID:21556205

The relationship among self-efficacy, perfectionism and academic burnout in medical school students

PubMed Central

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-01-01

Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students. PMID:26838568

Predictors of Dropout by Female Obese Patients Treated with a Group Cognitive Behavioral Therapy to Promote Weight Loss

PubMed Central

Sawamoto, Ryoko; Nozaki, Takehiro; Furukawa, Tomokazu; Tanahashi, Tokusei; Morita, Chihiro; Hata, Tomokazu; Komaki, Gen; Sudo, Nobuyuki

2016-01-01

Objective To investigate predictors of dropout from a group cognitive behavioral therapy (CBT) intervention for overweight or obese women. Methods 119 overweight and obese Japanese women aged 25-65 years who attended an outpatient weight loss intervention were followed throughout the 7-month weight loss phase. Somatic characteristics, socioeconomic status, obesity-related diseases, diet and exercise habits, and psychological variables (depression, anxiety, self-esteem, alexithymia, parenting style, perfectionism, and eating attitude) were assessed at baseline. Significant variables, extracted by univariate statistical analysis, were then used as independent variables in a stepwise multiple logistic regression analysis with dropout as the dependent variable. Results 90 participants completed the weight loss phase, giving a dropout rate of 24.4%. The multiple logistic regression analysis demonstrated that compared to completers the dropouts had significantly stronger body shape concern, tended to not have jobs, perceived their mothers to be less caring, and were more disorganized in temperament. Of all these factors, the best predictor of dropout was shape concern. Conclusion Shape concern, job condition, parenting care, and organization predicted dropout from the group CBT weight loss intervention for overweight or obese Japanese women. PMID:26745715

Measurement Consistency from Magnetic Resonance Images

PubMed Central

Chung, Dongjun; Chung, Moo K.; Durtschi, Reid B.; Lindell, R. Gentry; Vorperian, Houri K.

2010-01-01

Rationale and Objectives In quantifying medical images, length-based measurements are still obtained manually. Due to possible human error, a measurement protocol is required to guarantee the consistency of measurements. In this paper, we review various statistical techniques that can be used in determining measurement consistency. The focus is on detecting a possible measurement bias and determining the robustness of the procedures to outliers. Materials and Methods We review correlation analysis, linear regression, Bland-Altman method, paired t-test, and analysis of variance (ANOVA). These techniques were applied to measurements, obtained by two raters, of head and neck structures from magnetic resonance images (MRI). Results The correlation analysis and the linear regression were shown to be insufficient for detecting measurement inconsistency. They are also very sensitive to outliers. The widely used Bland-Altman method is a visualization technique so it lacks the numerical quantification. The paired t-test tends to be sensitive to small measurement bias. On the other hand, ANOVA performs well even under small measurement bias. Conclusion In almost all cases, using only one method is insufficient and it is recommended to use several methods simultaneously. In general, ANOVA performs the best. PMID:18790405

Effects of Climate Change on Salmonella Infections

PubMed Central

Akil, Luma; Reddy, Remata S.

2014-01-01

Abstract Background: Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. Methods: Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. Results: A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R2=0.554; R2=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. Conclusion: There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections. PMID:25496072

Failure of Standard Training Sets in the Analysis of Fast-Scan Cyclic Voltammetry Data.

PubMed

Johnson, Justin A; Rodeberg, Nathan T; Wightman, R Mark

2016-03-16

The use of principal component regression, a multivariate calibration method, in the analysis of in vivo fast-scan cyclic voltammetry data allows for separation of overlapping signal contributions, permitting evaluation of the temporal dynamics of multiple neurotransmitters simultaneously. To accomplish this, the technique relies on information about current-concentration relationships across the scan-potential window gained from analysis of training sets. The ability of the constructed models to resolve analytes depends critically on the quality of these data. Recently, the use of standard training sets obtained under conditions other than those of the experimental data collection (e.g., with different electrodes, animals, or equipment) has been reported. This study evaluates the analyte resolution capabilities of models constructed using this approach from both a theoretical and experimental viewpoint. A detailed discussion of the theory of principal component regression is provided to inform this discussion. The findings demonstrate that the use of standard training sets leads to misassignment of the current-concentration relationships across the scan-potential window. This directly results in poor analyte resolution and, consequently, inaccurate quantitation, which may lead to erroneous conclusions being drawn from experimental data. Thus, it is strongly advocated that training sets be obtained under the experimental conditions to allow for accurate data analysis.

Comparison of Prediction Model for Cardiovascular Autonomic Dysfunction Using Artificial Neural Network and Logistic Regression Analysis

PubMed Central

Zeng, Fangfang; Li, Zhongtao; Yu, Xiaoling; Zhou, Linuo

2013-01-01

Background This study aimed to develop the artificial neural network (ANN) and multivariable logistic regression (LR) analyses for prediction modeling of cardiovascular autonomic (CA) dysfunction in the general population, and compare the prediction models using the two approaches. Methods and Materials We analyzed a previous dataset based on a Chinese population sample consisting of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN and LR analysis, and were tested in the validation set. Performances of these prediction models were then compared. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with the prevalence of CA dysfunction (P<0.05). The mean area under the receiver-operating curve was 0.758 (95% CI 0.724–0.793) for LR and 0.762 (95% CI 0.732–0.793) for ANN analysis, but noninferiority result was found (P<0.001). The similar results were found in comparisons of sensitivity, specificity, and predictive values in the prediction models between the LR and ANN analyses. Conclusion The prediction models for CA dysfunction were developed using ANN and LR. ANN and LR are two effective tools for developing prediction models based on our dataset. PMID:23940593

Regression Analysis by Example. 5th Edition

ERIC Educational Resources Information Center

Chatterjee, Samprit; Hadi, Ali S.

2012-01-01

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

Age adjustment in ecological studies: using a study on arsenic ingestion and bladder cancer as an example.

PubMed

Guo, How-Ran

2011-10-20

Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example. A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.

Impact of External Price Referencing on Medicine Prices – A Price Comparison Among 14 European Countries

PubMed Central

Leopold, Christine; Mantel-Teeuwisse, Aukje Katja; Seyfang, Leonhard; Vogler, Sabine; de Joncheere, Kees; Laing, Richard Ogilvie; Leufkens, Hubert

2012-01-01

Objectives: This study aims to examine the impact of external price referencing (EPR) on on-patent medicine prices, adjusting for other factors that may affect price levels such as sales volume, exchange rates, gross domestic product (GDP) per capita, total pharmaceutical expenditure (TPE), and size of the pharmaceutical industry. Methods: Price data of 14 on-patent products, in 14 European countries in 2007 and 2008 were obtained from the Pharmaceutical Price Information Service of the Austrian Health Institute. Based on the unit ex-factory prices in EURO, scaled ranks per country and per product were calculated. For the regression analysis the scaled ranks per country and product were weighted; each country had the same sum of weights but within a country the weights were proportional to its sales volume in the year (data obtained from IMS Health). Taking the scaled ranks, several statistical analyses were performed by using the program “R”, including a multiple regression analysis (including variables such as GDP per capita and national industry size). Results: This study showed that on average EPR as a pricing policy leads to lower prices. However, the large variation in price levels among countries using EPR confirmed that the price level is not only driven by EPR. The unadjusted linear regression model confirms that applying EPR in a country is associated with a lower scaled weighted rank (p=0.002). This interaction persisted after inclusion of total pharmaceutical expenditure per capita and GDP per capita in the final model. Conclusions: The study showed that for patented products, prices are in general lower in case the country applied EPR. Nevertheless substantial price differences among countries that apply EPR could be identified. Possible explanations could be found through a correlation between pharmaceutical industry and the scaled price ranks. In conclusion, we found that implementing external reference pricing could lead to lower prices. PMID:23532710

"Singing in the Tube"--audiovisual assay of plant oil repellent activity against mosquitoes (Culex pipiens).

PubMed

Adams, Temitope F; Wongchai, Chatchawal; Chaidee, Anchalee; Pfeiffer, Wolfgang

2016-01-01

Plant essential oils have been suggested as a promising alternative to the established mosquito repellent DEET (N,N-diethyl-meta-toluamide). Searching for an assay with generally available equipment, we designed a new audiovisual assay of repellent activity against mosquitoes "Singing in the Tube," testing single mosquitoes in Drosophila cultivation tubes. Statistics with regression analysis should compensate for limitations of simple hardware. The assay was established with female Culex pipiens mosquitoes in 60 experiments, 120-h audio recording, and 2580 estimations of the distance between mosquito sitting position and the chemical. Correlations between parameters of sitting position, flight activity pattern, and flight tone spectrum were analyzed. Regression analysis of psycho-acoustic data of audio files (dB[A]) used a squared and modified sinus function determining wing beat frequency WBF ± SD (357 ± 47 Hz). Application of logistic regression defined the repelling velocity constant. The repelling velocity constant showed a decreasing order of efficiency of plant essential oils: rosemary (Rosmarinus officinalis), eucalyptus (Eucalyptus globulus), lavender (Lavandula angustifolia), citronella (Cymbopogon nardus), tea tree (Melaleuca alternifolia), clove (Syzygium aromaticum), lemon (Citrus limon), patchouli (Pogostemon cablin), DEET, cedar wood (Cedrus atlantica). In conclusion, we suggest (1) disease vector control (e.g., impregnation of bed nets) by eight plant essential oils with repelling velocity superior to DEET, (2) simple mosquito repellency testing in Drosophila cultivation tubes, (3) automated approaches and room surveillance by generally available audio equipment (dB[A]: ISO standard 226), and (4) quantification of repellent activity by parameters of the audiovisual assay defined by correlation and regression analyses.

P300 Amplitude in Alzheimer's Disease: A Meta-Analysis and Meta-Regression.

PubMed

Hedges, Dawson; Janis, Rebecca; Mickelson, Stephen; Keith, Cierra; Bennett, David; Brown, Bruce L

2016-01-01

Alzheimer's disease accounts for 60% of all dementia. Numerous biomarkers have been developed that can help in making an early diagnosis. The P300 is an event-related potential that may be abnormal in Alzheimer's disease. Given the possible association between P300 amplitude and Alzheimer's disease and the need for biomarkers in early Alzheimer's disease, the main purpose of this meta-analysis and meta-regression was to characterize P300 amplitude in probable Alzheimer's disease compared to healthy controls. Using online search engines, we identified peer-reviewed articles containing amplitude measures for the P300 in response to a visual or auditory oddball stimulus in subjects with Alzheimer's disease and in a healthy control group and pooled effect sizes for differences in P300 amplitude between Alzheimer's disease and control groups to obtain summary effect sizes. We also used meta-regression to determine whether age, sex, educational attainment, or dementia severity affected the association between P300 amplitude and Alzheimer's disease. Twenty articles containing a total of 646 subjects met inclusion and exclusion criteria. The overall effect size from all electrode locations was 1.079 (95% confidence interval=0.745-1.412, P<.001). The pooled effect sizes for the Cz, Fz, and Pz locations were 1.226 (P<.001), 0.724 (P=.0007), and 1.430 (P<.001), respectively. Meta-regression showed an association between amplitude and educational attainment, but no association between amplitude and age, sex, and dementia severity. In conclusion, P300 amplitude is smaller in subjects with Alzheimer's disease than in healthy controls. © EEG and Clinical Neuroscience Society (ECNS) 2014.

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.

A Large-Scale Initiative Inviting Patients to Share Personal Fitness Tracker Data with Their Providers: Initial Results

PubMed Central

Pevnick, Joshua M.; Fuller, Garth; Duncan, Ray; Spiegel, Brennan M. R.

2016-01-01

Background Personal fitness trackers (PFT) have substantial potential to improve healthcare. Objective To quantify and characterize early adopters who shared their PFT data with providers. Methods We used bivariate statistics and logistic regression to compare patients who shared any PFT data vs. patients who did not. Results A patient portal was used to invite 79,953 registered portal users to share their data. Of 66,105 users included in our analysis, 499 (0.8%) uploaded data during an initial 37-day study period. Bivariate and regression analysis showed that early adopters were more likely than non-adopters to be younger, male, white, health system employees, and to have higher BMIs. Neither comorbidities nor utilization predicted adoption. Conclusion Our results demonstrate that patients had little intrinsic desire to share PFT data with their providers, and suggest that patients most at risk for poor health outcomes are least likely to share PFT data. Marketing, incentives, and/or cultural change may be needed to induce such data-sharing. PMID:27846287

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Correlates of HIV knowledge and Sexual risk behaviors among Female Military Personnel

PubMed Central

Essien, E. James; Monjok, Emmanuel; Chen, Hua; Abughosh, Susan; Ekong, Ernest; Peters, Ronald J.; Holmes, Laurens; Holstad, Marcia M.; Mgbere, Osaro

2010-01-01

Objective Uniformed services personnel are at an increased risk of HIV infection. We examined the HIV/AIDS knowledge and sexual risk behaviors among female military personnel to determine the correlates of HIV risk behaviors in this population. Method The study used a cross-sectional design to examine HIV/AIDS knowledge and sexual risk behaviors in a sample of 346 females drawn from two military cantonments in Southwestern Nigeria. Data was collected between 2006 and 2008. Using bivariate analysis and multivariate logistic regression, HIV/AIDS knowledge and sexual behaviors were described in relation to socio-demographic characteristics of the participants. Results Multivariate logistic regression analysis revealed that level of education and knowing someone with HIV/AIDS were significant (p<0.05) predictors of HIV knowledge in this sample. HIV prevention self-efficacy was significantly (P<0.05) predicted by annual income and race/ethnicity. Condom use attitudes were also significantly (P<0.05) associated with number of children, annual income, and number of sexual partners. Conclusion Data indicates the importance of incorporating these predictor variables into intervention designs. PMID:20387111

The Calibration of AVHRR/3 Visible Dual Gain Using Meteosat-8 as a MODIS Calibration Transfer Medium

NASA Technical Reports Server (NTRS)

Avey, Lance; Garber, Donald; Nguyen, Louis; Minnis, Patrick

2007-01-01

This viewgraph presentation reviews the NOAA-17 AVHRR visible channels calibrated against MET-8/MODIS using dual gain regression methods. The topics include: 1) Motivation; 2) Methodology; 3) Dual Gain Regression Methods; 4) Examples of Regression methods; 5) AVHRR/3 Regression Strategy; 6) Cross-Calibration Method; 7) Spectral Response Functions; 8) MET8/NOAA-17; 9) Example of gain ratio adjustment; 10) Effect of mixed low/high count FOV; 11) Monitor dual gains over time; and 12) Conclusions

Multiple Regression Analysis of mRNA-miRNA Associations in Colorectal Cancer Pathway

PubMed Central

Wang, Fengfeng; Wong, S. C. Cesar; Chan, Lawrence W. C.; Cho, William C. S.; Yip, S. P.; Yung, Benjamin Y. M.

2014-01-01

Background. MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways. Results. A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues. Conclusion. Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC. PMID:24895601

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

PubMed

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

2018-05-04

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

An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis

PubMed Central

KAWAGUCHI, TAKUMI; SUETSUGU, TAKURO; OGATA, SHYOU; IMANAGA, MINAMI; ISHII, KUMIKO; ESAKI, NAO; SUGIMOTO, MASAKO; OTSUYAMA, JYURI; NAGAMATSU, AYU; TANIGUCHI, EITARO; ITOU, MINORU; ORIISHI, TETSUHARU; IWASAKI, SHOKO; MIURA, HIROKO; TORIMURA, TAKUJI

2016-01-01

The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16–0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD. PMID:27123257

An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis.

PubMed

Kawaguchi, Takumi; Suetsugu, Takuro; Ogata, Shyou; Imanaga, Minami; Ishii, Kumiko; Esaki, Nao; Sugimoto, Masako; Otsuyama, Jyuri; Nagamatsu, Ayu; Taniguchi, Eitaro; Itou, Minoru; Oriishi, Tetsuharu; Iwasaki, Shoko; Miura, Hiroko; Torimura, Takuji

2016-05-01

The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16-0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD.

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation

PubMed Central

Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-01-01

Background Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Objective Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Methods Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Results Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. Conclusions To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. PMID:29506966

Examination of Factors that Influence the Operation Income and Expenditure Balance Difference Rate of 20 Educational Foundation Universities.

PubMed

Nakajima, Hisato; Yano, Kouya; Nagasawa, Kaoko; Katou, Satoka; Yokota, Kuninobu

2017-01-01

The objective of this study is to examine the factors that influence the operation income and expenditure balance ratio of school corporations running university hospitals by multiple regression analysis. 1. We conducted cluster analysis of the financial ratio and classified the school corporations into those running colleges and universities.2. We conducted multiple regression analysis using the operation income and expenditure balance ratio of the colleges as the variables and the Diagnosis Procedure Combination data as the explaining variables.3. The predictive expression was used for multiple regression analysis. 1. The school corporations were divided into those running universities (7), colleges (20) and others. The medical income ratio and the debt ratio were high and the student payment ratio was low in the colleges.2. The numbers of emergency care hospitalizations, operations, radiation therapies, and ambulance conveyances, and the complexity index had a positive influence on the operation income and expenditure balance ratio. On the other hand, the number of general anesthesia procedures, the cover rate index, and the emergency care index had a negative influence.3. The predictive expression was as follows.Operation income and expenditure balance ratio = 0.027 × number of emergency care hospitalizations + 0.005 × number of operations + 0.019 × number of radiation therapies + 0.007 × number of ambulance conveyances - 0.003 × number of general anesthesia procedures + 648.344 × complexity index - 5877.210 × cover rate index - 2746.415 × emergency care index - 38.647Conclusion: In colleges, the number of emergency care hospitalizations, the number of operations, the number of radiation therapies, and the number of ambulance conveyances and the complexity index were factors for gaining ordinary profit.

Association between metabolic syndrome and bone fracture risk: A community-based study using a fracture risk assessment tool.

PubMed

Yu, Chia-Ying; Chen, Fang-Ping; Chen, Li-Wei; Kuo, Sheng-Fong; Chien, Rong-Nan

2017-12-01

Osteoporosis and metabolic syndrome (MS) share similar risk factors. Previous studies of association between bone marrow density (BMD) and MS are controversial. Moreover, some studies revealed that MS is associated with BMD but not with bone fracture. In clinical practice, patients pay more attention to bone fracture risk than BMD values. Hence, this study aimed to evaluate the association between MS and the 10-year bone fracture risk probability using a fracture risk assessment tool (FRAX) from community-based data. From March 2014 to August 2015, 2689 participants (897 men and 1792 women) were enrolled in this study. Inflammatory cytokines, such as tumor necrosis factor alpha and C-reactive protein, and adipokines were included for analysis.The mean age was 60.2 ± 10.7 years in men and 58.9 ± 9.6 years in women. The percentage of MS was 27.6% in men and 27.9% in women. Participants were divided into 2 groups, those with or without MS. Compared with women without MS, women with MS had a higher rate of fracture risk (22.8% vs 16.3%, P = .001). In contrast, men with MS had a lower rate of fracture risk then men without MS (5.6% vs 12.3%, P = .004). However, MS loss the association with a high bone fracture risk in men based on multivariate logistical regression analysis, after adjusting for confounding factor of body mass index (BMI). Conclusively, the result of regression analysis between MS and the bone fracture risk may be different in men and women, and BMI was an important confounding factor to interfere with the regression analysis. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Collaborative Chronic Care Models for Mental Health Conditions: Cumulative Meta-Analysis and Meta-Regression to Guide Future Research and Implementation

PubMed Central

Grogan-Kaylor, Andrew; Perron, Brian E.; Kilbourne, Amy M.; Woltmann, Emily; Bauer, Mark S.

2013-01-01

Objective Prior meta-analysis indicates that collaborative chronic care models (CCMs) improve mental and physical health outcomes for individuals with mental disorders. This study aimed to investigate the stability of evidence over time and identify patient and intervention factors associated with CCM effects in order to facilitate implementation and sustainability of CCMs in clinical practice. Method We reviewed 53 CCM trials that analyzed depression, mental quality of life (QOL), or physical QOL outcomes. Cumulative meta-analysis and meta-regression were supplemented by descriptive investigations across and within trials. Results Most trials targeted depression in the primary care setting, and cumulative meta-analysis indicated that effect sizes favoring CCM quickly achieved significance for depression outcomes, and more recently achieved significance for mental and physical QOL. Four of six CCM elements (patient self-management support, clinical information systems, system redesign, and provider decision support) were common among reviewed trials, while two elements (healthcare organization support and linkages to community resources) were rare. No single CCM element was statistically associated with the success of the model. Similarly, meta-regression did not identify specific factors associated with CCM effectiveness. Nonetheless, results within individual trials suggest that increased illness severity predicts CCM outcomes. Conclusions Significant CCM trials have been derived primarily from four original CCM elements. Nonetheless, implementing and sustaining this established model will require healthcare organization support. While CCMs have typically been tested as population-based interventions, evidence supports stepped care application to more severely ill individuals. Future priorities include developing implementation strategies to support adoption and sustainability of the model in clinical settings while maximizing fit of this multi-component framework to local contextual factors. PMID:23938600

Sample entropy analysis for the estimating depth of anaesthesia through human EEG signal at different levels of unconsciousness during surgeries

PubMed Central

Fan, Shou-Zen; Abbod, Maysam F.

2018-01-01

Estimating the depth of anaesthesia (DoA) in operations has always been a challenging issue due to the underlying complexity of the brain mechanisms. Electroencephalogram (EEG) signals are undoubtedly the most widely used signals for measuring DoA. In this paper, a novel EEG-based index is proposed to evaluate DoA for 24 patients receiving general anaesthesia with different levels of unconsciousness. Sample Entropy (SampEn) algorithm was utilised in order to acquire the chaotic features of the signals. After calculating the SampEn from the EEG signals, Random Forest was utilised for developing learning regression models with Bispectral index (BIS) as the target. Correlation coefficient, mean absolute error, and area under the curve (AUC) were used to verify the perioperative performance of the proposed method. Validation comparisons with typical nonstationary signal analysis methods (i.e., recurrence analysis and permutation entropy) and regression methods (i.e., neural network and support vector machine) were conducted. To further verify the accuracy and validity of the proposed methodology, the data is divided into four unconsciousness-level groups on the basis of BIS levels. Subsequently, analysis of variance (ANOVA) was applied to the corresponding index (i.e., regression output). Results indicate that the correlation coefficient improved to 0.72 ± 0.09 after filtering and to 0.90 ± 0.05 after regression from the initial values of 0.51 ± 0.17. Similarly, the final mean absolute error dramatically declined to 5.22 ± 2.12. In addition, the ultimate AUC increased to 0.98 ± 0.02, and the ANOVA analysis indicates that each of the four groups of different anaesthetic levels demonstrated significant difference from the nearest levels. Furthermore, the Random Forest output was extensively linear in relation to BIS, thus with better DoA prediction accuracy. In conclusion, the proposed method provides a concrete basis for monitoring patients’ anaesthetic level during surgeries. PMID:29844970

A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance

PubMed Central

2014-01-01

Background Greater use of antibiotics during the past 50 years has exerted selective pressure on susceptible bacteria and may have favoured the survival of resistant strains. Existing information on antibiotic resistance patterns from pathogens circulating among community-based patients is substantially less than from hospitalized patients on whom guidelines are often based. We therefore chose to assess the relationship between the antibiotic resistance pattern of bacteria circulating in the community and the consumption of antibiotics in the community. Methods Both gray literature and published scientific literature in English and other European languages was examined. Multiple regression analysis was used to analyse whether studies found a positive relationship between antibiotic consumption and resistance. A subsequent meta-analysis and meta-regression was conducted for studies for which a common effect size measure (odds ratio) could be calculated. Results Electronic searches identified 974 studies but only 243 studies were considered eligible for inclusion by the two independent reviewers who extracted the data. A binomial test revealed a positive relationship between antibiotic consumption and resistance (p < .001) but multiple regression modelling did not produce any significant predictors of study outcome. The meta-analysis generated a significant pooled odds ratio of 2.3 (95% confidence interval 2.2 to 2.5) with a meta-regression producing several significant predictors (F(10,77) = 5.82, p < .01). Countries in southern Europe produced a stronger link between consumption and resistance than other regions. Conclusions Using a large set of studies we found that antibiotic consumption is associated with the development of antibiotic resistance. A subsequent meta-analysis, with a subsample of the studies, generated several significant predictors. Countries in southern Europe produced a stronger link between consumption and resistance than other regions so efforts at reducing antibiotic consumption may need to be strengthened in this area. Increased consumption of antibiotics may not only produce greater resistance at the individual patient level but may also produce greater resistance at the community, country, and regional levels, which can harm individual patients. PMID:24405683

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

NITPICK: peak identification for mass spectrometry data

PubMed Central

Renard, Bernhard Y; Kirchner, Marc; Steen , Hanno; Steen, Judith AJ; Hamprecht , Fred A

2008-01-01

Background The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments. Results This contribution proposes a sparse template regression approach to peak picking called NITPICK. NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra. NITPICK is based on fractional averagine, a novel extension to Senko's well-known averagine model, and on a modified version of sparse, non-negative least angle regression, for which a suitable, statistically motivated early stopping criterion has been derived. The strength of NITPICK is the deconvolution of overlapping mixture mass spectra. Conclusion Extensive comparative evaluation has been carried out and results are provided for simulated and real-world data sets. NITPICK outperforms pepex, to date the only alternate, publicly available, non-greedy feature extraction routine. NITPICK is available as software package for the R programming language and can be downloaded from . PMID:18755032

Casemix funding for a specialist paediatrics hospital: a hedonic regression approach.

PubMed

Bridges, J F; Hanson, R M

2000-01-01

This paper inquires into the effects that Diagnosis Related Groups (DRGs) have had on the ability to explain patient-level costs in a specialist paediatrics hospital. Two hedonic models are estimated using 1996/97 New Children's Hospital (NCH) patient level cost data, one with and one without a casemix index (CMI). The results show that the inclusion of a casemix index as an explanatory variable leads to a better accounting of cost. The full hedonic model is then used to simulate a funding model for the 1997/98 NCH cost data. These costs are highly correlated with the actual costs reported for that year. In addition, univariate regression indicates that there has been inflation in costs in the order of 4.8% between the two years. In conclusion, hedonic analysis can provide valuable evidence for the design of funding models that account for casemix.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

[Multivariate ordinal logistic regression analysis on the association between consumption of fried food and both esophageal cancer and precancerous lesions].

PubMed

Guo, L W; Liu, S Z; Zhang, M; Chen, Q; Zhang, S K; Sun, X B

2017-12-10

Objective: To investigate the effect of fried food intake on the pathogenesis of esophageal cancer and precancerous lesions. Methods: From 2005 to 2013, all the residents aged 40-69 years from 11 counties (cities) where cancer screening of upper gastrointestinal cancer had been conducted in rural areas of Henan province, were recruited as the subjects of study. Information on demography and lifestyle was collected. The residents under study were screened with iodine staining endoscopic examination and biopsy samples were diagnosed pathologically, under standardized criteria. Subjects with high risk were divided into the groups based on their different pathological degrees. Multivariate ordinal logistic regression analysis was used to analyze the relationship between the frequency of fried food intake and esophageal cancer and precancerous lesions. Results: A total number of 8 792 cases with normal esophagus, 3 680 with mild hyperplasia, 972 with moderate hyperplasia, 413 with severe hyperplasia carcinoma in situ, and 336 cases of esophageal cancer were recruited. Results from multivariate logistic regression analysis showed that, when compared with those who did not eat fried food, the intake of fried food (<2 times/week: OR =1.60, 95% CI : 1.40-1.83; ≥2 times/week: OR =2.58, 95% CI : 1.98-3.37) appeared a risk factor for both esophageal cancer or precancerous lesions after adjustment for age, sex, marital status, educational level, body mass index, smoking and alcohol intake. Conclusion: The intake of fried food appeared a risk factor for both esophageal cancer and precancerous lesions.

An empirical study using permutation-based resampling in meta-regression

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

The time frame of Epstein-Barr virus latent membrane protein-1 gene to disappear in nasopharyngeal swabs after initiation of primary radiotherapy is an independently significant prognostic factor predicting local control for patients with nasopharyngeal carcinoma

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

Lin, S.-Y.; Chang, K.-P.; Graduate Institute of Clinical Medical Sciences, Chang Gung University, Linkou, Taiwan

Purpose: The presence of Epstein-Barr virus latent membrane protein-1 (LMP-1) gene in nasopharyngeal swabs indicates the presence of nasopharyngeal carcinoma (NPC) mucosal tumor cells. This study was undertaken to investigate whether the time taken for LMP-1 to disappear after initiation of primary radiotherapy (RT) was inversely associated with NPC local control. Methods and Materials: During July 1999 and October 2002, there were 127 nondisseminated NPC patients receiving serial examinations of nasopharyngeal swabbing with detection of LMP-1 during the RT course. The time for LMP-1 regression was defined as the number of days after initiation of RT for LMP-1 results tomore » turn negative. The primary outcome was local control, which was represented by freedom from local recurrence. Results: The time for LMP-1 regression showed a statistically significant influence on NPC local control both univariately (p < 0.0001) and multivariately (p = 0.004). In multivariate analysis, the administration of chemotherapy conferred a significantly more favorable local control (p = 0.03). Advanced T status ({>=} T2b), overall treatment time of external photon radiotherapy longer than 55 days, and older age showed trends toward being poor prognosticators. The time for LMP-1 regression was very heterogeneous. According to the quartiles of the time for LMP-1 regression, we defined the pattern of LMP-1 regression as late regression if it required 40 days or more. Kaplan-Meier plots indicated that the patients with late regression had a significantly worse local control than those with intermediate or early regression (p 0.0129). Conclusion: Among the potential prognostic factors examined in this study, the time for LMP-1 regression was the most independently significant factor that was inversely associated with NPC local control.« less

Higher-Than-Conventional Radiation Doses in Localized Prostate Cancer Treatment: A Meta-analysis of Randomized, Controlled Trials

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

Viani, Gustavo Arruda; Stefano, Eduardo Jose; Afonso, Sergio Luis

2009-08-01

Purpose: To determine in a meta-analysis whether the outcomes in men with localized prostate cancer treated with high-dose radiotherapy (HDRT) are better than those in men treated with conventional-dose radiotherapy (CDRT), by quantifying the effect of the total dose of radiotherapy on biochemical control (BC). Methods and Materials: The MEDLINE, EMBASE, CANCERLIT, and Cochrane Library databases, as well as the proceedings of annual meetings, were systematically searched to identify randomized, controlled studies comparing HDRT with CDRT for localized prostate cancer. To evaluate the dose-response relationship, we conducted a meta-regression analysis of BC ratios by means of weighted linear regression. Results:more » Seven RCTs with a total patient population of 2812 were identified that met the study criteria. Pooled results from these RCTs showed a significant reduction in the incidence of biochemical failure in those patients with prostate cancer treated with HDRT (p < 0.0001). However, there was no difference in the mortality rate (p = 0.38) and specific prostate cancer mortality rates (p = 0.45) between the groups receiving HDRT and CDRT. However, there were more cases of late Grade >2 gastrointestinal toxicity after HDRT than after CDRT. In the subgroup analysis, patients classified as being at low (p = 0.007), intermediate (p < 0.0001), and high risk (p < 0.0001) of biochemical failure all showed a benefit from HDRT. The meta-regression analysis also detected a linear correlation between the total dose of radiotherapy and biochemical failure (BC = -67.3 + [1.8 x radiotherapy total dose in Gy]; p = 0.04). Conclusions: Our meta-analysis showed that HDRT is superior to CDRT in preventing biochemical failure in low-, intermediate-, and high-risk prostate cancer patients, suggesting that this should be offered as a treatment for all patients, regardless of their risk status.« less

The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care.

PubMed

Taljaard, Monica; McKenzie, Joanne E; Ramsay, Craig R; Grimshaw, Jeremy M

2014-06-19

An interrupted time series design is a powerful quasi-experimental approach for evaluating effects of interventions introduced at a specific point in time. To utilize the strength of this design, a modification to standard regression analysis, such as segmented regression, is required. In segmented regression analysis, the change in intercept and/or slope from pre- to post-intervention is estimated and used to test causal hypotheses about the intervention. We illustrate segmented regression using data from a previously published study that evaluated the effectiveness of a collaborative intervention to improve quality in pre-hospital ambulance care for acute myocardial infarction (AMI) and stroke. In the original analysis, a standard regression model was used with time as a continuous variable. We contrast the results from this standard regression analysis with those from segmented regression analysis. We discuss the limitations of the former and advantages of the latter, as well as the challenges of using segmented regression in analysing complex quality improvement interventions. Based on the estimated change in intercept and slope from pre- to post-intervention using segmented regression, we found insufficient evidence of a statistically significant effect on quality of care for stroke, although potential clinically important effects for AMI cannot be ruled out. Segmented regression analysis is the recommended approach for analysing data from an interrupted time series study. Several modifications to the basic segmented regression analysis approach are available to deal with challenges arising in the evaluation of complex quality improvement interventions.

Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis

ERIC Educational Resources Information Center

Kim, Rae Seon

2011-01-01

When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…

Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis

PubMed Central

Nieves, Jeri W.; Gennings, Chris; Factor-Litvak, Pam; Hupf, Jonathan; Singleton, Jessica; Sharf, Valerie; Oskarsson, Björn; Fernandes Filho, J. Americo M.; Sorenson, Eric J.; D’Amico, Emanuele; Goetz, Ray; Mitsumoto, Hiroshi

2017-01-01

IMPORTANCE There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS). OBJECTIVE To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less. EXPOSURES Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ). MAIN OUTCOMES AND MEASURES Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale–Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC). RESULTS Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5–68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of “good” micronutrients and “good” food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses. CONCLUSIONS AND RELEVANCE Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional care of the patient with ALS should consider promoting fruit and vegetable intake since they are high in antioxidants and carotenes. PMID:27775751

High Expression of EphA4 Predicted Lesser Degree of Tumor Regression after Neoadjuvant Chemoradiotherapy in Rectal Cancer.

PubMed

Lin, Ching-Yih; Lee, Ying-En; Tian, Yu-Feng; Sun, Ding-Ping; Sheu, Ming-Jen; Lin, Chen-Yi; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Chang, I-Wei; Wang, Chieh-Tien; He, Hong-Lin

2017-01-01

Background: Numerous transmembrane receptor tyrosine kinase pathways have been found to play an important role in tumor progression in some cancers. This study was aimed to evaluate the clinical impact of Eph receptor A4 (EphA4) in patients with rectal cancer treated with neoadjuvant concurrent chemoradiotherapy (CCRT) combined with mesorectal excision, with special emphasis on tumor regression. Methods: Analysis of the publicly available expression profiling dataset of rectal cancer disclosed that EphA4 was the top-ranking, significantly upregulated, transmembrane receptor tyrosine kinase pathway-associated gene in the non-responders to CCRT, compared with the responders. Immunohistochemical study was conducted to assess the EphA4 expression in pre-treatment biopsy specimens from 172 rectal cancer patients without distant metastasis. The relationships between EphA4 expression and various clinicopathological factors or survival were statistically analyzed. Results: EphA4 expression was significantly associated with vascular invasion ( P =0.015), post-treatment depth of tumor invasion ( P =0.006), pre-treatment and post-treatment lymph node metastasis ( P =0.004 and P =0.011, respectively). More importantly, high EphA4 expression was significantly predictive for lesser degree of tumor regression after CCRT ( P =0.031). At univariate analysis, high EphA4 expression was a negative prognosticator for disease-specific survival ( P =0.0009) and metastasis-free survival ( P =0.0001). At multivariate analysis, high expression of EphA4 still served as an independent adverse prognostic factor for disease-specific survival (HR, 2.528; 95% CI, 1.131-5.651; P =0.024) and metastasis-free survival (HR, 3.908; 95% CI, 1.590-9.601; P =0.003). Conclusion: High expression of EphA4 predicted lesser degree of tumor regression after CCRT and served as an independent negative prognostic factor in patients with rectal cancer.

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center

PubMed Central

Mehra, Tarun; Müller, Christian Thomas Benedikt; Volbracht, Jörk; Seifert, Burkhardt; Moos, Rudolf

2015-01-01

Principles Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG. Methods 28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings. Results Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001). Conclusion We suggest considering psychiatric diagnosis, admission as an emergencay case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses. PMID:26517545

Machine Learning Algorithms Outperform Conventional Regression Models in Predicting Development of Hepatocellular Carcinoma

PubMed Central

Singal, Amit G.; Mukherjee, Ashin; Elmunzer, B. Joseph; Higgins, Peter DR; Lok, Anna S.; Zhu, Ji; Marrero, Jorge A; Waljee, Akbar K

2015-01-01

Background Predictive models for hepatocellular carcinoma (HCC) have been limited by modest accuracy and lack of validation. Machine learning algorithms offer a novel methodology, which may improve HCC risk prognostication among patients with cirrhosis. Our study's aim was to develop and compare predictive models for HCC development among cirrhotic patients, using conventional regression analysis and machine learning algorithms. Methods We enrolled 442 patients with Child A or B cirrhosis at the University of Michigan between January 2004 and September 2006 (UM cohort) and prospectively followed them until HCC development, liver transplantation, death, or study termination. Regression analysis and machine learning algorithms were used to construct predictive models for HCC development, which were tested on an independent validation cohort from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial. Both models were also compared to the previously published HALT-C model. Discrimination was assessed using receiver operating characteristic curve analysis and diagnostic accuracy was assessed with net reclassification improvement and integrated discrimination improvement statistics. Results After a median follow-up of 3.5 years, 41 patients developed HCC. The UM regression model had a c-statistic of 0.61 (95%CI 0.56-0.67), whereas the machine learning algorithm had a c-statistic of 0.64 (95%CI 0.60–0.69) in the validation cohort. The machine learning algorithm had significantly better diagnostic accuracy as assessed by net reclassification improvement (p<0.001) and integrated discrimination improvement (p=0.04). The HALT-C model had a c-statistic of 0.60 (95%CI 0.50-0.70) in the validation cohort and was outperformed by the machine learning algorithm (p=0.047). Conclusion Machine learning algorithms improve the accuracy of risk stratifying patients with cirrhosis and can be used to accurately identify patients at high-risk for developing HCC. PMID:24169273

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

ERIC Educational Resources Information Center

Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

The effect of first chromosome long arm duplication on survival of endometrial carcinoma

PubMed Central

Sever, Erman; Doğer, Emek; Çakıroğlu, Yiğit; Sünnetçi, Deniz; Çine, Naci; Savlı, Hakan; Yücesoy, İzzet

2014-01-01

Objective: The aim of this study is to investigate the effect of first chromosome long arm duplication (dup(1q)) in cases with endometrial carcinoma detected with array based comperative genomic hybridization (aCGH) on survival from the cancer. Materials and Methods: A total of 53 patients with the diagnosis of endometrial carcinom due to endometrial biopsy and who have been operated for this reason have been allocated in the study. Frozen section biopsy and staging surgery have been performed for all the cases. Samples obtained from the tumoral mass have been investigated for chromosomal aberrations with aCGH method. Kaplan-Meier and Cox-regression analysis have been performed for survival analysis. Results: Among 53 cases with endometrial carcinomas, dup(1q) was diagnosed in 14 (26.4%) of the cases. For the patient group that has been followed-up for 24 months (3-33 months), dup(1q) (p=.01), optimal cytoreduction (p<.001), lymph node positivity (p=.006), tumor stage >1 (p=.006) and presence of high risk tumor were the factors that were associated with survival. Cox-regression analysis has revealed that optimal cytoreduction was the most important prognostic factor (p=.02). Conclusion: Presence of 1q duplication can be used as a prognostic factor in the preoperative period. PMID:28913021

Nursing home cost and ownership type: evidence of interaction effects.

PubMed

Arling, G; Nordquist, R H; Capitman, J A

1987-06-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed.

Factors affecting cognitive function according to gender in community-dwelling elderly individuals

PubMed Central

2017-01-01

OBJECTIVES This study aimed to identify the factors affecting the cognitive function of elderly people in a community by gender. METHODS We obtained 4,878 secondary data of people aged ≥65 years in 2016 at a dementia prevention center in Gyeyang-gu, Incheon. Data were obtained through Mini-Mental Status Examination optimized for screening dementia and a questionnaire. The data were statistically analyzed using analysis of variance, analysis of covariance, and hierarchical regression. RESULTS There were significant differences in cognitive function according to gender, and the differences were significant even when age was controlled, but gender differences disappeared when education was controlled. Age, education, social activities, number of comorbid diseases, and alcohol drinking affected cognitive function through interaction with gender, but interaction with gender disappeared when education was controlled. Regression analysis showed that depression, cohabitant, social activities etc., had a significant impact on both men and women under controlled education and age. In men, the effect of social activities was greater than that of women, and hyperlipidemia had the effect only in women. CONCLUSIONS The differences in gender-related cognitive functions were due to differences in gender education period. The period of education is considered to have a great influence on cognitive function in relation to the economic level, occupation, and social activity. PMID:29141399

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

PubMed Central

Lin, Meihua; Li, Haoli; Zhao, Xiaolei; Qin, Jiheng

2013-01-01

Genome-wide analysis of gene-gene interactions has been recognized as a powerful avenue to identify the missing genetic components that can not be detected by using current single-point association analysis. Recently, several model-free methods (e.g. the commonly used information based metrics and several logistic regression-based metrics) were developed for detecting non-linear dependence between genetic loci, but they are potentially at the risk of inflated false positive error, in particular when the main effects at one or both loci are salient. In this study, we proposed two conditional entropy-based metrics to challenge this limitation. Extensive simulations demonstrated that the two proposed metrics, provided the disease is rare, could maintain consistently correct false positive rate. In the scenarios for a common disease, our proposed metrics achieved better or comparable control of false positive error, compared to four previously proposed model-free metrics. In terms of power, our methods outperformed several competing metrics in a range of common disease models. Furthermore, in real data analyses, both metrics succeeded in detecting interactions and were competitive with the originally reported results or the logistic regression approaches. In conclusion, the proposed conditional entropy-based metrics are promising as alternatives to current model-based approaches for detecting genuine epistatic effects. PMID:24339984

High Prevalence of Leptotrichia amnionii, Atopobium vaginae, Sneathia sanguinegens, and Factor 1 Microbes and Association of Spontaneous Abortion among Korean Women.

PubMed

Seo, Sang Soo; Arokiyaraj, Selvaraj; Kim, Mi Kyung; Oh, Hea Young; Kwon, Minji; Kong, Ji Sook; Shin, Moon Kyung; Yu, Ye Lee; Lee, Jae Kwan

2017-01-01

Objective. The purpose of this study was to (i) determine the cervical microbial composition in different abortion samples and to (ii) investigate the correlation between spontaneous abortion and cervical microbes in Korean women. Methods. We collected cervical swabs from women who had never undergone abortion ( N = 36), had spontaneous abortion ( N = 23), and had undergone induced abortion ( N = 88) and subjected those samples to 16S rRNA pyrosequencing. Further, factor analysis and correlation between cervical microbiota and spontaneous abortion were evaluated by logistic regression analysis. Results. In spontaneous abortion women, 16 S rRNA gene sequences showed significant increases in Atopobium vaginae , Megasphaera spp., Gardnerella vaginalis , Leptotrichia amnionii , and Sneathia sanguinegens compared to women in nonabortion group. In multivariate logistic regression analysis, A. vaginae (OD = 11.27; 95% = 1.57-81) , L. amnionii (OD = 11.47; 95% = 1.22-107.94), S. sanguinegens (OD = 6.89; 95% = 1.07-44.33), and factor 1 microbes (OD = 16.4; 95% = 1.88-42.5) were strongly associated with spontaneous abortion. Conclusions. This study showed a high prevalence of L. amnionii, A. vaginae, S. sanguinegens , and factor 1 microbes in spontaneous abortion and association with spontaneous abortion in Korean women.

High Prevalence of Leptotrichia amnionii, Atopobium vaginae, Sneathia sanguinegens, and Factor 1 Microbes and Association of Spontaneous Abortion among Korean Women

PubMed Central

Seo, Sang Soo; Arokiyaraj, Selvaraj; Oh, Hea Young; Kwon, Minji; Kong, Ji Sook; Shin, Moon Kyung; Yu, Ye Lee; Lee, Jae Kwan

2017-01-01

Objective. The purpose of this study was to (i) determine the cervical microbial composition in different abortion samples and to (ii) investigate the correlation between spontaneous abortion and cervical microbes in Korean women. Methods. We collected cervical swabs from women who had never undergone abortion (N = 36), had spontaneous abortion (N = 23), and had undergone induced abortion (N = 88) and subjected those samples to 16S rRNA pyrosequencing. Further, factor analysis and correlation between cervical microbiota and spontaneous abortion were evaluated by logistic regression analysis. Results. In spontaneous abortion women, 16 S rRNA gene sequences showed significant increases in Atopobium vaginae, Megasphaera spp., Gardnerella vaginalis, Leptotrichia amnionii, and Sneathia sanguinegens compared to women in nonabortion group. In multivariate logistic regression analysis, A. vaginae (OD = 11.27; 95% = 1.57–81), L. amnionii (OD = 11.47; 95% = 1.22–107.94), S. sanguinegens (OD = 6.89; 95% = 1.07–44.33), and factor 1 microbes (OD = 16.4; 95% = 1.88–42.5) were strongly associated with spontaneous abortion. Conclusions. This study showed a high prevalence of L. amnionii, A. vaginae, S. sanguinegens, and factor 1 microbes in spontaneous abortion and association with spontaneous abortion in Korean women. PMID:29479540

Comparisons between Arabidopsis thaliana and Drosophila melanogaster in relation to Coding and Noncoding Sequence Length and Gene Expression

PubMed Central

Caldwell, Rachel; Lin, Yan-Xia; Zhang, Ren

2015-01-01

There is a continuing interest in the analysis of gene architecture and gene expression to determine the relationship that may exist. Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. Although a negative correlation between expression level and gene (especially transcript) length has been generally accepted, there have been some conflicting results arising from the literature concerning the impacts of different regions of genes, and the underlying reason is not well understood. The research aims to apply quantile regression techniques for statistical analysis of coding and noncoding sequence length and gene expression data in the plant, Arabidopsis thaliana, and fruit fly, Drosophila melanogaster, to determine if a relationship exists and if there is any variation or similarities between these species. The quantile regression analysis found that the coding sequence length and gene expression correlations varied, and similarities emerged for the noncoding sequence length (5′ and 3′ UTRs) between animal and plant species. In conclusion, the information described in this study provides the basis for further exploration into gene regulation with regard to coding and noncoding sequence length. PMID:26114098

Patient satisfaction in Dental Healthcare Centers

PubMed Central

Ali, Dena A.

2016-01-01

Objectives: This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Materials and Methods: Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. Results: The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists’ performance, followed by the dental assistants’ services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R2) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Conclusion: Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required. PMID:27403045

Nursing home cost and ownership type: evidence of interaction effects.

PubMed Central

Arling, G; Nordquist, R H; Capitman, J A

1987-01-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed. PMID:3301746

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

PubMed Central

Zhang, Juanjuan; Yan, Li; Fu, Wenlong; Yi, Jing; Chen, Yuzhi; Liu, Chuanhe; Xu, Dongqun; Wang, Qiang

2016-01-01

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China's urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p < 0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (β = −19.572, p < 0.05). Furthermore, results had shown that hours of sunshine (β = −0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China. PMID:27556031

Quotation accuracy in medical journal articles-a systematic review and meta-analysis.

PubMed

Jergas, Hannah; Baethge, Christopher

2015-01-01

Background. Quotations and references are an indispensable element of scientific communication. They should support what authors claim or provide important background information for readers. Studies indicate, however, that quotations not serving their purpose-quotation errors-may be prevalent. Methods. We carried out a systematic review, meta-analysis and meta-regression of quotation errors, taking account of differences between studies in error ascertainment. Results. Out of 559 studies screened we included 28 in the main analysis, and estimated major, minor and total quotation error rates of 11,9%, 95% CI [8.4, 16.6] 11.5% [8.3, 15.7], and 25.4% [19.5, 32.4]. While heterogeneity was substantial, even the lowest estimate of total quotation errors was considerable (6.7%). Indirect references accounted for less than one sixth of all quotation problems. The findings remained robust in a number of sensitivity and subgroup analyses (including risk of bias analysis) and in meta-regression. There was no indication of publication bias. Conclusions. Readers of medical journal articles should be aware of the fact that quotation errors are common. Measures against quotation errors include spot checks by editors and reviewers, correct placement of citations in the text, and declarations by authors that they have checked cited material. Future research should elucidate if and to what degree quotation errors are detrimental to scientific progress.

Quotation accuracy in medical journal articles—a systematic review and meta-analysis

PubMed Central

Jergas, Hannah

2015-01-01

Background. Quotations and references are an indispensable element of scientific communication. They should support what authors claim or provide important background information for readers. Studies indicate, however, that quotations not serving their purpose—quotation errors—may be prevalent. Methods. We carried out a systematic review, meta-analysis and meta-regression of quotation errors, taking account of differences between studies in error ascertainment. Results. Out of 559 studies screened we included 28 in the main analysis, and estimated major, minor and total quotation error rates of 11,9%, 95% CI [8.4, 16.6] 11.5% [8.3, 15.7], and 25.4% [19.5, 32.4]. While heterogeneity was substantial, even the lowest estimate of total quotation errors was considerable (6.7%). Indirect references accounted for less than one sixth of all quotation problems. The findings remained robust in a number of sensitivity and subgroup analyses (including risk of bias analysis) and in meta-regression. There was no indication of publication bias. Conclusions. Readers of medical journal articles should be aware of the fact that quotation errors are common. Measures against quotation errors include spot checks by editors and reviewers, correct placement of citations in the text, and declarations by authors that they have checked cited material. Future research should elucidate if and to what degree quotation errors are detrimental to scientific progress. PMID:26528420

Parametric Methods for Dynamic 11C-Phenytoin PET Studies.

