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Risk factors for rescue analgesic use on the first postoperative day after upper limb surgery performed under single-injection brachial plexus block: a retrospective study of 930 cases

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JA CLINICAL REPORTS 2017年第1期3卷 39页

作者： Watanabe, Tatsunori Moriya, Koji Yoda, Takuya Tsubokawa, Naoto Petrenko, Andrey B. Baba, Hiroshi Niigata Univ Div Anesthesiol Grad Sch Med & Dent Sci Chuo Ku 1-754 Asahimachi Dori Niigata 9518520 Japan Niigata Hand Surg Fdn Seiro Japan Niigata Univ Uonuma Inst Community Med Dept Orthoped Med & Dent Hosp Minami Uonuma Japan

Background: Postoperative pain management after upper limb surgery is important for preventing adverse events that can prolong hospital stay and cause readmission. This study aimed to identify the risk factors associated with rescue analgesic use on the first postoperative day after upper limb surgery performed under single-injection brachial plexus block (BPB). Findings: We retrospectively analyzed records from 930 patients who underwent upper limb surgery under a single-injection BPB. Postoperatively, patients were administered oral loxoprofen regularly and rescue analgesics when analgesia was insufficient. We assessed the association between patient, surgical information, and rescue analgesic use on the first day after surgery (from 7:00 PM on the day of surgery to 7:00 AM on the first postoperative day), using a logistic regression model. Multivariate analysis revealed a significant association between rescue analgesic use and bone surgery, in particular, osteotomy, ligament repair and reconstruction, osteosynthesis, treatment for an amputated digit, and surgical duration. Conclusion: Bone surgery (osteotomy, ligament repair and reconstruction, osteosynthesis, treatment for an amputated digit) and a longer operative time were risk factors for rescue analgesic use for treating postoperative pain after upper limb surgery performed under single-injection BPB.

关键词： Upper limb surgery Brachial plexus block Rescue analgesia Risk factors logistic regression model

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Simulation-based Inference in a Zero-inflated Bernoulli regression model

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2016年第10期45卷 3597-3614页

作者： Diop, Aba Diop, Aliou Dupuy, Jean-Francois Univ La Rochelle Lab Math Image & Applicat La Rochelle France Univ Gaston Berger LERSTAD St Louis Senegal IRMAR Inst Natl Sci Appl Rennes Rennes France

The logistic regression model has become a standard tool to investigate the relationship between a binary outcome and a set of potential predictors. When analyzing binary data, it often arises that the observed proportion of zeros is greater than expected under the postulated logistic model. Zero-inflated binomial (ZIB) models have been developed to fit binary data that contain too many zeros. Maximum likelihood estimators in these models have been proposed and their asymptotic properties established. Several aspects of ZIB models still deserve attention however, such as the estimation of odds-ratios and event probabilities. In this article, we propose estimators of these quantities and we investigate their properties both theoretically and via simulations. Based on these results, we provide recommendations about the range of conditions (minimum sample size, maximum proportion of zeros in excess) under which a reliable statistical inference on the odds-ratios and event probabilities can be obtained in a ZIB regression model. A real-data example illustrates the proposed estimators.

关键词： Convergence logistic regression model Maximum likelihood estimation Mixture model Simulations 62 62J12

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Stochastic modeling for Coliform Count Assessment in Ground Water

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Journal of Statistical Science and Application 2017年第2期5卷 64-79页

作者： A. Udaya M. Kumaran P.V.Pushpaja Department of Statistics Nehru Arts and Science College KanhangadKasaragod Kerala India

Stochastic models are derived to estimate the level of coliform count in terms of MPN index, one of the most important water quality characteristic in ground water based on a set of water source location and soil characteristics. The study is based on about twenty location and soil characteristics, majority of them are observed through laboratory analysis of soil and water samples collected from nearly thee hundred locations of drinking water sources, wells and bore wells selected at random from the district of Kasaragod. The water contamination in wells are found to be relatively more as compared to bore wells. The study reveals that only 7 % of the wells and 40 o~ of the bore wells of the district are within the permissible limit of WHO standard of drinking water quality. The level of contamination is very high in the hospital premises and is very low in the forest area. Two separate multiple ordinal logistic regression models are developed to predict the level of coliform count, one for well and the other for bore well. The significant feature of this study is that in addition to scientifically proving the dependence of the water quality on the distances from waste disposal area and septic tanks etc., it highlights the dependence of two other very significant soil characteristics, the soil organic carbon and soil porosity. The models enable to predict the quality of water in a location based on the set of soil and location characteristics. One of the important uses of the model is in fixing safe locations for waste dump area, septic tank, digging well etc. in town planning, designing residential layouts, industrial layouts, hospital/hostel construction etc. This is the first ever study to describe the ground water quality in terms of the location and soil characteristics.

关键词： Generalized linear model logistic regression model Ordinal logistic regression model Coliform count MPN index Prediction Stochastic model Water quality.