PubMed

Mansor, Syahir; Yaqub, Maqsood; Boellaard, Ronald; Froklage, Femke E; de Vries, Anke; Bakker, Esther D M; Voskuyl, Rob A; Eriksson, Jonas; Schwarte, Lothar A; Verbeek, Joost; Windhorst, Albert D; Lammertsma, Adriaan A

2017-03-01

In this study, the performance of various methods for generating quantitative parametric images of dynamic 11 C-phenytoin PET studies was evaluated. Methods: Double-baseline 60-min dynamic 11 C-phenytoin PET studies, including online arterial sampling, were acquired for 6 healthy subjects. Parametric images were generated using Logan plot analysis, a basis function method, and spectral analysis. Parametric distribution volume (V T ) and influx rate ( K 1 ) were compared with those obtained from nonlinear regression analysis of time-activity curves. In addition, global and regional test-retest (TRT) variability was determined for parametric K 1 and V T values. Results: Biases in V T observed with all parametric methods were less than 5%. For K 1 , spectral analysis showed a negative bias of 16%. The mean TRT variabilities of V T and K 1 were less than 10% for all methods. Shortening the scan duration to 45 min provided similar V T and K 1 with comparable TRT performance compared with 60-min data. Conclusion: Among the various parametric methods tested, the basis function method provided parametric V T and K 1 values with the least bias compared with nonlinear regression data and showed TRT variabilities lower than 5%, also for smaller volume-of-interest sizes (i.e., higher noise levels) and shorter scan duration. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Predictors of quality of life: A quantitative investigation of the stress-coping model in children with asthma

PubMed Central

Peeters, Yvette; Boersma, Sandra N; Koopman, Hendrik M

2008-01-01

Background Aim of this study is to further explore predictors of health related quality of life in children with asthma using factors derived from to the extended stress-coping model. While the stress-coping model has often been used as a frame of reference in studying health related quality of life in chronic illness, few have actually tested the model in children with asthma. Method In this survey study data were obtained by means of self-report questionnaires from seventy-eight children with asthma and their parents. Based on data derived from these questionnaires the constructs of the extended stress-coping model were assessed, using regression analysis and path analysis. Results The results of both regression analysis and path analysis reveal tentative support for the proposed relationships between predictors and health related quality of life in the stress-coping model. Moreover, as indicated in the stress-coping model, HRQoL is only directly predicted by coping. Both coping strategies 'emotional reaction' (significantly) and 'avoidance' are directly related to HRQoL. Conclusion In children with asthma, the extended stress-coping model appears to be a useful theoretical framework for understanding the impact of the illness on their quality of life. Consequently, the factors suggested by this model should be taken into account when designing optimal psychosocial-care interventions. PMID:18366753

Can the provision of a home help service for the elderly population reduce the incidence of fall-related injuries? A quasi-experimental study of the community-level effects on hospital admissions in Swedish municipalities.

PubMed

Bonander, Carl; Gustavsson, Johanna; Nilson, Finn

2016-12-01

Fall-related injuries are a global public health problem, especially in elderly populations. The effect of an intervention aimed at reducing the risk of falls in the homes of community-dwelling elderly persons was evaluated. The intervention mainly involves the performance of complicated tasks and hazards assessment by a trained assessor, and has been adopted gradually over the last decade by 191 of 290 Swedish municipalities. A quasi-experimental design was used where intention-to-treat effect estimates were derived using panel regression analysis and a regression discontinuity (RD) design. The outcome measure was the incidence of fall-related hospitalisations in the treatment population, the age of which varied by municipality (≥65 years, ≥67 years, ≥70 years or ≥75 years). We found no statistically significant reductions in injury incidence in the panel regression (IRR 1.01 (95% CI 0.98 to 1.05)) or RD (IRR 1.00 (95% CI 0.97 to 1.03)) analyses. The results are robust to several different model specifications, including segmented panel regression analysis with linear trend change and community fixed effects parameters. It is unclear whether the absence of an effect is due to a low efficacy of the services provided, or a result of low adherence. Additional studies of the effects on other quality-of-life measures are recommended before conclusions are drawn regarding the cost-effectiveness of the provision of home help service programmes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Ranibizumab alone or in combination with photodynamic therapy vs photodynamic therapy for polypoidal choroidal vasculopathy: a systematic review and Meta-analysis

PubMed Central

Tang, Kai; Si, Jun-Kang; Guo, Da-Dong; Cui, Yan; Du, Yu-Xiang; Pan, Xue-Mei; Bi, Hong-Sheng

2015-01-01

AIM To compare the efficacy of intravitreal ranibizumab (IVR) alone or in combination with photodynamic therapy (PDT) vs PDT in patients with symptomatic polypoidal choroidal vasculopathy (PCV). METHODS A systematic search of a wide range of databases (including PubMed, EMBASE, Cochrane Library and Web of Science) was searched to identify relevant studies. Both randomized controlled trials (RCTs) and non-RCT studies were included. Methodological quality of included literatures was evaluated according to the Newcastle-Ottawa Scale. RevMan 5.2.7 software was used to do the Meta-analysis. RESULTS Three RCTs and 6 retrospective studies were included. The results showed that PDT monotherapy had a significantly higher proportion in patients who achieved complete regression of polyps than IVR monotherapy at months 3, 6, and 12 (All P≤0.01), respectively. However, IVR had a tendency to be more effective in improving vision on the basis of RCTs. The proportion of patients who gained complete regression of polyps revealed that there was no significant difference between the combination treatment and PDT monotherapy. The mean change of best-corrected visual acuity (BCVA) from baseline showed that the combination treatment had significant superiority in improving vision vs PDT monotherapy at months 3, 6 and 24 (All P<0.05), respectively. In the mean time, this comparison result was also significant at month 12 (P<0.01) after removal of a heterogeneous study. CONCLUSION IVR has non-inferiority compare with PDT either in stabilizing or in improving vision, although it can hardly promote the regression of polyps. The combination treatment of PDT and IVR can exert a synergistic effect on regressing polyps and on maintaining or improving visual acuity. Thus, it can be the first-line therapy for PCV. PMID:26558226

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

Alterations of papilla dimensions after orthodontic closure of the maxillary midline diastema: a retrospective longitudinal study

PubMed Central

2016-01-01

Purpose The aim of this study was to evaluate alterations of papilla dimensions after orthodontic closure of the diastema between maxillary central incisors. Methods Sixty patients who had a visible diastema between maxillary central incisors that had been closed by orthodontic approximation were selected for this study. Various papilla dimensions were assessed on clinical photographs and study models before the orthodontic treatment and at the follow-up examination after closure of the diastema. Influences of the variables assessed before orthodontic treatment on the alterations of papilla height (PH) and papilla base thickness (PBT) were evaluated by univariate regression analysis. To analyze potential influences of the 3-dimensional papilla dimensions before orthodontic treatment on the alterations of PH and PBT, a multiple regression model was formulated including the 3-dimensional papilla dimensions as predictor variables. Results On average, PH decreased by 0.80 mm and PBT increased after orthodontic closure of the diastema (P<0.01). Univariate regression analysis revealed that the PH (P=0.002) and PBT (P=0.047) before orthodontic treatment influenced the alteration of PH. With respect to the alteration of PBT, the diastema width (P=0.045) and PBT (P=0.000) were found to be influential factors. PBT before the orthodontic treatment significantly influenced the alteration of PBT in the multiple regression model. Conclusions PH decreased but PBT increased after orthodontic closure of the diastema. The papilla dimensions before orthodontic treatment influenced the alterations of PH and PBT after closure of the diastema. The PBT increased more when the diastema width before the orthodontic treatment was larger. PMID:27382507

A Comparison between Multiple Regression Models and CUN-BAE Equation to Predict Body Fat in Adults

PubMed Central

Fuster-Parra, Pilar; Bennasar-Veny, Miquel; Tauler, Pedro; Yañez, Aina; López-González, Angel A.; Aguiló, Antoni

2015-01-01

Background Because the accurate measure of body fat (BF) is difficult, several prediction equations have been proposed. The aim of this study was to compare different multiple regression models to predict BF, including the recently reported CUN-BAE equation. Methods Multi regression models using body mass index (BMI) and body adiposity index (BAI) as predictors of BF will be compared. These models will be also compared with the CUN-BAE equation. For all the analysis a sample including all the participants and another one including only the overweight and obese subjects will be considered. The BF reference measure was made using Bioelectrical Impedance Analysis. Results The simplest models including only BMI or BAI as independent variables showed that BAI is a better predictor of BF. However, adding the variable sex to both models made BMI a better predictor than the BAI. For both the whole group of participants and the group of overweight and obese participants, using simple models (BMI, age and sex as variables) allowed obtaining similar correlations with BF as when the more complex CUN-BAE was used (ρ = 0:87 vs. ρ = 0:86 for the whole sample and ρ = 0:88 vs. ρ = 0:89 for overweight and obese subjects, being the second value the one for CUN-BAE). Conclusions There are simpler models than CUN-BAE equation that fits BF as well as CUN-BAE does. Therefore, it could be considered that CUN-BAE overfits. Using a simple linear regression model, the BAI, as the only variable, predicts BF better than BMI. However, when the sex variable is introduced, BMI becomes the indicator of choice to predict BF. PMID:25821960

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

Parents’ Perceptions of Skin Cancer Threat and Children’s Physical Activity

PubMed Central

Tran, Alexander D.; Aalborg, Jenny; Asdigian, Nancy L.; Morelli, Joseph G.; Mokrohisky, Stefan T.; Dellavalle, Robert P.; Berwick, Marianne; Box, Neil F.

2012-01-01

Introduction Sun exposure is a major risk factor for skin cancer, but without physical activity, children are at risk of childhood obesity. The objective of this study was to explore relationships between parental perceptions of skin cancer threat, sun protection behaviors, physical activity, and body mass index (BMI) in children. Methods This is a cross-sectional analysis nested within the Colorado Kids Sun Care Program sun safety intervention trial. In summer 2007, parent telephone interviews provided data on demographics, perceptions of skin cancer threat, sun protection behaviors, and physical activity. Physical examinations provided data on phenotype, freckling, and BMI. Data from 999 Colorado children born in 1998 were included in analysis. We used analysis of variance, Spearman’s rho (ρ) correlation, and multivariable linear regression analysis to evaluate relationships with total amount of outdoor physical activity. Results After controlling for sex, race/ethnicity, skin color, and sun protection, regression analysis showed that each unit increase in perceived severity of nonmelanoma skin cancer was associated with a 30% increase in hours of outdoor physical activity (P = .005). Hours of outdoor physical activity were not related to perceived severity of melanoma or perceived susceptibility to skin cancer. BMI-for-age was not significantly correlated with perceptions of skin cancer threat, use of sun protection, or level of physical activity. Conclusion The promotion of sun safety is not likely to inhibit physical activity. Skin cancer prevention programs should continue to promote midday sun avoidance and sun protection during outdoor activities. PMID:22935145

GIS-based spatial statistical analysis of risk areas for liver flukes in Surin Province of Thailand.

PubMed

Rujirakul, Ratana; Ueng-arporn, Naporn; Kaewpitoon, Soraya; Loyd, Ryan J; Kaewthani, Sarochinee; Kaewpitoon, Natthawut

2015-01-01

It is urgently necessary to be aware of the distribution and risk areas of liver fluke, Opisthorchis viverrini, for proper allocation of prevention and control measures. This study aimed to investigate the human behavior, and environmental factors influencing the distribution in Surin Province of Thailand, and to build a model using stepwise multiple regression analysis with a geographic information system (GIS) on environment and climate data. The relationship between the human behavior, attitudes (<50%; X111), environmental factors like population density (148-169 pop/km2; X73), and land use as wetland (X64), were correlated with the liver fluke disease distribution at 0.000, 0.034, and 0.006 levels, respectively. Multiple regression analysis, by equations OV=-0.599+0.005(population density (148-169 pop/km2); X73)+0.040 (human attitude (<50%); X111)+0.022 (land used (wetland; X64), was used to predict the distribution of liver fluke. OV is the patients of liver fluke infection, R Square=0.878, and, Adjust R Square=0.849. By GIS analysis, we found Si Narong, Sangkha, Phanom Dong Rak, Mueang Surin, Non Narai, Samrong Thap, Chumphon Buri, and Rattanaburi to have the highest distributions in Surin province. In conclusion, the combination of GIS and statistical analysis can help simulate the spatial distribution and risk areas of liver fluke, and thus may be an important tool for future planning of prevention and control measures.

Association of nitrogen compounds in drinking water with incidence of esophageal squamous cell carcinoma in Shexian, China.

PubMed

Zhang, Nan; Yu, Cao; Wen, Denggui; Chen, Jun; Ling, Yiwei; Terajima, Kenshi; Akazawa, Kohei; Shan, Baoen; Wang, Shijie

2012-01-01

The incidence of esophageal squamous cell carcinoma (ESCC), which is the eighth most common malignancy worldwide, is highest in China. The purpose of this study was to investigate the association between nitrogen compounds in drinking water with the incidence of ESCC by geographical spatial analysis. The incidence of ESCC is high in Shexian county, China, and environmental factors, particularly nitrogen-contaminated drinking water, are the main suspected risk factors. This study focuses on three nitrogen compounds in drinking water, namely, nitrates, nitrites, and ammonia, all of which are derived mainly from domestic garbage and agricultural fertilizer. The study surveyed 48 villages in the Shexian area with a total population of 54,716 (661 adults with ESCC and 54,055 non-cancer subjects). Hot-spot analysis was used to identify spatial clusters with a high incidence of ESCC and a high concentration of nitrogen compounds. Logistic regression analysis was used to detect risk factors for ESCC incidence. Most areas with high concentrations of nitrate nitrogen in drinking water had a high incidence of ESCC. Correlation analysis revealed a significant positive relationship between nitrate concentration and ESCC (P = 0.01). Logistic regression analysis also confirmed that nitrate nitrogen has a significantly higher odds ratio. The results indicate that nitrate nitrogen is associated with ESCC incidence in Shexian county. In conclusion, high concentrations of nitrate nitrogen in drinking water may be a significant risk factor for the incidence of ESCC.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Femoral anteversion and tibial torsion only explain 25% of variance in regression analysis of foot progression angle in children with diplegic cerebral palsy

PubMed Central

2013-01-01

Background The relationship between torsional bony deformities and rotational gait parameters has not been sufficiently investigated. This study was to investigate the degree of contribution of torsional bony deformities to rotational gait parameters in patients with diplegic cerebral palsy (CP). Methods Thirty three legs from 33 consecutive ambulatory patients (average age 9.5 years, SD 6.9 years; 20 males and 13 females) with diplegic CP who underwent preoperative three dimensional gait analysis, foot radiographs, and computed tomography (CT) were included. Adjusted foot progression angle (FPA) was retrieved from gait analysis by correcting pelvic rotation from conventional FPA, which represented the rotational gait deviation of the lower extremity from the tip of the femoral head to the foot. Correlations between rotational gait parameters (FPA, adjusted FPA, average pelvic rotation, average hip rotation, and average knee rotation) and radiologic measurements (acetabular version, femoral anteversion, knee torsion, tibial torsion, and anteroposteriortalo-first metatarsal angle) were analyzed. Multiple regression analysis was performed to identify significant contributing radiographic measurements to adjusted FPA. Results Adjusted FPA was significantly correlated with FPA (r=0.837, p<0.001), contralateral FPA (r=0.492, p=0.004), pelvic rotation during gait (r=−0.489, p=0.004), knee rotation during gait (r=0.376, p=0.031), and femoral anteversion (r=0.350, p=0.046). In multiple regression analysis, femoral anteversion (p=0.026) and tibial torsion (p=0.034) were found to be the significant contributing structural deformities to the adjusted FPA (R2=0.247). Conclusions Femoral anteversion and tibial torsion were found to be the significant structural deformities that could affect adjusted FPA in patients with diplegic CP. Femoral anteversion and tibial torsion could explain only 24.7% of adjusted FPA. PMID:23767833

Beyond Reading Alone: The Relationship Between Aural Literacy And Asthma Management

PubMed Central

Rosenfeld, Lindsay; Rudd, Rima; Emmons, Karen M.; Acevedo-García, Dolores; Martin, Laurie; Buka, Stephen

2010-01-01

Objectives To examine the relationship between literacy and asthma management with a focus on the oral exchange. Methods Study participants, all of whom reported asthma, were drawn from the New England Family Study (NEFS), an examination of links between education and health. NEFS data included reading, oral (speaking), and aural (listening) literacy measures. An additional survey was conducted with this group of study participants related to asthma issues, particularly asthma management. Data analysis focused on bivariate and multivariable logistic regression. Results In bivariate logistic regression models exploring aural literacy, there was a statistically significant association between those participants with lower aural literacy skills and less successful asthma management (OR:4.37, 95%CI:1.11, 17.32). In multivariable logistic regression analyses, controlling for gender, income, and race in separate models (one-at-a-time), there remained a statistically significant association between those participants with lower aural literacy skills and less successful asthma management. Conclusion Lower aural literacy skills seem to complicate asthma management capabilities. Practice Implications Greater attention to the oral exchange, in particular the listening skills highlighted by aural literacy, as well as other related literacy skills may help us develop strategies for clear communication related to asthma management. PMID:20399060

Comparison of Total Solar Irradiance with NASA/NSO Spectromagnetograph Data in Solar Cycles 22 and 23

NASA Technical Reports Server (NTRS)

Jones, Harrison P.; Branston, Detrick D.; Jones, Patricia B.; Popescu, Miruna D.

2002-01-01

An earlier study compared NASA/NSO Spectromagnetograph (SPM) data with spacecraft measurements of total solar irradiance (TSI) variations over a 1.5 year period in the declining phase of solar cycle 22. This paper extends the analysis to an eight-year period which also spans the rising and early maximum phases of cycle 23. The conclusions of the earlier work appear to be robust: three factors (sunspots, strong unipolar regions, and strong mixed polarity regions) describe most of the variation in the SPM record, but only the first two are associated with TSI. Additionally, the residuals of a linear multiple regression of TSI against SPM observations over the entire eight-year period show an unexplained, increasing, linear time variation with a rate of about 0.05 W m(exp -2) per year. Separate regressions for the periods before and after 1996 January 01 show no unexplained trends but differ substantially in regression parameters. This behavior may reflect a solar source of TSI variations beyond sunspots and faculae but more plausibly results from uncompensated non-solar effects in one or both of the TSI and SPM data sets.

Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data.

PubMed

Yılmaz Isıkhan, Selen; Karabulut, Erdem; Alpar, Celal Reha

2016-01-01

Background/Aim . Evaluating the success of dose prediction based on genetic or clinical data has substantially advanced recently. The aim of this study is to predict various clinical dose values from DNA gene expression datasets using data mining techniques. Materials and Methods . Eleven real gene expression datasets containing dose values were included. First, important genes for dose prediction were selected using iterative sure independence screening. Then, the performances of regression trees (RTs), support vector regression (SVR), RT bagging, SVR bagging, and RT boosting were examined. Results . The results demonstrated that a regression-based feature selection method substantially reduced the number of irrelevant genes from raw datasets. Overall, the best prediction performance in nine of 11 datasets was achieved using SVR; the second most accurate performance was provided using a gradient-boosting machine (GBM). Conclusion . Analysis of various dose values based on microarray gene expression data identified common genes found in our study and the referenced studies. According to our findings, SVR and GBM can be good predictors of dose-gene datasets. Another result of the study was to identify the sample size of n = 25 as a cutoff point for RT bagging to outperform a single RT.

Regression: The Apple Does Not Fall Far From the Tree.

PubMed

Vetter, Thomas R; Schober, Patrick

2018-05-15

Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

A Highly Efficient Design Strategy for Regression with Outcome Pooling

PubMed Central

Mitchell, Emily M.; Lyles, Robert H.; Manatunga, Amita K.; Perkins, Neil J.; Schisterman, Enrique F.

2014-01-01

The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. PMID:25220822

Protective Effect of HLA-DQB1 Alleles Against Alloimmunization in Patients with Sickle Cell Disease

PubMed Central

Tatari-Calderone, Zohreh; Gordish-Dressman, Heather; Fasano, Ross; Riggs, Michael; Fortier, Catherine; Andrew; Campbell, D.; Charron, Dominique; Gordeuk, Victor R.; Luban, Naomi L.C.; Vukmanovic, Stanislav; Tamouza, Ryad

2015-01-01

Background Alloimmunization or the development of alloantibodies to Red Blood Cell (RBC) antigens is considered one of the major complications after RBC transfusions in patients with sickle cell disease (SCD) and can lead to both acute and delayed hemolytic reactions. It has been suggested that polymorphisms in HLA genes, may play a role in alloimmunization. We conducted a retrospective study analyzing the influence of HLA-DRB1 and DQB1 genetic diversity on RBC-alloimmunization. Study design Two-hundred four multi-transfused SCD patients with and without RBC-alloimmunization were typed at low/medium resolution by PCR-SSO, using IMGT-HLA Database. HLA-DRB1 and DQB1 allele frequencies were analyzed using logistic regression models, and global p-value was calculated using multiple logistic regression. Results While only trends towards associations between HLA-DR diversity and alloimmunization were observed, analysis of HLA-DQ showed that HLA-DQ2 (p=0.02), -DQ3 (p=0.02) and -DQ5 (p=0.01) alleles were significantly higher in non-alloimmunized patients, likely behaving as protective alleles. In addition, multiple logistic regression analysis showed both HLA-DQ2/6 (p=0.01) and HLA-DQ5/5 (p=0.03) combinations constitute additional predictor of protective status. Conclusion Our data suggest that particular HLA-DQ alleles influence the clinical course of RBC transfusion in patients with SCD, which could pave the way towards predictive strategies. PMID:26476208

A highly efficient design strategy for regression with outcome pooling.

PubMed

Mitchell, Emily M; Lyles, Robert H; Manatunga, Amita K; Perkins, Neil J; Schisterman, Enrique F

2014-12-10

The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. Copyright © 2014 John Wiley & Sons, Ltd.

Inferring microhabitat preferences of Lilium catesbaei (Liliaceae).

PubMed

Sommers, Kristen Penney; Elswick, Michael; Herrick, Gabriel I; Fox, Gordon A

2011-05-01

Microhabitat studies use varied statistical methods, some treating site occupancy as a dependent and others as an independent variable. Using the rare Lilium catesbaei as an example, we show why approaches to testing hypotheses of differences between occupied and unoccupied sites can lead to erroneous conclusions about habitat preferences. Predictive approaches like logistic regression can better lead to understanding of habitat requirements. Using 32 lily locations and 30 random locations >2 m from a lily (complete data: 31 lily and 28 random spots), we measured physical conditions--photosynthetically active radiation (PAR), canopy cover, litter depth, distance to and height of nearest shrub, and soil moisture--and number and identity of neighboring plants. Twelve lilies were used to estimate a photosynthetic assimilation curve. Analyses used logistic regression, discriminant function analysis (DFA), (multivariate) analysis of variance, and resampled Wilcoxon tests. Logistic regression and DFA found identical predictors of presence (PAR, canopy cover, distance to shrub, litter), but hypothesis tests pointed to a different set (PAR, litter, canopy cover, height of nearest shrub). Lilies are mainly in high-PAR spots, often close to light saturation. By contrast, PAR in random spots was often near the lily light compensation point. Lilies were near Serenoa repens less than at random; otherwise, neighbor identity had no significant effect. Predictive methods are more useful in this context than the hypothesis tests. Light availability plays a big role in lily presence, which may help to explain increases in flowering and emergence after fire and roller-chopping.

Factors Affecting Optimal Aortic Remodeling After Thoracic Endovascular Aortic Repair of Type B (IIIb) Aortic Dissection

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

Chen, I-Ming; Chen, Po-Lin; Huang, Chun-Yang

PurposeThe purpose of this study was to determine factors associated with entire aortic remodeling after thoracic endovascular aortic repair (TEVAR) in patients with type B dissection.Materials and MethodsThe patients with type B (IIIb) dissections who underwent TEVAR from 2006 to 2013 with minimum of 2 years of follow-up computed tomography data were retrospectively reviewed. Based on the status of false lumen remodeling of entire aorta, patients were divided into three groups: complete regression, total thrombosis, and inadequate regression with patent abdominal false lumen.ResultsA total of 90 patients (72 males, 18 females; mean age 56.6 ± 16.4 years) were included and divided into the completemore » regression (n = 22), total thrombosis (n = 18), and inadequate regression (n = 50) groups. Multivariate logistic regression analysis indicated that dissection extension to iliac arteries, increased preoperative number of dissection tear over abdominal aorta, and decreased preoperative abdominal aorta bifurcation true lumen ratio, as compared between the inadequate and complete regression groups, were associated with a persistent false lumen (odds ratio = 33.33, 2.304, and 0.021; all, p ≤ 0.012). Comparison of 6, 12, and 24 months postoperative data revealed no significant differences at any level, suggesting that the true lumen area ratio might not change after 6 months postoperatively.ConclusionsIncreased preoperative numbers of dissection tear around the abdominal visceral branches, dissection extension to the iliac arteries, and decreased preoperative true lumen area ratio of abdominal aorta are predictive of entire aortic remodeling after TEVAR in patients with type B dissection.Level of EvidenceIII.« less

Individual memory change after anterior temporal lobectomy: a base rate analysis using regression-based outcome methodology.

PubMed

Martin, R C; Sawrie, S M; Roth, D L; Gilliam, F G; Faught, E; Morawetz, R B; Kuzniecky, R

1998-10-01

To characterize patterns of base rate change on measures of verbal and visual memory after anterior temporal lobectomy (ATL) using a newly developed regression-based outcome methodology that accounts for effects of practice and regression towards the mean, and to comment on the predictive utility of baseline memory measures on postoperative memory outcome. Memory change was operationalized using regression-based change norms in a group of left (n = 53) and right (n = 48) ATL patients. All patients were administered tests of episodic verbal (prose recall, list learning) and visual (figure reproduction) memory, and semantic memory before and after ATL. ATL patients displayed a wide range of memory outcome across verbal and visual memory domains. Significant performance declines were noted for 25-50% of left ATL patients on verbal semantic and episodic memory tasks, while one-third of right ATL patients displayed significant declines in immediate and delayed episodic prose recall. Significant performance improvement was noted in an additional one-third of right ATL patients on delayed prose recall. Base rate change was similar between the two ATL groups across immediate and delayed visual memory. Approximately one-fourth of all patients displayed clinically meaningful losses on the visual memory task following surgery. Robust relationships between preoperative memory measures and nonstandardized change scores were attenuated or reversed using standardized memory outcome techniques. Our results demonstrated substantial group variability in memory outcome for ATL patients. These results extend previous research by incorporating known effects of practice and regression to the mean when addressing meaningful neuropsychological change following epilepsy surgery. Our findings also suggest that future neuropsychological outcome studies should take steps towards controlling for regression-to-the-mean before drawing predictive conclusions.

[RS estimation of inventory parameters and carbon storage of moso bamboo forest based on synergistic use of object-based image analysis and decision tree].

PubMed

Du, Hua Qiang; Sun, Xiao Yan; Han, Ning; Mao, Fang Jie

2017-10-01

By synergistically using the object-based image analysis (OBIA) and the classification and regression tree (CART) methods, the distribution information, the indexes (including diameter at breast, tree height, and crown closure), and the aboveground carbon storage (AGC) of moso bamboo forest in Shanchuan Town, Anji County, Zhejiang Province were investigated. The results showed that the moso bamboo forest could be accurately delineated by integrating the multi-scale ima ge segmentation in OBIA technique and CART, which connected the image objects at various scales, with a pretty good producer's accuracy of 89.1%. The investigation of indexes estimated by regression tree model that was constructed based on the features extracted from the image objects reached normal or better accuracy, in which the crown closure model archived the best estimating accuracy of 67.9%. The estimating accuracy of diameter at breast and tree height was relatively low, which was consistent with conclusion that estimating diameter at breast and tree height using optical remote sensing could not achieve satisfactory results. Estimation of AGC reached relatively high accuracy, and accuracy of the region of high value achieved above 80%.

Prediction of Return-to-original-work after an Industrial Accident Using Machine Learning and Comparison of Techniques

PubMed Central

2018-01-01

Background Many studies have tried to develop predictors for return-to-work (RTW). However, since complex factors have been demonstrated to predict RTW, it is difficult to use them practically. This study investigated whether factors used in previous studies could predict whether an individual had returned to his/her original work by four years after termination of the worker's recovery period. Methods An initial logistic regression analysis of 1,567 participants of the fourth Panel Study of Worker's Compensation Insurance yielded odds ratios. The participants were divided into two subsets, a training dataset and a test dataset. Using the training dataset, logistic regression, decision tree, random forest, and support vector machine models were established, and important variables of each model were identified. The predictive abilities of the different models were compared. Results The analysis showed that only earned income and company-related factors significantly affected return-to-original-work (RTOW). The random forest model showed the best accuracy among the tested machine learning models; however, the difference was not prominent. Conclusion It is possible to predict a worker's probability of RTOW using machine learning techniques with moderate accuracy. PMID:29736160

Gender differences in clinical status at time of coronary revascularisation in Spain

PubMed Central

Aguilar, M; Lazaro, P; Fitch, K; Luengo, S

2002-01-01

Design: Retrospective study of clinical records. Two stage stratified cluster sampling was used to select a nationally representative sample of patients receiving a coronary revascularisation procedure in 1997. Setting: All of Spain. Main outcome measures: Odds ratios (OR) in men and women for different clinical and diagnostic variables related with coronary disease. A logistic regression model was developed to estimate the association between coronary symptoms and gender. Results: In the univariate analysis the prevalence of the following risk factors for coronary heart disease was higher in women than in men: obesity (OR=1.8), hypertension (OR=2.9) and diabetes (OR=2.1). High surgical risk was also more prevalent among women (OR=2.6). In the logistic regression analysis women's risk of being symptomatic at the time of revascularisation was more than double that of men (OR=2.4). Conclusions: Women have more severe coronary symptoms at the time of coronary revascularisation than do men. These results suggest that women receive revascularisation at a more advanced stage of coronary disease. Further research is needed to clarify what social, cultural or biological factors may be implicated in the gender differences observed. PMID:12080167

Association of Access to Publicly Funded Family Planning Services With Adolescent Birthrates in California Counties

PubMed Central

Chabot, Marina J.; Navarro, Sandy; Swann, Diane; Darney, Philip; Thiel de Bocanegra, Heike

2014-01-01

Objectives. We examined the association of adolescent birthrates (ABRs) with access to and receipt of publicly funded family planning services in California counties provided through 2 state programs: Medi-Cal, California’s Medicaid program, and the Family Planning, Access, Care, and Treatment (Family PACT) program. Methods. Our key data sources included the California Health Interview Survey and California Women’s Health Survey, Medi-Cal and Family PACT claims data, and the Birth Statistical Master File. We constructed a linear regression analysis measuring the relationship of access to and receipt of family planning services with ABRs when controlling for counties’ select covariates. Results. The regression analysis indicated that a higher access rate to Family PACT in a county was associated with a lower ABR (B = −0.19; P < .01) when controlling for unemployment rate, percentage of foreign-born adolescents, and percentage of adult low-income births. Conclusions. Efforts to reduce ABRs, specifically in counties that had persistently high rates are critical to achieving a healthy future for the state and the nation. Family PACT played a crucial role in helping adolescents avoid unintended and early childbearing. PMID:24354841

Applied Multiple Linear Regression: A General Research Strategy

ERIC Educational Resources Information Center

Smith, Brandon B.

1969-01-01

Illustrates some of the basic concepts and procedures for using regression analysis in experimental design, analysis of variance, analysis of covariance, and curvilinear regression. Applications to evaluation of instruction and vocational education programs are illustrated. (GR)

Continuous infusion of low-dose unfractionated heparin after aneurysmal subarachnoid hemorrhage: a preliminary study of cognitive outcomes.

PubMed

James, Robert F; Khattar, Nicolas K; Aljuboori, Zaid S; Page, Paul S; Shao, Elaine Y; Carter, Lacey M; Meyer, Kimberly S; Daniels, Michael W; Craycroft, John; Gaughen, John R; Chaudry, M Imran; Rai, Shesh N; Everhart, D Erik; Simard, J Marc

2018-05-11

OBJECTIVE Cognitive dysfunction occurs in up to 70% of aneurysmal subarachnoid hemorrhage (aSAH) survivors. Low-dose intravenous heparin (LDIVH) infusion using the Maryland protocol was recently shown to reduce clinical vasospasm and vasospasm-related infarction. In this study, the Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive changes in aSAH patients treated with the Maryland LDIVH protocol compared with controls. METHODS A retrospective analysis of all patients treated for aSAH between July 2009 and April 2014 was conducted. Beginning in 2012, aSAH patients were treated with LDIVH in the postprocedural period. The MoCA was administered to all aSAH survivors prospectively during routine follow-up visits, at least 3 months after aSAH, by trained staff blinded to treatment status. Mean MoCA scores were compared between groups, and regression analyses were performed for relevant factors. RESULTS No significant differences in baseline characteristics were observed between groups. The mean MoCA score for the LDIVH group (n = 25) was 26.4 compared with 22.7 in controls (n = 22) (p = 0.013). Serious cognitive impairment (MoCA ≤ 20) was observed in 32% of controls compared with 0% in the LDIVH group (p = 0.008). Linear regression analysis demonstrated that only LDIVH was associated with a positive influence on MoCA scores (β = 3.68, p =0.019), whereas anterior communicating artery aneurysms and fevers were negatively associated with MoCA scores. Multivariable linear regression analysis resulted in all 3 factors maintaining significance. There were no treatment complications. CONCLUSIONS This preliminary study suggests that the Maryland LDIVH protocol may improve cognitive outcomes in aSAH patients. A randomized controlled trial is needed to determine the safety and potential benefit of unfractionated heparin in aSAH patients.

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

Predictive Utility of Marketed Volumetric Software Tools in Subjects at Risk for Alzheimer's: Do Regions Outside the Hippocampus Matter?

PubMed Central

Tanpitukpongse, Teerath P.; Mazurowski, Maciej A.; Ikhena, John; Petrella, Jeffrey R.

2016-01-01

Background and Purpose To assess prognostic efficacy of individual versus combined regional volumetrics in two commercially-available brain volumetric software packages for predicting conversion of patients with mild cognitive impairment to Alzheimer's disease. Materials and Methods Data was obtained through the Alzheimer's Disease Neuroimaging Initiative. 192 subjects (mean age 74.8 years, 39% female) diagnosed with mild cognitive impairment at baseline were studied. All had T1WI MRI sequences at baseline and 3-year clinical follow-up. Analysis was performed with NeuroQuant® and Neuroreader™. Receiver operating characteristic curves assessing the prognostic efficacy of each software package were generated using a univariable approach employing individual regional brain volumes, as well as two multivariable approaches (multiple regression and random forest), combining multiple volumes. Results On univariable analysis of 11 NeuroQuant® and 11 Neuroreader™ regional volumes, hippocampal volume had the highest area under the curve for both software packages (0.69 NeuroQuant®, 0.68 Neuroreader™), and was not significantly different (p > 0.05) between packages. Multivariable analysis did not increase the area under the curve for either package (0.63 logistic regression, 0.60 random forest NeuroQuant®; 0.65 logistic regression, 0.62 random forest Neuroreader™). Conclusion Of the multiple regional volume measures available in FDA-cleared brain volumetric software packages, hippocampal volume remains the best single predictor of conversion of mild cognitive impairment to Alzheimer's disease at 3-year follow-up. Combining volumetrics did not add additional prognostic efficacy. Therefore, future prognostic studies in MCI, combining such tools with demographic and other biomarker measures, are justified in using hippocampal volume as the only volumetric biomarker. PMID:28057634

Evaluation of spectral domain optical coherence tomography parameters in ocular hypertension, preperimetric, and early glaucoma

PubMed Central

Aydoğan, Tuğba; Akçay, Betül İlkay Sezgin; Kardeş, Esra; Ergin, Ahmet

2017-01-01

Purpose: The objective of this study is to evaluate the diagnostic ability of retinal nerve fiber layer (RNFL), macular, optic nerve head (ONH) parameters in healthy subjects, ocular hypertension (OHT), preperimetric glaucoma (PPG), and early glaucoma (EG) patients, to reveal factors affecting the diagnostic ability of spectral domain-optical coherence tomography (SD-OCT) parameters and risk factors for glaucoma. Methods: Three hundred and twenty-six eyes (89 healthy, 77 OHT, 94 PPG, and 66 EG eyes) were analyzed. RNFL, macular, and ONH parameters were measured with SD-OCT. The area under the receiver operating characteristic curve (AUC) and sensitivity at 95% specificity was calculated. Logistic regression analysis was used to determine the glaucoma risk factors. Receiver operating characteristic regression analysis was used to evaluate the influence of covariates on the diagnostic ability of parameters. Results: In PPG patients, parameters that had the largest AUC value were average RNFL thickness (0.83) and rim volume (0.83). In EG patients, parameter that had the largest AUC value was average RNFL thickness (0.98). The logistic regression analysis showed average RNFL thickness was a risk factor for both PPG and EG. Diagnostic ability of average RNFL and average ganglion cell complex thickness increased as disease severity increased. Signal strength index did not affect diagnostic abilities. Diagnostic ability of average RNFL and rim area increased as disc area increased. Conclusion: When evaluating patients with glaucoma, patients at risk for glaucoma, and healthy controls RNFL parameters deserve more attention in clinical practice. Further studies are needed to fully understand the influence of covariates on the diagnostic ability of OCT parameters. PMID:29133640

SPATIAL PATTERNS OF ARRESTS, POLICE ASSAULT, AND ADDICTION TREATMENT CENTER LOCATIONS IN TIJUANA, MEXICO

PubMed Central

Werb, D; Strathdee, SA; Vera, A; Arredondo, J; Beletsky, L; Gonzalez-Zuniga, P; Gaines, T

2016-01-01

Aims In the context of a public health-oriented drug policy reform in Mexico, we assessed the spatial distribution of police encounters among people who inject drugs (PWID) in Tijuana; determined the association between these encounters and the location of addiction treatment centers; and explored the association between police encounters and treatment access. Design Geographically weighted regression (GWR) and logistic regression analysis using prospective spatial data from a community-recruited cohort of PWID in Tijuana and official geographic arrest data from the Tijuana Municipal Police Department. Setting Tijuana, Mexico. Participants 608 participants (median age 37; 28.4% female) in the prospective Proyecto El Cuete cohort study recruited between January and December 2011. Measurements We compared the mean distance of police encounters and a randomly distributed set of events to treatment centers. GWR was undertaken to model the spatial relationship between police interactions and treatment centers. Logistic regression analysis was used to investigate factors associated with reporting police interactions. Findings During the study period, 27.5% of police encounters occurred within 500 meters of treatment centers. The GWR model suggested spatial correlation between encounters and treatment centers (Global R2 = 0.53). Reporting a need for addiction treatment was associated with reporting arrest and police assault (Adjusted Odds Ratio = 2.74, 95% Confidence Interval [CI]: 1.25–6.02, p = 0.012). Conclusions A geospatial analysis suggests that in Mexico, people who inject drugs are at greater risk of being a victim of police violence if they consider themselves in need of addiction treatment, and their interactions with police appear to be more frequent around treatment centres. PMID:26879179

Quality of life of patients who undergo breast reconstruction after mastectomy: effects of personality characteristics.

PubMed

Bellino, Silvio; Fenocchio, Marina; Zizza, Monica; Rocca, Giuseppe; Bogetti, Paolo; Bogetto, Filippo

2011-01-01

Reconstruction after mastectomy has become an integral part of breast cancer treatment. The effects of psychological factors on quality of life after reconstruction have been poorly investigated. The authors examined clinical and personality characteristics related to quality of life in patients receiving reconstructive surgery. All patients received immediate reconstruction and were evaluated in the week before tissue expander implantation (T0) with a semistructured interview for demographic and clinical characteristics, the Temperament and Character Inventory, the Inventory of Interpersonal Problems, the Short Form Health Survey, the Severity Item of the Clinical Global Impression, the Hamilton Depression Rating Scale, and the Hamilton Anxiety Rating Scale. Assessment with the Short Form was repeated 3 months after expander placement (T1). Statistics were calculated with univariate regression and analysis of variance. Significant variables were included in a multiple regression analysis to identify factors related to the change T1-T0 of the mean of the Short Form-transformed scores. Results were significant when p was less than or equal to 0.05. Fifty-seven women were enrolled. Results of multiple regression analysis showed that the Temperament and Character Inventory personality dimension harm avoidance and the Inventory of Interpersonal Problems domain vindictive/self-centered were significantly and independently related to the change in Short Form mean score. Personality dimensions and patterns of interpersonal functioning produce significant effects on patients' quality of life during breast reconstruction. Patients with high harm avoidance are apprehensive and doubtful. Restoration of body image could help them to reduce social anxiety and insecurity. Vindictive/self-centered patients are resentful and aggressive. Breast reconstruction could symbolize the conclusion of a reparative process and fulfill the desire of revenge on cancer.

On Becoming Trauma-Informed: Role of the Adverse Childhood Experiences Survey in Tertiary Child and Adolescent Mental Health Services and the Association with Standard Measures of Impairment and Severity

PubMed Central

Rahman, Abdul; Perri, Andrea; Deegan, Avril; Kuntz, Jennifer; Cawthorpe, David

2018-01-01

Context There is a movement toward trauma-informed, trauma-focused psychiatric treatment. Objective To examine Adverse Childhood Experiences (ACE) survey items by sex and by total scores by sex vs clinical measures of impairment to examine the clinical utility of the ACE survey as an index of trauma in a child and adolescent mental health care setting. Design Descriptive, polychoric factor analysis and regression analyses were employed to analyze cross-sectional ACE surveys (N = 2833) and registration-linked data using past admissions (N = 10,400) collected from November 2016 to March 2017 related to clinical data (28 independent variables), taking into account multicollinearity. Results Distinct ACE items emerged for males, females, and those with self-identified sex and for ACE total scores in regression analysis. In hierarchical regression analysis, the final models consisting of standard clinical measures and demographic and system variables (eg, repeated admissions) were associated with substantial ACE total score variance for females (44%) and males (38%). Inadequate sample size foreclosed on developing a reduced multivariable model for the self-identified sex group. Conclusion The ACE scores relate to independent clinical measures and system and demographic variables. There are implications for clinical practice. For example, a child presenting with anxiety and a high ACE score likely requires treatment that is different from a child presenting with anxiety and an ACE score of zero. The ACE survey score is an important index of presenting clinical status that guides patient care planning and intervention in the progress toward a trauma-focused system of care. PMID:29401055

Malignant testicular tumour incidence and mortality trends

PubMed Central

Wojtyła-Buciora, Paulina; Więckowska, Barbara; Krzywinska-Wiewiorowska, Małgorzata; Gromadecka-Sutkiewicz, Małgorzata

2016-01-01

Aim of the study In Poland testicular tumours are the most frequent cancer among men aged 20–44 years. Testicular tumour incidence since the 1980s and 1990s has been diversified geographically, with an increased risk of mortality in Wielkopolska Province, which was highlighted at the turn of the 1980s and 1990s. The aim of the study was the comparative analysis of the tendencies in incidence and death rates due to malignant testicular tumours observed among men in Poland and in Wielkopolska Province. Material and methods Data from the National Cancer Registry were used for calculations. The incidence/mortality rates among men due to malignant testicular cancer as well as the tendencies in incidence/death ratio observed in Poland and Wielkopolska were established based on regression equation. The analysis was deepened by adopting the multiple linear regression model. A p-value < 0.05 was arbitrarily adopted as the criterion of statistical significance, and for multiple comparisons it was modified according to the Bonferroni adjustment to a value of p < 0.0028. Calculations were performed with the use of PQStat v1.4.8 package. Results The incidence of malignant testicular neoplasms observed among men in Poland and in Wielkopolska Province indicated a significant rising tendency. The multiple linear regression model confirmed that the year variable is a strong incidence forecast factor only within the territory of Poland. A corresponding analysis of mortality rates among men in Poland and in Wielkopolska Province did not show any statistically significant correlations. Conclusions Late diagnosis of Polish patients calls for undertaking appropriate educational activities that would facilitate earlier reporting of the patients, thus increasing their chances for recovery. Introducing preventive examinations in the regions of increased risk of testicular tumour may allow earlier diagnosis. PMID:27095941

External Tank Liquid Hydrogen (LH2) Prepress Regression Analysis Independent Review Technical Consultation Report

NASA Technical Reports Server (NTRS)

Parsons, Vickie s.

2009-01-01

The request to conduct an independent review of regression models, developed for determining the expected Launch Commit Criteria (LCC) External Tank (ET)-04 cycle count for the Space Shuttle ET tanking process, was submitted to the NASA Engineering and Safety Center NESC on September 20, 2005. The NESC team performed an independent review of regression models documented in Prepress Regression Analysis, Tom Clark and Angela Krenn, 10/27/05. This consultation consisted of a peer review by statistical experts of the proposed regression models provided in the Prepress Regression Analysis. This document is the consultation's final report.

Reporting quality of statistical methods in surgical observational studies: protocol for systematic review.

PubMed

Wu, Robert; Glen, Peter; Ramsay, Tim; Martel, Guillaume

2014-06-28

Observational studies dominate the surgical literature. Statistical adjustment is an important strategy to account for confounders in observational studies. Research has shown that published articles are often poor in statistical quality, which may jeopardize their conclusions. The Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines have been published to help establish standards for statistical reporting.This study will seek to determine whether the quality of statistical adjustment and the reporting of these methods are adequate in surgical observational studies. We hypothesize that incomplete reporting will be found in all surgical observational studies, and that the quality and reporting of these methods will be of lower quality in surgical journals when compared with medical journals. Finally, this work will seek to identify predictors of high-quality reporting. This work will examine the top five general surgical and medical journals, based on a 5-year impact factor (2007-2012). All observational studies investigating an intervention related to an essential component area of general surgery (defined by the American Board of Surgery), with an exposure, outcome, and comparator, will be included in this systematic review. Essential elements related to statistical reporting and quality were extracted from the SAMPL guidelines and include domains such as intent of analysis, primary analysis, multiple comparisons, numbers and descriptive statistics, association and correlation analyses, linear regression, logistic regression, Cox proportional hazard analysis, analysis of variance, survival analysis, propensity analysis, and independent and correlated analyses. Each article will be scored as a proportion based on fulfilling criteria in relevant analyses used in the study. A logistic regression model will be built to identify variables associated with high-quality reporting. A comparison will be made between the scores of surgical observational studies published in medical versus surgical journals. Secondary outcomes will pertain to individual domains of analysis. Sensitivity analyses will be conducted. This study will explore the reporting and quality of statistical analyses in surgical observational studies published in the most referenced surgical and medical journals in 2013 and examine whether variables (including the type of journal) can predict high-quality reporting.

Maintenance Operations in Mission Oriented Protective Posture Level IV (MOPPIV)

DTIC Science & Technology

1987-10-01

Repair FADAC Printed Circuit Board ............. 6 3. Data Analysis Techniques ............................. 6 a. Multiple Linear Regression... ANALYSIS /DISCUSSION ............................... 12 1. Exa-ple of Regression Analysis ..................... 12 S2. Regression results for all tasks...6 * TABLE 9. Task Grouping for Analysis ........................ 7 "TABXLE 10. Remove/Replace H60A3 Power Pack................. 8 TABLE

Creep-Rupture Data Analysis - Engineering Application of Regression Techniques. Ph.D. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Rummler, D. R.

1976-01-01

The results are presented of investigations to apply regression techniques to the development of methodology for creep-rupture data analysis. Regression analysis techniques are applied to the explicit description of the creep behavior of materials for space shuttle thermal protection systems. A regression analysis technique is compared with five parametric methods for analyzing three simulated and twenty real data sets, and a computer program for the evaluation of creep-rupture data is presented.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

Meta-analysis identifies a MECOM gene as a novel predisposing factor of osteoporotic fracture

PubMed Central

Hwang, Joo-Yeon; Lee, Seung Hun; Go, Min Jin; Kim, Beom-Jun; Kou, Ikuyo; Ikegawa, Shiro; Guo, Yan; Deng, Hong-Wen; Raychaudhuri, Soumya; Kim, Young Jin; Oh, Ji Hee; Kim, Youngdoe; Moon, Sanghoon; Kim, Dong-Joon; Koo, Heejo; Cha, My-Jung; Lee, Min Hye; Yun, Ji Young; Yoo, Hye-Sook; Kang, Young-Ah; Cho, Eun-Hee; Kim, Sang-Wook; Oh, Ki Won; Kang, Moo II; Son, Ho Young; Kim, Shin-Yoon; Kim, Ghi Su; Han, Bok-Ghee; Cho, Yoon Shin; Cho, Myeong-Chan; Lee, Jong-Young; Koh, Jung-Min

2014-01-01

Background Osteoporotic fracture (OF) as a clinical endpoint is a major complication of osteoporosis. To screen for OF susceptibility genes, we performed a genome-wide association study and carried out de novo replication analysis of an East Asian population. Methods Association was tested using a logistic regression analysis. A meta-analysis was performed on the combined results using effect size and standard errors estimated for each study. Results In a combined meta-analysis of a discovery cohort (288 cases and 1139 controls), three hospital based sets in replication stage I (462 cases and 1745 controls), and an independent ethnic group in replication stage II (369 cases and 560 for controls), we identified a new locus associated with OF (rs784288 in the MECOM gene) that showed genome-wide significance (p=3.59×10−8; OR 1.39). RNA interference revealed that a MECOM knockdown suppresses osteoclastogenesis. Conclusions Our findings provide new insights into the genetic architecture underlying OF in East Asians. PMID:23349225

Intravenous N-Acetylcysteine for Prevention of Contrast-Induced Nephropathy: A Meta-Analysis of Randomized, Controlled Trials

PubMed Central

Sun, Zikai; Fu, Qiang; Cao, Longxing; Jin, Wen; Cheng, LingLing; Li, Zhiliang

2013-01-01

Background Contrast-induced nephropathy (CIN) is one of the common causes of acute renal insufficiency after contrast procedures. Whether intravenous N-acetylcysteine (NAC) is beneficial for the prevention of contrast-induced nephropathy is uncertain. In this meta-analysis of randomized controlled trials, we aimed to assess the efficacy of intravenous NAC for preventing CIN after administration of intravenous contrast media. Study Design Relevant studies published up to September 2012 that investigated the efficacy of intravenous N-acetylcysteine for preventing CIN were collected from MEDLINE, OVID, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and the conference proceedings from major cardiology and nephrology meetings. The primary outcome was CIN. Secondary outcomes included renal failure requiring dialysis, mortality, and length of hospitalization. Data were combined using random-effects models with the performance of standard tests to assess for heterogeneity and publication bias. Meta-regression analyses were also performed. Results Ten trials involving 1916 patients met our inclusion criteria. Trials varied in patient demographic characteristics, inclusion criteria, dosing regimens, and trial quality. The summary risk ratio for contrast-induced nephropathy was 0.68 (95% CI, 0.46 to 1.02), a nonsignificant trend towards benefit in patients treated with intravenous NAC. There was evidence of significant heterogeneity in NAC effect across studies (Q = 17.42, P = 0.04; I2 = 48%). Meta-regression revealed no significant relation between the relative risk of CIN and identified differences in participant or study characteristics. Conclusion This meta-analysis showed that research on intravenous N-acetylcysteine and the incidence of CIN is too inconsistent at present to warrant a conclusion on efficacy. A large, well designed trial that incorporates the evaluation of clinically relevant outcomes in participants with different underlying risks of CIN is required to more adequately assess the role for intravenous NAC in CIN prevention. PMID:23383076

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

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.

Weight loss efficacy of a novel mobile Diabetes Prevention Program delivery platform with human coaching

PubMed Central

Michaelides, Andreas; Raby, Christine; Wood, Meghan; Farr, Kit

2016-01-01

Objective To evaluate the weight loss efficacy of a novel mobile platform delivering the Diabetes Prevention Program. Research Design and Methods 43 overweight or obese adult participants with a diagnosis of prediabetes signed-up to receive a 24-week virtual Diabetes Prevention Program with human coaching, through a mobile platform. Weight loss and engagement were the main outcomes, evaluated by repeated measures analysis of variance, backward regression, and mediation regression. Results Weight loss at 16 and 24 weeks was significant, with 56% of starters and 64% of completers losing over 5% body weight. Mean weight loss at 24 weeks was 6.58% in starters and 7.5% in completers. Participants were highly engaged, with 84% of the sample completing 9 lessons or more. In-app actions related to self-monitoring significantly predicted weight loss. Conclusions Our findings support the effectiveness of a uniquely mobile prediabetes intervention, producing weight loss comparable to studies with high engagement, with potential for scalable population health management. PMID:27651911

The severity of Minamata disease declined in 25 years: temporal profile of the neurological findings analyzed by multiple logistic regression model.

PubMed

Uchino, Makoto; Hirano, Teruyuki; Satoh, Hiroshi; Arimura, Kimiyoshi; Nakagawa, Masanori; Wakamiya, Jyunji

2005-01-01

Minamata disease (MD) was caused by ingestion of seafood from the methylmercury-contaminated areas. Although 50 years have passed since the discovery of MD, there have been only a few studies on the temporal profile of neurological findings in certified MD patients. Thus, we evaluated changes in neurological symptoms and signs of MD using discriminants by multiple logistic regression analysis. The severity of predictive index declined in 25 years in most of the patients. Only a few patients showed aggravation of neurological findings, which was due to complications such as spino-cerebellar degeneration. Patients with chronic MD aged over 45 years had several concomitant diseases so that their clinical pictures were complicated. It was difficult to differentiate chronic MD using statistically established discriminants based on sensory disturbance alone. In conclusion, the severity of MD declined in 25 years along with the modification by age-related concomitant disorders.

Primary gastric mucosa associated lymphoid tissue lymphoma: Clinical data predicted treatment outcome

PubMed Central

Todorovic, Milena; Balint, Bela; Jevtic, Miodrag; Suvajdzic, Nada; Ceric, Amela; Stamatovic, Dragana; Markovic, Olivera; Perunicic, Maja; Marjanovic, Slobodan; Krstic, Miodrag

2008-01-01

AIM: To determine clinical characteristics and treatment outcome of gastric lymphoma after chemotherapy and immuno-chemotherapy. METHODS: Thirty four patients with primary gastric mucosa associated lymphoid tissue (MALT) lymphoma (Ann Arbor stages I to IV) were enrolled. All had upper gastric endoscopy, abdominal ultrasonography, CT and H pylori status assessment (histology and serology). After anti-H pylori treatment and initial chemotherapy, patients were re-examined every 4 mo. RESULTS: Histological regression of the lymphoma was complete in 22/34 (64.7%) and partial in 9 (26.5%) patients. Median follow up time for these 31 responders was 60 mo (range 48-120). No regression was noted in 3 patients. Among the 25 (73.5%) H pylori positive patients, the eradication rate was 100%. CONCLUSION: Using univariate analysis, predictive factors for overall survival were international prognostic index (IPI) score, hemoglobin level, erythrocyte sedimentation rate (ESR), and platelet numbers (P < 0.005). In addition to this, Cox proportion hazard model differentiate IPI score, ESR, and platelets as predictors of survival. PMID:18416467

Prediction of Advisability of Returning Home Using the Home Care Score

PubMed Central

Matsugi, Akiyoshi; Tani, Keisuke; Tamaru, Yoshiki; Yoshioka, Nami; Yamashita, Akira; Mori, Nobuhiko; Oku, Kosuke; Ikeda, Masashi; Nagano, Kiyoshi

2015-01-01

Purpose. The aim of this study was to assess whether the home care score (HCS), which was developed by the Ministry of Health and Welfare in Japan in 1992, is useful for the prediction of advisability of home care. Methods. Subjects living at home and in assisted-living facilities were analyzed. Binominal logistic regression analyses, using age, sex, the functional independence measure score, and the HCS, along with receiver operating characteristic curve analyses, were conducted. Findings/Conclusions. Only HCS was selected for the regression equation. Receiver operating characteristic curve analysis revealed that the area under the curve (0.9), sensitivity (0.82), specificity (0.83), and positive predictive value (0.84) for HCS were higher than those for the functional independence measure, indicating that the HCS is a powerful predictor for advisability of home care. Clinical Relevance. Comprehensive measurements of the condition of provided care and the activities of daily living of the subjects, which are included in the HCS, are required for the prediction of advisability of home care. PMID:26491568

A trend analysis of laboratory positive propoxyphene workplace urine drug screens before and after the product recall.

PubMed

Price, James

2015-01-01

Propoxyphene was withdrawn from the US market in November 2010. This drug is still tested for in the workplace as part of expanded panel nonregulated testing. A convenience sample of urine specimens (n = 7838) were provided by workers from various industries. The percentage of positive specimens with 95% confidence intervals was calculated for each year of the study. Logistic regression was used to assess the impact of the year upon the propoxyphene result. The prevalence of positive propoxyphene tests was much higher before the product's withdrawal from the market. Logistic regression provided evidence of a decreasing linear trend (P < 0.000; β = -0.71). The odds ratio signifies that for every additional year the urine specimens were 0.49 times less likely to be positive for propoxyphene. This favors the determination that the change in propoxyphene positive drug test over the years is not by chance. The conclusion supports no longer performing nonregulated workplace propoxyphene urine drug testing for this population.

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

PubMed

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Using a Regression Discontinuity Design to Estimate the Impact of Placement Decisions in Developmental Math

ERIC Educational Resources Information Center

Melguizo, Tatiana; Bos, Johannes M.; Ngo, Federick; Mills, Nicholas; Prather, George

2016-01-01

This study evaluates the effectiveness of math placement policies for entering community college students on these students' academic success in math. We estimate the impact of placement decisions by using a discrete-time survival model within a regression discontinuity framework. The primary conclusion that emerges is that initial placement in a…

Application of neural networks and sensitivity analysis to improved prediction of trauma survival.

PubMed

Hunter, A; Kennedy, L; Henry, J; Ferguson, I

2000-05-01

The performance of trauma departments is widely audited by applying predictive models that assess probability of survival, and examining the rate of unexpected survivals and deaths. Although the TRISS methodology, a logistic regression modelling technique, is still the de facto standard, it is known that neural network models perform better. A key issue when applying neural network models is the selection of input variables. This paper proposes a novel form of sensitivity analysis, which is simpler to apply than existing techniques, and can be used for both numeric and nominal input variables. The technique is applied to the audit survival problem, and used to analyse the TRISS variables. The conclusions discuss the implications for the design of further improved scoring schemes and predictive models.

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review.

PubMed

Weymann, Alexander; Sabashnikov, Anton; Ali-Hasan-Al-Saegh, Sadeq; Popov, Aron-Frederik; Jalil Mirhosseini, Seyed; Baker, William L; Lotfaliani, Mohammadreza; Liu, Tong; Dehghan, Hamidreza; Yavuz, Senol; de Oliveira Sá, Michel Pompeu Barros; Jang, Jae-Sik; Zeriouh, Mohamed; Meng, Lei; D'Ascenzo, Fabrizio; Deshmukh, Abhishek J; Biondi-Zoccai, Guiseppe; Dohmen, Pascal M; Calkins, Hugh; Cardiac Surgery And Cardiology-Group Imcsc-Group, Integrated Meta-Analysis Of Cardiac

2017-03-31

BACKGROUND The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. MATERIAL AND METHODS We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. RESULTS A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD) =197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1-2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004));  fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and  endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. CONCLUSIONS The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients.

Periodontal inflamed surface area as a novel numerical variable describing periodontal conditions

PubMed Central

2017-01-01

Purpose A novel index, the periodontal inflamed surface area (PISA), represents the sum of the periodontal pocket depth of bleeding on probing (BOP)-positive sites. In the present study, we evaluated correlations between PISA and periodontal classifications, and examined PISA as an index integrating the discrete conventional periodontal indexes. Methods This study was a cross-sectional subgroup analysis of data from a prospective cohort study investigating the association between chronic periodontitis and the clinical features of ankylosing spondylitis. Data from 84 patients without systemic diseases (the control group in the previous study) were analyzed in the present study. Results PISA values were positively correlated with conventional periodontal classifications (Spearman correlation coefficient=0.52; P<0.01) and with periodontal indexes, such as BOP and the plaque index (PI) (r=0.94; P<0.01 and r=0.60; P<0.01, respectively; Pearson correlation test). Porphyromonas gingivalis (P. gingivalis) expression and the presence of serum P. gingivalis antibodies were significant factors affecting PISA values in a simple linear regression analysis, together with periodontal classification, PI, bleeding index, and smoking, but not in the multivariate analysis. In the multivariate linear regression analysis, PISA values were positively correlated with the quantity of current smoking, PI, and severity of periodontal disease. Conclusions PISA integrates multiple periodontal indexes, such as probing pocket depth, BOP, and PI into a numerical variable. PISA is advantageous for quantifying periodontal inflammation and plaque accumulation. PMID:29093989

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review

PubMed Central

Weymann, Alexander; Sabashnikov, Anton; Ali-Hasan-Al-Saegh, Sadeq; Popov, Aron-Frederik; Mirhosseini, Seyed Jalil; Baker, William L.; Lotfaliani, Mohammadreza; Liu, Tong; Dehghan, Hamidreza; Yavuz, Senol; de Oliveira Sá, Michel Pompeu Barros; Jang, Jae-Sik; Zeriouh, Mohamed; Meng, Lei; D’Ascenzo, Fabrizio; Deshmukh, Abhishek J.; Biondi-Zoccai, Giuseppe; Dohmen, Pascal M.; Calkins, Hugh

2017-01-01

Background The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. Material/Methods We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. Results A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD)=197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1–2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004)); fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. Conclusions The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients. PMID:28360407

The Unstimulated Salivary Flow Rate in a Jordanian Healthy Adult Population

PubMed Central

Sawair, Faleh A.; Ryalat, Soukaina; Shayyab, Mohammad; Saku, Takashi

2009-01-01

Background Early diagnosis of xerostomia is very important for oral health. The purpose of this study was to determine the unstimulated whole salivary flow rates (UWSFR) in a Jordanian Arab population aged 15 years and older. The effect of age, gender, height, weight, body mass index (BMI), smoking, alcohol consumption, and dental conditions, on UWSFR was also investigated. Methods The study was conducted on 244 subjects, 110 males and 134 females, with an average age of 33 ± 15.5 years. They were healthy, unmedicated, and with no history of dry mouth. Unstimulated whole saliva was collected during five minutes, and UWSFRs (ml/min) were determined. Data were analyzed by univariate analysis and multivariate regression analysis. Results The mean UWSFR was 0.46 ± 0.25 ml/min (range: 0.10-1.6 ml/min). Eighteen patients (7.4%) had UWSFR between < 0.20 ml/min. In univariate analysis, UWSFR was significantly affected by age, BMI, number of missing and restored teeth, and DMFT score. Regression analysis revealed that only age and number of missing teeth were of significance in explaining the variability of the UWSFR. Conclusions We established basic standard values of UWSFR to be used in the evaluation of Jordanian patients with complaints of xerostomia and to be compared to data reported in other studies. UWSFR 0.1 ml/min could be considered the cut-off value that distinguishes normal from abnormal salivary function in this healthy unmedicated population. Keywords Whole saliva flow rate; Unstimulated; Jordan PMID:22461872

Detection of counterfeit brand spirits using 1H NMR fingerprints in comparison to sensory analysis.

PubMed

Kuballa, Thomas; Hausler, Thomas; Okaru, Alex O; Neufeld, Maria; Abuga, Kennedy O; Kibwage, Isaac O; Rehm, Jürgen; Luy, Burkhard; Walch, Stephan G; Lachenmeier, Dirk W

2018-04-15

Beverage fraud involving counterfeiting of brand spirits is an increasing problem not only due to deception of the consumer but also because it poses health risks e.g. from possible methanol admixture. Suspicious spirit samples from Russia and Kenya were analysed using 1 H nuclear magnetic resonance (NMR) spectroscopy in comparison to authentic products. Using linear regression analysis of spectral integral values, 4 counterfeited samples from Russia and 2 from Kenya were easily identifiable with R 2  < 0.7. Sensory analysis using triangle test methodology confirmed significant taste differences between counterfeited and authentic samples but the assessors were unable to correctly identify the counterfeited product in the majority of cases. An important conclusion is that consumers cannot assumed to be self-responsible when consuming counterfeit alcohol because there is no general ability to organoleptically detect counterfeit alcohol. Copyright © 2017 Elsevier Ltd. All rights reserved.

[A SAS marco program for batch processing of univariate Cox regression analysis for great database].

PubMed

Yang, Rendong; Xiong, Jie; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

2015-02-01

To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

USDA-ARS?s Scientific Manuscript database

Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

Live birth sex ratio after in vitro fertilization and embryo transfer in China--an analysis of 121,247 babies from 18 centers.

PubMed

Bu, Zhiqin; Chen, Zi-Jiang; Huang, Guoning; Zhang, Hanwang; Wu, Qiongfang; Ma, Yanping; Shi, Juanzi; Xu, Yanwen; Zhang, Songying; Zhang, Cuilian; Zhao, Xiaoming; Zhang, Bo; Huang, Yuanhua; Sun, Zhengyi; Kang, Yuefan; Wu, Riran; Wu, Xueqing; Sun, Haixiang; Sun, Yingpu

2014-01-01

In order to study the impact of procedures of IVF/ICSI technology on sex ratio in China, we conducted this multi-center retrospective study including 121,247 babies born to 93,895 women in China. There were 62,700 male babies and 58,477 female babies, making the sex ratio being 51.8% (Male: Female  = 107:100). In univariate logistic regression analysis, sex ratio was imbalance toward females of 50.3% when ICSI was preformed compared to 47.7% when IVF was used (P<0.01). The sex ratio in IVF/ICSI babies was significantly higher toward males in transfers of blastocyst (54.9%) and thawed embryo (52.4%) when compared with transfers of cleavage stage embryo (51.4%) and fresh embryo (51.5%), respectively. Multiple delivery was not associated with sex ratio. However, in multivariable logistic regression analysis after controlling for related factors, only ICSI (adjusted OR =  .90, 95%CI: 0.88-0.93; P<0.01) and blastocyst transfer (adjusted OR = 1.14, 95% CI: 1.09-1.20; P<0.01) were associated with sex ratio in IVF/ICSI babies. In conclusion, the live birth sex ratio in IVF/ICSI babies was influenced by the use of ICSI, which may decrease the percentage of male offspring, or the use of blastocyst transfer, which may increase the percentage of male offspring.

A Bayesian Meta-Analysis on Prevalence of Hepatitis B Virus Infection among Chinese Volunteer Blood Donors

PubMed Central

Liu, Guang-ying; Zheng, Yang; Deng, Yan; Gao, Yan-yan; Wang, Lie

2013-01-01

Background Although transfusion-transmitted infection of hepatitis B virus (HBV) threatens the blood safety of China, the nationwide circumstance of HBV infection among blood donors is still unclear. Objectives To comprehensively estimate the prevalence of HBsAg positive and HBV occult infection (OBI) among Chinese volunteer blood donors through bayesian meta-analysis. Methods We performed an electronic search in Pub-Med, Web of Knowledge, Medline, Wanfang Data and CNKI, complemented by a hand search of relevant reference lists. Two authors independently extracted data from the eligible studies. Then two bayesian random-effect meta-analyses were performed, followed by bayesian meta-regressions. Results 5957412 and 571227 donors were identified in HBsAg group and OBI group, respectively. The pooled prevalence of HBsAg group and OBI group among donors is 1.085% (95% credible interval [CI] 0.859%∼1.398%) and 0.094% (95% CI 0.0578%∼0.1655%). For HBsAg group, subgroup analysis shows the more developed area has a lower prevalence than the less developed area; meta-regression indicates there is a significant decreasing trend in HBsAg positive prevalence with sampling year (beta = −0.1202, 95% −0.2081∼−0.0312). Conclusion Blood safety against HBV infection in China is suffering serious threats and the government should take effective measures to improve this situation. PMID:24236110

Stressed and overworked? A cross-sectional study of the working situation of urban and rural general practitioners in Austria in the framework of the QUALICOPC project

PubMed Central

Hoffmann, Kathryn; Wojczewski, Silvia; George, Aaron; Schäfer, Willemijn L. A.; Maier, Manfred

2015-01-01

Aim To assess the workload of general practitioners (GPs) in Austria, with a focus on identifying the differences between GPs working in urban and rural areas. Methods Within the framework of the Quality and Costs of Primary Care in Europe (QUALICOPC) study, data were collected from a stratified sample of GPs using a standardized questionnaire between November 2011 and May 2012. Data analysis included descriptive statistics and regression analysis. Results The analysis included data from 173 GPs. GPs in rural areas reported an average of 49.3 working hours per week, plus 23.7 on-call duties per 3 months and 26.2 out-of-office care services per week. Compared to GPs working in urban areas, even in the fully adjusted regression model, rural GPs had significantly more working hours (B 7.00; P = 0.002) and on-call duties (B 18.91; P < 0.001). 65.8% of all GPs perceived their level of stress as high and 84.6% felt they were required to do unnecessary administrative work. Conclusion Our findings show a high workload among Austrian GPs, particularly those working in rural areas. Since physicians show a diminishing interest to work as GPs, there is an imperative to improve this situation. PMID:26321030

WINPEPI updated: computer programs for epidemiologists, and their teaching potential

PubMed Central

2011-01-01

Background The WINPEPI computer programs for epidemiologists are designed for use in practice and research in the health field and as learning or teaching aids. The programs are free, and can be downloaded from the Internet. Numerous additions have been made in recent years. Implementation There are now seven WINPEPI programs: DESCRIBE, for use in descriptive epidemiology; COMPARE2, for use in comparisons of two independent groups or samples; PAIRSetc, for use in comparisons of paired and other matched observations; LOGISTIC, for logistic regression analysis; POISSON, for Poisson regression analysis; WHATIS, a "ready reckoner" utility program; and ETCETERA, for miscellaneous other procedures. The programs now contain 122 modules, each of which provides a number, sometimes a large number, of statistical procedures. The programs are accompanied by a Finder that indicates which modules are appropriate for different purposes. The manuals explain the uses, limitations and applicability of the procedures, and furnish formulae and references. Conclusions WINPEPI is a handy resource for a wide variety of statistical routines used by epidemiologists. Because of its ready availability, portability, ease of use, and versatility, WINPEPI has a considerable potential as a learning and teaching aid, both with respect to practical procedures in the planning and analysis of epidemiological studies, and with respect to important epidemiological concepts. It can also be used as an aid in the teaching of general basic statistics. PMID:21288353

Future-Oriented Tweets Predict Lower County-Level HIV Prevalence in the United States

PubMed Central

Ireland, Molly E.; Schwartz, Hansen A.; Chen, Qijia; Ungar, Lyle; Albarracín, Dolores

2016-01-01

Objective Future orientation promotes health and well-being at the individual level. Computerized text analysis of a dataset encompassing billions of words used across the United States on Twitter tested whether community-level rates of future-oriented messages correlated with lower HIV rates and moderated the association between behavioral risk indicators and HIV. Method Over 150 million Tweets mapped to US counties were analyzed using two methods of text analysis. First, county-level HIV rates (cases per 100,000) were regressed on aggregate usage of future-oriented language (e.g., will, gonna). A second data-driven method regressed HIV rates on individual words and phrases. Results Results showed that counties with higher rates of future tense on Twitter had fewer HIV cases, independent of strong structural predictors of HIV such as population density. Future-oriented messages also appeared to buffer health risk: Sexually transmitted infection rates and references to risky behavior on Twitter were associated with higher HIV prevalence in all counties except those with high rates of future orientation. Data-driven analyses likewise showed that words and phrases referencing the future (e.g., tomorrow, would be) correlated with lower HIV prevalence. Conclusion Integrating big data approaches to text analysis and epidemiology with psychological theory may provide an inexpensive, real-time method of anticipating outbreaks of HIV and etiologically similar diseases. PMID:26651466

Factors Associated with Uncontrolled Hypertension among Renal Transplant Recipients Attending Nephrology Clinics in Nairobi, Kenya

PubMed Central

Kubo, Mary N.; Kayima, Joshua K.; Were, Anthony J.; McLigeyo, Seth O.; Ogola, Elijah N.

2015-01-01

Objective. To determine the factors associated with poor blood pressure control among renal transplant recipients in a resource-limited setting. Methods. A cross-sectional study was carried out on renal transplant recipients at the Kenyatta National Hospital. Sociodemographic details, blood pressure, urine albumin : creatinine ratio, and adherence using the MMAS-8 questionnaire were noted. Independent factors associated with uncontrolled hypertension were determined using logistic regression analysis. Results. 85 subjects were evaluated. Mean age was 42.4 (SD ± 12.2) years, with a male : female ratio of 1.9 : 1. Fifty-five patients (64.7%) had uncontrolled hypertension (BP ≥ 130/80 mmHg). On univariate analysis, male sex (OR 3.7, 95% CI 1.4–9.5, p = 0.006), higher levels of proteinuria (p = 0.042), and nonadherence to antihypertensives (OR 18, 95% CI 5.2–65.7, p < 0.001) were associated with uncontrolled hypertension. On logistic regression analysis, male sex (adjusted OR 4.6, 95% CI 1.1–19.0, p = 0.034) and nonadherence (adjusted OR 33.8, 95% CI 8.6–73.0, p < 0.001) were independently associated with uncontrolled hypertension. Conclusion. Factors associated with poor blood pressure control in this cohort were male sex and nonadherence to antihypertensives. Emphasis on adherence to antihypertensive therapy must be pursued within this population. PMID:26257920

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques

NASA Astrophysics Data System (ADS)

Deng, Chengbin; Wu, Changshan

2013-12-01

Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available.

Recurrence risk model for esophageal cancer after radical surgery

PubMed Central

Tao, Hua; Song, Dan; Chen, Cheng

2013-01-01

Objective The aim of the present study was to construct a risk assessment model which was tested by disease-free survival (DFS) of esophageal cancer after radical surgery. Methods A total of 164 consecutive esophageal cancer patients who had undergone radical surgery between January 2005 and December 2006 were retrospectively analyzed. The cutpoint of value at risk (VaR) was inferred by stem-and-leaf plot, as well as by independent-samples t-test for recurrence-free time, further confirmed by crosstab chi-square test, univariate analysis and Cox regression analysis for DFS. Results The cutpoint of VaR was 0.3 on the basis of our model. The rate of recurrence was 30.3% (30/99) and 52.3% (34/65) in VaR <0.3 and VaR ≥0.3 (chi-square test, χ2 =7.984, P=0.005), respectively. The 1-, 3-, and 5-year DFS of esophageal cancer after radical surgery was 70.4%, 48.7%, and 45.3%, respectively in VaR ≥0.3, whereas 91.5%, 75.8%, and 67.3%, respectively in VaR <0.3 (Log-rank test, χ2 =9.59, P=0.0020), and further confirmed by Cox regression analysis [hazard ratio =2.10, 95% confidence interval (CI): 1.2649-3.4751; P=0.0041]. Conclusions The model could be applied for integrated assessment of recurrence risk after radical surgery for esophageal cancer. PMID:24255579

Correlates of Willingness to Engage in Residential Gardening: Implications for Health Optimization in Ibadan, Nigeria

PubMed Central

Motunrayo Ibrahim, Fausat

2013-01-01

Background: Gardening is a worthwhile adventure which engenders health op­timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. Methods: In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar­dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Conclusion: Socio-psychological characteristics and being married are very rele­vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population. PMID:24688974

Prevalence of Celiac Disease in Latin America: A Systematic Review and Meta-Regression

PubMed Central

Parra-Medina, Rafael; Molano-Gonzalez, Nicolás; Rojas-Villarraga, Adriana; Agmon-Levin, Nancy; Arango, Maria-Teresa; Shoenfeld, Yehuda; Anaya, Juan-Manuel

2015-01-01

Background Celiac disease (CD) is an immune-mediated enteropathy triggered by the ingestion of gluten in susceptible individuals, and its prevalence varies depending on the studied population. Given that information on CD in Latin America is scarce, we aimed to investigate the prevalence of CD in this region of the world through a systematic review and meta-analysis. Methods and Findings This was a two-phase study. First, a cross-sectional analysis from 981 individuals of the Colombian population was made. Second, a systematic review and meta-regression analysis were performed following the Preferred Reporting Items for Systematic Meta- Analyses (PRISMA) guidelines. Our results disclosed a lack of celiac autoimmunity in the studied Colombian population (i.e., anti-tissue transglutaminase (tTG) and IgA anti-endomysium (EMA)). In the systematic review, 72 studies were considered. The estimated prevalence of CD in Latin Americans ranged between 0.46% and 0.64%. The prevalence of CD in first-degree relatives of CD probands was 5.5%. The coexistence of CD and type 1 diabetes mellitus varied from 4.6% to 8.7%, depending on the diagnosis methods (i.e., autoantibodies and/or biopsies). Conclusions Although CD seems to be a rare condition in Colombians; the general prevalence of the disease in Latin Americans seemingly corresponds to a similar scenario observed in Europeans. PMID:25942408

Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

PubMed

Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S-Y; Assam, Pryseley N; Claridge-Chang, Adam

2015-12-01

Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.

A multilateral modelling of Youth Soccer Performance Index (YSPI)

NASA Astrophysics Data System (ADS)

Bisyri Husin Musawi Maliki, Ahmad; Razali Abdullah, Mohamad; Juahir, Hafizan; Abdullah, Farhana; Ain Shahirah Abdullah, Nurul; Muazu Musa, Rabiu; Musliha Mat-Rasid, Siti; Adnan, Aleesha; Azura Kosni, Norlaila; Muhamad, Wan Siti Amalina Wan; Afiqah Mohamad Nasir, Nur

2018-04-01

This study aims to identify the most dominant factors that influencing performance of soccer player and to predict group performance for soccer players. A total of 184 of youth soccer players from Malaysia sport school and six soccer academy encompasses as respondence of the study. Exploratory factor analysis (EFA) and Confirmatory factor analysis (CFA) were computed to identify the most dominant factors whereas reducing the initial 26 parameters with recommended >0.5 of factor loading. Meanwhile, prediction of the soccer performance was predicted by regression model. CFA revealed that sit and reach, vertical jump, VO2max, age, weight, height, sitting height, calf circumference (cc), medial upper arm circumference (muac), maturation, bicep, triceps, subscapular, suprailiac, 5M, 10M, and 20M speed were the most dominant factors. Further index analysis forming Youth Soccer Performance Index (YSPI) resulting by categorizing three groups namely, high, moderate, and low. The regression model for this study was significant set as p < 0.001 and R2 is 0.8222 which explained that the model contributed a total of 82% prediction ability to predict the whole set of the variables. The significant parameters in contributing prediction of YSPI are discussed. As a conclusion, the precision of the prediction models by integrating a multilateral factor reflecting for predicting potential soccer player and hopefully can create a competitive soccer games.

Inverse expression of survivin and reprimo correlates with poor patient prognosis in gastric cancer

PubMed Central

Cerda-Opazo, Paulina; Valenzuela-Valderrama, Manuel; Wichmann, Ignacio; Rodríguez, Andrés; Contreras-Reyes, Daniel; Fernández, Elmer A.; Carrasco-Aviño, Gonzalo; Corvalán, Alejandro H.; Quest, Andrew F.G.

2018-01-01

BACKGROUND The objective of the study was to determine the relationship between Survivin and Reprimo transcript/protein expression levels, and gastric cancer outcome. METHODS In silico correlations between an agnostic set of twelve p53-dependent apoptosis and cell-cycle genes were explored in the gastric adenocarcinoma TCGA database, using cBioPortal. Findings were validated by regression analysis of RNAseq data. Separate regression analyses were performed to assess the impact of p53 status on Survivin and Reprimo. Quantitative reverse-transcription PCR (RT-qPCR) and immunohistochemistry confirmed in silico findings on fresh-frozen and paraffin-embedded gastric cancer tissues, respectively. Wild-type (AGS, SNU-1) and mutated p53 (NCI-N87) cell lines transfected with pEGFP-Survivin or pCMV6-Reprimo were evaluated by RT-qPCR and Western blotting. Kaplan-Meier method and Long-Rank test were used to assess differences in patient outcome. RESULTS cBioPortal analysis revealed an inverse correlation between Survivin and Reprimo expression (Pearson’s r= −0.3, Spearman’s ρ= −0.55). RNAseq analyses confirmed these findings (Spearman’s ρ= −0.37, p<4.2e-09) and revealed p53 dependence in linear regression models (p<0.05). mRNA and protein levels validated these observations in clinical samples (p<0.001). In vitro analysis in cell lines demonstrated that increasing Survivin reduced Reprimo, while increasing Reprimo reduced Survivin expression, but only did so in p53 wild-type gastric cells (p<0.05). Survivin-positive but Reprimo-negative patients displayed shorter overall survival rates (p=0.047, Long Rank Test) (HR=0.32; 95%IC: 0.11-0.97; p=0.044). CONCLUSIONS TCGA RNAseq data analysis, evaluation of clinical samples and studies in cell lines identified an inverse relationship between Survivin and Reprimo. Elevated Survivin and reduced Reprimo protein expression correlated with poor patient prognosis in gastric cancer. PMID:29560115

Isolated and synergistic effects of PM10 and average temperature on cardiovascular and respiratory mortality.

PubMed

Pinheiro, Samya de Lara Lins de Araujo; Saldiva, Paulo Hilário Nascimento; Schwartz, Joel; Zanobetti, Antonella

2014-12-01

OBJECTIVE To analyze the effect of air pollution and temperature on mortality due to cardiovascular and respiratory diseases. METHODS We evaluated the isolated and synergistic effects of temperature and particulate matter with aerodynamic diameter < 10 µm (PM10) on the mortality of individuals > 40 years old due to cardiovascular disease and that of individuals > 60 years old due to respiratory diseases in Sao Paulo, SP, Southeastern Brazil, between 1998 and 2008. Three methodologies were used to evaluate the isolated association: time-series analysis using Poisson regression model, bidirectional case-crossover analysis matched by period, and case-crossover analysis matched by the confounding factor, i.e., average temperature or pollutant concentration. The graphical representation of the response surface, generated by the interaction term between these factors added to the Poisson regression model, was interpreted to evaluate the synergistic effect of the risk factors. RESULTS No differences were observed between the results of the case-crossover and time-series analyses. The percentage change in the relative risk of cardiovascular and respiratory mortality was 0.85% (0.45;1.25) and 1.60% (0.74;2.46), respectively, due to an increase of 10 μg/m3 in the PM10 concentration. The pattern of correlation of the temperature with cardiovascular mortality was U-shaped and that with respiratory mortality was J-shaped, indicating an increased relative risk at high temperatures. The values for the interaction term indicated a higher relative risk for cardiovascular and respiratory mortalities at low temperatures and high temperatures, respectively, when the pollution levels reached approximately 60 μg/m3. CONCLUSIONS The positive association standardized in the Poisson regression model for pollutant concentration is not confounded by temperature, and the effect of temperature is not confounded by the pollutant levels in the time-series analysis. The simultaneous exposure to different levels of environmental factors can create synergistic effects that are as disturbing as those caused by extreme concentrations.

Benchmark Dose for Urinary Cadmium based on a Marker of Renal Dysfunction: A Meta-Analysis

PubMed Central

Woo, Hae Dong; Chiu, Weihsueh A.; Jo, Seongil; Kim, Jeongseon

2015-01-01

Background Low doses of cadmium can cause adverse health effects. Benchmark dose (BMD) and the one-sided 95% lower confidence limit of BMD (BMDL) to derive points of departure for urinary cadmium exposure have been estimated in several previous studies, but the methods to derive BMD and the estimated BMDs differ. Objectives We aimed to find the associated factors that affect BMD calculation in the general population, and to estimate the summary BMD for urinary cadmium using reported BMDs. Methods A meta-regression was performed and the pooled BMD/BMDL was estimated using studies reporting a BMD and BMDL, weighted by sample size, that were calculated from individual data based on markers of renal dysfunction. Results BMDs were highly heterogeneous across studies. Meta-regression analysis showed that a significant predictor of BMD was the cut-off point which denotes an abnormal level. Using the 95th percentile as a cut off, BMD5/BMDL5 estimates for 5% benchmark responses (BMR) of β2-microglobulinuria (β2-MG) estimated was 6.18/4.88 μg/g creatinine in conventional quantal analysis and 3.56/3.13 μg/g creatinine in the hybrid approach, and BMD5/BMDL5 estimates for 5% BMR of N-acetyl-β-d-glucosaminidase (NAG) was 10.31/7.61 μg/g creatinine in quantal analysis and 3.21/2.24 g/g creatinine in the hybrid approach. However, the meta-regression showed that BMD and BMDL were significantly associated with the cut-off point, but BMD calculation method did not significantly affect the results. The urinary cadmium BMDL5 of β2-MG was 1.9 μg/g creatinine in the lowest cut-off point group. Conclusion The BMD was significantly associated with the cut-off point defining the abnormal level of renal dysfunction markers. PMID:25970611

Meta-analysis and meta-regression of omega-3 polyunsaturated fatty acid supplementation for major depressive disorder.

PubMed

Mocking, R J T; Harmsen, I; Assies, J; Koeter, M W J; Ruhé, H G; Schene, A H

2016-03-15

Omega-3 polyunsaturated fatty acid (PUFA) supplementation has been proposed as (adjuvant) treatment for major depressive disorder (MDD). In the present meta-analysis, we pooled randomized placebo-controlled trials assessing the effects of omega-3 PUFA supplementation on depressive symptoms in MDD. Moreover, we performed meta-regression to test whether supplementation effects depended on eicosapentaenoic acid (EPA) or docosahexaenoic acid dose, their ratio, study duration, participants' age, percentage antidepressant users, baseline MDD symptom severity, publication year and study quality. To limit heterogeneity, we only included studies in adult patients with MDD assessed using standardized clinical interviews, and excluded studies that specifically studied perinatal/perimenopausal or comorbid MDD. Our PubMED/EMBASE search resulted in 1955 articles, from which we included 13 studies providing 1233 participants. After taking potential publication bias into account, meta-analysis showed an overall beneficial effect of omega-3 PUFAs on depressive symptoms in MDD (standardized mean difference=0.398 (0.114-0.682), P=0.006, random-effects model). As an explanation for significant heterogeneity (I(2)=73.36, P<0.001), meta-regression showed that higher EPA dose (β=0.00037 (0.00009-0.00065), P=0.009), higher percentage antidepressant users (β=0.0058 (0.00017-0.01144), P=0.044) and earlier publication year (β=-0.0735 (-0.143 to 0.004), P=0.04) were significantly associated with better outcome for PUFA supplementation. Additional sensitivity analyses were performed. In conclusion, present meta-analysis suggested a beneficial overall effect of omega-3 PUFA supplementation in MDD patients, especially for higher doses of EPA and in participants taking antidepressants. Future precision medicine trials should establish whether possible interactions between EPA and antidepressants could provide targets to improve antidepressant response and its prediction. Furthermore, potential long-term biochemical side effects of high-dosed add-on EPA supplementation should be carefully monitored.

Midlife use of written Japanese and protection from late life dementia

PubMed Central

Crane, Paul K.; Gibbons, Laura E.; Arani, Keerthi; Nguyen, Viet; Rhoads, Kristoffer; McCurry, Susan M.; Launer, Lenore; Masaki, Kamal; White, Lon

2011-01-01

Background The cognitive reserve hypothesis would predict that use of written Japanese should confer protection against dementia because of the complexity of its ideograms compared with written English. We sought to test this hypothesis in analyses from a longitudinal study of Japanese-American men. Methods Participants were second-generation Japanese-American men (Nisei) on the island of Oahu, Hawaii, who were seen in 1965 and in subsequent examinations to detect dementia beginning in 1991-1993. Use of spoken and written Japanese was self-reported in 1965 (Analyses 1 and 2), and mid-life use of written Japanese and written English was self-reported in 1994-1996 (Analysis 3). We analyzed prevalent dementia outcomes in 1991-1993 (Analysis 1, n=3,139) using logistic regression, and incident dementia outcomes in 1994-2002 (Analysis 2, n=2,299) and in 1997-2002 (Analysis 3, n=1,655) using Cox proportional hazards regression. Dementia outcomes included all-cause dementia, probable and possible Alzheimer disease, and probable vascular dementia. We adjusted models for probable and possible confounders. Results Participants who reported proficiency with written Japanese were older and had lower incomes. For Analysis 1, there were 154 prevalent cases of dementia, 74 of Alzheimer disease, and 43 of vascular dementia; for Analysis 2, 236 incident cases of dementia, 138 of Alzheimer disease, and 45 of vascular dementia; and for Analysis 3, 125 incident cases of dementia, 80 of Alzheimer disease, and 20 of vascular dementia. There was no relationship in adjusted models between self-reported proficiency with written Japanese and any dementia outcomes. Conclusions Proficiency with written Japanese does not appear to be protective for dementia. PMID:19593152

Development of a User Interface for a Regression Analysis Software Tool

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.

Regression Analysis and the Sociological Imagination

ERIC Educational Resources Information Center

De Maio, Fernando

2014-01-01

Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.

Dual oxidase 1: A predictive tool for the prognosis of hepatocellular carcinoma patients.

PubMed

Chen, Shengsen; Ling, Qingxia; Yu, Kangkang; Huang, Chong; Li, Ning; Zheng, Jianming; Bao, Suxia; Cheng, Qi; Zhu, Mengqi; Chen, Mingquan

2016-06-01

Dual oxidase 1 (DUOX1), which is the main source of reactive oxygen species (ROS) production in the airway, can be silenced in human lung cancer and hepatocellular carcinomas. However, the prognostic value of DUOX1 expression in hepatocellular carcinoma patients is still unclear. We investigated the prognostic value of DUOX1 expression in liver cancer patients. DUOX1 mRNA expression was determined in tumor tissues and non-tumor tissues by real‑time PCR. For evaluation of the prognostic value of DUOX1 expression, Kaplan-Meier method and Cox's proportional hazards model (univariate analysis and multivariate analysis) were employed. A simple risk score was devised by using significant variables obtained from the Cox's regression analysis to further predict the HCC patient prognosis. We observed a reduced DUOX1 mRNA level in the cancer tissues in comparison to the non‑cancer tissues. More importantly, Kaplan-Meier analysis showed that patients with high DUOX1 expression had longer disease-free survival and overall survival compared with those with low expression of DUOX1. Cox's regression analysis indicated that DUOX1 expression, age, and intrahepatic metastasis may be significant prognostic factors for disease-free survival and overall survival. Finally, we found that patients with total scores of >2 and >1 were more likely to relapse and succumb to the disease than patients whose total scores were ≤2 and ≤1. In conclusion, DUOX1 expression in liver tumors is a potential prognostic tool for patients. The risk scoring system is useful for predicting the survival of liver cancer patients after tumor resection.

A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases

PubMed Central

Imai, Chisato; Hashizume, Masahiro

2015-01-01

Background: Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Findings: Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. Conclusion: The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases. PMID:25859149

High Prevalence of Vitamin D Deficiency among Iranian Population: A Systematic Review and Meta-Analysis

PubMed Central

Tabrizi, Reza; Moosazadeh, Mahmood; Akbari, Maryam; Dabbaghmanesh, Mohammad Hossein; Mohamadkhani, Minoo; Asemi, Zatollah; Heydari, Seyed Taghi; Akbari, Mojtaba; Lankarani, Kamran B

2018-01-01

Background The prevention and correction of vitamin D deficiency requires a precise depiction of the current situation and identification of risk factors in each region. The present study attempted to determine these entities using a systematic review and meta-analysis in Iran. Methods Articles published online in Persian and English between 2000 and November 1, 2016, were reviewed. This was carried out using national databases such as SID, IranMedex, Magiran, and IranDoc and international databases such as PubMed, Google Scholar, and Scopus. The heterogeneity index among the studies was determined using the Cochran (Q) and I2 test. Based on the heterogeneity results, the random-effect model was applied to estimate the prevalence of vitamin D deficiency. In addition, meta-regression analysis was used to determine heterogeneity-suspected factors, and the Egger test was applied to identify publication bias. Results The meta-analysis of 48 studies identified 18531 individuals with vitamin D deficiency. According to the random-effect model, the prevalence of vitamin D deficiency among male, female, and pregnant women was estimated to be 45.64% (95% CI: 29.63 to 61.65), 61.90% (95% CI: 48.85 to 74.96), and 60.45% (95% CI: 23.73 to 97.16), respectively. The results of the meta-regression analysis indicated that the prevalence of vitamin D deficiency was significantly different in various geographical regions (β=4.4; P=0.023). Conclusion The results obtained showed a significant prevalence of vitamin D deficiency among the Iranian population, a condition to be addressed by appropriate planning. PMID:29749981

Curcumin downregulates human tumor necrosis factor-α levels: A systematic review and meta-analysis ofrandomized controlled trials.

PubMed

Sahebkar, Amirhossein; Cicero, Arrigo F G; Simental-Mendía, Luis E; Aggarwal, Bharat B; Gupta, Subash C

2016-05-01

Tumor necrosis factor-α (TNF-α) is a key inflammatory mediator and its reduction is a therapeutic target in several inflammatory diseases. Curcumin, a bioactive polyphenol from turmeric, has been shown in several preclinical studies to block TNF-α effectively. However, clinical evidence has not been fully conclusive. The aim of the present meta-analysis was to evaluate the efficacy of curcumin supplementation on circulating levels of TNF-α in randomized controlled trials (RCTs). The search included PubMed-Medline, Scopus, Web of Science and Google Scholar databases by up to September 21, 2015, to identify RCTs investigating the impact of curcumin on circulating TNF-α concentration. Quantitative data synthesis was performed using a random-effects model, with weighed mean difference (WMD) and 95% confidence interval (CI) as summary statistics. Meta-regression and leave-one-out sensitivity analyses were performed to assess the modifiers of treatment response. Eight RCTs comprising nine treatment arms were finally selected for the meta-analysis. There was a significant reduction of circulating TNF-α concentrations following curcumin supplementation (WMD: -4.69pg/mL, 95% CI: -7.10, -2.28, p<0.001). This effect size was robust in sensitivity analysis. Meta-regression did not suggest any significant association between the circulating TNF-α-lowering effects of curcumin with either dose or duration (slope: 0.197; 95% CI: -1.73, 2.12; p=0.841) of treatment. This meta-analysis of RCTs suggested a significant effect of curcumin in lowering circulating TNF-α concentration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Single-Nucleotide Polymorphisms Associated with Skin Naphthyl–Keratin Adduct Levels in Workers Exposed to Naphthalene

PubMed Central

Jiang, Rong; French, John E.; Stober, Vandy P.; Kang-Sickel, Juei-Chuan C.; Zou, Fei

2012-01-01

Background: Individual genetic variation that results in differences in systemic response to xenobiotic exposure is not accounted for as a predictor of outcome in current exposure assessment models. Objective: We developed a strategy to investigate individual differences in single-nucleotide polymorphisms (SNPs) as genetic markers associated with naphthyl–keratin adduct (NKA) levels measured in the skin of workers exposed to naphthalene. Methods: The SNP-association analysis was conducted in PLINK using candidate-gene analysis and genome-wide analysis. We identified significant SNP–NKA associations and investigated the potential impact of these SNPs along with personal and workplace factors on NKA levels using a multiple linear regression model and the Pratt index. Results: In candidate-gene analysis, a SNP (rs4852279) located near the CYP26B1 gene contributed to the 2-naphthyl–keratin adduct (2NKA) level. In the multiple linear regression model, the SNP rs4852279, dermal exposure, exposure time, task replacing foam, age, and ethnicity all were significant predictors of 2NKA level. In genome-wide analysis, no single SNP reached genome-wide significance for NKA levels (all p ≥ 1.05 × 10–5). Pathway and network analyses of SNPs associated with NKA levels were predicted to be involved in the regulation of cellular processes and homeostasis. Conclusions: These results provide evidence that a quantitative biomarker can be used as an intermediate phenotype when investigating the association between genetic markers and exposure–dose relationship in a small, well-characterized exposed worker population. PMID:22391508

Inequality and adolescent violence: an exploration of community, family, and individual factors.

PubMed Central

Bruce, Marino A.

2004-01-01

PURPOSE: The study seeks to examine whether the relationships among community, family, individual factors, and violent behavior are parallel across race- and gender-specific segments of the adolescent population. METHODS: Data from the National Longitudinal Study of Adolescent Health are analyzed to highlight the complex relationships between inequality, community, family, individual behavior, and violence. RESULTS: The results from robust regression analysis provide evidence that social environmental factors can influence adolescent violence in race- and gender-specific ways. CONCLUSIONS: Findings from this study establish the plausibility of multidimensional models that specify a complex relationship between inequality and adolescent violence. PMID:15101669

Can a bank crisis break your heart?

PubMed Central

Stuckler, David; Meissner, Christopher M; King, Lawrence P

2008-01-01

Background To assess whether a banking system crisis increases short-term population cardiovascular mortality rates. Methods International, longitudinal multivariate regression analysis of cardiovascular disease mortality data from 1960 to 2002 Results A system-wide banking crisis increases population heart disease mortality rates by 6.4% (95% CI: 2.5% to 10.2%, p < 0.01) in high income countries, after controlling for economic change, macroeconomic instability, and population age and social distribution. The estimated effect is nearly four times as large in low income countries. Conclusion Banking crises are a significant determinant of short-term increases in heart disease mortality rates, and may have more severe consequences for developing countries. PMID:18197979

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

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

Comparison of the Relationship between Women' Empowerment and Fertility between Single-child and Multi-child Families

PubMed Central

Saberi, Tahereh; Ehsanpour, Soheila; Mahaki, Behzad; Kohan, Shahnaz

2018-01-01

Background: The reduction in fertility and increase in the number of single-child families in Iran will result in an increased risk of population aging. One of the factors affecting fertility is women's empowerment. This study aimed to evaluate the relationship between women's empowerment and fertility in single-child and multi-child families. Materials and Methods: This case-control study was conducted among 350 women (120 who had only 1 child as case group and 230 who had 2 or more children as control group) of 15–49 years of age in Isfahan, Iran, in 2016. For data collection, a 2-part questionnaire was designed. Data were analyzed using independent t-test, Chi-square test, and logistic regression analysis. Results: The difference between average scores of women's empowerment in the case group 54.08 (9.88) and control group 51.47 (8.57) was significant (p = 0.002). Simple logistic regression analysis showed that under diploma education, compared to postgraduate education, (OR = 0.21, p = 0.001) and being a housewife, compared to being employed, (OR = 0.45, p = 0.004) decreased the odds of having only 1 child. Multiple logistic regression results showed that the relationship between women's empowerment and fertility was not significant (p = 0.265). Conclusions: Although women in single-child families were more empowered, this was not the main reason for their preference to have only 1 child. In fact, educated and employed women postpone marriage and childbearing and limit fertility to only 1 child despite their desire. PMID:29628961

Neighborhood food environment and body mass index among Japanese older adults: results from the Aichi Gerontological Evaluation Study (AGES)

PubMed Central

2011-01-01

Background The majority of studies of the local food environment in relation to obesity risk have been conducted in the US, UK, and Australia. The evidence remains limited to western societies. The aim of this paper is to examine the association of local food environment to body mass index (BMI) in a study of older Japanese individuals. Methods The analysis was based on 12,595 respondents from cross-sectional data of the Aichi Gerontological Evaluation Study (AGES), conducted in 2006 and 2007. Using Geographic Information Systems (GIS), we mapped respondents' access to supermarkets, convenience stores, and fast food outlets, based on a street network (both the distance to the nearest stores and the number of stores within 500 m of the respondents' home). Multiple linear regression and logistic regression analyses were performed to examine the association between food environment and BMI. Results In contrast to previous reports, we found that better access to supermarkets was related to higher BMI. Better access to fast food outlets or convenience stores was also associated with higher BMI, but only among those living alone. The logistic regression analysis, using categorized BMI, showed that the access to supermarkets was only related to being overweight or obese, but not related to being underweight. Conclusions Our findings provide mixed support for the types of food environment measures previously used in western settings. Importantly, our results suggest the need to develop culture-specific approaches to characterizing neighborhood contexts when hypotheses are extrapolated across national borders. PMID:21777439

The Andrews’ Principles of Risk, Need, and Responsivity as Applied in Drug Abuse Treatment Programs: Meta-Analysis of Crime and Drug Use Outcomes

PubMed Central

Prendergast, Michael L.; Pearson, Frank S.; Podus, Deborah; Hamilton, Zachary K.; Greenwell, Lisa

2013-01-01

Objectives The purpose of the present meta-analysis was to answer the question: Can the Andrews principles of risk, needs, and responsivity, originally developed for programs that treat offenders, be extended to programs that treat drug abusers? Methods Drawing from a dataset that included 243 independent comparisons, we conducted random-effects meta-regression and ANOVA-analog meta-analyses to test the Andrews principles by averaging crime and drug use outcomes over a diverse set of programs for drug abuse problems. Results For crime outcomes, in the meta-regressions the point estimates for each of the principles were substantial, consistent with previous studies of the Andrews principles. There was also a substantial point estimate for programs exhibiting a greater number of the principles. However, almost all of the 95% confidence intervals included the zero point. For drug use outcomes, in the meta-regressions the point estimates for each of the principles was approximately zero; however, the point estimate for programs exhibiting a greater number of the principles was somewhat positive. All of the estimates for the drug use principles had confidence intervals that included the zero point. Conclusions This study supports previous findings from primary research studies targeting the Andrews principles that those principles are effective in reducing crime outcomes, here in meta-analytic research focused on drug treatment programs. By contrast, programs that follow the principles appear to have very little effect on drug use outcomes. Primary research studies that experimentally test the Andrews principles in drug treatment programs are recommended. PMID:24058325

Logistic regression analysis of the risk factors of anastomotic fistula after radical resection of esophageal‐cardiac cancer

PubMed Central

Huang, Jinxi; Wang, Chenghu; Yuan, Weiwei; Zhang, Zhandong; Chen, Beibei; Zhang, Xiefu

2017-01-01

Background This study was conducted to investigate the risk factors of anastomotic fistula after the radical resection of esophageal‐cardiac cancer. Methods Five hundred and forty‐four esophageal‐cardiac cancer patients who underwent surgery and had complete clinical data were included in the study. Fifty patients diagnosed with postoperative anastomotic fistula were considered the case group and the remaining 494 subjects who did not develop postoperative anastomotic fistula were considered the control. The potential risk factors for anastomotic fistula, such as age, gender, diabetes history, smoking history, were collected and compared between the groups. Statistically significant variables were substituted into logistic regression to further evaluate the independent risk factors for postoperative anastomotic fistulas in esophageal‐cardiac cancer. Results The incidence of anastomotic fistulas was 9.2% (50/544). Logistic regression analysis revealed that female gender (P < 0.05), laparoscopic surgery (P < 0.05), decreased postoperative albumin (P < 0.05), and postoperative renal dysfunction (P < 0.05) were independent risk factors for anastomotic fistulas in patients who received surgery for esophageal‐cardiac cancer. Of the 50 anastomotic fistulas, 16 cases were small fistulas, which were only discovered by conventional imaging examination and not presenting clinical symptoms. All of the anastomotic fistulas occurred within seven days after surgery. Five of the patients with anastomotic fistulas underwent a second surgery and three died. Conclusion Female patients with esophageal‐cardiac cancer treated with endoscopic surgery and suffering from postoperative hypoproteinemia and renal dysfunction were susceptible to postoperative anastomotic fistula. PMID:28940985

Knowledge, attitudes and practices survey on organ donation among a selected adult population of Pakistan

PubMed Central

Saleem, Taimur; Ishaque, Sidra; Habib, Nida; Hussain, Syedda Saadia; Jawed, Areeba; Khan, Aamir Ali; Ahmad, Muhammad Imran; Iftikhar, Mian Omer; Mughal, Hamza Pervez; Jehan, Imtiaz

2009-01-01

Background To determine the knowledge, attitudes and practices regarding organ donation in a selected adult population in Pakistan. Methods Convenience sampling was used to generate a sample of 440; 408 interviews were successfully completed and used for analysis. Data collection was carried out via a face to face interview based on a pre-tested questionnaire in selected public areas of Karachi, Pakistan. Data was analyzed using SPSS v.15 and associations were tested using the Pearson's Chi square test. Multiple logistic regression was used to find independent predictors of knowledge status and motivation of organ donation. Results Knowledge about organ donation was significantly associated with education (p = 0.000) and socioeconomic status (p = 0.038). 70/198 (35.3%) people expressed a high motivation to donate. Allowance of organ donation in religion was significantly associated with the motivation to donate (p = 0.000). Multiple logistic regression analysis revealed that higher level of education and higher socioeconomic status were significant (p < 0.05) independent predictors of knowledge status of organ donation. For motivation, multiple logistic regression revealed that higher socioeconomic status, adequate knowledge score and belief that organ donation is allowed in religion were significant (p < 0.05) independent predictors. Television emerged as the major source of information. Only 3.5% had themselves donated an organ; with only one person being an actual kidney donor. Conclusion Better knowledge may ultimately translate into the act of donation. Effective measures should be taken to educate people with relevant information with the involvement of media, doctors and religious scholars. PMID:19534793

Prediction of accommodative optical response in prepresbyopic patients using ultrasound biomicroscopy

PubMed Central

Ramasubramanian, Viswanathan; Glasser, Adrian

2015-01-01

PURPOSE To determine whether relatively low-resolution ultrasound biomicroscopy (UBM) can predict the accommodative optical response in prepresbyopic eyes as well as in a previous study of young phakic subjects, despite lower accommodative amplitudes. SETTING College of Optometry, University of Houston, Houston, USA. DESIGN Observational cross-sectional study. METHODS Static accommodative optical response was measured with infrared photorefraction and an autorefractor (WR-5100K) in subjects aged 36 to 46 years. A 35 MHz UBM device (Vumax, Sonomed Escalon) was used to image the left eye, while the right eye viewed accommodative stimuli. Custom-developed Matlab image-analysis software was used to perform automated analysis of UBM images to measure the ocular biometry parameters. The accommodative optical response was predicted from biometry parameters using linear regression, 95% confidence intervals (CIs), and 95% prediction intervals. RESULTS The study evaluated 25 subjects. Per-diopter (D) accommodative changes in anterior chamber depth (ACD), lens thickness, anterior and posterior lens radii of curvature, and anterior segment length were similar to previous values from young subjects. The standard deviations (SDs) of accommodative optical response predicted from linear regressions for UBM-measured biometry parameters were ACD, 0.15 D; lens thickness, 0.25 D; anterior lens radii of curvature, 0.09 D; posterior lens radii of curvature, 0.37 D; and anterior segment length, 0.42 D. CONCLUSIONS Ultrasound biomicroscopy parameters can, on average, predict accommodative optical response with SDs of less than 0.55 D using linear regressions and 95% CIs. Ultrasound biomicroscopy can be used to visualize and quantify accommodative biometric changes and predict accommodative optical response in prepresbyopic eyes. PMID:26049831

Characterizing mammographic images by using generic texture features

PubMed Central

2012-01-01

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

Representational change and strategy use in children's number line estimation during the first years of primary school

PubMed Central

2012-01-01

Background The objective of this study was to scrutinize number line estimation behaviors displayed by children in mathematics classrooms during the first three years of schooling. We extend existing research by not only mapping potential logarithmic-linear shifts but also provide a new perspective by studying in detail the estimation strategies of individual target digits within a number range familiar to children. Methods Typically developing children (n = 67) from Years 1-3 completed a number-to-position numerical estimation task (0-20 number line). Estimation behaviors were first analyzed via logarithmic and linear regression modeling. Subsequently, using an analysis of variance we compared the estimation accuracy of each digit, thus identifying target digits that were estimated with the assistance of arithmetic strategy. Results Our results further confirm a developmental logarithmic-linear shift when utilizing regression modeling; however, uniquely we have identified that children employ variable strategies when completing numerical estimation, with levels of strategy advancing with development. Conclusion In terms of the existing cognitive research, this strategy factor highlights the limitations of any regression modeling approach, or alternatively, it could underpin the developmental time course of the logarithmic-linear shift. Future studies need to systematically investigate this relationship and also consider the implications for educational practice. PMID:22217191

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.

Complications after procedures of photorefractive keratectomy

NASA Astrophysics Data System (ADS)

Gierek-Ciaciura, Stanislawa

1998-10-01

Purpose: The aim of this study was to investigate the saveness of the PRK procedures. Material and method: 151 eyes after PRK for correction of myopia and 112 after PRK for correction of myopic astigmatism were examined. All PRK procedures have been performed with an excimer laser manufactured by Aesculap Meditec. Results: Haze, regression, decentration infection and overcorrection were found. Conclusions: The most often complication is regression. Corneal inflammation in the early postoperative period may cause the regression or haze. The greater corrected refractive error the greater haze degree. Haze decreases with time.

Regression Analysis: Legal Applications in Institutional Research

ERIC Educational Resources Information Center

Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.

2008-01-01

This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

DTIC Science & Technology

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

Predictors of condom use and refusal among the population of Free State province in South Africa

PubMed Central

2012-01-01

Background This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. Methods Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT) were used for analysing two response variables ‘ever used condom’ and ‘ever refused condom’. Results Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by ‘knowledge of correct use of condom’, condom availability, young age, being single and higher education. ‘Perceived need’ for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one’s HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms). In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. Conclusions The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need for condom-use and improving skills for correct use. They should also incorporate interventions to reduce the shame associated with condoms and individual counselling of those likely to refuse condoms. PMID:22639964

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

PubMed

Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H

2017-05-10

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value

A primer for biomedical scientists on how to execute model II linear regression analysis.

PubMed

Ludbrook, John

2012-04-01

1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.

Water quality parameter measurement using spectral signatures

NASA Technical Reports Server (NTRS)

White, P. E.

1973-01-01

Regression analysis is applied to the problem of measuring water quality parameters from remote sensing spectral signature data. The equations necessary to perform regression analysis are presented and methods of testing the strength and reliability of a regression are described. An efficient algorithm for selecting an optimal subset of the independent variables available for a regression is also presented.

Glaucoma Progression Detection by Retinal Nerve Fiber Layer Measurement Using Scanning Laser Polarimetry: Event and Trend Analysis

PubMed Central

Moon, Byung Gil; Cho, Jung Woo; Kang, Sung Yong; Yun, Sung-Cheol; Na, Jung Hwa; Lee, Youngrok; Kook, Michael S.

2012-01-01

Purpose To evaluate the use of scanning laser polarimetry (SLP, GDx VCC) to measure the retinal nerve fiber layer (RNFL) thickness in order to evaluate the progression of glaucoma. Methods Test-retest measurement variability was determined in 47 glaucomatous eyes. One eye each from 152 glaucomatous patients with at least 4 years of follow-up was enrolled. Visual field (VF) loss progression was determined by both event analysis (EA, Humphrey guided progression analysis) and trend analysis (TA, linear regression analysis of the visual field index). SLP progression was defined as a reduction of RNFL exceeding the predetermined repeatability coefficient in three consecutive exams, as compared to the baseline measure (EA). The slope of RNFL thickness change over time was determined by linear regression analysis (TA). Results Twenty-two eyes (14.5%) progressed according to the VF EA, 16 (10.5%) by VF TA, 37 (24.3%) by SLP EA and 19 (12.5%) by SLP TA. Agreement between VF and SLP progression was poor in both EA and TA (VF EA vs. SLP EA, k = 0.110; VF TA vs. SLP TA, k = 0.129). The mean (±standard deviation) progression rate of RNFL thickness as measured by SLP TA did not significantly differ between VF EA progressors and non-progressors (-0.224 ± 0.148 µm/yr vs. -0.218 ± 0.151 µm/yr, p = 0.874). SLP TA and EA showed similar levels of sensitivity when VF progression was considered as the reference standard. Conclusions RNFL thickness as measurement by SLP was shown to be capable of detecting glaucoma progression. Both EA and TA of SLP showed poor agreement with VF outcomes in detecting glaucoma progression. PMID:22670073

Real-time Supervised Detection of Pink Areas in Dermoscopic Images of Melanoma: Importance of Color Shades, Texture and Location

PubMed Central

Kaur, Ravneet; Albano, Peter P.; Cole, Justin G.; Hagerty, Jason; LeAnder, Robert W.; Moss, Randy H.; Stoecker, William V.

2015-01-01

Background/Purpose Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature of these early melanomas. If rapid and accurate automatic detection of pink color in these melanomas could be accomplished, there could be significant public health benefits. Methods Detection of three shades of pink (light pink, dark pink, and orange pink) was accomplished using color analysis techniques in five color planes (red, green, blue, hue and saturation). Color shade analysis was performed using a logistic regression model trained with an image set of 60 dermoscopic images of melanoma that contained pink areas. Detected pink shade areas were further analyzed with regard to the location within the lesion, average color parameters over the detected areas, and histogram texture features. Results Logistic regression analysis of a separate set of 128 melanomas and 128 benign images resulted in up to 87.9% accuracy in discriminating melanoma from benign lesions measured using area under the receiver operating characteristic curve. The accuracy in this model decreased when parameters for individual shades, texture, or shade location within the lesion were omitted. Conclusion Texture, color, and lesion location analysis applied to multiple shades of pink can assist in melanoma detection. When any of these three details: color location, shade analysis, or texture analysis were omitted from the model, accuracy in separating melanoma from benign lesions was lowered. Separation of colors into shades and further details that enhance the characterization of these color shades are needed for optimal discrimination of melanoma from benign lesions. PMID:25809473

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

Modelling typhoid risk in Dhaka Metropolitan Area of Bangladesh: the role of socio-economic and environmental factors

PubMed Central

2013-01-01

Background Developing countries in South Asia, such as Bangladesh, bear a disproportionate burden of diarrhoeal diseases such as Cholera, Typhoid and Paratyphoid. These seem to be aggravated by a number of social and environmental factors such as lack of access to safe drinking water, overcrowdedness and poor hygiene brought about by poverty. Some socioeconomic data can be obtained from census data whilst others are more difficult to elucidate. This study considers a range of both census data and spatial data from other sources, including remote sensing, as potential predictors of typhoid risk. Typhoid data are aggregated from hospital admission records for the period from 2005 to 2009. The spatial and statistical structures of the data are analysed and Principal Axis Factoring is used to reduce the degree of co-linearity in the data. The resulting factors are combined into a Quality of Life index, which in turn is used in a regression model of typhoid occurrence and risk. Results The three Principal Factors used together explain 87% of the variance in the initial candidate predictors, which eminently qualifies them for use as a set of uncorrelated explanatory variables in a linear regression model. Initial regression result using Ordinary Least Squares (OLS) were disappointing, this was explainable by analysis of the spatial autocorrelation inherent in the Principal factors. The use of Geographically Weighted Regression caused a considerable increase in the predictive power of regressions based on these factors. The best prediction, determined by analysis of the Akaike Information Criterion (AIC) was found when the three factors were combined into a quality of life index, using a method previously published by others, and had a coefficient of determination of 73%. Conclusions The typhoid occurrence/risk prediction equation was used to develop the first risk map showing areas of Dhaka Metropolitan Area whose inhabitants are at greater or lesser risk of typhoid infection. This, coupled with seasonal information on typhoid incidence also reported in this paper, has the potential to advise public health professionals on developing prevention strategies such as targeted vaccination. PMID:23497202

Extramural vascular invasion and response to neoadjuvant chemoradiotherapy in rectal cancer: Influence of the CpG island methylator phenotype

PubMed Central

Williamson, Jeremy Stuart; Jones, Huw Geraint; Williams, Namor; Griffiths, Anthony Paul; Jenkins, Gareth; Beynon, John; Harris, Dean Anthony

2017-01-01

AIM To identify whether CpG island methylator phenotype (CIMP) is predictive of response to neoadjuvant chemoradiotherapy (NACRT) and outcomes in rectal cancer. METHODS Patients undergoing NACRT and surgical resection for rectal cancer in a tertiary referral centre between 2002-2011 were identified. Pre-treatment tumour biopsies were analysed for CIMP status (high, intermediate or low) using methylation specific PCR. KRAS and BRAF status were also determined using pyrosequencing analysis. Clinical information was extracted from case records and cancer services databases. Response to radiotherapy was measured by tumour regression scores determined upon histological examination of the resected specimen. The relationship between these molecular features, response to NACRT and oncological outcomes were analysed. RESULTS There were 160 patients analysed with a median follow-up time of 46.4 mo. Twenty-one (13%) patients demonstrated high levels of CIMP methylation (CIMP-H) and this was significantly associated with increased risk of extramural vascular invasion (EMVI) compared with CIMP-L [8/21 (38%) vs 15/99 (15%), P = 0.028]. CIMP status was not related to tumour regression after radiotherapy or survival, however EMVI was significantly associated with adverse survival (P < 0.001). Intermediate CIMP status was significantly associated with KRAS mutation (P = 0.01). There were 14 (9%) patients with a pathological complete response (pCR) compared to 116 (73%) patients having no or minimal regression after neoadjuvant chemoradiotherapy. Those patients with pCR had median survival of 106 mo compared to 65.8 mo with minimal regression, although this was not statistically significant (P = 0.26). Binary logistic regression analysis of the relationship between EMVI and other prognostic features revealed, EMVI positivity was associated with poor overall survival, advanced “T” stage and CIMP-H but not nodal status, age, sex, KRAS mutation status and presence of local or systemic recurrence. CONCLUSION We report a novel association of pre-treatment characterisation of CIMP-H with EMVI status which has prognostic implications and is not readily detectable on pre-treatment histological examination. PMID:28567185

The effects of designation and volume of neonatal care on mortality and morbidity outcomes of very preterm infants in England: retrospective population-based cohort study

PubMed Central

Watson, S I; Arulampalam, W; Petrou, S; Marlow, N; Morgan, A S; Draper, E S; Santhakumaran, S; Modi, N

2014-01-01

Objective To examine the effects of designation and volume of neonatal care at the hospital of birth on mortality and morbidity outcomes in very preterm infants in a managed clinical network setting. Design A retrospective, population-based analysis of operational clinical data using adjusted logistic regression and instrumental variables (IV) analyses. Setting 165 National Health Service neonatal units in England contributing data to the National Neonatal Research Database at the Neonatal Data Analysis Unit and participating in the Neonatal Economic, Staffing and Clinical Outcomes Project. Participants 20 554 infants born at <33 weeks completed gestation (17 995 born at 27–32 weeks; 2559 born at <27 weeks), admitted to neonatal care and either discharged or died, over the period 1 January 2009–31 December 2011. Intervention Tertiary designation or high-volume neonatal care at the hospital of birth. Outcomes Neonatal mortality, any in-hospital mortality, surgery for necrotising enterocolitis, surgery for retinopathy of prematurity, bronchopulmonary dysplasia and postmenstrual age at discharge. Results Infants born at <33 weeks gestation and admitted to a high-volume neonatal unit at the hospital of birth were at reduced odds of neonatal mortality (IV regression odds ratio (OR) 0.70, 95% CI 0.53 to 0.92) and any in-hospital mortality (IV regression OR 0.68, 95% CI 0.54 to 0.85). The effect of volume on any in-hospital mortality was most acute among infants born at <27 weeks gestation (IV regression OR 0.51, 95% CI 0.33 to 0.79). A negative association between tertiary-level unit designation and mortality was also observed with adjusted logistic regression for infants born at <27 weeks gestation. Conclusions High-volume neonatal care provided at the hospital of birth may protect against in-hospital mortality in very preterm infants. Future developments of neonatal services should promote delivery of very preterm infants at hospitals with high-volume neonatal units. PMID:25001393

Martial arts as a mental health intervention for children? Evidence from the ECLS-K

PubMed Central

Strayhorn, Joseph M; Strayhorn, Jillian C

2009-01-01

Background Martial arts studios for children market their services as providing mental health outcomes such as self-esteem, self-confidence, concentration, and self-discipline. It appears that many parents enroll their children in martial arts in hopes of obtaining such outcomes. The current study used the data from the Early Childhood Longitudinal Study, Kindergarten class of 1998-1999, to assess the effects of martial arts upon such outcomes as rated by classroom teachers. Methods The Early Childhood Longitudinal Study used a multistage probability sampling design to gather a sample representative of U.S. children attending kindergarten beginning 1998. We made use of data collected in the kindergarten, 3rd grade, and 5th grade years. Classroom behavior was measured by a rating scale completed by teachers; participation in martial arts was assessed as part of a parent interview. The four possible combinations of participation and nonparticipation in martial arts at time 1 and time 2 for each analysis were coded into three dichotomous variables; the set of three variables constituted the measure of participation studied through regression. Multiple regression was used to estimate the association between martial arts participation and change in classroom behavior from one measurement occasion to the next. The change from kindergarten to third grade was studied as a function of martial arts participation, and the analysis was replicated studying behavior change from third grade to fifth grade. Cohen's f2 effect sizes were derived from these regressions. Results The martial arts variable failed to show a statistically significant effect on behavior, in either of the regression analyses; in fact, the f2 effect size for martial arts was 0.000 for both analyses. The 95% confidence intervals for regression coefficients for martial arts variables have upper and lower bounds that are all close to zero. The analyses not only fail to reject the null hypothesis, but also render unlikely a population effect size that differs greatly from zero. Conclusion The data from the ECLS-K fail to support enrolling children in martial arts to improve mental health outcomes as measured by classroom teachers. PMID:19828027

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Demirjian's method in the estimation of age: A study on human third molars

PubMed Central

Lewis, Amitha J.; Boaz, Karen; Nagesh, K. R; Srikant, N; Gupta, Neha; Nandita, K. P; Manaktala, Nidhi

2015-01-01

Aim: The primary aim of the following study is to estimate the chronological age based on the stages of third molar development following the eight stages (A to H) method of Demirjian et al. (along with two modifications-Orhan) and secondary aim is to compare third molar development with sex and age. Materials and Methods: The sample consisted of 115 orthopantomograms from South Indian subjects with known chronological age and gender. Multiple regression analysis was performed with chronological age as the dependable variable and third molar root development as independent variable. All the statistical analysis was performed using the SPSS 11.0 package (IBM ® Corporation). Results: Statistically no significant differences were found in third molar development between males and females. Depending on the available number of wisdom teeth in an individual, R2 varied for males from 0.21 to 0.48 and for females from 0.16 to 0.38. New equations were derived for estimating the chronological age. Conclusion: The chronological age of a South Indian individual between 14 and 22 years may be estimated based on the regression formulae. However, additional studies with a larger study population must be conducted to meet the need for population-based information on third molar development. PMID:26005306

High Maternal Blood Mercury Level Is Associated with Low Verbal IQ in Children.

PubMed

Jeong, Kyoung Sook; Park, Hyewon; Ha, Eunhee; Shin, Jiyoung; Hong, Yun Chul; Ha, Mina; Park, Hyesook; Kim, Bung Nyun; Lee, Boeun; Lee, Soo Jeong; Lee, Kyung Yeon; Kim, Ja Hyeong; Kim, Yangho

2017-07-01

The objective of the present study was to investigate the relationship of IQ in children with maternal blood mercury concentration during late pregnancy. The present study is a component of the Mothers and Children's Environmental Health (MOCEH) study, a multi-center birth cohort project in Korea that began in 2006. The study cohort consisted of 553 children whose mothers underwent testing for blood mercury during late pregnancy. The children were given the Korean language version of the Wechsler Preschool and Primary Scale of Intelligence, revised edition (WPPSI-R) at 60 months of age. Multivariate linear regression analysis, with adjustment for covariates, was used to assess the relationship between verbal, performance, and total IQ in children and blood mercury concentration of mothers during late pregnancy. The results of multivariate linear regression analysis indicated that a doubling of blood mercury was associated with the decrease in verbal and total IQ by 2.482 (95% confidence interval [CI], 0.749-4.214) and 2.402 (95% CI, 0.526-4.279), respectively, after adjustment. This inverse association remained after further adjustment for blood lead concentration. Fish intake is an effect modifier of child IQ. In conclusion, high maternal blood mercury level is associated with low verbal IQ in children. © 2017 The Korean Academy of Medical Sciences.

Chromium (VI) induced oxidative damage to DNA: increase of urinary 8-hydroxydeoxyguanosine concentrations (8-OHdG) among electroplating workers

PubMed Central

Kuo, H; Chang, S; Wu, K; Wu, F

2003-01-01

Aims: To investigate the concentration of urinary 8-hydroxydeoxyguanosine (8-OHdG) among electroplating workers in Taiwan. Methods: Fifty workers were selected from five chromium (Cr) electroplating plants in central Taiwan. The 20 control subjects were office workers with no previous exposure to Cr. Urinary 8-OHdG concentrations were determined using high performance liquid chromatography with electrochemical detection. Results: Urinary 8-OHdG concentrations among Cr workers (1149.5 pmol/kg/day) were higher than those in the control group (730.2 pmol/kg/day). There was a positive correlation between urinary 8-OHdG concentrations and urinary Cr concentration (r = 0.447, p < 0.01), and urinary 8-OHdG correlated positively with airborne Cr concentration (r = 0.285). Using multiple regression analysis, the factors that affected urinary 8-OHdG concentrations were alcohol, the common cold, and high urinary Cr concentration. There was a high correlation of urinary 8-OHdG with both smoking and drinking, but multiple regression analysis showed that smoking was not a significant factor. Age and gender were also non-significant factors. Conclusion: 8-OHdG, which is an indicator of oxidative DNA damage, was a sensitive biomarker for Cr exposure. PMID:12883020

Developing a global psychotherapeutic approach to schizophrenia: results of a five-year follow-up.

PubMed Central

Alanen, Y. O.; Räkköläinen, V.; Rasimus, R.; Laakso, J.; Kaljonen, A.

1985-01-01

This is an account of a long-range action research project to determine indications for and effects of a comprehensive psychotherapeutic approach, including various treatment modalities, in the treatment of schizophrenics. Four diagnostic groups were established among the 100 patients. In the course of data analysis, the group of typical schizophrenics (56 percent) was contrasted to or compared with the entire series. A further diagnostic differentiation was established according to ego functioning; i.e., imminent, acute, regressive, and paranoid ego disintegrations, respectively. Patients and family members were interviewed upon admission, and again two and five years later, and the data recorded on a 163-item form from which 40 clinical and psychosocial variables were constructed after the baseline examinations. In addition to cross-tabulation, logistic regression analysis was employed. The conclusion that the follow-up study supports the effectiveness of our global psychotherapeutic approach to treating schizophrenia seems justified. Results so far indicate that five modes of therapy in addition to drug treatments are optimal for different patients. The five modes are long-term individual psychotherapy, couple or conjoint family therapy for married patients, family therapy with the family of origin, flexible short-term crisis intervention with a family focus, and extensive long-term treatment focused on social rehabilitation for the most ill-starred patients. PMID:4049919

The correlations of psychological status, quality of life, self-esteem, social support and body image disturbance in Chinese patients with Systemic Lupus Erythematosus.

PubMed

Zhao, Qian; Chen, Haoyang; Yan, Hongyan; He, Yan; Zhu, Li; Fu, WenTing; Shen, Biyu

2018-01-31

This study aimed (i) to complement existing research by focusing on body image disturbance issues in Chinese Systemic Lupus Erythematosus (SLE) patients; (ii) to investigate how Chinese patients make sense of disease diagnosis and perceived cultural influences within the context of their SLE. A total of 118 SLE patients underwent standardized laboratory examinations and completed several questionnaires. Independent sample t-test, Mann-Whitney U-test, Chi-square test, and multivariate analysis using backward stepwise logistic regression model were used to analyze these data. We found 18.3% SLE patients had BID, which were significantly higher than the control group (.8%). SLE patients are more concerned about their physical changes caused by disease. There were significant correlations among personal health insurance, complication of diabetes, appearance of new rash, depression, anxiety, self-esteem and BID in patients with SLE. Meanwhile, logistic regression analysis revealed that appearance of new rash and high anxiety were significantly associated with BID in SLE patients. In conclusion, it is beneficial to pay attention to the physical and mental health of patients with rheumatic disease from the perspective of body image, to understand their needs and to provide effective and effective service for them.

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

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

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

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

Impact of Depression, Fatigue, and Global Measure of Cortical Volume on Cognitive Impairment in Multiple Sclerosis

PubMed Central

De Cola, Maria Cristina; D'Aleo, Giangaetano; Sessa, Edoardo; Marino, Silvia

2015-01-01

Objective. To investigate the influence of demographic and clinical variables, such as depression, fatigue, and quantitative MRI marker on cognitive performances in a sample of patients affected by multiple sclerosis (MS). Methods. 60 MS patients (52 relapsing remitting and 8 primary progressive) underwent neuropsychological assessments using Rao's Brief Repeatable Battery of Neuropsychological Tests (BRB-N), the Beck Depression Inventory-second edition (BDI-II), and the Fatigue Severity Scale (FSS). We performed magnetic resonance imaging to all subjects using a 3 T scanner and obtained tissue-specific volumes (normalized brain volume and cortical brain volume). We used Student's t-test to compare depressed and nondepressed MS patients. Finally, we performed a multivariate regression analysis in order to assess possible predictors of patients' cognitive outcome among demographic and clinical variables. Results. 27.12% of the sample (16/59) was cognitively impaired, especially in tasks requiring attention and information processing speed. From between group comparison, we find that depressed patients had worse performances on BRB-N score, greater disability and disease duration, and brain volume decrease. According to multiple regression analysis, the BDI-II score was a significant predictor for most of the neuropsychological tests. Conclusions. Our findings suggest that the presence of depressive symptoms is an important determinant of cognitive performance in MS patients. PMID:25861633

How Do Clinicians Prefer Cultural Competence Training? Findings from the DSM-5 Cultural Formulation Interview Field Trial

PubMed Central

Aggarwal, Neil Krishan; Lam, Peter; Castillo, Enrico; Weiss, Mitchell G.; Diaz, Esperanza; Alarcón, Renato D.; van Dijk, Rob; Rohlof, Hans; Ndetei, David M.; Scalco, Monica; Aguilar-Gaxiola, Sergio; Bassiri, Kavoos; Deshpande, Smita; Groen, Simon; Jadhav, Sushrut; Kirmayer, Laurence J.; Paralikar, Vasudeo; Westermeyer, Joseph; Santos, Filipa; Vega-Dienstmaier, Johann; Anez, Luis; Boiler, Marit; Nicasio, Andel V.; Lewis-Fernández, Roberto

2015-01-01

Objective This study’s objective is to analyze training methods clinicians reported as most and least helpful during the DSM-5 Cultural Formulation Interview field trial, reasons why, and associations between demographic characteristics and method preferences. Method The authors used mixed methods to analyze interviews from 75 clinicians in five continents on their training preferences after a standardized training session and clinicians’ first administration of the Cultural Formulation Interview. Content analysis identified most and least helpful educational methods by reason. Bivariate and logistic regression analysis compared clinician characteristics to method preferences. Results Most frequently, clinicians named case-based behavioral simulations as “most helpful” and video as “least helpful” training methods. Bivariate and logistic regression models, first unadjusted and then clustered by country, found that each additional year of a clinician’s age was associated with a preference for behavioral simulations: OR=1.05 (95% CI: 1.01–1.10; p=0.025). Conclusions Most clinicians preferred active behavioral simulations in cultural competence training, and this effect was most pronounced among older clinicians. Effective training may be best accomplished through a combination of reviewing written guidelines, video demonstration, and behavioral simulations. Future work can examine the impact of clinician training satisfaction on patient symptoms and quality of life. PMID:26449983

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.

The association between parental mental health and behavioral disorders in pre-school children

PubMed Central

Karimzadeh, Mansoureh; Rostami, Mohammad; Teymouri, Robab; Moazzen, Zahra; Tahmasebi, Siyamak

2017-01-01

Background and Aim Behavioral disorders among children reflect psychological problems of parents, as mental illness of either parent would increase the likelihood of mental disorder in the child. In view of the negative relationship between parents’ and children’s illness, the current study intended to determine the correlation between mental health of parents and behavioral disorders of pre-school children. Methods The present descriptive-correlational research studied 80 children registered at pre-school centers in Pardis Township, Tehran, Iran during 2014–2015 using convenience sampling. The research tools included General Health Questionnaire (GHQ) and Preschool Behavior Questionnaire (PBQ). The resulted data were analyzed using Pearson Product-moment Correlation Coefficient and regression analysis in SPSS 21. Results The research results showed that there was a significant positive correlation between all dimensions of mental health of parents with general behavioral disorders (p<0.001). The results of the regression analysis showed that parents’ depression was the first and the only predictive variable of behavioral disorders in children with 26.8% predictive strength. Conclusion Given the strong relationship between children’s behavioral disorders and parents’ general health, and the significant role of parents’ depression in children’s behavioral disorders, it seems necessary to take measures to decrease the impact of parents’ disorders on children. PMID:28848622

High preoperative ratio of blood urea nitrogen to creatinine increased mortality in gastrointestinal cancer patients who developed postoperative enteric fistulas.

PubMed

Lin, Hsing-Lin; Chen, Chao-Wen; Lu, Chien-Yu; Sun, Li-Chu; Shih, Ying-Ling; Chuang, Jui-Fen; Huang, Yu-Ho; Sheen, Maw-Chang; Wang, Jaw-Yuan

2012-08-01

Development of an enteric fistula after surgery is a major therapeutic complication. In this study, we retrospectively examined the potential relationship between preoperative laboratory data and patient mortality by collecting patient data from a tertiary medical center. We included patients who developed enteric fistulas after surgery for gastrointestinal (GI) cancer between January 2005 and December 2010. Patient demographics and data on preoperative and pre-parenteral nutritional statuses were compared between surviving and deceased patients. Logistic regression analysis and receiver operating characteristic (ROC) curves were used to determine the predictors and cut-off values, respectively. Patients with incomplete data and preoperative heart, lung, kidney, and liver diseases were excluded from the study; thus, out of 65 patients, 43 were enrolled. Logistic regression analysis showed that blood urea nitrogen-to-creatinine (BUN/Cr) ratio [p = 0.007; OR = 0.443, 95% confidence interval (CI), 0.245-0.802] was an independent predictor of mortality in patients who developed enteric fistulas after surgery for GI cancer. In conclusion, the results of our study showed that a high preoperative BUN/Cr ratio increases the risk of mortality in patients who develop enteric fistulas after surgery for GI cancer. Copyright © 2012. Published by Elsevier B.V.

Association between Diet and Lifestyle Habits and Irritable Bowel Syndrome: A Case-Control Study

PubMed Central

Guo, Yu-Bin; Zhuang, Kang-Min; Kuang, Lei; Zhan, Qiang; Wang, Xian-Fei; Liu, Si-De

2015-01-01

Background/Aims Recent papers have highlighted the role of diet and lifestyle habits in irritable bowel syndrome (IBS), but very few population-based studies have evaluated this association in developing countries. The aim of this study was to evaluate the association between diet and lifestyle habits and IBS. Methods A food frequency and lifestyle habits questionnaire was used to record the diet and lifestyle habits of 78 IBS subjects and 79 healthy subjects. Cross-tabulation analysis and logistic regression were used to reveal any association among lifestyle habits, eating habits, food consumption frequency, and other associated conditions. Results The results from logistic regression analysis indicated that IBS was associated with irregular eating (odds ratio [OR], 3.257), physical inactivity (OR, 3.588), and good quality sleep (OR, 0.132). IBS subjects ate fruit (OR, 3.082) vegetables (OR, 3.778), and legumes (OR, 2.111) and drank tea (OR, 2.221) significantly more frequently than the control subjects. After adjusting for age and sex, irregular eating (OR, 3.963), physical inactivity (OR, 6.297), eating vegetables (OR, 7.904), legumes (OR, 2.674), drinking tea (OR, 3.421) and good quality sleep (OR, 0.054) were independent predictors of IBS. Conclusions This study reveals a possible association between diet and lifestyle habits and IBS. PMID:25266811

Malaria treatment-seeking behaviour and related factors of Wa ethnic minority in Myanmar: a cross-sectional study

PubMed Central

2012-01-01

Background In Southeast Asia, data on malaria treatment-seeking behaviours and related affecting factors are rare. The population of the Wa ethnic in Myanmar has difficulty in accessing formal health care. To understand malaria treatment-seeking behaviour and household-affecting factors of the Wa people, a cross-sectional study carried out in Shan Special Region II, Myanmar. Methods The two methods, questionnaire-based household surveys to household heads and in-depth interviews to key informants, were carried out independently. The proportion of treatment-seeking patterns was calculated. Logistic regression was used to determine affecting factors of treatment-seeking. Qualitative data were analysed by using Text Analysis Markup System. Results Overall, 87.5% of the febrile population sought treatment, but only 32.0% did so within 24 hours. The proportion accessing the retail sector (79.6%) was statistically significant higher (P<0.0001) than accessing the public sector (10.6%). Multivariable logistic regression analysis identified family income, distances from a health facility, family decision and patient characteristics being independently associated with delayed malaria treatment. Conclusion Malaria treatment-seeking behaviour is not appropriate, and affecting factors include health service systems, social and cultural factors in Wa State of Myanmar. PMID:23237576

Relationship between Gender Roles and Sexual Assertiveness in Married Women

PubMed Central

Azmoude, Elham; Firoozi, Mahbobe; Sadeghi Sahebzad, Elahe; Asgharipour, Neghar

2016-01-01

ABSTRACT Background: Evidence indicates that sexual assertiveness is one of the important factors affecting sexual satisfaction. According to some studies, traditional gender norms conflict with women’s capability in expressing sexual desires. This study examined the relationship between gender roles and sexual assertiveness in married women in Mashhad, Iran. Methods: This cross-sectional study was conducted on 120 women who referred to Mashhad health centers through convenient sampling in 2014-15. Data were collected using Bem Sex Role Inventory (BSRI) and Hulbert index of sexual assertiveness. Data were analyzed using SPSS 16 by Pearson and Spearman’s correlation tests and linear Regression Analysis. Results: The mean scores of sexual assertiveness was 54.93±13.20. According to the findings, there was non-significant correlation between Femininity and masculinity score with sexual assertiveness (P=0.069 and P=0.080 respectively). Linear regression analysis indicated that among the predictor variables, only Sexual function satisfaction was identified as the sexual assertiveness summary predictor variables (P=0.001). Conclusion: Based on the results, sexual assertiveness in married women does not comply with gender role, but it is related to Sexual function satisfaction. So, counseling psychologists need to consider this variable when designing intervention programs for modifying sexual assertiveness and find other variables that affect sexual assertiveness. PMID:27713899

Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan T.

2012-01-01

Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…

A Quality Assessment Tool for Non-Specialist Users of Regression Analysis

ERIC Educational Resources Information Center

Argyrous, George

2015-01-01

This paper illustrates the use of a quality assessment tool for regression analysis. It is designed for non-specialist "consumers" of evidence, such as policy makers. The tool provides a series of questions such consumers of evidence can ask to interrogate regression analysis, and is illustrated with reference to a recent study published…

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

PubMed

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visual grading characteristics and ordinal regression analysis during optimisation of CT head examinations.

PubMed

Zarb, Francis; McEntee, Mark F; Rainford, Louise

2015-06-01

To evaluate visual grading characteristics (VGC) and ordinal regression analysis during head CT optimisation as a potential alternative to visual grading assessment (VGA), traditionally employed to score anatomical visualisation. Patient images (n = 66) were obtained using current and optimised imaging protocols from two CT suites: a 16-slice scanner at the national Maltese centre for trauma and a 64-slice scanner in a private centre. Local resident radiologists (n = 6) performed VGA followed by VGC and ordinal regression analysis. VGC alone indicated that optimised protocols had similar image quality as current protocols. Ordinal logistic regression analysis provided an in-depth evaluation, criterion by criterion allowing the selective implementation of the protocols. The local radiology review panel supported the implementation of optimised protocols for brain CT examinations (including trauma) in one centre, achieving radiation dose reductions ranging from 24 % to 36 %. In the second centre a 29 % reduction in radiation dose was achieved for follow-up cases. The combined use of VGC and ordinal logistic regression analysis led to clinical decisions being taken on the implementation of the optimised protocols. This improved method of image quality analysis provided the evidence to support imaging protocol optimisation, resulting in significant radiation dose savings. • There is need for scientifically based image quality evaluation during CT optimisation. • VGC and ordinal regression analysis in combination led to better informed clinical decisions. • VGC and ordinal regression analysis led to dose reductions without compromising diagnostic efficacy.

Diagnostic and Prognostic Value of Long-Axis Strain and Myocardial Contraction Fraction Using Standard Cardiovascular MR Imaging in Patients with Nonischemic Dilated Cardiomyopathies.

PubMed

Arenja, Nisha; Riffel, Johannes H; Fritz, Thomas; André, Florian; Aus dem Siepen, Fabian; Mueller-Hennessen, Matthias; Giannitsis, Evangelos; Katus, Hugo A; Friedrich, Matthias G; Buss, Sebastian J

2017-06-01

Purpose To assess the utility of established functional markers versus two additional functional markers derived from standard cardiovascular magnetic resonance (MR) images for their incremental diagnostic and prognostic information in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods Approval was obtained from the local ethics committee. MR images from 453 patients with NIDCM and 150 healthy control subjects were included between 2005 and 2013 and were analyzed retrospectively. Myocardial contraction fraction (MCF) was calculated by dividing left ventricular (LV) stroke volume by LV myocardial volume, and long-axis strain (LAS) was calculated from the distances between the epicardial border of the LV apex and the midpoint of a line connecting the origins of the mitral valve leaflets at end systole and end diastole. Receiver operating characteristic curve, Kaplan-Meier method, Cox regression, and classification and regression tree (CART) analyses were performed for diagnostic and prognostic performances. Results LAS (area under the receiver operating characteristic curve [AUC] = 0.93, P < .001) and MCF (AUC = 0.92, P < .001) can be used to discriminate patients with NIDCM from age- and sex-matched control subjects. A total of 97 patients reached the combined end point during a median follow-up of 4.8 years. In multivariate Cox regression analysis, only LV ejection fraction (EF) and LAS independently indicated the combined end point (hazard ratio = 2.8 and 1.9, respectively; P < .001 for both). In a risk stratification approach with classification and regression tree analysis, combined LV EF and LAS cutoff values were used to stratify patients into three risk groups (log-rank test, P < .001). Conclusion Cardiovascular MR-derived MCF and LAS serve as reliable diagnostic and prognostic markers in patients with NIDCM. LAS, as a marker for longitudinal contractile function, is an independent parameter for outcome and offers incremental information beyond LV EF and the presence of myocardial fibrosis. © RSNA, 2017 Online supplemental material is available for this article.

SU-E-J-256: Predicting Metastasis-Free Survival of Rectal Cancer Patients Treated with Neoadjuvant Chemo-Radiotherapy by Data-Mining of CT Texture Features of Primary Lesions

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

Zhong, H; Wang, J; Shen, L

Purpose: The purpose of this study is to investigate the relationship between computed tomographic (CT) texture features of primary lesions and metastasis-free survival for rectal cancer patients; and to develop a datamining prediction model using texture features. Methods: A total of 220 rectal cancer patients treated with neoadjuvant chemo-radiotherapy (CRT) were enrolled in this study. All patients underwent CT scans before CRT. The primary lesions on the CT images were delineated by two experienced oncologists. The CT images were filtered by Laplacian of Gaussian (LoG) filters with different filter values (1.0–2.5: from fine to coarse). Both filtered and unfiltered imagesmore » were analyzed using Gray-level Co-occurrence Matrix (GLCM) texture analysis with different directions (transversal, sagittal, and coronal). Totally, 270 texture features with different species, directions and filter values were extracted. Texture features were examined with Student’s t-test for selecting predictive features. Principal Component Analysis (PCA) was performed upon the selected features to reduce the feature collinearity. Artificial neural network (ANN) and logistic regression were applied to establish metastasis prediction models. Results: Forty-six of 220 patients developed metastasis with a follow-up time of more than 2 years. Sixtyseven texture features were significantly different in t-test (p<0.05) between patients with and without metastasis, and 12 of them were extremely significant (p<0.001). The Area-under-the-curve (AUC) of ANN was 0.72, and the concordance index (CI) of logistic regression was 0.71. The predictability of ANN was slightly better than logistic regression. Conclusion: CT texture features of primary lesions are related to metastasisfree survival of rectal cancer patients. Both ANN and logistic regression based models can be developed for prediction.« less

REGRESSION ANALYSIS OF SEA-SURFACE-TEMPERATURE PATTERNS FOR THE NORTH PACIFIC OCEAN.

DTIC Science & Technology

SEA WATER, *SURFACE TEMPERATURE, *OCEANOGRAPHIC DATA, PACIFIC OCEAN, REGRESSION ANALYSIS , STATISTICAL ANALYSIS, UNDERWATER EQUIPMENT, DETECTION, UNDERWATER COMMUNICATIONS, DISTRIBUTION, THERMAL PROPERTIES, COMPUTERS.

The process and utility of classification and regression tree methodology in nursing research.

PubMed

Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

2014-06-01

This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Discussion paper. English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984-2013. Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. © 2013 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

Advantages of the net benefit regression framework for economic evaluations of interventions in the workplace: a case study of the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders.

PubMed

Hoch, Jeffrey S; Dewa, Carolyn S

2014-04-01

Economic evaluations commonly accompany trials of new treatments or interventions; however, regression methods and their corresponding advantages for the analysis of cost-effectiveness data are not well known. To illustrate regression-based economic evaluation, we present a case study investigating the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders. We implement net benefit regression to illustrate its strengths and limitations. Net benefit regression offers a simple option for cost-effectiveness analyses of person-level data. By placing economic evaluation in a regression framework, regression-based techniques can facilitate the analysis and provide simple solutions to commonly encountered challenges. Economic evaluations of person-level data (eg, from a clinical trial) should use net benefit regression to facilitate analysis and enhance results.

Urban Sprawl as a Risk Factor in Motor Vehicle Occupant and Pedestrian Fatalities

PubMed Central

Ewing, Reid; Schieber, Richard A.; Zegeer, Charles V.

2003-01-01

Objectives. We sought to determine the association between urban sprawl and traffic fatalities. Methods. We created a sprawl index by applying principal components analysis to data for 448 US counties in the largest 101 metropolitan areas. Regression analysis was used to determine associations between the index and traffic fatalities. Results. For every 1% increase in the index (i.e., more compact, less sprawl), all-mode traffic fatality rates fell by 1.49% (P < .001) and pedestrian fatality rates fell by 1.47% to 3.56%, after adjustment for pedestrian exposure (P < .001). Conclusions. Urban sprawl was directly related to traffic fatalities and pedestrian fatalities. Subsequent studies should investigate relationships at a finer geographic scale and should strive to improve on the measure of exposure used to adjust pedestrian fatality rates. PMID:12948977

Methodological Issues in Design and Analysis of a Matched Case-Control Study of a Vaccine’s Effectiveness

PubMed Central

Niccolai, Linda M.; Ogden, Lorraine G.; Muehlenbein, Catherine E.; Dziura, James D.; Vázquez, Marietta; Shapiro, Eugene D.

2007-01-01

Objective Case-control studies of the effectiveness of a vaccine are useful to answer important questions, such as the effectiveness of a vaccine over time, that usually are not addressed by pre-licensure clinical trials of the vaccine’s efficacy. This report describes methodological issues related to design and analysis that were used to determine the effects of time since vaccination and age at the time of vaccination. Study Design and Setting A matched case-control study of the effectiveness of varicella vaccine. Results Sampling procedures and conditional logistic regression models including interaction terms are described. Conclusion Use of these methods will allow investigators to assess the effects of a wide range of variables, such as time since vaccination and age at the time of vaccination, on the effectiveness of a vaccine. PMID:17938054

Trends and spatial distribution of deaths of children aged 12-60 months in São Paulo, Brazil, 1980-98.

PubMed Central

Antunes, José Leopoldo Ferreira; Waldman, Eliseu Alves

2002-01-01

OBJECTIVE: To describe trends in the mortality of children aged 12-60 months and to perform spatial data analysis of its distribution at the inner city district level in São Paulo from 1980 to 1998. METHODS: Official mortality data were analysed in relation to the underlying causes of death. The population of children aged 12-60 months, disaggregated by sex and age, was estimated for each year. Educational levels, income, employment status, and other socioeconomic indices were also assessed. Statistical Package for Social Sciences software was used for the statistical processing of time series. The Cochrane-Orcutt procedure of generalized least squares regression analysis was used to estimate the regression parameters with control of first-order autocorrelation. Spatial data analysis employed the discrimination of death rates and socioeconomic indices at the inner city district level. For classifying area-level death rates the method of K-means cluster analysis was used. Spatial correlation between variables was analysed by the simultaneous autoregressive regression method. FINDINGS: There was a steady decline in death rates during the 1980s at an average rate of 3.08% per year, followed by a levelling off. Infectious diseases remained the major cause of mortality, accounting for 43.1% of deaths during the last three years of the study. Injuries accounted for 16.5% of deaths. Mortality rates at the area level clearly demonstrated inequity in the city's health profile: there was an increasing difference between the rich and the underprivileged social strata in this respect. CONCLUSION: The overall mortality rate among children aged 12-60 months dropped by almost 30% during the study period. Most of the decline happened during the 1980s. Many people still live in a state of deprivation in underserved areas. Time-series and spatial data analysis provided indications of potential value in the planning of social policies promoting well-being, through the identification of factors affecting child survival and the regions with the worst health profiles, to which programmes and resources should be preferentially directed. PMID:12077615

CADDIS Volume 4. Data Analysis: Basic Analyses

EPA Pesticide Factsheets

Use of statistical tests to determine if an observation is outside the normal range of expected values. Details of CART, regression analysis, use of quantile regression analysis, CART in causal analysis, simplifying or pruning resulting trees.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Radiation Dose-Response Model for Locally Advanced Rectal Cancer After Preoperative Chemoradiation Therapy

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

Appelt, Ane L., E-mail: ane.lindegaard.appelt@slb.regionsyddanmark.dk; University of Southern Denmark, Odense; Ploen, John

2013-01-01

Purpose: Preoperative chemoradiation therapy (CRT) is part of the standard treatment of locally advanced rectal cancers. Tumor regression at the time of operation is desirable, but not much is known about the relationship between radiation dose and tumor regression. In the present study we estimated radiation dose-response curves for various grades of tumor regression after preoperative CRT. Methods and Materials: A total of 222 patients, treated with consistent chemotherapy and radiation therapy techniques, were considered for the analysis. Radiation therapy consisted of a combination of external-beam radiation therapy and brachytherapy. Response at the time of operation was evaluated from themore » histopathologic specimen and graded on a 5-point scale (TRG1-5). The probability of achieving complete, major, and partial response was analyzed by ordinal logistic regression, and the effect of including clinical parameters in the model was examined. The radiation dose-response relationship for a specific grade of histopathologic tumor regression was parameterized in terms of the dose required for 50% response, D{sub 50,i}, and the normalized dose-response gradient, {gamma}{sub 50,i}. Results: A highly significant dose-response relationship was found (P=.002). For complete response (TRG1), the dose-response parameters were D{sub 50,TRG1} = 92.0 Gy (95% confidence interval [CI] 79.3-144.9 Gy), {gamma}{sub 50,TRG1} = 0.982 (CI 0.533-1.429), and for major response (TRG1-2) D{sub 50,TRG1} and {sub 2} = 72.1 Gy (CI 65.3-94.0 Gy), {gamma}{sub 50,TRG1} and {sub 2} = 0.770 (CI 0.338-1.201). Tumor size and N category both had a significant effect on the dose-response relationships. Conclusions: This study demonstrated a significant dose-response relationship for tumor regression after preoperative CRT for locally advanced rectal cancer for tumor dose levels in the range of 50.4-70 Gy, which is higher than the dose range usually considered.« less

A Note on the Relationship between the Number of Indicators and Their Reliability in Detecting Regression Coefficients in Latent Regression Analysis

ERIC Educational Resources Information Center

Dolan, Conor V.; Wicherts, Jelte M.; Molenaar, Peter C. M.

2004-01-01

We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators…

Uremic Pruritus, Dialysis Adequacy, and Metabolic Profiles in Hemodialysis Patients: A Prospective 5-Year Cohort Study

PubMed Central

Chen, Hung-Yuan; Chiu, Yen-Ling; Hsu, Shih-Ping; Pai, Mei-Fen; Ju-YehYang; Lai, Chun-Fu; Lu, Hui-Min; Huang, Shu-Chen; Yang, Shao-Yu; Wen, Su-Yin; Chiu, Hsien-Ching; Hu, Fu-Chang; Peng, Yu-Sen; Jee, Shiou-Hwa

2013-01-01

Background Uremic pruritus is a common and intractable symptom in patients on chronic hemodialysis, but factors associated with the severity of pruritus remain unclear. This study aimed to explore the associations of metabolic factors and dialysis adequacy with the aggravation of pruritus. Methods We conducted a 5-year prospective cohort study on patients with maintenance hemodialysis. A visual analogue scale (VAS) was used to assess the intensity of pruritus. Patient demographic and clinical characteristics, laboratory parameters, dialysis adequacy (assessed by Kt/V), and pruritus intensity were recorded at baseline and follow-up. Change score analysis of the difference score of VAS between baseline and follow-up was performed using multiple linear regression models. The optimal threshold of Kt/V, which is associated with the aggravation of uremic pruritus, was determined by generalized additive models and receiver operating characteristic analysis. Results A total of 111 patients completed the study. Linear regression analysis showed that lower Kt/V and use of low-flux dialyzer were significantly associated with the aggravation of pruritus after adjusting for the baseline pruritus intensity and a variety of confounding factors. The optimal threshold value of Kt/V for pruritus was 1.5 suggested by both generalized additive models and receiver operating characteristic analysis. Conclusions Hemodialysis with the target of Kt/V ≥1.5 and use of high-flux dialyzer may reduce the intensity of pruritus in patients on chronic hemodialysis. Further clinical trials are required to determine the optimal dialysis dose and regimen for uremic pruritus. PMID:23940749

Endovascular Therapy is Effective and Safe for Patients with Severe Ischemic Stroke: Pooled Analysis of IMS III and MR CLEAN Data

PubMed Central

Broderick, Joseph P.; Berkhemer, Olvert A.; Palesch, Yuko Y.; Dippel, Diederik W.J.; Foster, Lydia D.; Roos, Yvo B.W.E.M.; van der Lugt, Aad; Tomsick, Thomas A.; Majoie, Charles B.L.M.; van Zwam, Wim H.; Demchuk, Andrew M.; van Oostenbrugge, Robert J.; Khatri, Pooja; Lingsma, Hester F.; Hill, Michael D.; Roozenbeek, Bob; Jauch, Edward C.; Jovin, Tudor G.; Yan, Bernard; von Kummer, Rüdiger; Molina, Carlos A.; Goyal, Mayank; Schonewille, Wouter J.; Mazighi, Mikael; Engelter, Stefan T.; Anderson, Craig S.; Spilker, Judith; Carrozzella, Janice; Ryckborst, Karla J.; Janis, L. Scott; Simpson, Kit

2015-01-01

Background and Purpose We assessed the effect of endovascular treatment in acute ischemic stroke patients with severe neurological deficit (NIHSS ≥20) following a pre-specified analysis plan. Methods The pooled analysis of the IMS III and MR CLEAN trial included participants with an NIHSS ≥20 prior to intravenous (IV) t-PA treatment (IMS III) or randomization (MR CLEAN) who were treated with IV t-PA ≤ 3 hours of stroke onset. Our hypothesis was that participants with severe stroke randomized to endovascular therapy following IV t-PA would have improved 90-day outcome (distribution of modified Rankin scale [mRS] scores), as compared to those who received IV t-PA alone. Results Among 342 participants in the pooled analysis (194 from IMS III, 148 from MR CLEAN), an ordinal logistic regression model showed that the endovascular group had superior 90-day outcome compared to the IV t-PA group (adjusted odds ratio [aOR] 1.78; 95% confidence interval [CI] 1.20-2.66). In the logistic regression model of the dichotomous outcome (mRS 0-2, or ‘functional independence’), the endovascular group had superior outcomes (aOR 1.97; 95% CI 1.09-3.56). Functional independence (mRS ≤2) at 90 days was 25% in the endovascular group as compared to 14% in the IV t-PA group. Conclusions Endovascular therapy following IV t-PA within 3 hours of symptom onset improves functional outcome at 90 days after severe ischemic stroke. PMID:26486865

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

Association of Sociodemographic Factors, Smoking-Related Beliefs, and Smoking Restrictions With Intention to Quit Smoking in Korean Adults: Findings From the ITC Korea Survey

PubMed Central

Myung, Seung-Kwon; Seo, Hong Gwan; Cheong, Yoo-Seock; Park, Sohee; Lee, Wonkyong B; Fong, Geoffrey T

2012-01-01

Background Few studies have reported the factors associated with intention to quit smoking among Korean adult smokers. This study aimed to examine sociodemographic characteristics, smoking-related beliefs, and smoking-restriction variables associated with intention to quit smoking among Korean adult smokers. Methods We used data from the International Tobacco Control Korea Survey, which was conducted from November through December 2005 by using random-digit dialing and computer-assisted telephone interviewing of male and female smokers aged 19 years or older in 16 metropolitan areas and provinces of Korea. We performed univariate analysis and multiple logistic regression analysis to identify predictors of intention to quit. Results A total of 995 respondents were included in the final analysis. Of those, 74.9% (n = 745) intended to quit smoking. In univariate analyses, smokers with an intention to quit were younger, smoked fewer cigarettes per day, had a higher annual income, were more educated, were more likely to have a religious affiliation, drank less alcohol per week, were less likely to have self-exempting beliefs, and were more likely to have self-efficacy beliefs regarding quitting, to believe that smoking had damaged their health, and to report that smoking was never allowed anywhere in their home. In multiple logistic regression analysis, higher education level, having a religious affiliation, and a higher self-efficacy regarding quitting were significantly associated with intention to quit. Conclusions Sociodemographic factors, smoking-related beliefs, and smoking restrictions at home were associated with intention to quit smoking among Korean adults. PMID:22186157

Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis B-related fibrosis: a leading meta-analysis

PubMed Central

2012-01-01

Background The aspartate aminotransferase-to-platelet ratio index (APRI), a tool with limited expense and widespread availability, is a promising noninvasive alternative to liver biopsy for detecting hepatic fibrosis. The objective of this study was to systematically review the performance of the APRI in predicting significant fibrosis and cirrhosis in hepatitis B-related fibrosis. Methods Areas under summary receiver operating characteristic curves (AUROC), sensitivity and specificity were used to examine the accuracy of the APRI for the diagnosis of hepatitis B-related significant fibrosis and cirrhosis. Heterogeneity was explored using meta-regression. Results Nine studies were included in this meta-analysis (n = 1,798). Prevalence of significant fibrosis and cirrhosis were 53.1% and 13.5%, respectively. The summary AUCs of the APRI for significant fibrosis and cirrhosis were 0.79 and 0.75, respectively. For significant fibrosis, an APRI threshold of 0.5 was 84% sensitive and 41% specific. At the cutoff of 1.5, the summary sensitivity and specificity were 49% and 84%, respectively. For cirrhosis, an APRI threshold of 1.0-1.5 was 54% sensitive and 78% specific. At the cutoff of 2.0, the summary sensitivity and specificity were 28% and 87%, respectively. Meta-regression analysis indicated that the APRI accuracy for both significant fibrosis and cirrhosis was affected by histological classification systems, but not influenced by the interval between Biopsy & APRI or blind biopsy. Conclusion Our meta-analysis suggests that APRI show limited value in identifying hepatitis B-related significant fibrosis and cirrhosis. PMID:22333407

Parenchymal Texture Analysis in Digital Breast Tomosynthesis for Breast Cancer Risk Estimation: A Preliminary Study

PubMed Central

Kontos, Despina; Bakic, Predrag R.; Carton, Ann-Katherine; Troxel, Andrea B.; Conant, Emily F.; Maidment, Andrew D.A.

2009-01-01

Rationale and Objectives Studies have demonstrated a relationship between mammographic parenchymal texture and breast cancer risk. Although promising, texture analysis in mammograms is limited by tissue superimposition. Digital breast tomosynthesis (DBT) is a novel tomographic x-ray breast imaging modality that alleviates the effect of tissue superimposition, offering superior parenchymal texture visualization compared to mammography. Our study investigates the potential advantages of DBT parenchymal texture analysis for breast cancer risk estimation. Materials and Methods DBT and digital mammography (DM) images of 39 women were analyzed. Texture features, shown in studies with mammograms to correlate with cancer risk, were computed from the retroareolar breast region. We compared the relative performance of DBT and DM texture features in correlating with two measures of breast cancer risk: (i) the Gail and Claus risk estimates, and (ii) mammographic breast density. Linear regression was performed to model the association between texture features and increasing levels of risk. Results No significant correlation was detected between parenchymal texture and the Gail and Claus risk estimates. Significant correlations were observed between texture features and breast density. Overall, the DBT texture features demonstrated stronger correlations with breast percent density (PD) than DM (p ≤0.05). When dividing our study population in groups of increasing breast PD, the DBT texture features appeared to be more discriminative, having regression lines with overall lower p-values, steeper slopes, and higher R2 estimates. Conclusion Although preliminary, our results suggest that DBT parenchymal texture analysis could provide more accurate characterization of breast density patterns, which could ultimately improve breast cancer risk estimation. PMID:19201357

"A Bayesian sensitivity analysis to evaluate the impact of unmeasured confounding with external data: a real world comparative effectiveness study in osteoporosis".

PubMed

Zhang, Xiang; Faries, Douglas E; Boytsov, Natalie; Stamey, James D; Seaman, John W

2016-09-01

Observational studies are frequently used to assess the effectiveness of medical interventions in routine clinical practice. However, the use of observational data for comparative effectiveness is challenged by selection bias and the potential of unmeasured confounding. This is especially problematic for analyses using a health care administrative database, in which key clinical measures are often not available. This paper provides an approach to conducting a sensitivity analyses to investigate the impact of unmeasured confounding in observational studies. In a real world osteoporosis comparative effectiveness study, the bone mineral density (BMD) score, an important predictor of fracture risk and a factor in the selection of osteoporosis treatments, is unavailable in the data base and lack of baseline BMD could potentially lead to significant selection bias. We implemented Bayesian twin-regression models, which simultaneously model both the observed outcome and the unobserved unmeasured confounder, using information from external sources. A sensitivity analysis was also conducted to assess the robustness of our conclusions to changes in such external data. The use of Bayesian modeling in this study suggests that the lack of baseline BMD did have a strong impact on the analysis, reversing the direction of the estimated effect (odds ratio of fracture incidence at 24 months: 0.40 vs. 1.36, with/without adjusting for unmeasured baseline BMD). The Bayesian twin-regression models provide a flexible sensitivity analysis tool to quantitatively assess the impact of unmeasured confounding in observational studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A pilot evaluation of a computer-based psychometric test battery designed to detect impairment in patients with cirrhosis

PubMed Central

Cook, Nicola A; Kim, Jin Un; Pasha, Yasmin; Crossey, Mary ME; Schembri, Adrian J; Harel, Brian T; Kimhofer, Torben; Taylor-Robinson, Simon D

2017-01-01

Background Psychometric testing is used to identify patients with cirrhosis who have developed hepatic encephalopathy (HE). Most batteries consist of a series of paper-and-pencil tests, which are cumbersome for most clinicians. A modern, easy-to-use, computer-based battery would be a helpful clinical tool, given that in its minimal form, HE has an impact on both patients’ quality of life and the ability to drive and operate machinery (with societal consequences). Aim We compared the Cogstate™ computer battery testing with the Psychometric Hepatic Encephalopathy Score (PHES) tests, with a view to simplify the diagnosis. Methods This was a prospective study of 27 patients with histologically proven cirrhosis. An analysis of psychometric testing was performed using accuracy of task performance and speed of completion as primary variables to create a correlation matrix. A stepwise linear regression analysis was performed with backward elimination, using analysis of variance. Results Strong correlations were found between the international shopping list, international shopping list delayed recall of Cogstate and the PHES digit symbol test. The Shopping List Tasks were the only tasks that consistently had P values of <0.05 in the linear regression analysis. Conclusion Subtests of the Cogstate battery correlated very strongly with the digit symbol component of PHES in discriminating severity of HE. These findings would indicate that components of the current PHES battery with the international shopping list tasks of Cogstate would be discriminant and have the potential to be used easily in clinical practice. PMID:28919805

[The related factors of head and neck mocosal melanoma with lymph node metastasis].

PubMed

Yin, G F; Guo, W; Chen, X H; Huang, Z G

2017-12-05

Objective: To investigate the related factors of mucosal melanoma of head and neck with lymph node metastasis for early diagnosis and further treatments. Method: A retrospective analysis of 117 cases of head and neck mucosal malignant melanoma patients which received surgical treatment was performed. Eleven cases of patients with pathologically confirmed lymph node metastasis and 33 cases without lymph node metastasis (1∶3) were randomly selected to analyze. The related factors of lymph node metastasis of head and neck mucosal melanoma patients including age, gender, whether the existence of recurrence, bone invasion, lesion location were analyzed. The single factor and logistic regression analysis were performed, P <0.05 difference was statistically significant. Result: The lymph node metastasis rate of head and neck mucosal melanoma was 9.40%(11/117), the single factor analysis showed that there were 3 factors to be associated with lymph node metastasis, which was recurrence ( P =0.0000), bone invasion ( P =0.001), primary position ( P =0.007). Recurrence ( P =0.021) was a risk factor for lymph node metastasis according to the Logistic regression analysis, and the impact of bone invasion ( P =0.487) and primary location ( P =0.367) remained to be further explored. Conclusion: The patients of head and neck mucosal melanoma with the presence of recurrent usually accompanied by a further progression of the disease, such as lymph node metastasis, so for recurrent patients should pay special attention to the situation of lymph node and choose the reasonable treatment. Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.

An improved portmanteau test for autocorrelated errors in interrupted time-series regression models.

PubMed

Huitema, Bradley E; McKean, Joseph W

2007-08-01

A new portmanteau test for autocorrelation among the errors of interrupted time-series regression models is proposed. Simulation results demonstrate that the inferential properties of the proposed Q(H-M) test statistic are considerably more satisfactory than those of the well known Ljung-Box test and moderately better than those of the Box-Pierce test. These conclusions generally hold for a wide variety of autoregressive (AR), moving averages (MA), and ARMA error processes that are associated with time-series regression models of the form described in Huitema and McKean (2000a, 2000b).

A points-based algorithm for prognosticating clinical outcome of Chiari malformation Type I with syringomyelia: results from a predictive model analysis of 82 surgically managed adult patients.

PubMed

Thakar, Sumit; Sivaraju, Laxminadh; Jacob, Kuruthukulangara S; Arun, Aditya Atal; Aryan, Saritha; Mohan, Dilip; Sai Kiran, Narayanam Anantha; Hegde, Alangar S

2018-01-01

OBJECTIVE Although various predictors of postoperative outcome have been previously identified in patients with Chiari malformation Type I (CMI) with syringomyelia, there is no known algorithm for predicting a multifactorial outcome measure in this widely studied disorder. Using one of the largest preoperative variable arrays used so far in CMI research, the authors attempted to generate a formula for predicting postoperative outcome. METHODS Data from the clinical records of 82 symptomatic adult patients with CMI and altered hindbrain CSF flow who were managed with foramen magnum decompression, C-1 laminectomy, and duraplasty over an 8-year period were collected and analyzed. Various preoperative clinical and radiological variables in the 57 patients who formed the study cohort were assessed in a bivariate analysis to determine their ability to predict clinical outcome (as measured on the Chicago Chiari Outcome Scale [CCOS]) and the resolution of syrinx at the last follow-up. The variables that were significant in the bivariate analysis were further analyzed in a multiple linear regression analysis. Different regression models were tested, and the model with the best prediction of CCOS was identified and internally validated in a subcohort of 25 patients. RESULTS There was no correlation between CCOS score and syrinx resolution (p = 0.24) at a mean ± SD follow-up of 40.29 ± 10.36 months. Multiple linear regression analysis revealed that the presence of gait instability, obex position, and the M-line-fourth ventricle vertex (FVV) distance correlated with CCOS score, while the presence of motor deficits was associated with poor syrinx resolution (p ≤ 0.05). The algorithm generated from the regression model demonstrated good diagnostic accuracy (area under curve 0.81), with a score of more than 128 points demonstrating 100% specificity for clinical improvement (CCOS score of 11 or greater). The model had excellent reliability (κ = 0.85) and was validated with fair accuracy in the validation cohort (area under the curve 0.75). CONCLUSIONS The presence of gait imbalance and motor deficits independently predict worse clinical and radiological outcomes, respectively, after decompressive surgery for CMI with altered hindbrain CSF flow. Caudal displacement of the obex and a shorter M-line-FVV distance correlated with good CCOS scores, indicating that patients with a greater degree of hindbrain pathology respond better to surgery. The proposed points-based algorithm has good predictive value for postoperative multifactorial outcome in these patients.

The influence of sexual harassment on mental health among female military personnel of the Republic of Korea Armed Forces

PubMed Central

Kim, Tae Kyung; Lee, H-C; Lee, S G; Han, K-T; Park, E-C

2017-01-01

Introduction Reports of sexual harassment are becoming more frequent in Republic of Korea (ROK) Armed Forces. This study aimed to analyse the impact of sexual harassment on mental health among female military personnel of the ROK Armed Forces. Methods Data from the 2014 Military Health Survey were used. Instances of sexual harassment were recorded as ‘yes’ or ‘no’. Analysis of variance (ANOVA) was carried out to compare Kessler Psychological Distress Scale 10 (K-10) scores. Multiple logistic regression analysis was performed to identify associations between sexual harassment and K-10 scores. Results Among 228 female military personnel, 13 (5.7%) individuals experienced sexual harassment. Multiple logistic regression analysis revealed that sexual harassment had a significantly negative impact on K-10 scores (3.486, p<0.04). Higher K-10 scores among individuals experiencing sexual harassment were identified in the unmarried (including never-married) group (6.761, p<0.04), the short-term military service group (12.014, p<0.03) and the group whose length of service was <2 years (11.067, p<0.02). Conclusions Sexual harassment has a negative impact on mental health. Factors associated with worse mental health scores included service classification and length of service. The results provide helpful information with which to develop measures for minimising the negative psychological effects from sexual harassment and promoting sexual harassment prevention policy. PMID:27084842

Do drug treatment variables predict cognitive performance in multidrug-treated opioid-dependent patients? A regression analysis study

PubMed Central

2012-01-01

Background Cognitive deficits and multiple psychoactive drug regimens are both common in patients treated for opioid-dependence. Therefore, we examined whether the cognitive performance of patients in opioid-substitution treatment (OST) is associated with their drug treatment variables. Methods Opioid-dependent patients (N = 104) who were treated either with buprenorphine or methadone (n = 52 in both groups) were given attention, working memory, verbal, and visual memory tests after they had been a minimum of six months in treatment. Group-wise results were analysed by analysis of variance. Predictors of cognitive performance were examined by hierarchical regression analysis. Results Buprenorphine-treated patients performed statistically significantly better in a simple reaction time test than methadone-treated ones. No other significant differences between groups in cognitive performance were found. In each OST drug group, approximately 10% of the attention performance could be predicted by drug treatment variables. Use of benzodiazepine medication predicted about 10% of performance variance in working memory. Treatment with more than one other psychoactive drug (than opioid or BZD) and frequent substance abuse during the past month predicted about 20% of verbal memory performance. Conclusions Although this study does not prove a causal relationship between multiple prescription drug use and poor cognitive functioning, the results are relevant for psychosocial recovery, vocational rehabilitation, and psychological treatment of OST patients. Especially for patients with BZD treatment, other treatment options should be actively sought. PMID:23121989

Inequitable childhood immunization uptake in Nigeria: a multilevel analysis of individual and contextual determinants

PubMed Central

2009-01-01

Background Immunization coverage in many parts of Nigeria is far from optimal, and far from equitable. Nigeria accounts for half of the deaths from Measles in Africa, the highest prevalence of circulating wild poliovirus in the world, and the country is among the ten countries in the world with vaccine coverage below 50 percent. Studies focusing on community-level determinants therefore have serious policy implications Methods Multilevel multivariable regression analysis was used on a nationally-representative sample of women aged 15-49 years from the 2003 Nigeria Demographic and Health Survey. Multilevel regression analysis was performed with children (level 1) nested within mothers (level 2), who were in turn nested within communities (level 3). Results Results show that the pattern of full immunization clusters within families and communities, and that socio-economic characteristics are important in explaining the differentials in full immunization among the children in the study. At the individual level, ethnicity, mothers' occupation, and mothers' household wealth were characteristics of the mothers associated with full immunization of the children. At the community level, the proportion of mothers that had hospital delivery was a determinant of full immunization status. Conclusion Significant community-level variation remaining after having controlled for child- and mother-level characteristics is indicative of a need for further research on community-levels factors, which would enable extensive tailoring of community-level interventions aimed at improving full immunization and other child health outcomes. PMID:19930573

Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

PubMed Central

Nima, Ali Al; Rosenberg, Patricia; Archer, Trevor; Garcia, Danilo

2013-01-01

Background Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression. Methods Two hundred and two university students (males  = 93, females  = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses. Main Findings The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression. Conclusion The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators. PMID:24039896

Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

PubMed Central

He, Xiangyi; Zhong, Jie; Wang, Shuwei; Zhou, Yufen; Wang, Lei; Zhang, Yongping; Yuan, Yaozong

2017-01-01

To establish a screening strategy for pancreatic cancer (PC) based on new-onset diabetic mellitus (NO-DM), serum metabolomics analysis and a search for the metabolic pathways associated with PC related DM were performed. Serum samples from patients with NO-DM (n = 30) and patients with pancreatic cancer and NO-DM were examined by liquid chromatography-mass spectrometry. Data were analyzed using principal components analysis (PCA) and orthogonal projection to latent structures (OPLS) of the most significant metabolites. The diagnostic model was constructed using logistic regression analysis. Metabolic pathways were analyzed using the web-based tool MetPA. PC patients with NO-DM were older and had a lower BMI and shorter duration of DM than those with NO-DM. The metabolomic profiles of patients with PC and NO-DM were significantly different from those of patients with NO-DM in the PCA and OPLS models. Sixty two differential metabolites were identified by the OPLS model. The logistic regression model using a panel of two metabolites including N_Succinyl_L_diaminopimelic_acid and PE (18:2) had high sensitivity (93.3%) and specificity (93.1%) for PC. The top three metabolic pathways associated with PC related DM were valine, leucine and isoleucine biosynthesis and degradation, primary bile acid biosynthesis, and sphingolipid metabolism. In conclusion, screening for PC based on NO-DM using serum metabolomics in combination with clinic characteristics and CA19-9 is a potential useful strategy. Several metabolic pathways differed between PC related DM and type 2 DM. PMID:28418859

Vital capacity and selected metabolic diseases in middle-aged Japanese men

PubMed Central

Sakuta, Hidenari; Suzuki, Takashi; Yasuda, Hiroko; Ito, Teizo

2006-01-01

OBJECTIVE To elucidate the association between vital capacity and the presence of selected metabolic diseases in middle-aged Japanese men. METHODS A cross-sectional analysis of the associations among forced vital capacity (FVC), static vital capacity as a percentage of that predicted (%VC) and the presence of metabolic diseases was performed. RESULTS In a univariate linear regression analysis, FVC and %VC were inversely associated with poor vegetable intake, cigarette smoking and body mass index, but not with physical activity or ethanol consumption. In a logistic regression analysis adjusted for lifestyle factors, body mass index and age, the odds ratios for the presence of metabolic disease per 0.54 L (1 SD) decrease in FVC were 1.24 (95% CI 1.03 to 1.50) for type II diabetes, 1.21 (95% CI 1.02 to 1.42) for hypertension, 1.34 (95% CI 1.11 to 1.63) for hypertriglyceridemia, 1.23 (95% CI 1.03 to 1.46) for high gamma-glutamyl transferase levels and 1.63 (95% CI 1.10 to 2.41) for an episode of cardiovascular disease. FVC did not correlate with hyperhomocysteinemia, hypercholesterolemia or high white blood cell count. Similar results were also obtained for the association between %VC and metabolic diseases. CONCLUSIONS A decrease in FVC or %VC was associated with the presence of some metabolic diseases. The association may partly explain the reported association between low FVC and cardiovascular disease. PMID:16550264

Patterns of Adult Cross-Racial Friendships: A Context for Understanding Contemporary Race Relations

PubMed Central

Plummer, Deborah L.; Allison, Jeroan; Stone, Rosalie Torres; Powell, Lauren

2016-01-01

Objectives This study examined patterns, characteristics, and predictors of cross-racial friendships as the context for understanding contemporary race relations. Methods A national survey included 1,055 respondents, of whom 55% was white, 32% was black, and 74% was female; ages ranged from 18 to ≥ 65 years. Focus groups were conducted to assess societal and personal benefits. Participants (n=31) were racially diverse and aged 20–66 years. Results After accounting for multiple covariates, regression analysis revealed that Asians, Hispanics, and multiracial individuals are more likely than their white and black counterparts to have cross-racial friends. Females were less likely than males to have eight or more cross-racial friends. Regression analysis revealed that the depth of cross-racial friendships was greater for women than men and for those who shared more life experiences. Increasing age was associated with lower cross-racial friendship depth. Qualitative analysis of open-ended questions and focus group data established the social context as directly relevant to the number and depth of friendships. Despite the level of depth in cross-racial friendships, respondents described a general reluctance to discuss any racially charged societal events, such as police shootings of unarmed black men. Conclusion This study identified salient characteristics of individuals associated with cross-racial friendships and highlighted the influence of the social, historical, and political context in shaping such friendships. Our findings suggest that contemporary race relations reflect progress as well as polarization. PMID:27077797

Risk factors for repetitive strain injuries among school teachers in Thailand.

PubMed

Chaiklieng, Sunisa; Suggaravetsiri, Pornnapa

2012-01-01

Prolonged posture, static works and repetition are previously reported as the cause of repetitive strain injuries (RSIs) among workers including teachers. This cross-sectional analytic study aimed to investigate the prevalence and risk factors of RSIs among school teachers. Participants were 452 full-time school teachers in Thailand. Data were collected by the structural questionnaires, illuminance measurements and the physical fitness tests. Descriptive statistics and inferential statistics which were Chi-square test and multiple logistic regression analysis were used. Most teachers in this study were females (57.3%), the mean years of work experience was 22.6 ± 10.4 years. The six-month prevalence of RSIs was 73.7%. The univariate analysis identified the related risk factors to RSIs which were chronic disease (OR=1.8; 95% CI = 1.16-2.73), history of trauma (OR=2.0; 95% CI = 1.02-4.01), member of family had RSIs (OR=2.0; 95% CI = 1.02- 4.01), stretch to write on board (OR=1.7; 95% CI = 1.06-1.70) and high heel shoe >2 inch (OR=1.6; 95% CI = 1.03-2.51). Multiple logistic regression analysis showed that chronic diseases and high heel shoe >2 inch significantly related to developing of RSIs. The poor grip strength and back muscle flexibility significantly affected RSIs of teachers. In conclusions, RSIs were highly prevalent in school teachers that they should be aware of health promotion to prevent RSIs.

Measuring Work Environment and Performance in Nursing Homes

PubMed Central

Temkin-Greener, Helena; Zheng, Nan (Tracy); Katz, Paul; Zhao, Hongwei; Mukamel, Dana B.

2008-01-01

Background Qualitative studies of the nursing home work environment have long suggested that such attributes as leadership and communication may be related to nursing home performance, including residents' outcomes. However, empirical studies examining these relationships have been scant. Objectives This study is designed to: develop an instrument for measuring nursing home work environment and perceived work effectiveness; test the reliability and validity of the instrument; and identify individual and facility-level factors associated with better facility performance. Research Design and Methods The analysis was based on survey responses provided by managers (N=308) and direct care workers (N=7,418) employed in 162 facilities throughout New York State. Exploratory factor analysis, Chronbach's alphas, analysis of variance, and regression models were used to assess instrument reliability and validity. Multivariate regression models, with fixed facility effects, were used to examine factors associated with work effectiveness. Results The reliability and the validity of the survey instrument for measuring work environment and perceived work effectiveness has been demonstrated. Several individual (e.g. occupation, race) and facility characteristics (e.g. management style, workplace conditions, staffing) that are significant predictors of perceived work effectiveness were identified. Conclusions The organizational performance model used in this study recognizes the multidimensionality of the work environment in nursing homes. Our findings suggest that efforts at improving work effectiveness must also be multifaceted. Empirical findings from such a line of research may provide insights for improving the quality of the work environment and ultimately the quality of residents' care. PMID:19330892

The Relationship of Hypochondriasis to Anxiety, Depressive, and Somatoform Disorders

PubMed Central

Scarella, Timothy M.; Laferton, Johannes A. C.; Ahern, David K.; Fallon, Brian A.; Barsky, Arthur

2015-01-01

Background Though the phenotype of anxiety about medical illness has long been recognized, there continues to be debate as to whether it is a distinct psychiatric disorder and, if so, to which diagnostic category it belongs. Our objective was to investigate the pattern of psychiatric co-morbidity in hypochondriasis and to assess the relationship of health anxiety to anxiety, depressive, and somatoform disorders. Methods Data were collected as part of a clinical trial on treatment methods for hypochondriasis. 194 participants meeting criteria for DSM-IV hypochondriasis were assessed by sociodemographic variables, results of structured diagnostic interviews, and validated instruments for assessing various symptom dimensions of psychopathology. Results The majority of individuals with hypochondriasis had co-morbid psychiatric illness; the mean number of co-morbid diagnoses was 1.4, and 35.1% had hypochondriasis as their only diagnosis. Participants were more likely to have only co-morbid anxiety disorders than only co-morbid depressive or somatoform disorders. Multiple regression analysis of continuous measures of symptoms revealed the strongest correlation of health anxiety with anxiety symptoms, and a weaker correlation with somatoform symptoms; in multiple regression analysis, there was no correlation between health anxiety and depressive symptoms. Conclusion Our findings suggest that the entity of health anxiety (Hypochondriasis in DSM-IV, Illness Anxiety Disorder in DSM-5) is a clinical syndrome distinct from other psychiatric disorders. Analysis of co-morbidity patterns and continuous measures of symptoms suggest its appropriate classification is with anxiety rather than somatoform or mood disorders. PMID:26785798

Matsuda-DeFronzo insulin sensitivity index is a better predictor than HOMA-IR of hypertension in Japanese: the Tanno-Sobetsu study.

PubMed

Furugen, M; Saitoh, S; Ohnishi, H; Akasaka, H; Mitsumata, K; Chiba, M; Furukawa, T; Miyazaki, Y; Shimamoto, K; Miura, T

2012-05-01

Here we examined whether the Matsuda-DeFronzo insulin sensitivity index (ISI-M) is more efficient than the homeostasis model assessment of insulin resistance (HOMA-IR) for assessing risk of hypertension. Cross-sectional and longitudinal analyses were conducted using normotensive subjects who were selected among 1399 subjects in the Tanno-Sobetsu cohort. In the cross-sectional analysis (n=740), blood pressure (BP) level was correlated with HOMA-IR and with ISI-M, but correlation coefficients indicate a tighter correlation with ISI-M. Multiple linear regression analysis adjusted by age, sex, body mass index (BMI) and serum triglyceride level (TG) showed contribution of ISI-M and fasting plasma glucose, but not of HOMA-IR. In the longitudinal analysis (n=607), 241 subjects (39.7%) developed hypertension during a 10-year follow-up period, and multiple logistic regression indicated that age, TG, systolic BP and ISI-M, but not HOMA-IR, were associated with development of hypertension. In subjects <60 years old, odds ratio of new-onset hypertension was higher in the low ISI-M group (ISI-M, less than the median) than in the high ISI-M group for any tertile of BMI. In conclusion, ISI-M is a better predictor of hypertension than is HOMA-IR. Non-hepatic IR may be a determinant, which is independent of TG, BP level and BMI, of the development of hypertension.

Incorporating health care quality into health antitrust law

PubMed Central

2008-01-01

Background Antitrust authorities treat price as a proxy for hospital quality since health care quality is difficult to observe. As the ability to measure quality improved, more research became necessary to investigate the relationship between hospital market power and patient outcomes. This paper examines the impact of hospital competition on the quality of care as measured by the risk-adjusted mortality rates with the hospital as the unit of analysis. The study separately examines the effect of competition on non-profit hospitals. Methods We use California Office of Statewide Health Planning and Development (OSHPD) data from 1997 through 2002. Empirical model is a cross-sectional study of 373 hospitals. Regression analysis is used to estimate the relationship between Coronary Artery Bypass Graft (CABG) risk-adjusted mortality rates and hospital competition. Results Regression results show lower risk-adjusted mortality rates in the presence of a more competitive environment. This result holds for all alternative hospital market definitions. Non-profit hospitals do not have better patient outcomes than investor-owned hospitals. However, they tend to provide better quality in less competitive environments. CABG volume did not have a significant effect on patient outcomes. Conclusion Quality should be incorporated into the antitrust analysis. When mergers lead to higher prices and lower quality, thus lower social welfare, the antitrust challenge of hospital mergers is warranted. The impact of lower hospital competition on quality of care delivered by non-profit hospitals is ambiguous. PMID:18430219

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

PubMed Central

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

2015-01-01

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

Diabetes and Risk of Surgical Site Infection: A systematic review and meta-analysis

PubMed Central

Kaye, Keith S.; Knott, Caitlin; Nguyen, Huong; Santarossa, Maressa; Evans, Richard; Bertran, Elizabeth; Jaber, Linda

2016-01-01

Objective To determine the independent association between diabetes and SSI across multiple surgical procedures. Design Systematic review and meta-analysis. Methods Studies indexed in PubMed published between December 1985 and through July 2015 were identified through the search terms “risk factors” or “glucose” and “surgical site infection”. A total of 3,631 abstracts were identified through the initial search terms. Full texts were reviewed for 522 articles. Of these, 94 articles met the criteria for inclusion. Standardized data collection forms were used to extract study-specific estimates for diabetes, blood glucose levels, and body mass index (BMI). Random-effects meta-analysis was used to generate pooled estimates and meta-regression was used to evaluate specific hypothesized sources of heterogeneity. Results The primary outcome was SSI, as defined by the Centers for Disease Control and Prevention surveillance criteria. The overall effect size for the association between diabetes and SSI was OR=1.53 (95% Predictive Interval 1.11, 2.12, I2: 57.2%). SSI class, study design, or patient BMI did not significantly impact study results in a meta-regression model. The association was higher for cardiac surgery 2.03 (95% Predictive Interval 1.13, 4.05) compared to surgeries of other types (p=0.001). Conclusion These results support the consideration of diabetes as an independent risk factor for SSIs for multiple surgical procedure types. Continued efforts are needed to improve surgical outcomes for diabetic patients. PMID:26503187

Retrospective study of adjuvant icotinib in postoperative lung cancer patients harboring epidermal growth factor receptor mutations

PubMed Central

Yao, Shuyang; Zhi, Xiuyi; Wang, Ruotian; Qian, Kun; Hu, Mu

2016-01-01

Background Epidermal growth factor receptor (EGFR) mutations occur in about 50% of Asian patients with non‐small cell lung cancer (NSCLC). Patients with advanced NSCLC and EGFR mutations derive clinical benefit from treatment with EGFR‐tyrosine kinase inhibitors (TKIs). This study assessed the efficacy and safety of adjuvant icotinib without chemotherapy in EGFR‐mutated NSCLC patients undergoing resection of stage IB–IIIA. Methods Our retrospective study enrolled 20 patients treated with icotinib as adjuvant therapy. Survival factors were evaluated by univariate and Cox regression analysis. Results The median follow‐up time was 30 months (range 24–41). At the data cut‐off, five patients (25%) had recurrence or metastasis and one patient had died of the disease. The two‐year disease‐free survival (DFS) rate was 85%. No recurrence occurred in the high‐risk stage IB subgroup during the follow‐up period. In univariate analysis, the micropapillary pattern had a statistically significant effect on DFS (P = 0.040). Multivariate logistic regression analysis showed that there was no independent predictor. Drug related adverse events (AEs) occurred in nine patients (45.0%). The most common AEs were skin‐related events and diarrhea, but were relatively mild. No grade 3 AEs or occurrences of intolerable toxicity were observed. Conclusions Icotinib as adjuvant therapy is effective in patients harboring EGFR mutations after complete resection, with an acceptable AE profile. Further trials with larger sample sizes might confirm the efficiency of adjuvant TKI in selected patients. PMID:27766784

[Relationship between shift work and overweight/obesity in male steel workers].

PubMed

Xiao, M Y; Wang, Z Y; Fan, H M; Che, C L; Lu, Y; Cong, L X; Gao, X J; Liu, Y J; Yuan, J X; Li, X M; Hu, B; Chen, Y P

2016-11-10

Objective: To investigate the relationship between shift work and overweight/obesity in male steel workers. Methods: A questionnaire survey was conducted among the male steel workers selected during health examination in Tangshan Steel Company from March 2015 to March 2016. The relationship between shift work and overweight/obesity in the male steel workers were analyzed by using logistic regression model and restricted cubic splinemodel. Results: A total of 7 262 male steel workers were surveyed, the overall prevalence of overweight/obesitywas 64.5% (4 686/7 262), the overweight rate was 34.3% and the obesity rate was 30.2%, respectively. After adjusting for age, educational level and average family income level per month by multivariable logistic regression analysis, shift work was associated with overweight/obesity and obesity in the male steel workers. The OR was 1.19(95% CI : 1.05-1.35) and 1.15(95% CI : 1.00-1.32). Restricted cubic spline model analysis showed that the relationship between shift work years and overweight/obesity in the male steel workers was a nonlinear dose response one (nonlinear test χ 2 =7.43, P <0.05). Restricted cubic spline model analysis showed that the relationship between shift work years and obesity in the male steel workers was a nonlinear dose response one (nonlinear test χ 2 =10.48, P <0.05). Conclusion: Shift work was associated with overweight and obesity in the male steel workers, and shift work years and overweight/obesity had a nonlinear relationship.

[Awareness of health co-benefits of carbon emissions reduction in urban residents in Beijing: a cross-sectional survey].

PubMed

Gao, J H; Zhang, Y; Wang, J; Chen, H J; Zhang, G B; Liu, X B; Wu, H X; Li, J; Li, J; Liu, Q Y

2017-05-10

Objective: To understand the awareness of the health co-benefits of carbon emission reduction in urban residents in Beijing and the influencing factors, and provide information for policy decision on carbon emission reduction and health education campaigns. Methods: Four communities were selected randomly from Fangshan, Haidian, Huairou and Dongcheng districts of Beijing, respectively. The sample size was estimated by using Kish-Leslie formula for descriptive analysis. 90 participants were recruited from each community. χ (2) test was conducted to examine the associations between socio-demographic variables and individuals' awareness of the health co-benefits of carbon emission reduction. Ordinal logistic regression analysis was performed to investigate the factors influencing the awareness about the health co-benefits. Results: In 369 participants surveyed, 12.7 % reported they knew the health co-benefits of carbon emission reduction. The final logistic regression analysis revealed that age ( OR =0.98), attitude to climate warming ( OR =0.72) and air pollution ( OR =1.59), family monthly average income ( OR =1.27), and low carbon lifestyle ( OR =2.36) were important factors influencing their awareness of the health co-benefits of carbon emission reduction. Conclusion: The awareness of the health co-benefits of carbon emissions reduction were influenced by people' socio-demographic characteristics (age and family income), concerns about air pollution and climate warming, and low carbon lifestyle. It is necessary to take these factors into consideration in future development and implementation of carbon emission reduction policies and related health education campaigns.

Factors Predicting a Good Symptomatic Outcome After Prostate Artery Embolisation (PAE).

PubMed

Maclean, D; Harris, M; Drake, T; Maher, B; Modi, S; Dyer, J; Somani, B; Hacking, N; Bryant, T

2018-02-26

As prostate artery embolisation (PAE) becomes an established treatment for benign prostatic obstruction, factors predicting good symptomatic outcome remain unclear. Pre-embolisation prostate size as a predictor is controversial with a handful of papers coming to conflicting conclusions. We aimed to investigate if an association existed in our patient cohort between prostate size and clinical benefit, in addition to evaluating percentage volume reduction as a predictor of symptomatic outcome following PAE. Prospective follow-up of 86 PAE patients at a single institution between June 2012 and January 2016 was conducted (mean age 64.9 years, range 54-80 years). Multiple linear regression analysis was performed to assess strength of association between clinical improvement (change in IPSS) and other variables, of any statistical correlation, through Pearson's bivariate analysis. No major procedural complications were identified and clinical success was achieved in 72.1% (n = 62) at 12 months. Initial prostate size and percentage reduction were found to have a significant association with clinical improvement. Multiple linear regression analysis (r 2  = 0.48) demonstrated that percentage volume reduction at 3 months (r = 0.68, p < 0.001) had the strongest correlation with good symptomatic improvement at 12 months after adjusting for confounding factors. Both the initial prostate size and percentage volume reduction at 3 months predict good symptomatic outcome at 12 months. These findings therefore aid patient selection and counselling to achieve optimal outcomes for men undergoing prostate artery embolisation.

The effectiveness of school-based sex education programs in the promotion of abstinent behavior: a meta-analysis.

PubMed

Silva, Mónica

2002-08-01

This review presents the findings from controlled school-based sex education interventions published in the last 15 years in the US. The effects of the interventions in promoting abstinent behavior reported in 12 controlled studies were included in the meta-analysis. The results of the analysis indicated a very small overall effect of the interventions in abstinent behavior. Moderator analysis could only be pursued partially because of limited information in primary research studies. Parental participation in the program, age of the participants, virgin-status of the sample, grade level, percentage of females, scope of the implementation and year of publication of the study were associated with variations in effect sizes for abstinent behavior in univariate tests. However, only parental participation and percentage of females were significant in the weighted least-squares regression analysis. The richness of a meta-analytic approach appears limited by the quality of the primary research. Unfortunately, most of the research does not employ designs to provide conclusive evidence of program effects. Suggestions to address this limitation are provided.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra

PubMed Central

Shin, S M; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

Objectives: To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. Methods: The sample included 24 female and 19 male patients with hand–wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Results: Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Conclusions: Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index. PMID:25411713

Moderation analysis using a two-level regression model.

PubMed

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

Fever Is Associated with Reduced, Hypothermia with Increased Mortality in Septic Patients: A Meta-Analysis of Clinical Trials

PubMed Central

Rumbus, Zoltan; Matics, Robert; Hegyi, Peter; Zsiboras, Csaba; Szabo, Imre; Illes, Anita; Petervari, Erika; Balasko, Marta; Marta, Katalin; Miko, Alexandra; Parniczky, Andrea; Tenk, Judit; Rostas, Ildiko; Solymar, Margit

2017-01-01

Background Sepsis is usually accompanied by changes of body temperature (Tb), but whether fever and hypothermia predict mortality equally or differently is not fully clarified. We aimed to find an association between Tb and mortality in septic patients with meta-analysis of clinical trials. Methods We searched the PubMed, EMBASE, and Cochrane Controlled Trials Registry databases (from inception to February 2016). Human studies reporting Tb and mortality of patients with sepsis were included in the analyses. Average Tb with SEM and mortality rate of septic patient groups were extracted by two authors independently. Results Forty-two studies reported Tb and mortality ratios in septic patients (n = 10,834). Pearson correlation analysis revealed weak negative linear correlation (R2 = 0.2794) between Tb and mortality. With forest plot analysis, we found a 22.2% (CI, 19.2–25.5) mortality rate in septic patients with fever (Tb > 38.0°C), which was higher, 31.2% (CI, 25.7–37.3), in normothermic patients, and it was the highest, 47.3% (CI, 38.9–55.7), in hypothermic patients (Tb < 36.0°C). Meta-regression analysis showed strong negative linear correlation between Tb and mortality rate (regression coefficient: -0.4318; P < 0.001). Mean Tb of the patients was higher in the lowest mortality quartile than in the highest: 38.1°C (CI, 37.9–38.4) vs 37.1°C (CI, 36.7–37.4). Conclusions Deep Tb shows negative correlation with the clinical outcome in sepsis. Fever predicts lower, while hypothermia higher mortality rates compared with normal Tb. Septic patients with the lowest (< 25%) chance of mortality have higher Tb than those with the highest chance (> 75%). PMID:28081244

Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis

PubMed Central

Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong

2015-01-01

Background Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. Objectives This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. Methods We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. Results There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. Conclusion The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent. PMID:26053876

Acoustic Radiation Force Impulse Imaging for the Differentiation of Benign and Malignant Lymph Nodes: A Systematic Review and Meta-Analysis

PubMed Central

Yu, Cheng; Xie, Mingxing; Lv, Qing

2016-01-01

Objective To evaluate the overall performance of acoustic radiation force impulse imaging (ARFI) in differentiating between benign and malignant lymph nodes (LNs) by conducting a meta-analysis. Methods PubMed, Embase, Web of Science, the Cochrane Library and the China National Knowledge Infrastructure were comprehensively searched for potential studies through August 13th, 2016. Studies that investigated the diagnostic power of ARFI for the differential diagnosis of benign and malignant LNs by using virtual touch tissue quantification (VTQ) or virtual touch tissue imaging quantification (VTIQ) were collected. The included articles were published in English or Chinese. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to evaluate the methodological quality. The pooled sensitivity, specificity, and the area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated by means of a bivariate mixed-effects regression model. Meta-regression analysis was performed to identify the potential sources of between study heterogeneity. Fagan plot analysis was used to explore the clinical utilities. Publication bias was assessed using Deek’s funnel plot. Results Nine studies involving 1084 LNs from 929 patients were identified to analyze in the meta-analysis. The summary sensitivity and specificity of ARFI in detecting malignant LNs were 0.87 (95% confidence interval [CI], 0.83–0.91) and 0.88 (95% CI, 0.82–0.92), respectively. The AUC was 0.93 (95% CI, 0.90–0.95). The pooled DOR was 49.59 (95% CI, 26.11–94.15). Deek’s funnel plot revealed no significant publication bias. Conclusion ARFI is a promising tool for the differentiation of benign and malignant LNs with high sensitivity and specificity. PMID:27855188

Dental age estimation employing CBCT scans enhanced with Mimics software: Comparison of two different approaches using pulp/tooth volumetric analysis.

PubMed

Asif, Muhammad Khan; Nambiar, Phrabhakaran; Mani, Shani Ann; Ibrahim, Norliza Binti; Khan, Iqra Muhammad; Sukumaran, Prema

2018-02-01

The methods of dental age estimation and identification of unknown deceased individuals are evolving with the introduction of advanced innovative imaging technologies in forensic investigations. However, assessing small structures like root canal volumes can be challenging in spite of using highly advanced technology. The aim of the study was to investigate which amongst the two methods of volumetric analysis of maxillary central incisors displayed higher strength of correlation between chronological age and pulp/tooth volume ratio for Malaysian adults. Volumetric analysis of pulp cavity/tooth ratio was employed in Method 1 and pulp chamber/crown ratio (up to cemento-enamel junction) was analysed in Method 2. The images were acquired employing CBCT scans and enhanced by manipulating them with the Mimics software. These scans belonged to 56 males and 54 females and their ages ranged from 16 to 65 years. Pearson correlation and regression analysis indicated that both methods used for volumetric measurements had strong correlation between chronological age and pulp/tooth volume ratio. However, Method 2 gave higher coefficient of determination value (R2 = 0.78) when compared to Method 1 (R2 = 0.64). Moreover, manipulation in Method 2 was less time consuming and revealed higher inter-examiner reliability (0.982) as no manual intervention during 'multiple slice editing phase' of the software was required. In conclusion, this study showed that volumetric analysis of pulp cavity/tooth ratio is a valuable gender independent technique and the Method 2 regression equation should be recommended for dental age estimation. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Research Trends in Evidence-Based Medicine: A Joinpoint Regression Analysis of More than 50 Years of Publication Data

PubMed Central

Hung, Bui The; Long, Nguyen Phuoc; Hung, Le Phi; Luan, Nguyen Thien; Anh, Nguyen Hoang; Nghi, Tran Diem; Van Hieu, Mai; Trang, Nguyen Thi Huyen; Rafidinarivo, Herizo Fabien; Anh, Nguyen Ky; Hawkes, David; Huy, Nguyen Tien; Hirayama, Kenji

2015-01-01

Background Evidence-based medicine (EBM) has developed as the dominant paradigm of assessment of evidence that is used in clinical practice. Since its development, EBM has been applied to integrate the best available research into diagnosis and treatment with the purpose of improving patient care. In the EBM era, a hierarchy of evidence has been proposed, including various types of research methods, such as meta-analysis (MA), systematic review (SRV), randomized controlled trial (RCT), case report (CR), practice guideline (PGL), and so on. Although there are numerous studies examining the impact and importance of specific cases of EBM in clinical practice, there is a lack of research quantitatively measuring publication trends in the growth and development of EBM. Therefore, a bibliometric analysis was constructed to determine the scientific productivity of EBM research over decades. Methods NCBI PubMed database was used to search, retrieve and classify publications according to research method and year of publication. Joinpoint regression analysis was undertaken to analyze trends in research productivity and the prevalence of individual research methods. Findings Analysis indicates that MA and SRV, which are classified as the highest ranking of evidence in the EBM, accounted for a relatively small but auspicious number of publications. For most research methods, the annual percent change (APC) indicates a consistent increase in publication frequency. MA, SRV and RCT show the highest rate of publication growth in the past twenty years. Only controlled clinical trials (CCT) shows a non-significant reduction in publications over the past ten years. Conclusions Higher quality research methods, such as MA, SRV and RCT, are showing continuous publication growth, which suggests an acknowledgement of the value of these methods. This study provides the first quantitative assessment of research method publication trends in EBM. PMID:25849641

Effect of sour tea (Hibiscus sabdariffa L.) on arterial hypertension: a systematic review and meta-analysis of randomized controlled trials.

PubMed

Serban, Corina; Sahebkar, Amirhossein; Ursoniu, Sorin; Andrica, Florina; Banach, Maciej

2015-06-01

Hibiscus sabdariffa L. is a tropical wild plant rich in organic acids, polyphenols, anthocyanins, polysaccharides, and volatile constituents that are beneficial for the cardiovascular system. Hibiscus sabdariffa beverages are commonly consumed to treat arterial hypertension, yet the evidence from randomized controlled trials (RCTs) has not been fully conclusive. Therefore, we aimed to assess the potential antihypertensive effects of H. sabdariffa through systematic review of literature and meta-analysis of available RCTs. The search included PUBMED, Cochrane Library, Scopus, and EMBASE (up to July 2014) to identify RCTs investigating the efficacy of H. sabdariffa supplementation on SBP and DBP values. Two independent reviewers extracted data on the study characteristics, methods, and outcomes. Quantitative data synthesis and meta-regression were performed using a fixed-effect model, and sensitivity analysis using leave-one-out method. Five RCTs (comprising seven treatment arms) were selected for the meta-analysis. In total, 390 participants were randomized, of whom 225 were allocated to the H. sabdariffa supplementation group and 165 to the control group in the selected studies. Fixed-effect meta-regression indicated a significant effect of H. sabdariffa supplementation in lowering both SBP (weighed mean difference -7.58 mmHg, 95% confidence interval -9.69 to -5.46, P < 0.00001) and DBP (weighed mean difference -3.53 mmHg, 95% confidence interval -5.16 to -1.89, P < 0.0001). These effects were inversely associated with baseline BP values, and were robust in sensitivity analyses. This meta-analysis of RCTs showed a significant effect of H. sabdariffa in lowering both SBP and DBP. Further well designed trials are necessary to validate these results.

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

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,…

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

ERIC Educational Resources Information Center

Beckstead, Jason W.

2012-01-01

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

Logistic Regression: Concept and Application

ERIC Educational Resources Information Center

Cokluk, Omay

2010-01-01

The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

Nationwide forestry applications program. Ten-Ecosystem Study (TES) site 6, Fort Yukon, Alaska

NASA Technical Reports Server (NTRS)

Ward, J. F. (Principal Investigator); Edwards, B. F.

1978-01-01

The author has identified the following significant results. Analysis of the processing results has led to the following conclusions: (1) LANDSAT imagery was a reliable resource for the stratification of level 2 forest features (softwood, hardwood, tundra, and water). These features can be classified with an accuracy of 72.4 percent + or - 5.9 percent at the 90 percent confidence level. (2) Training fields selected for signature development from only 10 percent of the area did not adequately and efficiently cover the class variability for the entire area. (3) Derived regression transformations were ineffective in recovering the loss of level 1 forest proportions and level 2 softwood and hardwood proportions.

Sociodemographic factors associated with pregnant women's level of knowledge about oral health

PubMed Central

Barbieri, Wander; Peres, Stela Verzinhasse; Pereira, Carla de Britto; Peres, João; de Sousa, Maria da Luz Rosário; Cortellazzi, Karine Laura

2018-01-01

ABSTRACT Objective To evaluate knowledge on oral health and associated sociodemographic factors in pregnant women. Methods A cross-sectional study with a sample of 195 pregnant women seen at the Primary Care Unit Paraisópolis I, in São Paulo (SP), Brazil. For statistical analysis, χ2 or Fisher's exact test and multiple logistic regression were used. A significance level of 5% was used in all analyses. Results Schooling level equal to or greater than 8 years and having one or two children were associated with an adequate knowledge about oral health. Conclusion Oral health promotion strategies during prenatal care should take into account sociodemographic aspects. PMID:29694612

The Influencing Factor Analysis on the Performance Evaluation of Assembly Line Balancing Problem Level 1 (SALBP-1) Based on ANOVA Method

NASA Astrophysics Data System (ADS)

Chen, Jie; Hu, Jiangnan

2017-06-01

Industry 4.0 and lean production has become the focus of manufacturing. A current issue is to analyse the performance of the assembly line balancing. This study focus on distinguishing the factors influencing the assembly line balancing. The one-way ANOVA method is applied to explore the significant degree of distinguished factors. And regression model is built to find key points. The maximal task time (tmax ), the quantity of tasks (n), and degree of convergence of precedence graph (conv) are critical for the performance of assembly line balancing. The conclusion will do a favor to the lean production in the manufacturing.

Gardening/yard work and depressive symptoms in African Americans

PubMed Central

Torres, Elisa R.; Sampselle, Carolyn M.; Ronis, David L.; Neighbors, Harold W.; Gretebeck, Kimberlee A.

2015-01-01

Background The purpose of this study was to examine the frequency of gardening/yard work in relation to depressive symptoms in African-Americans while controlling for biological and social factors. Methods A secondary analysis was performed on the National Survey of American Life (n=2,903) using logistic regression for complex samples. Gardening/yard work was measured by self-reported frequency. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression scale. Results Biological and social factors, not gardening/yard work, were associated with depressive symptoms. Conclusions Biological and social factors may need to be addressed before the association between gardening/yard work and depressive symptoms can be determined. PMID:26992864

Urban environmental health applications of remote sensing, summary report

NASA Technical Reports Server (NTRS)

Rush, M.; Goldstein, J.; Hsi, B. P.; Olsen, C. B.

1975-01-01

Health and its association with the physical environment was studied based on the hypothesis that there is a relationship between the man-made physical environment and health status of a population. The statistical technique of regression analysis was employed to show the degree of association and aspects of physical environment which accounted for the greater variation in health status. Mortality, venereal disease, tuberculosis, hepatitis, meningitis, shigella/salmonella, hypertension and cardiac arrest/myocardial infarction were examined. The statistical techniques were used to measure association and variation, not necessarily cause and effect. Conclusions drawn show that the association still exists in the decade of the 1970's and that it can be successfully monitored with the methodology of remote sensing.

Applying Regression Analysis to Problems in Institutional Research.

ERIC Educational Resources Information Center

Bohannon, Tom R.

1988-01-01

Regression analysis is one of the most frequently used statistical techniques in institutional research. Principles of least squares, model building, residual analysis, influence statistics, and multi-collinearity are described and illustrated. (Author/MSE)

Extended opening hours and patient experience of general practice in England: multilevel regression analysis of a national patient survey

PubMed Central

Cowling, Thomas E; Harris, Matthew; Majeed, Azeem

2017-01-01

Background The UK government plans to extend the opening hours of general practices in England. The ‘extended hours access scheme’ pays practices for providing appointments outside core times (08:00 to 18.30, Monday to Friday) for at least 30 min per 1000 registered patients each week. Objective To determine the association between extended hours access scheme participation and patient experience. Methods Retrospective analysis of a national cross-sectional survey completed by questionnaire (General Practice Patient Survey 2013–2014); 903 357 survey respondents aged ≥18 years old and registered to 8005 general practices formed the study population. Outcome measures were satisfaction with opening hours, experience of making an appointment and overall experience (on five-level interval scales from 0 to 100). Mean differences between scheme participation groups were estimated using multilevel random-effects regression, propensity score matching and instrumental variable analysis. Results Most patients were very (37.2%) or fairly satisfied (42.7%) with the opening hours of their general practices; results were similar for experience of making an appointment and overall experience. Most general practices participated in the extended hours access scheme (73.9%). Mean differences in outcome measures between scheme participants and non-participants were positive but small across estimation methods (mean differences ≤1.79). For example, scheme participation was associated with a 1.25 (95% CI 0.96 to 1.55) increase in satisfaction with opening hours using multilevel regression; this association was slightly greater when patients could not take time off work to see a general practitioner (2.08, 95% CI 1.53 to 2.63). Conclusions Participation in the extended hours access scheme has a limited association with three patient experience measures. This questions expected impacts of current plans to extend opening hours on patient experience. PMID:27343274

Effect of ionized serum calcium on outcomes in acute kidney injury needing renal replacement therapy: Secondary analysis of the Acute Renal Failure Trial Network Study

PubMed Central

Afshinnia, Farsad; Belanger, Karen; Palevsky, Paul M.; Young, Eric W.

2014-01-01

Background Hypocalcemia is very common in critically ill patients. While the effect of ionized calcium (iCa) on outcome is not well understood, manipulation of iCa in critically ill patients is a common practice. We analyzed all-cause mortality and several secondary outcomes in patients with acute kidney injury (AKI) by categories of serum iCa among participants in the Acute Renal Failure Trial Network (ATN) Study. Methods This is a post hoc secondary analysis of the ATN Study which was not preplanned in the original trial. Risk of mortality and renal recovery by categories of iCa were compared using multiple fixed and adjusted time-varying Cox regression models. Multiple linear regression models were used to explore the impact of baseline iCa on days free from ICU and hospital. Results A total of 685 patients were included in the analysis. Mean age was 60 (SD=15) years. There were 502 male patients (73.3%). Sixty-day all-cause mortality was 57.0%, 54.8%, and 54.4%, in patients with an iCa <1, 1–1.14, and ≥1.15 mmol/L, respectively (P=0.87). Mean of days free from ICU or hospital in all patients and the 28-day renal recovery in survivors to day 28 were not significantly different by categories of iCa. The hazard for death in a fully adjusted time-varying Cox regression survival model was 1.7 (95% CI: 1.3–2.4) comparing iCa <1 to iCa ≥1.15 mmol/L. No outcome was different for levels of iCa >1 mmol/L. Conclusion Severe hypocalcemia with iCa <1 mmol/L independently predicted mortality in patients with AKI needing renal replacement therapy. PMID:23992422

A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training-induced gains in muscle mass and strength in healthy adults

PubMed Central

Morton, Robert W; Murphy, Kevin T; McKellar, Sean R; Schoenfeld, Brad J; Henselmans, Menno; Helms, Eric; Aragon, Alan A; Devries, Michaela C; Banfield, Laura; Krieger, James W

2018-01-01

Objective We performed a systematic review, meta-analysis and meta-regression to determine if dietary protein supplementation augments resistance exercise training (RET)-induced gains in muscle mass and strength. Data sources A systematic search of Medline, Embase, CINAHL and SportDiscus. Eligibility criteria Only randomised controlled trials with RET ≥6 weeks in duration and dietary protein supplementation. Design Random-effects meta-analyses and meta-regressions with four a priori determined covariates. Two-phase break point analysis was used to determine the relationship between total protein intake and changes in fat-free mass (FFM). Results Data from 49 studies with 1863 participants showed that dietary protein supplementation significantly (all p<0.05) increased changes (means (95% CI)) in: strength—one-repetition-maximum (2.49 kg (0.64, 4.33)), FFM (0.30 kg (0.09, 0.52)) and muscle size—muscle fibre cross-sectional area (CSA; 310 µm2 (51, 570)) and mid-femur CSA (7.2 mm2 (0.20, 14.30)) during periods of prolonged RET. The impact of protein supplementation on gains in FFM was reduced with increasing age (−0.01 kg (−0.02,–0.00), p=0.002) and was more effective in resistance-trained individuals (0.75 kg (0.09, 1.40), p=0.03). Protein supplementation beyond total protein intakes of 1.62 g/kg/day resulted in no further RET-induced gains in FFM. Summary/conclusion Dietary protein supplementation significantly enhanced changes in muscle strength and size during prolonged RET in healthy adults. Increasing age reduces and training experience increases the efficacy of protein supplementation during RET. With protein supplementation, protein intakes at amounts greater than ~1.6 g/kg/day do not further contribute RET-induced gains in FFM. PMID:28698222

Aspirin as a potential modality for the chemoprevention of breast cancer: A dose-response meta-analysis of cohort studies from 857,831 participants

PubMed Central

Lu, Liming; Shi, Leiyu; Zeng, Jingchun; Wen, Zehuai

2017-01-01

Background Previous meta-analyses on the relationship between aspirin use and breast cancer risk have drawn inconsistent results. In addition, the threshold effect of different doses, frequencies and durations of aspirin use in preventing breast cancer have yet to be established. Results The search yielded 13 prospective cohort studies (N=857,831 participants) that reported an average of 7.6 cases/1,000 person-years of breast cancer during a follow-up period of from 4.4 to 14 years. With a random effects model, a borderline significant inverse association was observed between overall aspirin use and breast cancer risk, with a summarized RR = 0.94 (P = 0.051, 95% CI 0.87-1.01). The linear regression model was a better fit for the dose-response relationship, which displayed a potential relationship between the frequency of aspirin use and breast cancer risk (RR = 0.97, 0.95 and 0.90 for 5, 10 and 20 times/week aspirin use, respectively). It was also a better fit for the duration of aspirin use and breast cancer risk (RR = 0.86, 0.73 and 0.54 for 5, 10 and 20 years of aspirin use). Methods We searched MEDLINE, EMBASE and CENTRAL databases through early October 2016 for relevant prospective cohort studies of aspirin use and breast cancer risk. Meta-analysis of relative risks (RR) estimates associated with aspirin intake were presented by fixed or random effects models. The dose-response meta-analysis was performed by linear trend regression and restricted cubic spline regression. Conclusion Our study confirmed a dose-response relationship between aspirin use and breast cancer risk. For clinical prevention, long term (>5 years) consistent use (2-7 times/week) of aspirin appears to be more effective in achieving a protective effect against breast cancer. PMID:28418881

Long term results of a randomized trial in locally advanced rectal cancer: No benefit from adding a brachytherapy boost

PubMed Central

Appelt, Ane L; Vogelius, Ivan R; Pløen, John; Rafaelsen, Søren R; Lindebjerg, Jan; Havelund, Birgitte M; Bentzen, Søren M; Jakobsen, Anders

2014-01-01

Purpose/Objective(s) Mature data on tumor control and survival are presented from a randomized trial of the addition of a brachytherapy boost to long-course neoadjuvant chemoradiation (CRT) for locally advanced rectal cancer. Methods and Materials Between March 2005 and November 2008, 248 patients withT3-4N0-2M0 rectal cancer were prospectively randomized to either long-course preoperative CRT (50.4Gy in 28 fractions, peroral UFT and L-leucovorin) alone or the same CRT schedule plus a brachytherapy boost (10Gy in 2 fractions). Primary trial endpoint was pathological complete response (pCR) at time of surgery; secondary endpoints included overall survival (OS), progression-free survival (PFS) and freedom from locoregional failure. Results Results for the primary endpoint have previously been reported. This analysis presents survival data for the 224 patients in the Danish part of the trial. 221 patients (111 control arm, 110 brachytherapy boost arm) had data available for analysis, with a median follow-up of 5.4 years. Despite a significant increase in tumor response at the time of surgery, no differences in 5-year OS (70.6% vs 63.6%, HR=1.24, p=0.34) and PFS (63.9% vs 52.0%, HR=1.22, p=0.32) were observed. Freedom from locoregional failure at 5 years were 93.9% and 85.7% (HR=2.60, 1.00–6.73, p=0.06) in the standard and in the brachytherapy arm, respectively. There was no difference in the prevalence of stoma. Explorative analysis based on stratification for tumor regression grade and resection margin status indicated the presence of response migration. Conclusions Despite increased pathological tumor regression at the time of surgery, we observed no benefit on late outcome. Improved tumor regression does not necessarily lead to a relevant clinical benefit when the neoadjuvant treatment is followed by high-quality surgery. PMID:25015203

Association Between Bone Marrow Dosimetric Parameters and Acute Hematologic Toxicity in Anal Cancer Patients Treated With Concurrent Chemotherapy and Intensity-Modulated Radiotherapy

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

Mell, Loren K.; Schomas, David A.; Salama, Joseph K.

Purpose: To test the hypothesis that the volume of pelvic bone marrow (PBM) receiving 10 and 20 Gy or more (PBM-V{sub 10} and PBM-V{sub 20}) is associated with acute hematologic toxicity (HT) in anal cancer patients treated with concurrent chemoradiotherapy. Methods and Materials: We analyzed 48 consecutive anal cancer patients treated with concurrent chemotherapy and intensity-modulated radiation therapy. The median radiation dose to gross tumor and regional lymph nodes was 50.4 and 45 Gy, respectively. Pelvic bone marrow was defined as the region extending from the iliac crests to the ischial tuberosities, including the os coxae, lumbosacral spine, and proximalmore » femora. Endpoints included the white blood cell count (WBC), absolute neutrophil count (ANC), hemoglobin, and platelet count nadirs. Regression models with multiple independent predictors were used to test associations between dosimetric parameters and HT. Results: Twenty patients (42%) had Stage T3-4 disease; 15 patients (31%) were node positive. Overall, 27 (56%), 24 (50%), 4 (8%), and 13 (27%) experienced acute Grade 3-4 leukopenia, neutropenia, anemia, and thrombocytopenia, respectively. On multiple regression analysis, increased PBM-V{sub 5}, V{sub 10}, V{sub 15}, and V{sub 20} were significantly associated with decreased WBC and ANC nadirs, as were female gender, decreased body mass index, and increased lumbosacral bone marrow V{sub 10}, V{sub 15}, and V{sub 20} (p < 0.05 for each association). Lymph node positivity was significantly associated with a decreased WBC nadir on multiple regression analysis (p < 0.05). Conclusion: This analysis supports the hypothesis that increased low-dose radiation to PBM is associated with acute HT during chemoradiotherapy for anal cancer. Techniques to limit bone marrow irradiation may reduce HT in anal cancer patients.« less

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

PubMed Central

Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

2016-01-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis. PMID:27274911

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

PubMed

Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

2016-04-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

Combination of pharmacotherapy and psychotherapy in the treatment of chronic depression: A systematic review and meta-analysis

PubMed Central

2012-01-01

Background Chronic depression represents a substantial portion of depressive disorders and is associated with severe consequences. This review examined whether the combination of pharmacological treatments and psychotherapy is associated with higher effectiveness than pharmacotherapy alone via meta-analysis; and identified possible treatment effect modifiers via meta-regression-analysis. Methods A systematic search was conducted in the following databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, ISI Web of Science, BIOSIS, PsycINFO, and CINAHL. Primary efficacy outcome was a response to treatment; primary acceptance outcome was dropping out of the study. Only randomized controlled trials were considered. Results We identified 8 studies with a total of 9 relevant comparisons. Our analysis revealed small, but statistically not significant effects of combined therapies on outcomes directly related to depression (BR = 1.20) with substantial heterogeneity between studies (I² = 67%). Three treatment effect modifiers were identified: target disorders, the type of psychotherapy and the type of pharmacotherapy. Small but statistically significant effects of combined therapies on quality of life (SMD = 0.18) were revealed. No differences in acceptance rates and the long-term effects between combined treatments and pure pharmacological interventions were observed. Conclusions This systematic review could not provide clear evidence for the combination of pharmacotherapy and psychotherapy. However, due to the small amount of primary studies further research is needed for a conclusive decision. PMID:22694751

A Heckman selection model for the safety analysis of signalized intersections

PubMed Central

Wong, S. C.; Zhu, Feng; Pei, Xin; Huang, Helai; Liu, Youjun

2017-01-01

Purpose The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years. Results The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections. PMID:28732050

Local modelling of land consumption in Germany with RegioClust

NASA Astrophysics Data System (ADS)

Hagenauer, Julian; Helbich, Marco

2018-03-01

Germany is experiencing extensive land consumption. This necessitates local models to understand actual and future land consumption patterns. This research examined land consumption rates on a municipality level in Germany for the period 2000-10 and predicted rates for 2010-20. For this purpose, RegioClust, an algorithm that combines hierarchical clustering and regression analysis to identify regions with similar relationships between land consumption and its drivers, was developed. The performance of RegioClust was compared against geographically weighted regression (GWR). Distinct spatially varying relationships across regions emerged, whereas population density is suggested as the central driver. Although both RegioClust and GWR predicted an increase in land consumption rates for east Germany for 2010-20, only RegioClust forecasts a decline for west Germany. In conclusion, both models predict for 2010-20 a rate of land consumption that suggests that the policy objective of reducing land consumption to 30 ha per day in 2020 will not be achieved. Policymakers are advised to take action and revise existing planning strategies to counteract this development.

KRAS polymorphisms are associated with survival of CRC in Chinese population.

PubMed

Dai, Qiong; Wei, Hui Lian; Huang, Juan; Zhou, Tie Jun; Chai, Li; Yang, Zhi-Hui

2016-04-01

rs12245, rs12587, rs9266, rs1137282, rs61764370, and rs712 of KRAS oncogene are characterized in the 3'UTR. The study highlights the important role of these polymorphisms playing in the susceptibility, oxaliplatin-based chemotherapy sensitivity, progression, and prognosis of CRC. Improved multiplex ligation detection reaction (iMLDR) technique is used for genotyping. An unconditional logistic regression model was used to estimate the association of certain polymorphism and CRC risk. The Kaplan-Meier method, log-rank test, and Cox regression model were used to evaluate the effects of polymorphisms on survival analysis. Results demonstrated that TT genotype and T allele of rs712 were associated with the increased risk of CRC; the patients with GG genotype and G allele of rs61764370 had a shorter survival and a higher risk of relapse or metastasis of CRC. Our studies supported the conclusions that rs61764370 and rs712 polymorphisms of the KRAS are functional and it may play an important role in the development of CRC and oxaliplatin-based chemotherapy efficiency and prognosis of CRC.

Association between domestic violence and women's quality of life 1

PubMed Central

de Lucena, Kerle Dayana Tavares; Vianna, Rodrigo Pinheiro de Toledo; do Nascimento, João Agnaldo; Campos, Hemílio Fernandes Coelho; Oliveira, Elaine Cristina Tôrres

2017-01-01

ABSTRACT Objective: to analyze the association between domestic violence against women and quality of life. Method: a cross-sectional population-based household survey conducted with women 18 years and older, using a stratified sample by neighborhoods. For analysis, prevalence of domestic violence and quality of life index was verified and logistic regression was used to determine associations, with a significance level of 5%. Results: 424 women who had a prevalence of domestic violence of 54.4% and a quality of life index of 61.59 participated in this study. It was verified, through logistic regression, that domestic violence is associated with women's quality of life (p=0,017). The observed variables that influence the occurrence of domestic violence were in the social relations domain (p=0,000), provision of medical treatment for women (p=0,019) and safety (p=0,006). Conclusion: the study confirmed the evidence of an association between domestic violence against women and quality of life, a situation that reaffirms the importance of constructing public policies focused on gender emancipation. PMID:28591305

Differences in the Drinking Behaviors of Chinese, Filipino, Korean, and Vietnamese College Students*

PubMed Central

Lum, Chris; Corliss, Heather L.; Mays, Vickie M.; Cochran, Susan D.; Lui, Camillia K.

2009-01-01

Objective: This study examined alcohol drinking behaviors across ethnic subgroups of Asian college students by gender, foreign-born status, and college-related living arrangements. Method: Univariate and ordinal logistic regression analyses were employed to explore male and female Asian subgroup differences in alcohol drinking behaviors. The sample included 753 male and female undergraduates between the ages of 18 and 27 years who self-identified as Chinese, Filipino, Korean, or Vietnamese and who varied in their foreign-born status. Participants completed a self-administered questionnaire on their alcohol drinking practices. Results: Ordinal regression analysis assessed risks for increased consumption and found that Korean and Filipino students reported higher levels of alcohol consumption compared with other Asian subgroups. Students living in on-campus dormitories and in off-campus apartments reported higher alcohol consumption than did those living at home. Being born in the United States was a significant predictor of higher levels of alcohol consumption for women but not for men. Conclusions: Results of this study indicate the need for campus alcohol education and prevention programs capable of responding to specific Asian subgroup needs. PMID:19515297

One-year symptom trajectories in patients with stable schizophrenia maintained on antipsychotics versus placebo: meta-analysis.

PubMed

Takeuchi, Hiroyoshi; Kantor, Navot; Sanches, Marcos; Fervaha, Gagan; Agid, Ofer; Remington, Gary

2017-09-01

Background As definitions of relapse differ substantially between studies, in investigations involving data aggregation, total scores on clinical rating scales provide a more generalisable outcome. Aims To compare total symptom trajectories for antipsychotic versus placebo treatment over a 1-year period of maintenance treatment in schizophrenia. Method Randomised controlled trials with antipsychotic and placebo treatment arms in patients with stable schizophrenia that reported Positive and Negative Syndrome Scale and Brief Psychiatric Rating Scale total scores at more than one time point were included. Meta-regression analyses were employed using a mixed model. Results A total of 11 studies involving 2826 patients were included. Meta-regression analyses revealed significant interactions between group and time ( PS <0.0001); both standardised total scores and per cent score changes remained almost unchanged in patients continuing antipsychotic treatment, whereas symptoms continuously worsened over time in those switching to placebo treatment. Conclusions When considering long-term antipsychotic treatment of schizophrenia, clinicians must balance symptomatic and functional outcomes. © The Royal College of Psychiatrists 2017.

Prehospital Helicopter Transport and Survival of Patients With Traumatic Brain Injury

PubMed Central

Mackenzie, Todd A.

2015-01-01

Objective To investigate the association of helicopter transport with survival of patients with traumatic brain injury (TBI), in comparison with ground emergency medical services (EMS). Background Helicopter utilization and its effect on the outcomes of TBI remain controversial. Methods We performed a retrospective cohort study involving patients with TBI who were registered in the National Trauma Data Bank between 2009 and 2011. Regression techniques with propensity score matching were used to investigate the association of helicopter transport with survival of patients with TBI, in comparison with ground EMS. Results During the study period, there were 209,529 patients with TBI who were registered in the National Trauma Data Bank and met the inclusion criteria. Of these patients, 35,334 were transported via helicopters and 174,195 via ground EMS. For patients transported to level I trauma centers, 2797 deaths (12%) were recorded after helicopter transport and 8161 (7.8%) after ground EMS. Multivariable logistic regression analysis demonstrated an association of helicopter transport with increased survival [OR (odds ratio), 1.95; 95% confidence interval (CI), 1.81–2.10; absolute risk reduction (ARR), 6.37%]. This persisted after propensity score matching (OR, 1.88; 95% CI, 1.74–2.03; ARR, 5.93%). For patients transported to level II trauma centers, 1282 deaths (10.6%) were recorded after helicopter transport and 5097 (7.3%) after ground EMS. Multivariable logistic regression analysis demonstrated an association of helicopter transport with increased survival (OR, 1.81; 95% CI, 1.64–2.00; ARR 5.17%). This again persisted after propensity score matching (OR, 1.73; 95% CI, 1.55–1.94; ARR, 4.69). Conclusions Helicopter transport of patients with TBI to level I and II trauma centers was associated with improved survival, in comparison with ground EMS. PMID:24743624

Relation between increased numbers of safe playing areas and decreased vehicle related child mortality rates in Japan from 1970 to 1985: a trend analysis

PubMed Central

Nakahara, S.; Nakamura, Y.; Ichikawa, M.; Wakai, S.

2004-01-01

Objectives: To examine vehicle related mortality trends of children in Japan; and to investigate how environmental modifications such as the installation of public parks and pavements are associated with these trends. Design: Poisson regression was used for trend analysis, and multiple regression modelling was used to investigate the associations between trends in environmental modifications and trends in motor vehicle related child mortality rates. Setting: Mortality data of Japan from 1970 to 1994, defined as E-code 810–23 from 1970 to 1978 and E810–25 from 1979 to 1994, were obtained from vital statistics. Multiple regression modelling was confined to the 1970–1985 data. Data concerning public parks and other facilities were obtained from the Ministry of Land, Infrastructure, and Transport. Subjects: Children aged 0–14 years old were examined in this study and divided into two groups: 0–4 and 5–14 years. Main results: An increased number of public parks was associated with decreased vehicle related mortality rates among children aged 0–4 years, but not among children aged 5–14. In contrast, there was no association between trends in pavements and mortality rates. Conclusions: An increased number of public parks might reduce vehicle related preschooler deaths, in particular those involving pedestrians. Safe play areas in residential areas might reduce the risk of vehicle related child death by lessening the journey both to and from such areas as well as reducing the number of children playing on the street. However, such measures might not be effective in reducing the vehicle related mortalities of school age children who have an expanded range of activities and walk longer distances. PMID:15547055

Peak Weight and Height Velocity to Age 36 Months and Asthma Development: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; Stigum, Hein; Håberg, Siri E.; Nafstad, Per; London, Stephanie J.; Nystad, Wenche

2015-01-01

Background The immediate postnatal period is the period of the fastest growth in the entire life span and a critical period for lung development. Therefore, it is interesting to examine the association between growth during this period and childhood respiratory disorders. Methods We examined the association of peak weight and height velocity to age 36 months with maternal report of current asthma at 36 months (n = 50,311), recurrent lower respiratory tract infections (LRTIs) by 36 months (n = 47,905) and current asthma at 7 years (n = 24,827) in the Norwegian Mother and Child Cohort Study. Peak weight and height velocity was calculated using the Reed1 model through multilevel mixed-effects linear regression. Multivariable log-binomial regression was used to calculate adjusted relative risks (adj.RR) and 95% confidence intervals (CI). We also conducted a sibling pair analysis using conditional logistic regression. Results Peak weight velocity was positively associated with current asthma at 36 months [adj.RR 1.22 (95%CI: 1.18, 1.26) per standard deviation (SD) increase], recurrent LRTIs by 36 months [adj.RR 1.14 (1.10, 1.19) per SD increase] and current asthma at 7 years [adj.RR 1.13 (95%CI: 1.07, 1.19) per SD increase]. Peak height velocity was not associated with any of the respiratory disorders. The positive association of peak weight velocity and asthma at 36 months remained in the sibling pair analysis. Conclusions Higher peak weight velocity, achieved during the immediate postnatal period, increased the risk of respiratory disorders. This might be explained by an influence on neonatal lung development, shared genetic/epigenetic mechanisms and/or environmental factors. PMID:25635872

Left atrial accessory appendages, diverticula, and left-sided septal pouch in multi-slice computed tomography. Association with atrial fibrillation and cerebrovascular accidents.

PubMed

Hołda, Mateusz K; Koziej, Mateusz; Wszołek, Karolina; Pawlik, Wiesław; Krawczyk-Ożóg, Agata; Sorysz, Danuta; Łoboda, Piotr; Kuźma, Katarzyna; Kuniewicz, Marcin; Lelakowski, Jacek; Dudek, Dariusz; Klimek-Piotrowska, Wiesława

2017-10-01

The aim of this study is to provide a morphometric description of the left-sided septal pouch (LSSP), left atrial accessory appendages, and diverticula using cardiac multi-slice computed tomography (MSCT) and to compare results between patient subgroups. Two hundred and ninety four patients (42.9% females) with a mean of 69.4±13.1years of age were investigated using MSCT. The presence of the LSSP, left atrial accessory appendages, and diverticula was evaluated. Multiple logistic regression analysis was performed to check whether the presence of additional left atrial structures is associated with increased risk of atrial fibrillation and cerebrovascular accidents. At least one additional left atrial structure was present in 51.7% of patients. A single LSSP, left atrial diverticulum, and accessory appendage were present in 35.7%, 16.0%, and 4.1% of patients, respectively. After adjusting for other risk factors via multiple logistic regression, patients with LSSP are more likely to have atrial fibrillation (OR=2.00, 95% CI=1.14-3.48, p=0.01). The presence of a LSSP was found to be associated with an increased risk of transient ischemic attack using multiple logistic regression analysis after adjustment for other risk factors (OR=3.88, 95% CI=1.10-13.69, p=0.03). In conclusion LSSPs, accessory appendages, and diverticula are highly prevalent anatomic structures within the left atrium, which could be easily identified by MSCT. The presence of LSSP is associated with increased risk for atrial fibrillation and transient ischemic attack. Copyright © 2017 Elsevier B.V. All rights reserved.

Progression-free survival as a surrogate endpoint for overall survival in glioblastoma: a literature-based meta-analysis from 91 trials

PubMed Central

Han, Kelong; Ren, Melanie; Wick, Wolfgang; Abrey, Lauren; Das, Asha; Jin, Jin; Reardon, David A.

2014-01-01

Background The aim of this study was to determine correlations between progression-free survival (PFS) and the objective response rate (ORR) with overall survival (OS) in glioblastoma and to evaluate their potential use as surrogates for OS. Method Published glioblastoma trials reporting OS and ORR and/or PFS with sufficient detail were included in correlative analyses using weighted linear regression. Results Of 274 published unique glioblastoma trials, 91 were included. PFS and OS hazard ratios were strongly correlated; R2 = 0.92 (95% confidence interval [CI], 0.71–0.99). Linear regression determined that a 10% PFS risk reduction would yield an 8.1% ± 0.8% OS risk reduction. R2 between median PFS and median OS was 0.70 (95% CI, 0.59–0.79), with a higher value in trials using Response Assessment in Neuro-Oncology (RANO; R2 = 0.96, n = 8) versus Macdonald criteria (R2 = 0.70; n = 83). No significant differences were demonstrated between temozolomide- and bevacizumab-containing regimens (P = .10) or between trials using RANO and Macdonald criteria (P = .49). The regression line slope between median PFS and OS was significantly higher in newly diagnosed versus recurrent disease (0.58 vs 0.35, P = .04). R2 for 6-month PFS with 1-year OS and median OS were 0.60 (95% CI, 0.37–0.77) and 0.64 (95% CI, 0.42–0.77), respectively. Objective response rate and OS were poorly correlated (R2 = 0.22). Conclusion In glioblastoma, PFS and OS are strongly correlated, indicating that PFS may be an appropriate surrogate for OS. Compared with OS, PFS offers earlier assessment and higher statistical power at the time of analysis. PMID:24335699

Epistasis Analysis for Estrogen Metabolic and Signaling Pathway Genes on Young Ischemic Stroke Patients

PubMed Central

Hsieh, Yi-Chen; Jeng, Jiann-Shing; Lin, Huey-Juan; Hu, Chaur-Jong; Yu, Chia-Chen; Lien, Li-Ming; Peng, Giia-Sheun; Chen, Chin-I; Tang, Sung-Chun; Chi, Nai-Fang; Tseng, Hung-Pin; Chern, Chang-Ming; Hsieh, Fang-I; Bai, Chyi-Huey; Chen, Yi-Rhu; Chiou, Hung-Yi; Jeng, Jiann-Shing; Tang, Sung-Chun; Yeh, Shin-Joe; Tsai, Li-Kai; Kong, Shin; Lien, Li-Ming; Chiu, Hou-Chang; Chen, Wei-Hung; Bai, Chyi-Huey; Huang, Tzu-Hsuan; Chi-Ieong, Lau; Wu, Ya-Ying; Yuan, Rey-Yue; Hu, Chaur-Jong; Sheu, Jau- Jiuan; Yu, Jia-Ming; Ho, Chun-Sum; Chen, Chin-I; Sung, Jia-Ying; Weng, Hsing-Yu; Han, Yu-Hsuan; Huang, Chun-Ping; Chung, Wen-Ting; Ke, Der-Shin; Lin, Huey-Juan; Chang, Chia-Yu; Yeh, Poh-Shiow; Lin, Kao-Chang; Cheng, Tain-Junn; Chou, Chih-Ho; Yang, Chun-Ming; Peng, Giia-Sheun; Lin, Jiann-Chyun; Hsu, Yaw-Don; Denq, Jong-Chyou; Lee, Jiunn-Tay; Hsu, Chang-Hung; Lin, Chun-Chieh; Yen, Che-Hung; Cheng, Chun-An; Sung, Yueh-Feng; Chen, Yuan-Liang; Lien, Ming-Tung; Chou, Chung-Hsing; Liu, Chia-Chen; Yang, Fu-Chi; Wu, Yi-Chung; Tso, An-Chen; Lai, Yu- Hua; Chiang, Chun-I; Tsai, Chia-Kuang; Liu, Meng-Ta; Lin, Ying-Che; Hsu, Yu-Chuan; Chen, Chih-Hung; Sung, Pi-Shan; Chern, Chang-Ming; Hu, Han-Hwa; Wong, Wen-Jang; Luk, Yun-On; Hsu, Li-Chi; Chung, Chih-Ping; Tseng, Hung-Pin; Liu, Chin-Hsiung; Lin, Chun-Liang; Lin, Hung-Chih; Hu, Chaur-Jong

2012-01-01

Background Endogenous estrogens play an important role in the overall cardiocirculatory system. However, there are no studies exploring the hormone metabolism and signaling pathway genes together on ischemic stroke, including sulfotransferase family 1E (SULT1E1), catechol-O-methyl-transferase (COMT), and estrogen receptor α (ESR1). Methods A case-control study was conducted on 305 young ischemic stroke subjects aged ≦ 50 years and 309 age-matched healthy controls. SULT1E1 -64G/A, COMT Val158Met, ESR1 c.454−397 T/C and c.454−351 A/G genes were genotyped and compared between cases and controls to identify single nucleotide polymorphisms associated with ischemic stroke susceptibility. Gene-gene interaction effects were analyzed using entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional multiple regression models. Results COMT Val158Met polymorphism showed a significant association with susceptibility of young ischemic stroke among females. There was a two-way interaction between SULT1E1 -64G/A and COMT Val158Met in both MDR and CART analysis. The logistic regression model also showed there was a significant interaction effect between SULT1E1 -64G/A and COMT Val158Met on ischemic stroke of the young (P for interaction = 0.0171). We further found that lower estradiol level could increase the risk of young ischemic stroke for those who carry either SULT1E1 or COMT risk genotypes, showing a significant interaction effect (P for interaction = 0.0174). Conclusions Our findings support that a significant epistasis effect exists among estrogen metabolic and signaling pathway genes and gene-environment interactions on young ischemic stroke subjects. PMID:23112845

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

Characterization of Microbiota in Children with Chronic Functional Constipation

PubMed Central

de Meij, Tim G. J.; de Groot, Evelien F. J.; Eck, Anat; Budding, Andries E.; Kneepkens, C. M. Frank; Benninga, Marc A.; van Bodegraven, Adriaan A.; Savelkoul, Paul H. M.

2016-01-01

Objectives Disruption of the intestinal microbiota is considered an etiological factor in pediatric functional constipation. Scientifically based selection of potential beneficial probiotic strains in functional constipation therapy is not feasible due to insufficient knowledge of microbiota composition in affected subjects. The aim of this study was to describe microbial composition and diversity in children with functional constipation, compared to healthy controls. Study Design Fecal samples from 76 children diagnosed with functional constipation according to the Rome III criteria (median age 8.0 years; range 4.2–17.8) were analyzed by IS-pro, a PCR-based microbiota profiling method. Outcome was compared with intestinal microbiota profiles of 61 healthy children (median 8.6 years; range 4.1–17.9). Microbiota dissimilarity was depicted by principal coordinate analysis (PCoA), diversity was calculated by Shannon diversity index. To determine the most discriminative species, cross validated logistic ridge regression was performed. Results Applying total microbiota profiles (all phyla together) or per phylum analysis, no disease-specific separation was observed by PCoA and by calculation of diversity indices. By ridge regression, however, functional constipation and controls could be discriminated with 82% accuracy. Most discriminative species were Bacteroides fragilis, Bacteroides ovatus, Bifidobacterium longum, Parabacteroides species (increased in functional constipation) and Alistipes finegoldii (decreased in functional constipation). Conclusions None of the commonly used unsupervised statistical methods allowed for microbiota-based discrimination of children with functional constipation and controls. By ridge regression, however, both groups could be discriminated with 82% accuracy. Optimization of microbiota-based interventions in constipated children warrants further characterization of microbial signatures linked to clinical subgroups of functional constipation. PMID:27760208

[Bibliometrics and visualization analysis of land use regression models in ambient air pollution research].

PubMed

Zhang, Y J; Zhou, D H; Bai, Z P; Xue, F X

2018-02-10

Objective: To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies. Methods: Relevant literature from the PubMed database before June 30, 2017 was analyzed, using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0). Keywords co-occurrence networks, cluster mapping and timeline mapping were generated, using the CiteSpace 5.1.R5 software. Relevant literature identified in three Chinese databases was also reviewed. Results: Four hundred sixty four relevant papers were retrieved from the PubMed database. The number of papers published showed an annual increase, in line with the growing trend of the index. Most papers were published in the journal of Environmental Health Perspectives . Results from the Co-word cluster analysis identified five clusters: cluster#0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution; cluster#1 referred to land use regression modeling and exposure assessment; cluster#2 was related to the epidemiology on traffic exposure; cluster#3 dealt with the exposure to ultrafine particles and related health effects; cluster#4 described the exposure to black carbon and related health effects. Data from Timeline mapping indicated that cluster#0 and#1 were the main research areas while cluster#3 and#4 were the up-coming hot areas of research. Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling. Conclusion: In order to better assess the health-related risks of ambient air pollution, and to best inform preventative public health intervention policies, application of LUR models to environmental epidemiology studies in China should be encouraged.

Hypoalbuminaemia predicts outcome in adult patients with congenital heart disease

PubMed Central

Kempny, Aleksander; Diller, Gerhard-Paul; Alonso-Gonzalez, Rafael; Uebing, Anselm; Rafiq, Isma; Li, Wei; Swan, Lorna; Hooper, James; Donovan, Jackie; Wort, Stephen J; Gatzoulis, Michael A; Dimopoulos, Konstantinos

2015-01-01

Background In patients with acquired heart failure, hypoalbuminaemia is associated with increased risk of death. The prevalence of hypoproteinaemia and hypoalbuminaemia and their relation to outcome in adult patients with congenital heart disease (ACHD) remains, however, unknown. Methods Data on patients with ACHD who underwent blood testing in our centre within the last 14 years were collected. The relation between laboratory, clinical or demographic parameters at baseline and mortality was assessed using Cox proportional hazards regression analysis. Results A total of 2886 patients with ACHD were included. Mean age was 33.3 years (23.6–44.7) and 50.1% patients were men. Median plasma albumin concentration was 41.0 g/L (38.0–44.0), whereas hypoalbuminaemia (<35 g/L) was present in 13.9% of patients. The prevalence of hypoalbuminaemia was significantly higher in patients with great complexity ACHD (18.2%) compared with patients with moderate (11.3%) or simple ACHD lesions (12.1%, p<0.001). During a median follow-up of 5.7 years (3.3–9.6), 327 (11.3%) patients died. On univariable Cox regression analysis, hypoalbuminaemia was a strong predictor of outcome (HR 3.37, 95% CI 2.67 to 4.25, p<0.0001). On multivariable Cox regression, after adjusting for age, sodium and creatinine concentration, liver dysfunction, functional class and disease complexity, hypoalbuminaemia remained a significant predictor of death. Conclusions Hypoalbuminaemia is common in patients with ACHD and is associated with a threefold increased risk of risk of death. Hypoalbuminaemia, therefore, should be included in risk-stratification algorithms as it may assist management decisions and timing of interventions in the growing ACHD population. PMID:25736048

Hazard Regression Models of Early Mortality in Trauma Centers

PubMed Central

Clark, David E; Qian, Jing; Winchell, Robert J; Betensky, Rebecca A

2013-01-01

Background Factors affecting early hospital deaths after trauma may be different from factors affecting later hospital deaths, and the distribution of short and long prehospital times may vary among hospitals. Hazard regression (HR) models may therefore be more useful than logistic regression (LR) models for analysis of trauma mortality, especially when treatment effects at different time points are of interest. Study Design We obtained data for trauma center patients from the 2008–9 National Trauma Data Bank (NTDB). Cases were included if they had complete data for prehospital times, hospital times, survival outcome, age, vital signs, and severity scores. Cases were excluded if pulseless on admission, transferred in or out, or ISS<9. Using covariates proposed for the Trauma Quality Improvement Program and an indicator for each hospital, we compared LR models predicting survival at 8 hours after injury to HR models with survival censored at 8 hours. HR models were then modified to allow time-varying hospital effects. Results 85,327 patients in 161 hospitals met inclusion criteria. Crude hazards peaked initially, then steadily declined. When hazard ratios were assumed constant in HR models, they were similar to odds ratios in LR models associating increased mortality with increased age, firearm mechanism, increased severity, more deranged physiology, and estimated hospital-specific effects. However, when hospital effects were allowed to vary by time, HR models demonstrated that hospital outliers were not the same at different times after injury. Conclusions HR models with time-varying hazard ratios reveal inconsistencies in treatment effects, data quality, and/or timing of early death among trauma centers. HR models are generally more flexible than LR models, can be adapted for censored data, and potentially offer a better tool for analysis of factors affecting early death after injury. PMID:23036828

Willingness to Accept HIV Pre-Exposure Prophylaxis among Chinese Men Who Have Sex with Men

PubMed Central

Li, Shuming; Li, Dongliang; Zhang, Lifen; Fan, Wensheng; Yang, Xueying; Yu, Mingrun; Xiao, Dong; Yan, Li; Zhang, Zheng; Shi, Wei; Luo, Fengji; Ruan, Yuhua; Jin, Qi

2012-01-01

Objective We investigated the awareness and acceptability of pre-exposure prophylaxis (PrEP) among men who have sex with men (MSM) and potential predicting factors. Methods This study was conducted among MSM in Beijing, China. Study participants, randomly selected from an MSM cohort, completed a structured questionnaire, and provided their blood samples to test for HIV infection and syphilis. Univariate logistic regression analyses were performed to evaluate the factors associated with willingness to accept (WTA) PrEP. Factors independently associated with willingness to accept were identified by entering variables into stepwise logistic regression analysis. Results A total of 152 MSM completed the survey; 11.2% had ever heard of PrEP and 67.8% were willing to accept it. Univariate analysis showed that age, years of education, consistent condom use in the past 6 months, heterosexual behavior in the past 6 months, having ever heard of PrEP and the side effects of antiretroviral drugs, and worry about antiretroviral drugs cost were significantly associated with willingness to accept PrEP. In the multivariate logistic regression model, only consistent condom use in the past 6 months (odds ratio [OR]: 0.31; 95% confidence interval [CI]: 0.13–0.70) and having ever heard of the side effects of antiretroviral drugs (OR: 0.30; 95% CI: 0.14–0.67) were independently associated with willingness to accept PrEP. Conclusions The awareness of PrEP in the MSM population was low. Sexual behavioral characteristics and knowledge about ART drugs may have effects on willingness to accept PrEP. Comprehensive prevention strategies should be recommended in the MSM community. PMID:22479320

Ethnicity and acculturation: do they predict weight status in a longitudinal study among Asian, Hispanic, and non-Hispanic White early adolescent females?

PubMed Central

Fialkowski, Marie K; Ettienne, Reynolette; Shvetsov, Yurii B; Rivera, Rebecca L; Van Loan, Marta D; Savaiano, Dennis A; Boushey, Carol J

2015-01-01

Background The prevalence of overweight and obesity among adolescents has increased over the past decade. Prevalence rates are disparate among certain racial and ethnic groups. This study sought to longitudinally examine the relationship between overweight status (≥85th percentile according to the Centers for Disease Control and Prevention growth charts) and ethnic group, as well as acculturation (generation and language spoken in the home) in a sample of adolescent females. Methods Asian (n=160), Hispanic (n=217), and non-Hispanic White (n=304) early adolescent girls participating in the multistate calcium intervention study with complete information on weight, ethnicity, and acculturation were included. Multiple methods of assessing longitudinal relationships (binary logistic regression model, linear regression model, Cox proportional-hazards regression analysis, and Kaplan–Meier survival analysis) were used to examine the relationship. Results The total proportion of girls overweight at baseline was 36%. When examining by ethnic group, the proportion varied with Hispanic girls having the highest percentage (46%) in comparison to their Asian (23%) and Non-Hispanic White (35%) counterparts. Although the total proportion of overweight was 36% at 18 months, the variation across the ethnic groups remained with the proportion of Hispanic girls becoming overweight (55%) being greater than their Asian (18%) and non-Hispanic White (34%) counterparts. However, regardless of the statistical approach used, there were no significant associations between overweight status and acculturation over time. Conclusion These unexpected results warrant further exploration into factors associated with overweight, especially among Hispanic girls, and further investigation of acculturation’s role is warranted. Identifying these risk factors will be important for developing targeted obesity prevention initiatives. PMID:25624775

Peripapillary Choroidal Thickness Variation With Age and Race in Normal Eyes

PubMed Central

Rhodes, Lindsay A.; Huisingh, Carrie; Johnstone, John; Fazio, Massimo A.; Smith, Brandon; Wang, Lan; Clark, Mark; Downs, J. Crawford; Owsley, Cynthia; Girard, Michael J. A.; Mari, Jean Martial; Girkin, Christopher A.

2015-01-01

Purpose. This study examined the association between peripapillary choroidal thickness (PCT) with age and race in a group of African descent (AD) and European descent (ED) subjects with normal eyes. Methods. Optic nerve head images from enhanced depth imaging spectral-domain optical coherence tomography of 166 normal eyes from 84 subjects of AD and ED were manually delineated to identify the principal surfaces of Bruch's membrane (BM), Bruch's membrane opening (BMO), and anterior sclera (AS). Peripapillary choroidal thickness was measured between BM and AS at increasing distance away from BMO. The mean PCT was compared between AD and ED subjects and generalized estimating equation (GEE) regression analysis was used to examine the association between race and PCT overall, in each quadrant, and by distance from BMO. Models were adjusted for age, BMO area, and axial length in the regression analysis. Results. Overall, the mean PCT increased from 63.9 μm ± 18.1 at 0 to 250 μm to 170.3 μm ± 56.7 at 1500 to 2000 μm from BMO. Individuals of AD had a greater mean PCT than those of ED at all distances from BMO (P < 0.05 at each distance) and in each quadrant (P < 0.05 in each quadrant). Results from multivariate regression indicate that ED subjects had significantly lower PCT compared to AD overall and in all quadrants and distances from BMO. Increasing age was also significantly associated with a lower PCT in both ED and AD participants. Conclusions. Peripapillary choroidal thickness varies with race and age, as individuals of AD have a thicker peripapillary choroid than those of ED. (ClinicalTrials.gov number, NCT00221923.) PMID:25711640

Prognostic Factors for Neurologic Outcome in Patients with Carotid Artery Stenting

PubMed Central

Hung, Chi-Sheng; Lin, Mao-Shin; Chen, Ying-Hsien; Huang, Ching-Chang; Li, Hung-Yuan; Kao, Hsien-Li

2016-01-01

Background Carotid artery stenting (CAS) is a valid treatment for patients with carotid artery stenosis. The long-term outcome and prognostic factors in Asian population after CAS are not clear. This study aimed to identify the prognostic factors among Asian patients who have undergone CAS. Methods We retrospectively analyzed 246 patients with CAS. Annual carotid duplex ultrasound was used to identify restenosis. Peri-procedural complications, restenosis, neurologic outcomes, and mortality were recorded. Cox regression analyses were used to identify prognostic factors. Results The mean follow-up time was 49.2 months. Procedural success was achieved in 237 patients (98.3%), and protection devices were used in 208 patients (84.5%). Within 30 days of CAS, 13 (4.3% per procedure) peri-procedural complications occurred. During the follow-up period, 24 (9.7%) patients developed restenosis, and 37 (15.0%) developed ischemic strokes. In a multiple logistic regression analysis, head and neck radiotherapy [hazard ratio (HR) = 9.9, 95% confidence interval (CI), 3.38-29.1, p < .001], stent diameter (HR = 0.72, 95% CI, 0.58-0.89, p = .003), and predilatation (HR = 3.08 95% CI, 1.21-7.81, p = .018) were independent predictors for restenosis. In Cox regression analysis, hypercholesterolemia (HR = 0.25, 95% CI, 0.07-0.94, p = .04), head and neck radiotherapy (HR = 6.2, 95% CI, 1.8-21.3, p = .004), and restenosis (HR = 3.6, 95% CI, 1.1-11.18, p = .04) were predictors for recurrent ipsilateral ischemic stroke. Conclusions CAS provides reliable long-term results in Asian patients with carotid stenosis. Restenosis is associated with an increased rate of recurrent stroke and should be monitored carefully following CAS. PMID:27122951

Genital Warts and Vulvar Intraepithelial Neoplasia: Natural History and Effects of Treatment and Human Immunodeficiency Virus Infection

PubMed Central

Massad, L. Stewart; Xie, Xianhong; Darragh, Teresa; Minkoff, Howard; Levine, Alexandra M.; Watts, D. Heather; Wright, Rodney L.; D’Souza, Gypsyamber; Colie, Christine; Strickler, Howard D.

2011-01-01

Objective To describe the natural history of genital warts and vulvar intraepithelial neoplasia (VIN) in women with human immunodeficiency virus (HIV). Methods A cohort of 2,791 HIV infected and 953 uninfected women followed for up to 13 years had genital examinations at 6-month intervals, with biopsy for lesions suspicious for VIN. Results The prevalence of warts was 4.4% (5.3% for HIV seropositive women and 1.9% for seronegative women, P < 0.0001). The cumulative incidence of warts was 33% (95% C.I. 30, 36%) in HIV seropositive and 9% (95% C.I. 6, 12%) in seronegative women (P < 0.0001). In multivariable analysis, lower CD4 lymphocyte count, younger age, and current smoking were strongly associated with risk for incident warts. Among 501 HIV seropositive and 43 seronegative women, warts regressed in 410 (82%) seropositive and 41 (95%) seronegative women (P = 0.02), most in the first year after diagnosis. In multivariable analysis, regression was negatively associated with HIV status and lower CD4 count as well as older age. Incident VIN of any grade occurred more frequently among HIV seropositive than seronegative women: 0.42 (0.33 – 0.53) vs 0.07 (0.02 – 0.18)/100 person-years (P < 0.0001). VIN2+ was found in 58 women (55 with and 3 without HIV, P < 0.001). Two women with HIV developed stage IB squamous cell vulvar cancers. Conclusion While genital warts and VIN are more common among HIV seropositive than seronegative women, wart regression is common even in women with HIV, and cancers are infrequent. PMID:21934446

New diagnostic index for sarcopenia in patients with cardiovascular diseases

PubMed Central

Kai, Hisashi; Shibata, Rei; Niiyama, Hiroshi; Nishiyama, Yasuhiro; Murohara, Toyoaki; Yoshida, Noriko; Katoh, Atsushi; Ikeda, Hisao

2017-01-01

Background Sarcopenia is an aging and disease-related syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, with the risk of frailty and poor quality of life. Sarcopenia is diagnosed by a decrease in skeletal muscle index (SMI) and reduction of either handgrip strength or gait speed. However, measurement of SMI is difficult for general physicians because it requires special equipment for bioelectrical impedance assay or dual-energy X-ray absorptiometry. The purpose of this study was, therefore, to explore a novel, simple diagnostic method of sarcopenia evaluation in patients with cardiovascular diseases (CVD). Methods We retrospectively investigated 132 inpatients with CVD (age: 72±12 years, age range: 27–93 years, males: 61%) Binomial logistic regression and correlation analyses were used to assess the associations of sarcopenia with simple physical data and biomarkers, including muscle-related inflammation makers and nutritional markers. Results Sarcopenia was present in 29.5% of the study population. Serum concentrations of adiponectin and sialic acid were significantly higher in sarcopenic than non-sarcopenic CVD patients. Stepwise multivariate binomial logistic regression analysis revealed that adiponectin, sialic acid, sex, age, and body mass index were independent factors for sarcopenia detection. Sarcopenia index, obtained from the diagnostic regression formula for sarcopenia detection including the five independent factors, indicated a high accuracy in ROC curve analysis (sensitivity 94.9%, specificity 69.9%) and the cutoff value for sarcopenia detection was -1.6134. Sarcopenia index had a significant correlation with the conventional diagnostic parameters of sarcopenia. Conclusions Our new sarcopenia index using simple parameters would be useful for diagnosing sarcopenia in CVD patients. PMID:28542531

The intermediate endpoint effect in logistic and probit regression

PubMed Central

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

2010-01-01

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

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

Interpreting Bivariate Regression Coefficients: Going beyond the Average

ERIC Educational Resources Information Center

Halcoussis, Dennis; Phillips, G. Michael

2010-01-01

Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

Regression Commonality Analysis: A Technique for Quantitative Theory Building

ERIC Educational Resources Information Center

Nimon, Kim; Reio, Thomas G., Jr.

2011-01-01

When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

Regression of coronary atherosclerosis with infusions of the high-density lipoprotein mimetic CER-001 in patients with more extensive plaque burden

PubMed Central

Kataoka, Yu; Andrews, Jordan; Duong, MyNgan; Nguyen, Tracy; Schwarz, Nisha; Fendler, Jessica; Puri, Rishi; Butters, Julie; Keyserling, Constance; Paolini, John F.; Dasseux, Jean-Louis

2017-01-01

Background CER-001 is an engineered pre-beta high-density lipoprotein (HDL) mimetic, which rapidly mobilizes cholesterol. Infusion of CER-001 3 mg/kg exhibited a potentially favorable effect on plaque burden in the CHI-SQUARE (Can HDL Infusions Significantly Quicken Atherosclerosis Regression) study. Since baseline atheroma burden has been shown as a determinant for the efficacy of HDL infusions, the degree of baseline atheroma burden might influence the effect of CER-001. Methods CHI-SQUARE compared the effect of 6 weekly infusions of CER-001 (3, 6 and 12 mg/kg) vs. placebo on coronary atherosclerosis in 369 patients with acute coronary syndrome (ACS) using serial intravascular ultrasound (IVUS). Baseline percent atheroma volume (B-PAV) cutoff associated with atheroma regression following CER-001 infusions was determined by receiver-operating characteristics curve analysis. 369 subjects were stratified according to the cutoff. The effect of CER-001 at different doses was compared to placebo in each group. Results A B-PAV ≥30% was the optimal cutoff associated with PAV regression following CER-001 infusions. CER-001 induced PAV regression in patients with B-PAV ≥30% but not in those with B-PAV <30% (−0.45%±2.65% vs. +0.34%±1.69%, P=0.01). Compared to placebo, the greatest PAV regression was observed with CER-001 3mg/kg in patients with B-PAV ≥30% (−0.96%±0.34% vs. −0.25%±0.31%, P=0.01), whereas there were no differences between placebo (+0.09%±0.36%) versus CER-001 in patients with B-PAV <30% (3 mg/kg; +0.41%±0.32%, P=0.39; 6 mg/kg; +0.27%±0.36%, P=0.76; 12 mg/kg; +0.32%±0.37%, P=0.97). Conclusions Infusions of CER-001 3 mg/kg induced the greatest atheroma regression in ACS patients with higher B-PAV. These findings identify ACS patients with more extensive disease as most likely to benefit from HDL mimetic therapy. PMID:28567351

Approach to addressing missing data for electronic medical records and pharmacy claims data research.

PubMed

Bounthavong, Mark; Watanabe, Jonathan H; Sullivan, Kevin M

2015-04-01

The complete capture of all values for each variable of interest in pharmacy research studies remains aspirational. The absence of these possibly influential values is a common problem for pharmacist investigators. Failure to account for missing data may translate to biased study findings and conclusions. Our goal in this analysis was to apply validated statistical methods for missing data to a previously analyzed data set and compare results when missing data methods were implemented versus standard analytics that ignore missing data effects. Using data from a retrospective cohort study, the statistical method of multiple imputation was used to provide regression-based estimates of the missing values to improve available data usable for study outcomes measurement. These findings were then contrasted with a complete-case analysis that restricted estimation to subjects in the cohort that had no missing values. Odds ratios were compared to assess differences in findings of the analyses. A nonadjusted regression analysis ("crude analysis") was also performed as a reference for potential bias. Veterans Integrated Systems Network that includes VA facilities in the Southern California and Nevada regions. New statin users between November 30, 2006, and December 2, 2007, with a diagnosis of dyslipidemia. We compared the odds ratios (ORs) and 95% confidence intervals (CIs) for the crude, complete-case, and multiple imputation analyses for the end points of a 25% or greater reduction in atherogenic lipids. Data were missing for 21.5% of identified patients (1665 subjects of 7739). Regression model results were similar for the crude, complete-case, and multiple imputation analyses with overlap of 95% confidence limits at each end point. The crude, complete-case, and multiple imputation ORs (95% CIs) for a 25% or greater reduction in low-density lipoprotein cholesterol were 3.5 (95% CI 3.1-3.9), 4.3 (95% CI 3.8-4.9), and 4.1 (95% CI 3.7-4.6), respectively. The crude, complete-case, and multiple imputation ORs (95% CIs) for a 25% or greater reduction in non-high-density lipoprotein cholesterol were 3.5 (95% CI 3.1-3.9), 4.5 (95% CI 4.0-5.2), and 4.4 (95% CI 3.9-4.9), respectively. The crude, complete-case, and multiple imputation ORs (95% CIs) for 25% or greater reduction in TGs were 3.1 (95% CI 2.8-3.6), 4.0 (95% CI 3.5-4.6), and 4.1 (95% CI 3.6-4.6), respectively. The use of the multiple imputation method to account for missing data did not alter conclusions based on a complete-case analysis. Given the frequency of missing data in research using electronic health records and pharmacy claims data, multiple imputation may play an important role in the validation of study findings. © 2015 Pharmacotherapy Publications, Inc.

Regression Model Optimization for the Analysis of Experimental Data

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2009-01-01

A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.

A new approach to correct the QT interval for changes in heart rate using a nonparametric regression model in beagle dogs.

PubMed

Watanabe, Hiroyuki; Miyazaki, Hiroyasu

2006-01-01

Over- and/or under-correction of QT intervals for changes in heart rate may lead to misleading conclusions and/or masking the potential of a drug to prolong the QT interval. This study examines a nonparametric regression model (Loess Smoother) to adjust the QT interval for differences in heart rate, with an improved fitness over a wide range of heart rates. 240 sets of (QT, RR) observations collected from each of 8 conscious and non-treated beagle dogs were used as the materials for investigation. The fitness of the nonparametric regression model to the QT-RR relationship was compared with four models (individual linear regression, common linear regression, and Bazett's and Fridericia's correlation models) with reference to Akaike's Information Criterion (AIC). Residuals were visually assessed. The bias-corrected AIC of the nonparametric regression model was the best of the models examined in this study. Although the parametric models did not fit, the nonparametric regression model improved the fitting at both fast and slow heart rates. The nonparametric regression model is the more flexible method compared with the parametric method. The mathematical fit for linear regression models was unsatisfactory at both fast and slow heart rates, while the nonparametric regression model showed significant improvement at all heart rates in beagle dogs.

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

PubMed

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules

PubMed Central

Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules’ 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively. PMID:29228030

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules.

PubMed

Pang, Tiantian; Huang, Leidan; Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Gong, Xuehao; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules' 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively.

Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina

PubMed Central

Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

2015-01-01

OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation. PMID:26270011

Bagging Voronoi classifiers for clustering spatial functional data

NASA Astrophysics Data System (ADS)

Secchi, Piercesare; Vantini, Simone; Vitelli, Valeria

2013-06-01

We propose a bagging strategy based on random Voronoi tessellations for the exploration of geo-referenced functional data, suitable for different purposes (e.g., classification, regression, dimensional reduction, …). Urged by an application to environmental data contained in the Surface Solar Energy database, we focus in particular on the problem of clustering functional data indexed by the sites of a spatial finite lattice. We thus illustrate our strategy by implementing a specific algorithm whose rationale is to (i) replace the original data set with a reduced one, composed by local representatives of neighborhoods covering the entire investigated area; (ii) analyze the local representatives; (iii) repeat the previous analysis many times for different reduced data sets associated to randomly generated different sets of neighborhoods, thus obtaining many different weak formulations of the analysis; (iv) finally, bag together the weak analyses to obtain a conclusive strong analysis. Through an extensive simulation study, we show that this new procedure - which does not require an explicit model for spatial dependence - is statistically and computationally efficient.

Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina.

PubMed

Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

2015-01-01

OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation.

The Relationship Between Serum Endocan Levels With the Presence of Slow Coronary Flow: A Cross-Sectional Study.

PubMed

Kundi, Harun; Gok, Murat; Kiziltunc, Emrullah; Topcuoglu, Canan; Cetin, Mustafa; Cicekcioglu, Hulya; Ugurlu, Burcu; Ulusoy, Feridun Vasfi

2017-07-01

The aim of this study was to investigate the relationship between endocan levels with the presence of slow coronary flow (SCF). In this cross-sectional study, a total of 88 patients, who admitted to our hospital, were included in this study. Of these, 53 patients with SCF and 35 patients with normal coronary flow were included in the final analysis. Coronary flow rates of all patients were determined by the Timi Frame Count (TFC) method. In correlation analysis, endocan levels revealed a significantly positive correlation with high sensitive C-reactive protein and corrected TFC. In multivariate logistic regression analysis, the endocan levels were found as independently associated with the presence of SCF. Finally, using a cutoff level of 2.3, endocan level predicted the presence of SCF with a sensitivity of 77.2% and specificity of 75.2%. In conclusion, our study showed that higher endocan levels were significantly and independently related to the presence of SCF.

Kinetics of corneal thermal shrinkage

NASA Astrophysics Data System (ADS)

Borja, David; Manns, Fabrice; Lee, William E.; Parel, Jean-Marie

2004-07-01

Purpose: The purpose of this study was to determine the effects of temperature and heating duration on the kinetics of thermal shrinkage in corneal strips using a custom-made shrinkage device. Methods: Thermal shrinkage was induced and measured in corneal strips under a constant load placed while bathed in 25% Dextran irrigation solution. A study was performed on 57 Florida Lions Eye Bank donated human cadaver eyes to determine the effect of temperature on the amount and rate of thermal shrinkage. Further experiments were performed on 20 human cadaver eyes to determine the effects of heating duration on permanent shrinkage. Data analysis was performed to determine the effects of temperature, heating duration, and age on the amount and kinetics of shrinkage. Results: Shrinkage consisted of two phases: a shrinkage phase during heating and a regression phase after heating. Permanent shrinkage increased with temperature and duration. The shrinkage and regression time constants followed Arrhenius type temperature dependence. The shrinkage time constants where calculated to be 67, 84, 121, 560 and 1112 (s) at 80, 75, 70, 65, and 60°C respectively. At 65°C the permanent shrinkage time constant was calculated to be 945s. Conclusion: These results show that shrinkage treatments need to raise the temperature of the tissue above 75°C for several seconds in order to prevent regression of the shrinkage effect immediately after treatment and to induce the maximum amount of permanent irreversible shrinkage.

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Disconcordance in Statistical Models of Bisphenol A and Chronic Disease Outcomes in NHANES 2003-08

PubMed Central

Casey, Martin F.; Neidell, Matthew

2013-01-01

Background Bisphenol A (BPA), a high production chemical commonly found in plastics, has drawn great attention from researchers due to the substance’s potential toxicity. Using data from three National Health and Nutrition Examination Survey (NHANES) cycles, we explored the consistency and robustness of BPA’s reported effects on coronary heart disease and diabetes. Methods And Findings We report the use of three different statistical models in the analysis of BPA: (1) logistic regression, (2) log-linear regression, and (3) dose-response logistic regression. In each variation, confounders were added in six blocks to account for demographics, urinary creatinine, source of BPA exposure, healthy behaviours, and phthalate exposure. Results were sensitive to the variations in functional form of our statistical models, but no single model yielded consistent results across NHANES cycles. Reported ORs were also found to be sensitive to inclusion/exclusion criteria. Further, observed effects, which were most pronounced in NHANES 2003-04, could not be explained away by confounding. Conclusions Limitations in the NHANES data and a poor understanding of the mode of action of BPA have made it difficult to develop informative statistical models. Given the sensitivity of effect estimates to functional form, researchers should report results using multiple specifications with different assumptions about BPA measurement, thus allowing for the identification of potential discrepancies in the data. PMID:24223205

Plasma and serum L-selectin and clinical and subclinical the Multi-Ethnic Study of Atherosclerosis (MESA)cardiovascular disease

PubMed Central

BERARDI, CECILIA; DECKER, PAUL A.; KIRSCH, PHILLIP S.; DE ANDRADE, MARIZA; TSAI, MICHAEL Y.; PANKOW, JAMES S.; SALE, MICHELE M.; SICOTTE, HUGUES; TANG, WEIHONG; HANSON, NAOMI; POLAK, JOSEPH F.; BIELINSKI, SUZETTE J.

2014-01-01

L-selectin has been suggested to play a role in atherosclerosis. Previous studies on cardiovascular disease (CVD) and serum or plasma L-selectin are inconsistent. The association of serum L-selectin (sL-selectin) with carotid intima-media thickness, coronary artery calcium, ankle-brachial index (subclinical CVD) and incident CVD was assessed within 2403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Regression analysis and the Tobit model were used to study subclinical disease; Cox Proportional Hazards regression for incident CVD. Mean age was 63 ± 10, 47% were males; mean sL-selectin was significantly different across ethnicities. Within each race/ethnicity, sL-selectin was associated with age and sex; among Caucasians and African Americans, it was associated with smoking status and current alcohol use. sL-selectin levels did not predict subclinical or clinical CVD after correction for multiple comparisons. Conditional logistic regression models were used to study plasma L-selectin and CVD within 154 incident CVD cases, occurred in a median follow up of 8.5 years, and 306 age-, sex-, and ethnicity-matched controls. L-selectin levels in plasma were significantly lower than in serum and the overall concordance was low. Plasma levels were not associated with CVD. In conclusion, this large multi-ethnic population, soluble L-selectin levels did not predict clinical or subclinical CVD. PMID:24631064

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China

PubMed Central

Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao

2018-01-01

Background This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Methods Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Results Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). Conclusions The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention. PMID:29561835

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

PubMed Central

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

2013-01-01

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

Serum Uric Acid Is Associated with Poor Outcome in Black Africans in the Acute Phase of Stroke

PubMed Central

Ayeah, Chia Mark; Ba, H.; Mbahe, Salomon

2017-01-01

Background Prognostic significance of serum uric acid (SUA) in acute stroke still remains controversial. Objectives To determine the prevalence of hyperuricemia and its association with outcome of stroke patients in the Douala General Hospital (DGH). Methods This was a hospital based prospective cohort study which included acute stroke patients with baseline SUA levels and 3-month poststroke follow-up data. Associations between high SUA levels and stroke outcomes were analyzed using multiple logistic regression and survival analysis (Cox regression and Kaplan-Meier). Results A total of 701 acute stroke patients were included and the prevalence of hyperuricemia was 46.6% with a mean SUA level of 68.625 ± 24 mg/l. Elevated SUA after stroke was associated with death (OR = 2.067; 95% CI: 1.449–2.950; p < 0.001) but did not predict this issue. However, an independent association between increasing SUA concentration and mortality was noted in a Cox proportional hazards regression model (adjusted HR = 1.740; 95% CI: 1.305–2.320; p < 0.001). Furthermore, hyperuricemia was an independent predictor of poor functional outcome within 3 months after stroke (OR = 2.482; 95% CI: 1.399–4.404; p = 0.002). Conclusion The prevalence of hyperuricemia in black African stroke patients is quite high and still remains a predictor of poor outcome. PMID:29082062

Comment on "Cosmic-ray-driven reaction and greenhouse effect of halogenated molecules: Culprits for atmospheric ozone depletion and global climate change"

NASA Astrophysics Data System (ADS)

Nuccitelli, Dana; Cowtan, Kevin; Jacobs, Peter; Richardson, Mark; Way, Robert G.; Blackburn, Anne-Marie; Stolpe, Martin B.; Cook, John

2014-04-01

Lu (2013) (L13) argued that solar effects and anthropogenic halogenated gases can explain most of the observed warming of global mean surface air temperatures since 1850, with virtually no contribution from atmospheric carbon dioxide (CO2) concentrations. Here we show that this conclusion is based on assumptions about the saturation of the CO2-induced greenhouse effect that have been experimentally falsified. L13 also confuses equilibrium and transient response, and relies on data sources that have been superseeded due to known inaccuracies. Furthermore, the statistical approach of sequential linear regression artificially shifts variance onto the first predictor. L13's artificial choice of regression order and neglect of other relevant data is the fundamental cause of the incorrect main conclusion. Consideration of more modern data and a more parsimonious multiple regression model leads to contradiction with L13's statistical results. Finally, the correlation arguments in L13 are falsified by considering either the more appropriate metric of global heat accumulation, or data on longer timescales.

John Snow, William Farr and the 1849 outbreak of cholera that affected London: a reworking of the data highlights the importance of the water supply.

PubMed

Bingham, P; Verlander, N Q; Cheal, M J

2004-09-01

This paper examines why Snow's contention that cholera was principally spread by water was not accepted in the 1850s by the medical elite. The consequence of rejection was that hundreds in the UK continued to die. Logistic regression was used to re-analyse data, first published in 1852 by William Farr, consisting of the 1849 mortality rate from cholera and eight potential explanatory variables for the 38 registration districts of London. Logistic regression does not support Farr's original conclusion that a district's elevation above high water was the most important explanatory variable. Elevation above high water, water supply and poor rate each have an independent significant effect on district cholera mortality rate, but in terms of size of effect, it can be argued that water supply most strongly 'invited' further consideration. The science of epidemiology, that Farr helped to found, has continued to advance. Had logistic regression been available to Farr, its application to his 1852 data set would have changed his conclusion.

Investigation on the association between NLRP3 gene polymorphisms and susceptibility to primary gout.

PubMed

Wang, L F; Ding, Y J; Zhao, Q; Zhang, X L

2015-12-09

We conducted a case-control study to investigate the association between 3 common NALP3 polymorphisms (rs10754558, rs7512998, and rs12137901) and the susceptibility to primary gout. A total of 320 patients with primary gout and 320 controls were included in this study. The genotyping of NALP3 rs10754558, rs7512998, and rs12137901 were conducted by polymerase chain reaction-restriction fragment length polymorphism. Comparison analysis showed that primary gout patients were more likely to have higher body mass index, prevalence of hypertension, blood glucose, triglycerides, urea nitrogen, and uric acid (P < 0.05). Logistic regression analysis revealed no significant association between the NALP3 rs10754558, rs7512998, and rs12137901 polymorphisms and the risk of gouty arthritis. In conclusion, we found no significant association between NALP3 gene polymorphisms and the risk of primary gout.

Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

NASA Astrophysics Data System (ADS)

Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi

2016-11-01

Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

Quality of Work: Validation of a New Instrument in Three Languages

PubMed Central

Steffgen, Georges; Kohl, Diane; Reese, Gerhard; Happ, Christian; Sischka, Philipp

2015-01-01

Introduction and objective: A new instrument to measure quality of work was developed in three languages (German, French and Luxembourgish) and validated in a study of employees working in Luxembourg. Methods and results: A representative sample (n = 1529) was taken and exploratory factor analysis revealed a six-factor solution for the 21-item instrument (satisfaction and respect, mobbing, mental strain at work, cooperation, communication and feedback, and appraisal). Reliability analysis showed satisfying reliability for all six factors and the total questionnaire. In order to examine the construct validity of the new instrument, regression analyses were conducted to test whether the instrument predicted work characteristics’ influence on three components of well-being—burnout, psychological stress and maladaptive coping behaviors. Conclusion: The present validation offers a trilingual inventory for measuring quality of work that may be used, for example, as an assessment tool or for testing the effectiveness of interventions. PMID:26703634

Survival Analysis of Patients with End Stage Renal Disease

NASA Astrophysics Data System (ADS)

Urrutia, J. D.; Gayo, W. S.; Bautista, L. A.; Baccay, E. B.

2015-06-01

This paper provides a survival analysis of End Stage Renal Disease (ESRD) under Kaplan-Meier Estimates and Weibull Distribution. The data were obtained from the records of V. L. MakabaliMemorial Hospital with respect to time t (patient's age), covariates such as developed secondary disease (Pulmonary Congestion and Cardiovascular Disease), gender, and the event of interest: the death of ESRD patients. Survival and hazard rates were estimated using NCSS for Weibull Distribution and SPSS for Kaplan-Meier Estimates. These lead to the same conclusion that hazard rate increases and survival rate decreases of ESRD patient diagnosed with Pulmonary Congestion, Cardiovascular Disease and both diseases with respect to time. It also shows that female patients have a greater risk of death compared to males. The probability risk was given the equation R = 1 — e-H(t) where e-H(t) is the survival function, H(t) the cumulative hazard function which was created using Cox-Regression.

Motivations and Predictors of Cheating in Pharmacy School

PubMed Central

Nguyen, Kathy; Shah, Bijal M.; Doroudgar, Shadi; Bidwal, Monica K.

2016-01-01

Objective. To assess the prevalence, methods, and motivations for didactic cheating among pharmacy students and to determine predictive factors for cheating in pharmacy colleges and schools. Methods. A 45-item cross-sectional survey was conducted at all four doctor of pharmacy programs in Northern California. For data analysis, t test, Fisher exact test, and logistic regression were used. Results. Overall, 11.8% of students admitted to cheating in pharmacy school. Primary motivations for cheating included fear of failure, procrastination, and stress. In multivariate analysis, the only predictor for cheating in pharmacy school was a history of cheating in undergraduate studies. Conclusion. Cheating occurs in pharmacy schools and is motivated by fear of failure, procrastination, and stress. A history of past cheating predicts pharmacy school cheating. The information presented may help programs better understand their student population and lead to a reassessment of ethical culture, testing procedures, and prevention programs. PMID:27899829

THE ROLE OF PERSONALITY CHARACTERISTICS OF ATHLETES IN COACH-ATHLETE RELATIONSHIPS.

PubMed

Hülya Aşçı, F; Kelecek, Selen; AltintaŞ, Atahan

2015-10-01

This study investigated the relationship between athletes' personality characteristics and the quality of the coach-athlete relationship. 84 female (M age = 20.6 yr., SD = 2.8) and 129 male (M age = 22.0 yr., SD = 3.3) elite youth athletes competing at least for 7 yr. participated in this study. The Five-Factor Personality Inventory (short version) and the Quality of Relationships Inventory were administered to all participants. Stepwise multiple regression analysis assessed which of the five personality factors predicted scores for the different subscales of the Quality of Relationships Inventory (Depth, Support, and Conflict). Results indicated that depth of relationship was not predicted by personality factors. On the other hand, neuroticism and extraversion were significant predictors of support dimension of relationship. Analysis indicated that conscientiousness was the strongest predictor of conflict. In conclusion, athletes' personality characteristics may be important in determining the quality of the coach-athlete relationship.

Analyzing effective municipal solid waste recycling programs: the case of county-level MSW recycling performance in Florida, USA.

PubMed

Park, Seejeen; Berry, Frances S

2013-09-01

Municipal solid waste (MSW) recycling performance, both nationally and in Florida, USA, has shown little improvement during the past decade. This research examines variations in the MSW recycling program performance in Florida counties in an attempt to identify effective recycling programs. After reviewing trends in the MSW management literature, we conducted an empirical analysis using cross-sectional multiple regression analysis. The findings suggest that the convenience-based hypothesis was supported by showing that curbside recycling had a positive effect on MSW recycling performance. Financial (cost-saving) incentive-based hypotheses were partially supported meaning that individual level incentives can influence recycling performance. Citizen environmental concern was found to positively affect the amount of county recycling, while education and political affiliation yielded no significant results. In conclusion, this article discusses the implications of the findings for both academic research and practice of MSW recycling programs.

Determination of butter adulteration with margarine using Raman spectroscopy.

PubMed

Uysal, Reyhan Selin; Boyaci, Ismail Hakki; Genis, Hüseyin Efe; Tamer, Ugur

2013-12-15

In this study, adulteration of butter with margarine was analysed using Raman spectroscopy combined with chemometric methods (principal component analysis (PCA), principal component regression (PCR), partial least squares (PLS)) and artificial neural networks (ANNs). Different butter and margarine samples were mixed at various concentrations ranging from 0% to 100% w/w. PCA analysis was applied for the classification of butters, margarines and mixtures. PCR, PLS and ANN were used for the detection of adulteration ratios of butter. Models were created using a calibration data set and developed models were evaluated using a validation data set. The coefficient of determination (R(2)) values between actual and predicted values obtained for PCR, PLS and ANN for the validation data set were 0.968, 0.987 and 0.978, respectively. In conclusion, a combination of Raman spectroscopy with chemometrics and ANN methods can be applied for testing butter adulteration. Copyright © 2013 Elsevier Ltd. All rights reserved.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

The Precision Efficacy Analysis for Regression Sample Size Method.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.

The general purpose of this study was to examine the efficiency of the Precision Efficacy Analysis for Regression (PEAR) method for choosing appropriate sample sizes in regression studies used for precision. The PEAR method, which is based on the algebraic manipulation of an accepted cross-validity formula, essentially uses an effect size to…

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

Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: Analysis of 2008-2010 Korean National Health and Nutrition Examination Survey data

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

Kim, Yangho; Lee, Byung-Kook, E-mail: bklee@sch.ac.kr

Introduction: The objective of this study was to evaluate associations between blood lead, cadmium, and mercury levels with estimated glomerular filtration rate in a general population of South Korean adults. Methods: This was a cross-sectional study based on data obtained in the Korean National Health and Nutrition Examination Survey (KNHANES) (2008-2010). The final analytical sample consisted of 5924 participants. Estimated glomerular filtration rate (eGFR) was calculated using the MDRD Study equation as an indicator of glomerular function. Results: In multiple linear regression analysis of log2-transformed blood lead as a continuous variable on eGFR, after adjusting for covariates including cadmium andmore » mercury, the difference in eGFR levels associated with doubling of blood lead were -2.624 mL/min per 1.73 m Superscript-Two (95% CI: -3.803 to -1.445). In multiple linear regression analysis using quartiles of blood lead as the independent variable, the difference in eGFR levels comparing participants in the highest versus the lowest quartiles of blood lead was -3.835 mL/min per 1.73 m Superscript-Two (95% CI: -5.730 to -1.939). In a multiple linear regression analysis using blood cadmium and mercury, as continuous or categorical variables, as independent variables, neither metal was a significant predictor of eGFR. Odds ratios (ORs) and 95% CI values for reduced eGFR calculated for log2-transformed blood metals and quartiles of the three metals showed similar trends after adjustment for covariates. Discussion: In this large, representative sample of South Korean adults, elevated blood lead level was consistently associated with lower eGFR levels and with the prevalence of reduced eGFR even in blood lead levels below 10 {mu}g/dL. In conclusion, elevated blood lead level was associated with lower eGFR in a Korean general population, supporting the role of lead as a risk factor for chronic kidney disease.« less

How Does Physical Activity Intervention Improve Self-Esteem and Self-Concept in Children and Adolescents? Evidence from a Meta-Analysis

PubMed Central

Liu, Mingli; Wu, Lang; Ming, Qingsen

2015-01-01

Objective To perform a systematic review and meta-analysis for the effects of physical activity intervention on self-esteem and self-concept in children and adolescents, and to identify moderator variables by meta-regression. Design A meta-analysis and meta-regression. Method Relevant studies were identified through a comprehensive search of electronic databases. Study inclusion criteria were: (1) intervention should be supervised physical activity, (2) reported sufficient data to estimate pooled effect sizes of physical activity intervention on self-esteem or self-concept, (3) participants’ ages ranged from 3 to 20 years, and (4) a control or comparison group was included. For each study, study design, intervention design and participant characteristics were extracted. R software (version 3.1.3) and Stata (version 12.0) were used to synthesize effect sizes and perform moderation analyses for determining moderators. Results Twenty-five randomized controlled trial (RCT) studies and 13 non-randomized controlled trial (non-RCT) studies including a total of 2991 cases were identified. Significant positive effects were found in RCTs for intervention of physical activity alone on general self outcomes (Hedges’ g = 0.29, 95% confidence interval [CI]: 0.14 to 0.45; p = 0.001), self-concept (Hedges’ g = 0.49, 95%CI: 0.10 to 0.88, p = 0.014) and self-worth (Hedges’ g = 0.31, 95%CI: 0.13 to 0.49, p = 0.005). There was no significant effect of intervention of physical activity alone on any outcomes in non-RCTs, as well as in studies with intervention of physical activity combined with other strategies. Meta-regression analysis revealed that higher treatment effects were associated with setting of intervention in RCTs (β = 0.31, 95%CI: 0.07 to 0.55, p = 0.013). Conclusion Intervention of physical activity alone is associated with increased self-concept and self-worth in children and adolescents. And there is a stronger association with school-based and gymnasium-based intervention compared with other settings. PMID:26241879

[Analysis of the prevalence and risk factors of preoperative angiography confirmed coronary artery stenosis in patients with degenerative valvular heart disease].

PubMed

Xu, Z J; Pan, J; Zhou, Q; Wang, D J

2017-10-24

Objective: To estimate the prevalence and the risk factors of preoperative coronary angiography (CAG) confirmed coronary stenosis in patients with degenerative valvular heart disease. Methods: A total of 491 patients who underwent screening CAG before valvular surgery due to degenerative valvular heart disease were enrolled from January 2011 to September 2014 in our hospital, and clinical data were analyzed. According to CAG results, patients were divided into positive CAG result (PCAG) group or negative CAG (NCAG) group. Positive CAG result was defined as stenosis ≥50% of the diameter of the left main coronary artery or stenosis ≥70% of the diameter of left anterior descending, left circumflex artery, and right coronary artery.Risk factors of positive CAG result were analyzed by multivariable logistic regression analysis, and Bootstrap method was used to verify the results. Results: There were 47(9.57%)degenerative valvular heart disease patients with PCAG. Patients were older ((68.0±7.6)years vs.(62.6±7.1)years, P <0.001) and the prevalence of typical angina was significantly higher (14.89%(7/47)vs. 2.03%(9/444), P <0.001)in PCAG group than in NCAG group. Multivariable logistic regression analysis showed that age ( OR =1.118, 95% CI 1.067-1.172, P <0.001), typical angina ( OR =8.970, 95% CI 2.963-27.154, P <0.001), and serum concentration of apolipoprotein B ( OR =20.311, 95% CI 4.774-86.416, P <0.001) were the independent risk factors of PCAG in degenerative valvular heart disease patients. Bootstrap method revealed satisfactory repeatability of multivariable logistic regression analysis results (age: OR =1.118, 95% CI 1.068-1.178, P =0.001; typical angina: OR =8.970, 95% CI 2.338-35.891, P =0.001; serum concentration of apolipoprotein B: OR =20.311, 95% CI 4.639-91.977, P =0.001). Conclusions: A low prevalence of PCAG before valvular surgery is observed in degenerative valvular heart disease patients in this patient cohort. Age, typical angina, and serum concentration of apolipoprotein B are independent risk factors of PCAG in this patient cohort.

Common pitfalls in statistical analysis: Linear regression analysis

PubMed Central

Aggarwal, Rakesh; Ranganathan, Priya

2017-01-01

In a previous article in this series, we explained correlation analysis which describes the strength of relationship between two continuous variables. In this article, we deal with linear regression analysis which predicts the value of one continuous variable from another. We also discuss the assumptions and pitfalls associated with this analysis. PMID:28447022

A cross-sectional examination of psychological distress, positive mental health and their predictors in medical students in their clinical clerkships.

PubMed

van Dijk, Inge; Lucassen, Peter L B J; van Weel, Chris; Speckens, Anne E M

2017-11-17

Medical students can experience the transition from theory to clinical clerkships as stressful. Scientific literature on the mental health of clinical clerkship students is scarce and mental health is usually defined as absence of psychological distress without assessing psychological, emotional and social wellbeing, together called 'positive mental health'. This cross-sectional study examines the prevalence of psychological distress and positive mental health and explores possible predictors in a Dutch sample of clinical clerkship students. Fourth-year medical students in their first year of clinical clerkships were invited to complete an online questionnaire assessing demographics, psychological distress (Brief Symptom Inventory), positive mental health (Mental Health Continuum- SF), dysfunctional cognitions (Irrational Beliefs Inventory) and dispositional mindfulness skills (Five Facet Mindfulness Questionnaire). Multiple linear regression analysis was used to explore relationships between psychological distress, positive mental health (dependent variables) and demographics, dysfunctional cognitions and dispositional mindfulness skills (predictors). Of 454 eligible students, 406 (89%) completed the assessment of whom 21% scored in the clinical range of psychological distress and 41% reported a flourishing mental health. These proportions partially overlap each other. Female students reported a significantly higher mean level of psychological distress than males. In the regression analysis the strongest predictors of psychological distress were 'acting with awareness' (negative) and 'worrying' (positive). Strongest predictors of positive mental health were 'problem avoidance' (negative) and 'emotional irresponsibility' (negative). The prevalence of psychopathology in our sample of Dutch clinical clerkship students is slightly higher than in the general population. Our results support conclusions of previous research that psychological distress and positive mental health are not two ends of one continuum but partially overlap. Although no conclusion on causality can be drawn, this study supports the idea that self-awareness and active, nonavoidant coping strategies are related to lower distress and higher positive mental health.

Comparison of dust related respiratory effects in Dutch and Canadian grain handling industries: a pooled analysis.

PubMed Central

Peelen, S J; Heederik, D; Dimich-Ward, H D; Chan-Yeung, M; Kennedy, S M

1996-01-01

OBJECTIVES: Four previously conducted epidemiological studies in more than 1200 grain workers were used to compare exposure-response relations between exposure to grain dust and respiratory health. METHODS: The studies included Dutch workers from an animal feed mill and a transfer grain elevator and Canadian workers from a terminal grain elevator and the docks. Relations between forced expiratory volume in one second (FEV1) and exposure were analysed with multiple regression analysis corrected for smoking, age, and height. Exposure variables examined included cumulative and current dust exposure and the numbers of years a subject was employed in the industry. Sampling efficiencies of the Dutch and Canadian measurement techniques were compared in a pilot study. Results of this study were used to correct slopes of exposure-response relations for differences in dust fractions sampled by Dutch and Canadian personal dust samplers. RESULTS: Negative exposure-response relations were shown for regressions of FEV1 on cumulative and current exposure and years employed. Slopes of the exposure-response relations differed by a factor of three to five between industries, apart from results for cumulative exposure. Here the variation in slopes differed by a factor of 100, from -1 to -0.009 ml/mg.y/m3. The variation in slopes between industries reduced to between twofold to fivefold when the Dutch transfer elevator workers were not considered. There was evidence that the small exposure-response slope found for this group is caused by misclassification of exposure and a strong healthy worker effect. Alternative, but less likely explanations for the variation in slopes were differences in exposure concentrations, composition of grain dust, exposure characteristics, and measurement techniques. CONCLUSION: In conclusion, this study showed moderately similar negative exposure-response relations for four different populations from different countries, despite differences in methods of exposure assessment and exposure estimation. PMID:8983468

Financial ties and concordance between results and conclusions in meta-analyses: retrospective cohort study.

PubMed

Yank, Veronica; Rennie, Drummond; Bero, Lisa A

2007-12-08

To determine whether financial ties to one drug company are associated with favourable results or conclusions in meta-analyses on antihypertensive drugs. Retrospective cohort study. Meta-analyses published up to December 2004 that were not duplicates and evaluated the effects of antihypertensive drugs compared with any comparator on clinical end points in adults. Financial ties were categorised as one drug company compared with all others. The main outcomes were the results and conclusions of meta-analyses, with both outcomes separately categorised as being favourable or not favourable towards the study drug. We also collected data on characteristics of meta-analyses that the literature suggested might be associated with favourable results or conclusions. 124 meta-analyses were included in the study, 49 (40%) of which had financial ties to one drug company. On univariate logistic regression analyses, meta-analyses of better methodological quality were more likely to have favourable results (odds ratio 1.16, 95% confidence interval 1.07 to 1.27). Although financial ties to one drug company were not associated with favourable results, such ties constituted the only characteristic significantly associated with favourable conclusions (4.09, 1.30 to 12.83). When controlling for other characteristics of meta-analyses in multiple logistic regression analyses, meta-analyses that had financial ties to one drug company remained more likely to report favourable conclusions (5.11, 1.54 to 16.92). Meta-analyses on antihypertensive drugs and with financial ties to one drug company are not associated with favourable results but are associated with favourable conclusions.

Correlates of Mandrax use and condom beliefs in preventing sexually transmitted infections among a cohort of South African prison inmates

PubMed Central

Stephens, Torrance T.; Gardner, Darius; Jones, Keena; Sifunda, Sibusiso; Braithwaite, Ronald; Smith, Selina E.

2016-01-01

Background This study was designed to identify the extent to which self-reported Mandrax use impacts condom-use beliefs amongst South African prison inmates. Methods Participants were inmates from four prisons in the provinces of KwaZulu-Natal and Mpumalanga. In total, 357 inmates participated in the parent study of which 121 are included in this analysis based on their self-reported use of Mandrax. The questionnaire was developed in English, translated into Zulu, and back translated into English. Age significantly predicted the use of Mandrax: younger prison inmates reported higher use. Linear regression analysis was conducted to determine whether the use of Mandrax was associated with length of incarceration and other demographic variables, as well as participants' self-reported condom use beliefs behavior. Results Regression results indicated that two factors operationalizing condom-use beliefs were impacted by Mandrax use: 1) it is important to use condoms every time you have sex (p<0.01); 2) condoms work well to prevent the spread of HIV (p<0.02). Both factors were also inversely related to Mandrax use. Conclusion STI prevention programs among prison inmates that seek to promote safer sex behaviors among men must address attitudes to condom use, specifically consistent and correct use of latex condoms and reducing substance misuse. PMID:26316220

Oral health status and the epidemiologic paradox within latino immigrant groups

PubMed Central

2012-01-01

Background According to the United States census, there are 28 categories that define “Hispanic/Latinos.” This paper compares differences in oral health status between Mexican immigrants and other Latino immigrant groups. Methods Derived from a community-based sample (N = 240) in Los Angeles, this cross-sectional study uses an interview covering demographic and behavioral measures, and an intraoral examination using NIDCR epidemiologic criteria. Descriptive, bivariate analysis, and multiple regression analysis were conducted to examine the determinants that are associated with the Oral Health Status Index (OHSI). Results Mexican immigrants had a significantly higher OHSI (p < .05) compared to other Latinos. The multilinear regression showed that both age and gender (p < .05), percentage of untreated decayed teeth (p < .001), number of replaced missing teeth (p < .001), and attachment loss (p < .001) were significant. Conclusions Compared with the other Latino immigrants in our sample, Mexican immigrants have significantly better oral health status. This confirms the epidemiologic paradox previously found in comparisons of Mexicans with whites and African Americans. In this case of oral health status the paradox also occurs between Mexicans and other Latinos. Therefore, when conducting oral health studies of Latinos, more consideration needs to be given to differences within Latino subgroups, such as their country of origin and their unique ethnic and cultural characteristics. PMID:22958726

Factors associated with abdominal obesity in children

PubMed Central

Melzer, Matheus Ribeiro Theodósio Fernandes; Magrini, Isabella Mastrangi; Domene, Semíramis Martins Álvares; Martins, Paula Andrea

2015-01-01

Objective: To identify the association of dietary, socioeconomic factors, sedentary behaviors and maternal nutritional status with abdominal obesity in children. Methods: A cross-sectional study with household-based survey, in 36 randomly selected census tracts in the city of Santos, SP. 357 families were interviewed and questionnaires and anthropometric measurements were applied in mothers and their 3-10 years-old children. Assessment of abdominal obesity was made by maternal and child's waist circumference measurement; for classification used cut-off points proposed by World Health Organization (1998) and Taylor et al. (2000) were applied. The association between variables was performed by multiple logistic regression analysis. Results: 30.5% of children had abdominal obesity. Associations with children's and maternal nutritional status and high socioeconomic status were shown in the univariate analysis. In the regression model, children's body mass index for age (OR=93.7; 95%CI 39.3-223.3), female gender (OR=4.1; 95%CI 1.8-9.3) and maternal abdominal obesity (OR=2.7; 95%CI 1.2-6.0) were significantly associated with children's abdominal obesity, regardless of the socioeconomic status. Conclusions: Abdominal obesity in children seems to be associated with maternal nutritional status, other indicators of their own nutritional status and female gender. Intervention programs for control of childhood obesity and prevention of metabolic syndrome should consider the interaction of the nutritional status of mothers and their children. PMID:26298655

Relationship between pelvic incidence and osteoarthritis of the hip

PubMed Central

Weinberg, D. S.; Bohl, M. S.; Liu, R. W.

2016-01-01

Objectives Sagittal alignment of the lumbosacral spine, and specifically pelvic incidence (PI), has been implicated in the development of spine pathology, but generally ignored with regards to diseases of the hip. We aimed to determine if increased PI is correlated with higher rates of hip osteoarthritis (HOA). The effect of PI on the development of knee osteoarthritis (KOA) was used as a negative control. Methods We studied 400 well-preserved cadaveric skeletons ranging from 50 to 79 years of age at death. Each specimen’s OA of the hip and knee were graded using a previously described method. PI was measured from standardised lateral photographs of reconstructed pelvises. Multiple regression analysis was performed to determine the relationship between age and PI with HOA and KOA. Results The mean age was 60.2 years (standard deviation (sd) 8.1), and the mean PI was 46.7° (sd 10.7°). Multiple regression analysis demonstrated a significant correlation between increased PI and HOA (standardised beta = 0.103, p = 0.017). There was no correlation between PI and KOA (standardised beta = 0.003, p = 0.912). Conclusion Higher PI in the younger individual may contribute to the development of HOA in later life. Cite this article: Dr J. J. Gebhart. Relationship between pelvic incidence and osteoarthritis of the hip. Bone Joint Res 2016;5:66–72. DOI: 10.1302/2046-3758.52.2000552. PMID:26912384

Association Between Monetary Deposits and Weight Loss in Online Commitment Contracts

PubMed Central

Lesser, Lenard I.; Thompson, Caroline A.; Luft, Harold S.

2017-01-01

Purpose To examine the characteristics of voluntary online commitment contracts that may be associated with greater weight loss. Design Retrospective analysis of weight loss commitment contracts derived from a company that provides web-based support for personal commitment contracts. Using regression, we analyzed whether percentage weight loss differed between participants who incentivized their contract using monetary deposits and those who did not. Setting Online. Participants Users (N = 3857) who voluntarily signed up online in 2013 for a weight loss contract. Intervention Participants specified their own weight loss goal, time period, and self-reported weekly weight. Deposits were available in the following 3 categories: charity, anticharity (a nonprofit one does not like), or donations made to a friend. Measures Percentage weight loss per week. Analysis Multivariable linear regressions. Results Controlling for several participant and contract characteristics, contracts with anticharity, charity, and friend deposits had greater reported weight loss than nonincentivized contracts. Weight change per week relative to those without deposits was −0.33%, −0.28%, and −0.25% for anti-charity, charity, and friend, respectively (P < 0.001). Contracts without a weight verification method claimed more weight loss than those with verification. Conclusion Voluntary use of commitment contracts may be an effective tool to assist weight loss. Those who choose to use monetary incentives report more weight loss. It is not clear whether this is due to the incentives or higher motivation. PMID:27502832

Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students

PubMed Central

2017-01-01

Objective. Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design. In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results. Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (B = −0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion. As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities. PMID:28154839

[Relationship between personality characteristics and turnover intention of medical staff in an infectious disease hospital].

PubMed

Ma, K H; Cui, Z Y; Li, L; Chao, H; Wang, Y

2017-12-20

Objective: To investigate the relationship between personality characteristics and turnover intention of the medical staff in an infectious diseases hospital. Methods: Using the cluster sampling method, a total of 366 members of medical staff were selected from different departments in an infectious disease hospital from May to August, 2013. The general information, such as sex, age, education level, and professional title, were collected and they were subjected to a survey using Cattell's 16 Personality Factor Questionnaire and Turnover Intention Scale. The data were subjected to logistic regression analysis. Results: Compared with the Chinese norm, the medical staff in the infectious disease hospital had significantly higher scores of intelligence, stability, bullying, excitability, perseverance, social boldness, fantasy, privateness, independence, and self-discipline and significantly lower scores of gregariousness, sensitivity, suspicion, anxiety, and tension ( P <0.05). Of the 366 members of medical staff, 22 (6.01%) had a very low turnover intention, low in 152 (41.53%) , high in 61 (16.67%) , and very high in 131 (35.79%). The logistic regression analysis showed that sensitivity, suspicion, fantasy, privateness, anxiety, openness to change, and independence were the risk factors for turnover intention ( P <0.05) . Conclusion: Compared with the Chinese norm, the medical staff in the infectious disease hospital have a better mental quality and a higher turnover intention. The individuals with sensitivity, suspicion, fantasy, and anxiety are prone to having turnover intention.

Multidimensional Predictors of Fatigue among Octogenarians and Centenarians

PubMed Central

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W.

2012-01-01

Background Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. Objective: This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Methods Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Results Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. Conclusion The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. PMID:22094445

Serum Leptin Is a Biomarker of Malnutrition in Decompensated Cirrhosis

PubMed Central

Rachakonda, Vikrant; Borhani, Amir A.; Dunn, Michael A.; Andrzejewski, Margaret; Martin, Kelly; Behari, Jaideep

2016-01-01

Background and Aims Malnutrition is a leading cause of morbidity and mortality in cirrhosis. There is no consensus as to the optimal approach for identifying malnutrition in end-stage liver disease. The aim of this study was to measure biochemical, serologic, hormonal, radiographic, and anthropometric features in a cohort of hospitalized cirrhotic patients to characterize biomarkers for identification of malnutrition. Design In this prospective observational cohort study, 52 hospitalized cirrhotic patients were classified as malnourished (42.3%) or nourished (57.7%) based on mid-arm muscle circumference < 23 cm and dominant handgrip strength < 30 kg. Anthropometric measurements were obtained. Appetite was assessed using the Simplified Nutrition Appetite Questionnaire (SNAQ) score. Fasting levels of serum adipokines, cytokines, and hormones were determined using Luminex assays. Logistic regression analysis was used to determine features independently associated with malnutrition. Results Subjects with and without malnutrition differed in several key features of metabolic phenotype including wet and dry BMI, skeletal muscle index, visceral fat index and HOMA-IR. Serum leptin levels were lower and INR was higher in malnourished subjects. Serum leptin was significantly correlated with HOMA-IR, wet and dry BMI, mid-arm muscle circumference, skeletal muscle index, and visceral fat index. Logistic regression analysis revealed that INR and log-transformed leptin were independently associated with malnutrition. Conclusions Low serum leptin and elevated INR are associated with malnutrition in hospitalized patients with end-stage liver disease. PMID:27583675

High energy injury is a risk factor for preoperative venous thromboembolism in the patients with hip fractures: A prospective observational study.

PubMed

Park, Jin Sup; Jang, Jae Hoon; Park, Ki Young; Moon, Nam Hoon

2018-06-01

The purpose of this study was to identify the incidence of preoperative venous thromboembolism (VTE), and determine if high energy hip fracture affects preoperative VTE occurrence. Three-hundred nine patients (244 low and 61 high energy injuries) treated between March 2015 and March 2017 were included in this study. Indirect multidetector computed tomographic venography for the detection of preoperative VTE was performed at admission. The incidence of preoperative VTE was compared between high and low energy injury hip fractures. Logistic regression analysis was used to identify independent risk factors for preoperative VTE. The overall incidence of preoperative VTE was 18.4% (56 of 305 patients). Preoperative VTE was identified in 17 (27.9%) and 39 (16.0%) patients in the high and low energy injury groups, respectively (p = 0.034). Multivariate logistic regression analysis showed that high energy injury, history of VTE, and myeloproliferative disease were significant predictive factors of preoperative VTE (OR = 2.451; 95% CI = 1.227-4.896, OR = 11.174; 95% CI = 3.500-35.673, OR = 6.936; 95% CI = 1.641-29.321, respectively) CONCLUSION: Because high energy hip fracture is significantly associated with preoperative VTE occurrence, preoperative evaluation and proper thromboprophylaxis should be performed for patients with a high-energy hip fracture. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of Weibull and Lognormal Cure Models with Cox in the Survival Analysis Of Breast Cancer Patients in Rafsanjan.

PubMed

Hoseini, Mina; Bahrampour, Abbas; Mirzaee, Moghaddameh

2017-02-16

Breast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer. A cohort study. The current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14. According to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study. Based on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.

Fasting Insulin Levels and Metabolic Risk Factors in Type 2 Diabetic Patients at the First Visit in Japan

PubMed Central

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-01-01

OBJECTIVE To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. RESEARCH DESIGN AND METHODS In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. RESULTS Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. CONCLUSIONS During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs. PMID:22665215

Use of Antihypotensive Therapies in Extremely Preterm Infants

PubMed Central

Li, Lei; Newman, Nancy S.; Das, Abhik; Watterberg, Kristi L.; Yoder, Bradley A.; Faix, Roger G.; Laughon, Matthew M.; Stoll, Barbara J.; Van Meurs, Krisa P.; Carlo, Waldemar A.; Poindexter, Brenda B.; Bell, Edward F.; Sánchez, Pablo J.; Ehrenkranz, Richard A.; Goldberg, Ronald N.; Laptook, Abbot R.; Kennedy, Kathleen A.; Frantz, Ivan D.; Shankaran, Seetha; Schibler, Kurt; Higgins, Rosemary D.; Walsh, Michele C.

2013-01-01

OBJECTIVE: To investigate the relationships among blood pressure (BP) values, antihypotensive therapies, and in-hospital outcomes to identify a BP threshold below which antihypotensive therapies may be beneficial. METHODS: Prospective observational study of infants 230/7 to 266/7 weeks’ gestational age. Hourly BP values and antihypotensive therapy use in the first 24 hours were recorded. Low BP was investigated by using 15 definitions. Outcomes were examined by using regression analysis controlling for gestational age, the number of low BP values, and illness severity. RESULTS: Of 367 infants enrolled, 203 (55%) received at least 1 antihypotensive therapy. Treated infants were more likely to have low BP by any definition (P < .001), but for the 15 definitions of low BP investigated, therapy was not prescribed to 3% to 49% of infants with low BP and, paradoxically, was administered to 28% to 41% of infants without low BP. Treated infants were more likely than untreated infants to develop severe retinopathy of prematurity (15% vs 8%, P = .03) or severe intraventricular hemorrhage (22% vs 11%, P < .01) and less likely to survive (67% vs 78%, P = .02). However, with regression analysis, there were no significant differences between groups in survival or in-hospital morbidity rates. CONCLUSIONS: Factors other than BP contributed to the decision to use antihypotensive therapies. Infant outcomes were not improved with antihypotensive therapy for any of the 15 definitions of low BP investigated. PMID:23650301

Dispositional optimism, depression, disability and quality of life in Parkinson’s disease

PubMed Central

Gison, Annalisa; Dall’Armi, Valentina; Donati, Valentina; Rizza, Federica; Giaquinto, Salvatore

2014-01-01

Summary Very little research on dispositional optimism (DO) has been carried out in the field of Parkinson’s disease (PD). The present cross-sectional study, focusing on this personality trait, was performed with two main aims: i) to compare DO between patients with PD and a control group (CG); ii) to perform, in the PD group, a regression analysis including health-related variables, such as depression, anxiety, quality of life (QoL) and activities of daily living. Seventy PD participants and 70 healthy volunteers were enrolled in the study. The Mann-Whitney test was used to compare life orientation between the PD and CG groups. In the PD group, Pearson’s correlation analysis was used to investigate the relationship between the measures of DO and the other variables. Means of log-linear regression were also used. Mean ratios adjusted for sex, age, education, and severity of disease were estimated, with relative 95% confidence intervals and p-values. The main results were as follows: i) no significant difference in DO was found between the PD participants and the CG; ii) DO was positively associated with QoL and emotional distress and inversely correlated with the Unified Parkinson’s Disease Rating Scale; iii) DO was not correlated with disability. In conclusion, high DO predicts a satisfactory quality of life, low emotional distress and reduced disease severity in PD. PMID:25306121

Smoking in Movies and Increased Smoking Among Young Adults

PubMed Central

Song, Anna V.; Ling, Pamela M.; Neilands, Torsten B.; Glantz, Stanton A.

2010-01-01

Objective This study assessed whether smoking in the movies was associated with smoking in young adults. Methods A national web-enabled cross-sectional survey of 1528 young adults, aged 18–25, was performed between September and November 2005. Logistic regression and path analysis using probit regression were used to assess relationships between exposure to smoking in the movies and smoking behavior. Analysis was completed in December 2006. Results Exposure to smoking in the movies predicted current smoking. The adjusted odds of current smoking increased by a factor of 1.21 for each quartile increase in exposure to smoking (p<0.01) in the movies, reaching 1.77 for the top exposure quartile. The unadjusted odds of established smoking (100+ cigarettes with current smoking) increased by 1.23 per quartile (p<0.001) of exposure, reaching 1.86 for the top quartile. This effect on established smoking was mediated by two factors related to smoking in the movies: positive expectations about smoking and exposure to friends and relatives who smoked, with positive expectations accounting for about two thirds of the effect. Conclusions The association between smoking in the movies and young adult smoking behavior exhibited a dose–response relationship; the more a young adult was exposed to smoking in the movies, the more likely he or she would have smoked in the past 30 days or have become an established smoker. PMID:17950405

Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students.

PubMed

Faramarzi, Mahbobeh; Khafri, Soraya

2017-01-01

Objective . Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design . In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results . Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students ( B = -0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion . As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.

The effect of hospital mergers on long-term sickness absence among hospital employees: a fixed effects multivariate regression analysis using panel data

PubMed Central

2014-01-01

Background Hospitals are merging to become more cost-effective. Mergers are often complex and difficult processes with variable outcomes. The aim of this study was to analyze the effect of mergers on long-term sickness absence among hospital employees. Methods Long-term sickness absence was analyzed among hospital employees (N = 107 209) in 57 hospitals involved in 23 mergers in Norway between 2000 and 2009. Variation in long-term sickness absence was explained through a fixed effects multivariate regression analysis using panel data with years-since-merger as the independent variable. Results We found a significant but modest effect of mergers on long-term sickness absence in the year of the merger, and in years 2, 3 and 4; analyzed by gender there was a significant effect for women, also for these years, but only in year 4 for men. However, men are less represented among the hospital workforce; this could explain the lack of significance. Conclusions Mergers has a significant effect on employee health that should be taken into consideration when deciding to merge hospitals. This study illustrates the importance of analyzing the effects of mergers over several years and the need for more detailed analyses of merger processes and of the changes that may occur as a result of such mergers. PMID:24490750

Risk factors for indications of intraoperative blood transfusion among patients undergoing surgical treatment for colorectal adenocarcinoma.

PubMed

Gonçalves, Iara; Linhares, Marcelo; Bordin, Jose; Matos, Delcio

2009-01-01

Identification of risk factors for requiring transfusions during surgery for colorectal cancer may lead to preventive actions or alternative measures, towards decreasing the use of blood components in these procedures, and also rationalization of resources use in hemotherapy services. This was a retrospective case-control study using data from 383 patients who were treated surgically for colorectal adenocarcinoma at 'Fundação Pio XII', in Barretos-SP, Brazil, between 1999 and 2003. To recognize significant risk factors for requiring intraoperative blood transfusion in colorectal cancer surgical procedures. Univariate analyses were performed using Fisher's exact test or the chi-squared test for dichotomous variables and Student's t test for continuous variables, followed by multivariate analysis using multiple logistic regression. In the univariate analyses, height (P = 0.06), glycemia (P = 0.05), previous abdominal or pelvic surgery (P = 0.031), abdominoperineal surgery (P<0.001), extended surgery (P<0.001) and intervention with radical intent (P<0.001) were considered significant. In the multivariate analysis using logistic regression, intervention with radical intent (OR = 10.249, P<0.001, 95% CI = 3.071-34.212) and abdominoperineal amputation (OR = 3.096, P = 0.04, 95% CI = 1.445-6.623) were considered to be independently significant. This investigation allows the conclusion that radical intervention and the abdominoperineal procedure in the surgical treatment of colorectal adenocarcinoma are risk factors for requiring intraoperative blood transfusion.

ARMS2 variants may predict the 3-year outcome of photodynamic therapy for wet age-related macular degeneration

PubMed Central

Nakai, Shunichiro; Matsumiya, Wataru; Miki, Akiko; Nakamura, Makoto

2017-01-01

Purpose To determine the association of age-related maculopathy susceptibility 2 (ARMS2) gene polymorphisms with the 3-year outcomes of photodynamic therapy (PDT) in wet age-related macular degeneration (wet AMD). Methods The single nucleotide polymorphism (SNP) at rs10490924 in the ARMS2 gene of 65 patients with wet AMD who underwent PDT was genotyped using the TaqMan assay. The clinical characteristics and the outcomes of PDT were compared among the three genotypes at rs10490924. A multivariate regression analysis was performed to evaluate the influence of the clinical cofactors on the association of rs10490924 with the visual outcome at 36 months after the first PDT. Results A significant difference was found among the genotypes in the age and the baseline lesion size. The patients with the GG genotype showed a significant improvement in vision, and the patients with the TT genotype showed a significant worsening of vision at all time points measured after the initial PDT. In the multivariate regression analysis, the number of the G allele at rs10490924 was associated with a significantly greater improvement in the baseline best-corrected visual acuity (BCVA) at 36 months after the first PDT. Conclusions ARMS2 variants are likely associated with the 3-year outcomes of PDT in patients with wet AMD. PMID:28761324

Atmospheric pollutants and hospital admissions due to pneumonia in children

PubMed Central

Negrisoli, Juliana; Nascimento, Luiz Fernando C.

2013-01-01

OBJECTIVE: To analyze the relationship between exposure to air pollutants and hospitalizations due to pneumonia in children of Sorocaba, São Paulo, Brazil. METHODS: Time series ecological study, from 2007 to 2008. Daily data were obtained from the State Environmental Agency for Pollution Control for particulate matter, nitric oxide, nitrogen dioxide, ozone, besides air temperature and relative humidity. The data concerning pneumonia admissions were collected in the public health system of Sorocaba. Correlations between the variables of interest using Pearson cofficient were calculated. Models with lags from zero to five days after exposure to pollutants were performed to analyze the association between the exposure to environmental pollutants and hospital admissions. The analysis used the generalized linear model of Poisson regression, being significant p<0.05. RESULTS: There were 1,825 admissions for pneumonia, with a daily mean of 2.5±2.1. There was a strong correlation between pollutants and hospital admissions, except for ozone. Regarding the Poisson regression analysis with the multi-pollutant model, only nitrogen dioxide was statistically significant in the same day (relative risk - RR=1.016), as well as particulate matter with a lag of four days (RR=1.009) after exposure to pollutants. CONCLUSIONS: There was an acute effect of exposure to nitrogen dioxide and a later effect of exposure to particulate matter on children hospitalizations for pneumonia in Sorocaba. PMID:24473956

Does Human Milk Modulate Body Composition in Late Preterm Infants at Term-Corrected Age?

PubMed

Giannì, Maria Lorella; Consonni, Dario; Liotto, Nadia; Roggero, Paola; Morlacchi, Laura; Piemontese, Pasqua; Menis, Camilla; Mosca, Fabio

2016-10-23

(1) Background: Late preterm infants account for the majority of preterm births and are at risk of altered body composition. Because body composition modulates later health outcomes and human milk is recommended as the normal method for infant feeding, we sought to investigate whether human milk feeding in early life can modulate body composition development in late preterm infants; (2) Methods: Neonatal, anthropometric and feeding data of 284 late preterm infants were collected. Body composition was evaluated at term-corrected age by air displacement plethysmography. The effect of human milk feeding on fat-free mass and fat mass content was evaluated using multiple linear regression analysis; (3) Results: Human milk was fed to 68% of the infants. According to multiple regression analysis, being fed any human milk at discharge and at  term-corrected and being fed exclusively human milk at term-corrected age were positively associated with fat-free mass content(β = -47.9, 95% confidence interval (CI) = -95.7; -0.18; p = 0.049; β = -89.6, 95% CI = -131.5; -47.7; p < 0.0001; β = -104.1, 95% CI = -151.4; -56.7, p < 0.0001); (4) Conclusion: Human milk feeding appears to be associated with fat-free mass deposition in late preterm infants. Healthcare professionals should direct efforts toward promoting and supporting breastfeeding in these vulnerable infants.

Age-related normative values for handgrip strength and grip strength’s usefulness as a predictor of mortality and both cognitive and physical decline in older adults in northwest Russia

PubMed Central

Turusheva, A.; Frolova, E.; Degryse, J-M.

2017-01-01

Objectives: This paper sought to provide normative values for grip strength among older adults across different age groups in northwest Russia and to investigate their predictive value for adverse events. Methods: A population-based prospective cohort study of 611 community-dwelling individuals 65+. Grip strength was measured using the standard protocol applied in the Groningen Elderly Tests. The cut-off thresholds for grip strength were defined separately for men and women of different ages using a weighted polynomial regression. A Cox regression analysis, the c-statistic, a risk reclassification analysis, and bootstrapping techniques were used to analyze the data. The outcomes were the 5-year mortality rate, the loss of autonomy and mental decline. Results: We determined the age-related reference intervals of grip strength for older adults. The 5th and 10th percentiles of grip strength were associated with a higher risk for malnutrition, low autonomy, physical and mental functioning and 5-year mortality. The 5th percentile of grip strength was associated with a decline in autonomy. Conclusions: This study presents age- and sex-specific reference values for grip strength in the 65+ Russian population derived from a prospective cohort study. The norms can be used in clinical practice to identify patients at increased risk for adverse outcomes. PMID:28250246

Social Desirability Bias in Self-Reporting of Hearing Protector Use among Farm Operators

PubMed Central

McCullagh, Marjorie C.; Rosemberg, Marie-Anne

2015-01-01

Objective: The purposes of this study were (i) to examine the relationship between reported hearing protector use and social desirability bias, and (ii) to compare results of the Marlowe-Crowne social desirability instrument when administered using two different methods (i.e. online and by telephone). Methods: A shortened version of the Marlowe-Crowne social desirability instrument, as well as a self-administered instrument measuring use of hearing protectors, was administered to 497 participants in a study of hearing protector use. The relationship between hearing protector use and social desirability bias was examined using regression analysis. The results of two methods of administration of the Marlowe-Crowne social desirability instrument were compared using t-tests and regression analysis. Results: Reliability (using Cronbach’s alpha) for the shortened seven-item scale for this sample was 0.58. There was no evidence of a relationship between reported hearing protector use and social desirability reporting bias, as measured by the shortened Marlowe-Crowne. The difference in results by method of administration (i.e. online, telephone) was very small. Conclusions: This is the first published study to measure social desirability bias in reporting of hearing protector use among farmers. Findings of this study do not support the presence of social desirability bias in farmers’ reporting of hearing protector use, lending support for the validity of self-report in hearing protector use in this population. PMID:26209595

Gender and metabolic differences of gallstone diseases

PubMed Central

Sun, Hui; Tang, Hong; Jiang, Shan; Zeng, Li; Chen, En-Qiang; Zhou, Tao-You; Wang, You-Juan

2009-01-01

AIM: To investigate the risk factors for gallstone disease in the general population of Chengdu, China. METHODS: This study was conducted at the West China Hospital. Subjects who received a physical examination at this hospital between January and December 2007 were included. Body mass index, blood pressure, fasting plasma glucose, serum lipid and lipoproteins concentrations were analyzed. Gallstone disease was diagnosed by ultrasound or on the basis of a history of cholecystectomy because of gallstone disease. Unconditional logistic regression analysis was used to investigate the risk factors for gallstone disease, and the Chi-square test was used to analyze differences in the incidence of metabolic disorders between subjects with and without gallstone disease. RESULTS: A total of 3573 people were included, 10.7% (384/3573) of whom had gallstone diseases. Multiple logistic regression analysis indicated that the incidence of gallstone disease in subjects aged 40-64 or ≥ 65 years was significantly different from that in those aged 18-39 years (P < 0.05); the incidence was higher in women than in men (P < 0.05). In men, a high level of fasting plasma glucose was obvious in gallstone disease (P < 0.05), and in women, hypertriglyceridemia or obesity were significant in gallstone disease (P < 0.05). CONCLUSION: We assume that age and sex are profoundly associated with the incidence of gallstone disease; the metabolic risk factors for gallstone disease were different between men and women. PMID:19370788

Body composition: A predictive factor of cycle fecundity

PubMed Central

Kayatas, Semra; Api, Murat; Kurt, Didar; Eroglu, Mustafa; Arınkan, Sevcan Arzu

2014-01-01

Objective To study the effect of body composition on reproduction in women with unexplained infertility treated with a controlled ovarian hyperstimulation and intrauterine insemination programme. Methods This prospective observational study was conducted on 308 unexplained infertile women who were scheduled for a controlled ovarian hyperstimulation and intrauterine insemination programme and were grouped as pregnant and non-pregnant. Anthropometric measurements were performed using TANITA-420MA before the treatment cycle. Body composition was determined using a bioelectrical impedance analysis system. Results Body fat mass was significantly lower in pregnant women than in non-pregnant women (15.61±3.65 vs.18.78±5.97, respectively) (p=0.01). In a multiple regression analysis, body fat mass proved to have a stronger association with fecundity than the percentage of body fat, body mass index, or the waist/hip ratio (standardized regression coefficient≥0.277, t-value≥2.537; p<0.05). The cut-off value of fat mass, which was evaluated using the receiver operating characteristics curve, was 16.65 with a sensitivity of 61.8% and a specificity of 70.2%. Below this cut-off value, the odds of the pregnancy occurrence was found to be 2.5 times more likely. Conclusion Body fat mass can be predictive for pregnancy in patients with unexplained infertility scheduled for a controlled ovarian hyperstimulation and intrauterine insemination programme. PMID:25045631

Association between Organizational Commitment and Personality Traits of Faculty Members of Ahvaz Jundishapur University of Medical Sciences

PubMed Central

Khiavi, Farzad Faraji; Dashti, Rezvan; Mokhtari, Saeedeh

2016-01-01

Introduction Individual characteristics are important factors influencing organizational commitment. Also, committed human resources can lead organizations to performance improvement as well as personal and organizational achievements. This research aimed to determine the association between organizational commitment and personality traits among faculty members of Ahvaz Jundishapur University of Medical Sciences. Methods the research population of this cross-sectional study was the faculty members of Ahvaz Jundishapur University of Medical Sciences (Ahvaz, Iran). The sample size was determined to be 83. Data collection instruments were the Allen and Meyer questionnaire for organizational commitment and Neo for characteristics’ features. The data were analyzed through Pearson’s product-moment correlation and the independent samples t-test, ANOVA, and simple linear regression analysis (SLR) by SPSS. Results Continuance commitment showed a significant positive association with neuroticism, extroversion, agreeableness, and conscientiousness. Normative commitment showed a significant positive association with conscientiousness and a negative association with extroversion (p = 0.001). Openness had a positive association with affective commitment. Openness and agreeableness, among the five characteristics’ features, had the most effect on organizational commitment, as indicated by simple linear regression analysis. Conclusion Faculty members’ characteristics showed a significant association with their organizational commitment. Determining appropriate characteristic criteria for faculty members may lead to employing committed personnel to accomplish the University’s objectives and tasks. PMID:27123222

Evaluation of a complex intervention to improve primary care prescribing: a phase IV segmented regression interrupted time series analysis

PubMed Central

MacBride-Stewart, Sean; Marwick, Charis; Houston, Neil; Watt, Iain; Patton, Andrea; Guthrie, Bruce

2017-01-01

Background It is uncertain whether improvements in primary care high-risk prescribing seen in research trials can be realised in the real-world setting. Aim To evaluate the impact of a 1-year system-wide phase IV prescribing safety improvement initiative, which included education, feedback, support to identify patients to review, and small financial incentives. Design and setting An interrupted time series analysis of targeted high-risk prescribing in all 56 general practices in NHS Forth Valley, Scotland, was performed. In 2013–2014, this focused on high-risk non-steroidal anti-inflammatory drugs (NSAIDs) in older people and NSAIDs with oral anticoagulants; in 2014–2015, it focused on antipsychotics in older people. Method The primary analysis used segmented regression analysis to estimate impact at the end of the intervention, and 12 months later. The secondary analysis used difference-in-difference methods to compare Forth Valley changes with those in NHS Greater Glasgow and Clyde (GGC). Results In the primary analysis, downward trends for all three NSAID measures that were existent before the intervention statistically significantly steepened following implementation of the intervention. At the end of the intervention period, 1221 fewer patients than expected were prescribed a high-risk NSAID. In contrast, antipsychotic prescribing in older people increased slowly over time, with no intervention-associated change. In the secondary analysis, reductions at the end of the intervention period in all three NSAID measures were statistically significantly greater in NHS Forth Valley than in NHS GGC, but only significantly greater for two of these measures 12 months after the intervention finished. Conclusion There were substantial and sustained reductions in the high-risk prescribing of NSAIDs, although with some waning of effect 12 months after the intervention ceased. The same intervention had no effect on antipsychotic prescribing in older people. PMID:28347986

Quality of life in breast cancer patients--a quantile regression analysis.

PubMed

Pourhoseingholi, Mohamad Amin; Safaee, Azadeh; Moghimi-Dehkordi, Bijan; Zeighami, Bahram; Faghihzadeh, Soghrat; Tabatabaee, Hamid Reza; Pourhoseingholi, Asma

2008-01-01

Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.

Do medical students like communication? Validation of the German CSAS (Communication Skills Attitude Scale)

PubMed Central

Busch, Anne-Kathrin; Rockenbauch, Katrin; Schmutzer, Gabriele; Brähler, Elmar

2015-01-01

Objectives: Attitudes towards communication skills of medical undergraduates can be gathered using the Communication Skills Attitude Scale (CSAS). We aimed to develop a German version of the CSAS (CSAS-G) in order to explore attitudes towards communication skills in a German cohort. Additionally the potential influence of demographic factors was examined. Methods: We realized the CSAS-G and conducted a survey with 529 participants from 3 different years of study. We then carried out an explorative as well as confirmatory factor analysis and compared the attitudinal scores. Multiple regression analysis was performed. Results: The confirmatory analysis confirmed the two-subscale system revealed by the explorative factor analysis. Students indicate low levels of negative attitudes and moderate levels of positive attitudes. Attitudinal scores differ significantly in relation to gender. Conclusion: The CSAS-G can be used in German cohorts to evaluate attitudes towards communication skills. Medical students in our study show basically a positive approach. Further investigation is necessary to explore and understand attitudes towards communication skills of German medical students. PMID:25699103

The microcomputer scientific software series 2: general linear model--regression.

Treesearch

Harold M. Rauscher

1983-01-01

The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

Incorrect likelihood methods were used to infer scaling laws of marine predator search behaviour.

PubMed

Edwards, Andrew M; Freeman, Mervyn P; Breed, Greg A; Jonsen, Ian D

2012-01-01

Ecologists are collecting extensive data concerning movements of animals in marine ecosystems. Such data need to be analysed with valid statistical methods to yield meaningful conclusions. We demonstrate methodological issues in two recent studies that reached similar conclusions concerning movements of marine animals (Nature 451:1098; Science 332:1551). The first study analysed vertical movement data to conclude that diverse marine predators (Atlantic cod, basking sharks, bigeye tuna, leatherback turtles and Magellanic penguins) exhibited "Lévy-walk-like behaviour", close to a hypothesised optimal foraging strategy. By reproducing the original results for the bigeye tuna data, we show that the likelihood of tested models was calculated from residuals of regression fits (an incorrect method), rather than from the likelihood equations of the actual probability distributions being tested. This resulted in erroneous Akaike Information Criteria, and the testing of models that do not correspond to valid probability distributions. We demonstrate how this led to overwhelming support for a model that has no biological justification and that is statistically spurious because its probability density function goes negative. Re-analysis of the bigeye tuna data, using standard likelihood methods, overturns the original result and conclusion for that data set. The second study observed Lévy walk movement patterns by mussels. We demonstrate several issues concerning the likelihood calculations (including the aforementioned residuals issue). Re-analysis of the data rejects the original Lévy walk conclusion. We consequently question the claimed existence of scaling laws of the search behaviour of marine predators and mussels, since such conclusions were reached using incorrect methods. We discourage the suggested potential use of "Lévy-like walks" when modelling consequences of fishing and climate change, and caution that any resulting advice to managers of marine ecosystems would be problematic. For reproducibility and future work we provide R source code for all calculations.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

USAF (United States Air Force) Stability and Control DATCOM (Data Compendium)

DTIC Science & Technology

1978-04-01

regression analysis involves the study of a group of variables to determine their effect on a given parameter. Because of the empirical nature of this...regression analysis of mathematical statistics. In general, a regression analysis involves the study of a group of variables to determine their effect on a...Excperiment, OSR TN 58-114, MIT Fluid Dynamics Research Group Rapt. 57-5, 1957. (U) 90. Kennet, H., and Ashley, H.: Review of Unsteady Aerodynamic Studies in

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Breastfeeding and maternal health outcomes: a systematic review and meta-analysis

PubMed Central

Chowdhury, Ranadip; Sinha, Bireshwar; Sankar, Mari Jeeva; Taneja, Sunita; Bhandari, Nita; Rollins, Nigel; Bahl, Rajiv; Martines, Jose

2015-01-01

Aim To evaluate the effect of breastfeeding on long-term (breast carcinoma, ovarian carcinoma, osteoporosis and type 2 diabetes mellitus) and short-term (lactational amenorrhoea, postpartum depression, postpartum weight change) maternal health outcomes. Methods A systematic literature search was conducted in PubMed, Cochrane Library and CABI databases. Outcome estimates of odds ratios or relative risks or standardised mean differences were pooled. In cases of heterogeneity, subgroup analysis and meta-regression were explored. Results Breastfeeding >12 months was associated with reduced risk of breast and ovarian carcinoma by 26% and 37%, respectively. No conclusive evidence of an association between breastfeeding and bone mineral density was found. Breastfeeding was associated with 32% lower risk of type 2 diabetes. Exclusive breastfeeding and predominant breastfeeding were associated with longer duration of amenorrhoea. Shorter duration of breastfeeding was associated with higher risk of postpartum depression. Evidence suggesting an association of breastfeeding with postpartum weight change was lacking. Conclusion This review supports the hypothesis that breastfeeding is protective against breast and ovarian carcinoma, and exclusive breastfeeding and predominant breastfeeding increase the duration of lactational amenorrhoea. There is evidence that breastfeeding reduces the risk of type 2 diabetes. However, an association between breastfeeding and bone mineral density or maternal depression or postpartum weight change was not evident. PMID:26172878

Routine educational outcome measures in health studies: Key Stage 1 in the ORACLE Children Study follow-up of randomised trial cohorts.

PubMed

Jones, David R; Pike, Katie; Kenyon, Sara; Pike, Laura; Henderson, Brian; Brocklehurst, Peter; Marlow, Neil; Salt, Alison; Taylor, David J

2011-01-01

Statutory educational attainment measures are rarely used as health study outcomes, but Key Stage 1 (KS1) data formed secondary outcomes in the long-term follow-up to age 7 years of the ORACLE II trial of antibiotic use in preterm babies. This paper describes the approach, compares different approaches to analysis of the KS1 data and compares use of summary KS1 (level) data with use of individual question scores. 3394 children born to women in the ORACLE Children Study and resident in England at age 7. Analysis of educational achievement measured by national end of KS1 data (KS1) using Poisson regression modelling and anchoring of the KS1 data using external standards. KS1 summary level data were obtained for 3239 (95%) eligible children; raw individual question scores were obtained for 1899 (54%). Use of individual question scores where available did not change the conclusion of no evidence of treatment effects based on summary KS1 outcome data. When accessible for medical research purposes, routinely collected educational outcome data may have advantages of low cost and standardised definition. Here, summary scores lead to similar conclusions to raw (individual question) scores and so are attractive and cost-effective alternatives.

Quasi-experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: A Systematic Review.

PubMed

Alsaggaf, Rotana; O'Hara, Lyndsay M; Stafford, Kristen A; Leekha, Surbhi; Harris, Anthony D

2018-02-01

OBJECTIVE A systematic review of quasi-experimental studies in the field of infectious diseases was published in 2005. The aim of this study was to assess improvements in the design and reporting of quasi-experiments 10 years after the initial review. We also aimed to report the statistical methods used to analyze quasi-experimental data. DESIGN Systematic review of articles published from January 1, 2013, to December 31, 2014, in 4 major infectious disease journals. METHODS Quasi-experimental studies focused on infection control and antibiotic resistance were identified and classified based on 4 criteria: (1) type of quasi-experimental design used, (2) justification of the use of the design, (3) use of correct nomenclature to describe the design, and (4) statistical methods used. RESULTS Of 2,600 articles, 173 (7%) featured a quasi-experimental design, compared to 73 of 2,320 articles (3%) in the previous review (P<.01). Moreover, 21 articles (12%) utilized a study design with a control group; 6 (3.5%) justified the use of a quasi-experimental design; and 68 (39%) identified their design using the correct nomenclature. In addition, 2-group statistical tests were used in 75 studies (43%); 58 studies (34%) used standard regression analysis; 18 (10%) used segmented regression analysis; 7 (4%) used standard time-series analysis; 5 (3%) used segmented time-series analysis; and 10 (6%) did not utilize statistical methods for comparisons. CONCLUSIONS While some progress occurred over the decade, it is crucial to continue improving the design and reporting of quasi-experimental studies in the fields of infection control and antibiotic resistance to better evaluate the effectiveness of important interventions. Infect Control Hosp Epidemiol 2018;39:170-176.

Genetic polymorphisms in pre-miRNAs predict the survival of non-small-cell lung cancer in Chinese population: a cohort study and a meta-analysis

PubMed Central

Xia, Lingzi; Yin, Zhihua; Li, Xuelian; Ren, Yangwu; Zhang, Haibo; Zhao, Yuxia; Zhou, Baosen

2017-01-01

Background To explore the association of genetic polymorphisms in pre-miRNA 30c-1 rs928508 and pre-miRNA 27a rs895819 with non-small-cell lung cancer prognosis. Materials and Methods 480 patients from five hospitals were enrolled in this prospective cohort study. They were followed up for five years. The association between genotypes and overall survival was assessed by Cox proportional hazards regression models. A meta-analysis was conducted to provide evidence for the effect of microRNA 27a rs895819 on cancer survival. Results G-allele containing genotypes of microRNA 30c-1 polymorphisms and C-allele containing genotypes of microRNA 27a were significantly associated with poorer overall survival. Multivariate Cox regression models indicated that these genetic polymorhpisms were independently predictive factors of poorer overall survival. In stratified analysis, the effect was observed in many strata. The significant joint effect was also observed in our study. Patients with G allele of microRNA 30c-1 rs928508 and C allele of microRNA 27a rs895819 had the poorer overall survival than patients with C allele of rs928508 and T allele of rs895819. The effect of the microRNA 27a rs895819 on non-small cell lung cancer overall survival was supported by the meta-analysis results. Conclusions The two single nucleotide polymorphisms in microRNA 30c-1 and microRNA 27a can predict the outcome of non-small cell lung cancer patients and they may decrease the sensitivity to anti-cancer drugs. PMID:29100439

Is Tamsulosin 0.2 mg Effective and Safe as a First-Line Treatment Compared with Other Alpha Blockers?: A Meta-Analysis and a Moderator Focused Study

PubMed Central

Shim, Sung Ryul; Chang, In Ho; Shin, In Soo; Hwang, Sung Dong; Kim, Khae Hwan; Yoon, Sang Jin; Song, Yun Seob

2016-01-01

Purpose Tamsulosin 0.2 mg is used widely in Asian people, but the low dose has been studied less than tamsulosin 0.4 mg or other alpha blockers of standard dose. This study investigated the efficacy and safety of tamsulosin 0.2 mg by a meta-analysis and meta-regression. Materials and Methods We conducted a meta-analysis of efficacy of tamsulosin 0.2 mg using International Prostate Symptom Score (IPSS), maximal urinary flow rate (Qmax), post-voided residual volume (PVR), and quality of life (QoL). Safety was analyzed using adverse events. Relevant studies were searched using MEDLINE, EMBASE, and Cochrane library from January 1980 to June 2013. Results Ten studies were included with a total sample size of 1418 subjects [722 tamsulosin 0.2 mg group and 696 other alpha-blockers (terazosin, doxazosin, naftopidil, silodosin) group]. Study duration ranged from 4 to 24 weeks. The pooled overall standardized mean differences (SMD) in the mean change of IPSS from baseline for the tamsulosin group versus the control group was 0.02 [95% confidence interval (CI); -0.20, 0.25]. The pooled overall SMD in the mean change of QoL from baseline for the tamsulosin group versus the control group was 0.16 (95% CI; -0.16, 0.48). The regression analysis with the continuous variables (number of patients, study duration) revealed no significance in all outcomes as IPSS, QoL, and Qmax. Conclusion This study clarifies that tamsulosin 0.2 mg has similar efficacy and fewer adverse events compared with other alpha-blockers as an initial treatment strategy for men with lower urinary tract symptoms. PMID:26847294

Exposure to Fluoride in Drinking Water and Hip Fracture Risk: A Meta-Analysis of Observational Studies

PubMed Central

Yin, Xin-Hai; Huang, Guang-Lei; Lin, Du-Ren; Wan, Cheng-Cheng; Wang, Ya-Dong; Song, Ju-Kun; Xu, Ping

2015-01-01

Background Many observational studies have shown that exposure to fluoride in drinking water is associated with hip fracture risk. However, the findings are varied or even contradictory. In this work, we performed a meta-analysis to assess the relationship between fluoride exposure and hip fracture risk. Methods PubMed and EMBASE databases were searched to identify relevant observational studies from the time of inception until March 2014 without restrictions. Data from the included studies were extracted and analyzed by two authors. Summary relative risks (RRs) with corresponding 95% confidence intervals (CIs) were pooled using random- or fixed-effects models as appropriate. Sensitivity analyses and meta-regression were conducted to explore possible explanations for heterogeneity. Finally, publication bias was assessed. Results Fourteen observational studies involving thirteen cohort studies and one case-control study were included in the meta-analysis. Exposure to fluoride in drinking water does not significantly increase the incidence of hip fracture (RRs, 1.05; 95% CIs, 0.96–1.15). Sensitivity analyses based on adjustment for covariates, effect measure, country, sex, sample size, quality of Newcastle–Ottawa Scale scores, and follow-up period validated the strength of the results. Meta-regression showed that country, gender, quality of Newcastle–Ottawa Scale scores, adjustment for covariates and sample size were not sources of heterogeneity. Little evidence of publication bias was observed. Conclusion The present meta-analysis suggests that chronic fluoride exposure from drinking water does not significantly increase the risk of hip fracture. Given the potential confounding factors and exposure misclassification, further large-scale, high-quality studies are needed to evaluate the association between exposure to fluoride in drinking water and hip fracture risk. PMID:26020536

Structural equation model of factors related to quality of life for community-dwelling schizophrenic patients in Japan

PubMed Central

2014-01-01

Background This study aimed to clarify how community mental healthcare systems can be improved. Methods We included 79 schizophrenic patients, aged 20 to 80 years, residing in the Tokyo metropolitan area who regularly visited rehabilitation facilities offering assistance to psychiatric patients and were receiving treatment on an outpatient basis. No subjects had severe cognitive disorders or were taking medication with side effects that could prevent the completion of questionnaires. Questionnaires included items related to quality of life, self-efficacy, self-esteem, psychosis based on the Behavior and Symptom Identification Scale, health locus of control, and socio-demographic factors. We performed multiple linear regression analysis with quality of life as the dependent variable and, based on covariance structural analysis, evaluated the goodness of fit of the resulting structural equations models. Results Self-efficacy, self-esteem, and degree of psychosis significantly impacted quality of life. Marital status, age, and types of medications also influenced quality of life. Multiple linear regression analysis revealed psychiatric symptoms (Behavior and Symptom Identification Scale-32 [daily living and role functioning] (Beta = −0.537, p < 0.001) and self-efficacy (Beta = 0.249, p < 0.05) to be predictors of total quality of life score. Based on covariance structural analysis, the resulting model was found to exhibit reasonable goodness of fit. Conclusions Self-efficacy had an especially strong and direct impact on QOL. Therefore, it is important to provide more positive feedback to patients, provide social skills training based on cognitive behavioral therapy, and engage patients in role playing to improve self-efficacy and self-concept. PMID:25101143

Induction of osteoporosis with its influence on osteoporotic determinants and their interrelationships in rats by DEXA

PubMed Central

Heiss, Christian; Govindarajan, Parameswari; Schlewitz, Gudrun; Hemdan, Nasr Y.A.; Schliefke, Nathalie; Alt, Volker; Thormann, Ulrich; Lips, Katrin Susanne; Wenisch, Sabine; Langheinrich, Alexander C.; Zahner, Daniel; Schnettler, Reinhard

2012-01-01

Summary Background As women are the population most affected by multifactorial osteoporosis, research is focused on unraveling the underlying mechanism of osteoporosis induction in rats by combining ovariectomy (OVX) either with calcium, phosphorus, vitamin C and vitamin D2/D3 deficiency, or by administration of glucocorticoid (dexamethasone). Material/Methods Different skeletal sites of sham, OVX-Diet and OVX-Steroid rats were analyzed by Dual Energy X-ray Absorptiometry (DEXA) at varied time points of 0, 4 and 12 weeks to determine and compare the osteoporotic factors such as bone mineral density (BMD), bone mineral content (BMC), area, body weight and percent fat among different groups and time points. Comparative analysis and interrelationships among osteoporotic determinants by regression analysis were also determined. Results T scores were below-2.5 in OVX-Diet rats at 4 and 12 weeks post-OVX. OVX-diet rats revealed pronounced osteoporotic status with reduced BMD and BMC than the steroid counterparts, with the spine and pelvis as the most affected skeletal sites. Increase in percent fat was observed irrespective of the osteoporosis inducers applied. Comparative analysis and interrelationships between osteoporotic determinants that are rarely studied in animals indicate the necessity to analyze BMC and area along with BMD in obtaining meaningful information leading to proper prediction of probability of osteoporotic fractures. Conclusions Enhanced osteoporotic effect observed in OVX-Diet rats indicates that estrogen dysregulation combined with diet treatment induces and enhances osteoporosis with time when compared to the steroid group. Comparative and regression analysis indicates the need to determine BMC along with BMD and area in osteoporotic determination. PMID:22648240

The impact of loneliness on self-rated health symptoms among victimized school children

PubMed Central

2012-01-01

Background Loneliness is associated with peer victimization, and the two adverse experiences are both related to ill health in childhood and adolescence. There is, however, a lack of knowledge on the importance of loneliness among victimized children. Therefore, possible modifying effects of loneliness on victimized school children’s self-rated health were assessed. Methods A population based cross-section study included 419 children in grades 1–10 from five schools. The prevalence of loneliness and victimization across grades was analyzed by linear test for trend, and associations of the adverse experiences with four health symptoms (sadness, anxiety, stomach ache, and headache) were estimated by logistic regression. Results In crude regression analysis, both victimization and loneliness showed positive associations with all the four health symptoms. However, in multivariable analysis, the associations of victimization with health symptoms were fully attenuated except for headache. In contrast, loneliness retained about the same strength of associations in the multivariable analysis as in the crude analysis. More detailed analyses demonstrated that children who reported both victimization and loneliness had three to seven times higher prevalence of health symptoms compared to children who reported neither victimization nor loneliness (the reference group). Rather surprisingly, victimized children who reported no loneliness did not have any higher prevalence of health symptoms than the reference group, whereas lonely children without experiences of victimization had almost the same prevalence of health symptoms (except for stomach ache) as children who were both victimized and lonely. Conclusions Adverse effects of loneliness need to be highlighted, and for victimized children, experiences of loneliness may be an especially harsh risk factor related to ill health. PMID:22643050

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

PubMed

Wardenaar, K J; van Loo, H M; Cai, T; Fava, M; Gruber, M J; Li, J; de Jonge, P; Nierenberg, A A; Petukhova, M V; Rose, S; Sampson, N A; Schoevers, R A; Wilcox, M A; Alonso, J; Bromet, E J; Bunting, B; Florescu, S E; Fukao, A; Gureje, O; Hu, C; Huang, Y Q; Karam, A N; Levinson, D; Medina Mora, M E; Posada-Villa, J; Scott, K M; Taib, N I; Viana, M C; Xavier, M; Zarkov, Z; Kessler, R C

2014-11-01

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI.

PubMed

Spisák, Tamás; Jakab, András; Kis, Sándor A; Opposits, Gábor; Aranyi, Csaba; Berényi, Ervin; Emri, Miklós

2014-01-01

Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that "resting-state" fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons.

[Job Satisfaction of Young Professionals in Health Care].

PubMed

Ulrich, Gert; Homberg, Angelika; Karstens, Sven; Goetz, Katja; Mahler, Cornelia

2017-05-29

Background Job satisfaction in health care is currently important in view of workforce shortage in the health care area. The purpose of this study was to evaluate job satisfaction in young health professionals and to identify factors possibly influencing overall job satisfaction. Methods About one year after graduating from vocational training, a total of 579 graduates from various health care professions [Nursing (N), Nursing and Geriatric Nursing; Therapy (TP), Physical therapy and Logopaedics; Diagnostics (D), Diagnostic Radiography and Biomedical Science], were invited to participate in an online-survey. Job satisfaction was assessed with the 10-item Warr-Cook-Wall (WCW) job satisfaction questionnaire. Descriptive analysis of the WCW was performed, and the impact of various factors on job satisfaction was determined by stepwise linear regression analysis. Results In total, 189 graduates (N, n=121; TP, n=32; D, n=36) were included in data analysis (32.6% response rate). Overall job satisfaction in all young professionals was 4.9±1.6 (mean±SD) and was slightly higher in TP (5.4±1.4) compared with N (4.7±1.6) and D (5.0±1.5), respectively. Highest satisfaction was identified with "colleagues" and lowest satisfaction with "income" was identified in all professional groups. Colleagues and fellow workers showed the highest score of association regarding overall job satisfaction in regression analysis. Conclusions As a whole, our data suggest good to very good satisfaction in various WCW items of job satisfaction. "Colleagues" were shown to have a high impact on job satisfaction. To improve the attractiveness of job profiles in health care, the presented results may provide a valuable input regarding workforce shortage. © Georg Thieme Verlag KG Stuttgart · New York.

Co-morbidity but not dysglycaemia reduces quality of life in patients with type-2 diabetes treated with oral mono- or dual combination therapy – an analysis of the DiaRegis registry

PubMed Central

2013-01-01

Background Type-2 diabetes mellitus has a major impact on health related quality of life (HRQoL). We aimed to identify patient and treatment related variables having a major impact. Methods DiaRegis is a prospective diabetes registry. The EQ-5D was used to describe differences in HRQoL at baseline. Odds ratios (OR) with 95% confidence intervals (CI) were determined from univariable regression analysis. For the identification of independent predictors of a low score on the EQ-5D, multivariable unconditional logistic regression analysis was performed. Results A total of 2,760 patients were available for the present analysis (46.7% female, median age 66.2 years). Patients had considerable co-morbidity (18.3% coronary artery disease, 10.6% heart failure, 5.9% PAD and 5.0% stroke/TIA). Baseline HbA1c was 7.4%, fasting- and postprandial plasma glucose 139 mg/dl and 183 mg/dl. The median EQ-5D was 0.9 (interquartile range [IQR] 0.8–1.0). Independent predictors for a low EQ-5D were age > 66 years (OR 1.49; 95%CI 1.08–2.06), female gender (2.11; 1.55–2.86), hypertension (1.73; 1.03–2.93), peripheral neuropathy (1.62; 0.93–2.84) and clinically relevant depression (11.01; 3.97–30.50). There was no influence of dysglycaemia on the EQ-5D score. Conclusion The present study suggests, that co-morbidity but not average glycaemic control reduces health related quality of life in type 2 diabetes mellitus. PMID:23510200

A retrospective analysis of the role of proton pump inhibitors in colorectal cancer disease survival

PubMed Central

Graham, C.; Orr, C.; Bricks, C.S.; Hopman, W.M.; Hammad, N.; Ramjeesingh, R.

2016-01-01

Background Proton pump inhibitors (ppis) are a commonly used medication. A limited number of studies have identified a weak-to-moderate association between ppi use and colorectal cancer (crc) risk, but none to date have identified an effect of ppi use on crc survival. We therefore postulated that an association between ppi use and crc survival might potentially exist. Methods We performed a retrospective chart review of 1304 crc patients diagnosed from January 2005 to December 2011 and treated at the Cancer Centre of Southeastern Ontario. Kaplan–Meier analysis and Cox proportional hazards regression models were used to evaluate overall survival (os). Results We identified 117 patients (9.0%) who were taking ppis at the time of oncology consult. Those taking a ppi were also more often taking asa or statins (or both) and had a statistically significantly increased rate of cardiac disease. No identifiable difference in tumour characteristics was evident in the two groups, including tumour location, differentiation, lymph node status, and stage. Univariate analysis identified a statistically nonsignificant difference in survival, with those taking a ppi experiencing lesser 1-year (82.1% vs. 86.7%, p = 0.161), 2-year (70.1% vs. 76.8%, p = 0.111), and 5-year os (55.2% vs. 62.9%, p = 0.165). When controlling for patient demographics and tumour characteristics, multivariate Cox regression analysis identified a statistically significant effect of ppi in our patient population (hazard ratio: 1.343; 95% confidence interval: 1.011 to 1.785; p = 0.042). Conclusions Our results suggest a potential adverse effect of ppi use on os in crc patients. These results need further evaluation in prospective analyses. PMID:28050148

Performance of Photoscreener in Detection of Refractive Error in All Age Groups and Amblyopia Risk Factors in Children in a Tribal District of Odisha: The Tribal Odisha Eye Disease Study (TOES) # 3

PubMed Central

Panda, Lapam; Barik, Umasankar; Nayak, Suryasmita; Barik, Biswajit; Behera, Gyanaranjan; Kekunnaya, Ramesh

2018-01-01

Purpose To evaluate effectiveness of Welch Allyn Spot Vision Screener in detecting refractive error in all age groups and amblyopia risk factors in children in a tribal district of India. Methods All participants received dry retinoscopy and photorefraction; children also received cycloplegic retinoscopy. Statistical analysis included Bland-Altman and coefficient of determination (R2). Results Photoscreener could not elicit a response in 113 adults and 5 children of 580 recruited participants. In Bland-Altman analysis mean difference of Spot screener spherical equivalent (SSSE) and dry retinoscopy spherical equivalent (DRSE) was 0.32 diopters (D) in adults and 0.18 D in children; this was an overestimation of hyperopia and underestimation of myopia. In Bland-Altman analysis of SSSE and cycloplegic retinoscopy spherical equivalent (CRSE) the mean difference was −0.30 D in children; this was an overestimation of myopia and underestimation of hyperopia. In regression analysis the relationship between SSSE and DRSE was poor in adults (R2 = 0.50) and good in children (R2 = 0.92). Cubic regression model for Spot versus cycloretinoscopy in children was: CRSE = 0.34 + 0.85 SSSE − 0.01 SSSE2 + 0.006 SSSE3. It was 87% accurate. Sensitivity and specificity of Spot in detecting amblyopia risk factors (2013 American Association for Pediatric Ophthalmology and Strabismus [AAPOS] criteria) was 93.3% and 96.9% respectively. Sensitivity of Spot screener in detection of amblyopia was 72%. Conclusions Photoscreener has 87% accuracy in refraction in children. Its value could be used for subjective correction tests. Translational Relevance Photoscreening could complement traditional retinoscopy to address refractive error in children in a resource-limited facility region. PMID:29881649

Home-measured heart rate is associated with albuminuria in patients with type 2 diabetes mellitus: a post-hoc analysis of a cross-sectional multicenter study.

PubMed

Ushigome, Emi; Fukui, Michiaki; Hamaguchi, Masahide; Tanaka, Toru; Atsuta, Haruhiko; Ohnishi, Masayoshi; Tsunoda, Sei; Yamazaki, Masahiro; Hasegawa, Goji; Nakamura, Naoto

2014-06-01

Epidemiological studies have shown that elevated heart rate (HR) is associated with an increased risk of diabetic nephropathy, as well as cardiovascular events and mortality, in patients with type 2 diabetes mellitus. Recently, the advantages of the self-measurement of blood pressure (BP) at home have been recognized. The aim of this study was to investigate the relationship between home-measured HR and albuminuria in patients with type 2 diabetes mellitus. We designed a cross-sectional multicenter analysis of 1245 patients with type 2 diabetes mellitus. We investigated the relationship between the logarithm of urinary albumin excretion (log UAE) and home-measured HR or other factors that may be related to nephropathy using univariate and multivariate analyses. Multivariate linear regression analysis indicated that age, duration of diabetes mellitus, morning HR (β=0.131, P<0.001), morning systolic BP (β=0.311, P<0.001), hemoglobin A1C, triglycerides, daily consumption of alcohol, use of angiotensin II receptor blockers and use of beta-blockers were independently associated with the log UAE. Multivariate logistic regression analysis indicated that the odds ratio (95% confidence interval) associated with 1 beat per min and 1 mm Hg increases in the morning HR and morning systolic BP for albuminuria were 1.024 ((1.008-1.040), P=0.004) and 1.039 ((1.029-1.048), P<0.001), respectively. In conclusion, home-measured HR was significantly associated with albuminuria independent of the known risk factors for nephropathy, including home-measured systolic BP, in patients with type 2 diabetes mellitus.

Risk Factors of Catheter-Related Thrombosis (CRT) in Cancer Patients: A Patient-Level Data (IPD) Meta-Analysis of Clinical Trials and Prospective Studies

PubMed Central

Saber, W.; Moua, T.; Williams, E. C.; Verso, M.; Agnelli, G.; Couban, S.; Young, A.; De Cicco, M.; Biffi, R.; van Rooden, C. J.; Huisman, M. V.; Fagnani, D.; Cimminiello, C.; Moia, M.; Magagnoli, M.; Povoski, S. P.; Malak, S. F.; Lee, A. Y.

2010-01-01

Background Knowledge of independent, baseline risk factors of catheter-related thrombosis (CRT) may help select adult cancer patients at high risk to receive thromboprophylaxis. Objectives We conducted a meta-analysis of individual patient-level data to identify these baseline risk factors. Patients/Methods MEDLINE, EMBASE, CINAHL, CENTRAL, DARE, Grey literature databases were searched in all languages from 1995-2008. Prospective studies and randomized controlled trials (RCTs) were eligible. Studies were included if original patient-level data were provided by the investigators and if CRT was objectively confirmed with valid imaging. Multivariate logistic regression analysis of 17 prespecified baseline characteristics was conducted. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated. Results A total sample of 5636 subjects from 5 RCTs and 7 prospective studies was included in the analysis. Among these subjects, 425 CRT events were observed. In multivariate logistic regression, the use of implanted ports as compared with peripherally implanted central venous catheters (PICC), decreased CRT risk (OR = 0.43; 95% CI, 0.23-0.80), whereas past history of deep vein thrombosis (DVT) (OR = 2.03; 95% CI, 1.05-3.92), subclavian venipuncture insertion technique (OR = 2.16; 95% CI, 1.07-4.34), and improper catheter tip location (OR = 1.92; 95% CI, 1.22-3.02), increased CRT risk. Conclusions CRT risk is increased with using PICC catheters, previous history of DVT, subclavian venipuncture insertion technique and improper positioning of the catheter tip. These factors may be useful for risk stratifying patients to select those for thromboprophylaxis. Prospective studies are needed to validate these findings. PMID:21040443

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument

PubMed Central

2013-01-01

Background This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Methods Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Results Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach’s alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. Conclusions This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies. PMID:23642223

[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Prediction by regression and intrarange data scatter in surface-process studies

USGS Publications Warehouse

Toy, T.J.; Osterkamp, W.R.; Renard, K.G.

1993-01-01

Modeling is a major component of contemporary earth science, and regression analysis occupies a central position in the parameterization, calibration, and validation of geomorphic and hydrologic models. Although this methodology can be used in many ways, we are primarily concerned with the prediction of values for one variable from another variable. Examination of the literature reveals considerable inconsistency in the presentation of the results of regression analysis and the occurrence of patterns in the scatter of data points about the regression line. Both circumstances confound utilization and evaluation of the models. Statisticians are well aware of various problems associated with the use of regression analysis and offer improved practices; often, however, their guidelines are not followed. After a review of the aforementioned circumstances and until standard criteria for model evaluation become established, we recommend, as a minimum, inclusion of scatter diagrams, the standard error of the estimate, and sample size in reporting the results of regression analyses for most surface-process studies. ?? 1993 Springer-Verlag.

Quantile regression for the statistical analysis of immunological data with many non-detects.

PubMed

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions

EPA Pesticide Factsheets

Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.