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Methods for evaluating the utilities of local and global maps for increasing the precision of estimates of subtropical forest area

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CANADIAN JOURNAL OF FOREST RESEARCH 2016年第7期46卷 924-932页

作者： McRoberts, Ronald E. Vibrans, Alexander C. Sannier, Christophe Naesset, Erik Hansen, Matthew C. Walters, Brian F. Lingner, Debora V. US Forest Serv No Res Stn St Paul MN USA Univ Reg Blumenau Blumenau SC Brazil Syst Informat Reference Spatiale Villeneuve Dascq France Norwegian Univ Life Sci Dept Ecol & Nat Resource Management As Norway Univ Maryland Dept Geog Sci College Pk MD 20742 USA

For a study area in the Brazilian state of Santa Catarina, the utilities of local and global forest maps in combination with poststratified and model-assisted estimators for increasing the precision of estimates of forest area were compared. Auxiliary information was in the form of local maps, the recent Global Forest Change map, and combinations of these maps. The poststratified estimators produced estimates of greater precision than the model-assisted regression estimators for maps of categorical variables, but the model assisted estimators produced estimates of greater precision for maps of continuous variables. The Global Forest Change map was the least accurate of all the maps, but it produced estimates of forest area that were similar to those for the other maps and that were more precise than if the map had not been used. Thus, the Global Forest Change map may be an attractive option if local maps are not available or cannot be constructed. The primary contributions of the study are two-fold. First, this is one of the first case studies that rigorously assess the utility of global maps for national estimation. After accumulation of a few more such studies, broader generalizations should be forthcoming. Second, a statistical basis is provided for the previously unexplained greater precision for poststratified estimators than for model-assisted estimators.

关键词： logistic regression model inference Santa Catarina Brazil

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A Multi-national Survey of Low-Energy and Smoking Materials Ignition Fires

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FIRE TECHNOLOGY 2016年第6期52卷 1709-1735页

作者： Anderson, Austin Janssens, Marc Univ Texas Austin Dept Mech Engn 204 East Dean Keeton St Austin TX 78712 USA Southwest Res Inst Ctr Nucl Waste Regulatory Anal 6220 Culebra Rd San Antonio TX 78238 USA

The three-part study described in this paper involved a detailed evaluation of fire statistics from four countries to compare the number of deaths and injuries from structure fires started by a small open flame ignition source to casualty counts from fires started by smoking materials. First, a qualitative multi-national comparison of low-energy and smoking materials ignition fires is made based on fire statistics obtained from the U.S., the U.K., Japan, and Finland for the period between 2002 and 2012. From this comparison it can be concluded that, compared to the other nations, the U.K. appears to have more of a problem with smoking materials ignition fires resulting in fatalities;and that Japan appears to have appreciably more smoking materials ignition fires, but not fatalities from such fires, than the other nations. A more detailed quantitative analysis is then performed to examine the contribution of low-energy (match, lighter, space heater, etc.) versus smoking materials (cigar, pipe, cigarette, etc.) ignition to the U.S. fire problem. An attempt was made to address two issues with the U.S. NFIRS database, i.e., the fact that it is based on a voluntary sample of U.S. fire department incident reports and that many of the data categories relevant to the present study contain unknown fields. From this analysis it is apparent that smoking materials ignition fires tend to more commonly result in fatalities than low-energy ignition fires, while the overall volume of low-energy ignition fires and corresponding losses and injuries are greater. Finally, a logistic regression model is presented that can be used to predict the probability that a fire resulting in a fatality was started by low-energy ignition based on the age and race of the victim, the item first ignited, and the season in the year when the fire took place. The model indicates that older persons are generally more susceptible to perishing in a fire resulting from smoking materials ignition rather than

关键词： Fire statistics logistic regression model Low-energy ignition fires Open flame ignition fires Smoking materials ignition fires

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Internal exposure levels of typical POPs and their associations with childhood asthma in Shanghai, China

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ENVIRONMENTAL RESEARCH 2016年 146卷 125-135页

作者： Meng, Ge Feng, Yan Nie, Zhiqing Wu, Xiaomeng Wei, Hongying Wu, Shaowei Yin, Yong Wang, Yan Shanghai Jiao Tong Univ Sch Publ Hlth Shanghai 200025 Peoples R China Shanghai Childrens Med Ctr Shanghai 200127 Peoples R China Shanghai Jiao Tong Univ Sch Environm Sci & Engn Shanghai 200240 Peoples R China Peking Univ Sch Publ Hlth Dept Occupat & Environm Hlth Sci Beijing 100191 Peoples R China Harvard Univ TH Chan Sch Publ Hlth Dept Environm Hlth Boston MA 02115 USA Shanghai Jiao Tong Univ Sch Med Hongqiao Int Inst Med Shanghai Tongren HospFac Basic Med Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Med Fac Publ Hlth Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Med MOE Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Xinhua Hosp Shanghai Key Lab Childrens Environm Hlth Shanghai 200240 Peoples R China

Polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) are common persistent organic pollutants (POPS) that may be associated with childhood asthma. The concentrations of PBDEs, PCBs and OCPs were analyzed in pooled serum samples from both asthmatic and non-asthmatic children. The differences in the internal exposure levels between the case and control groups were tested (p value <0.0012). The associations between the internal exposure concentrations of the POPs and childhood asthma were estimated based on the odds ratios (ORs) calculated using logistic regression models. There were significant differences in three PBDEs, 26 PCBs and seven OCPs between the two groups, with significantly higher levels in the cases. The multiple logistic regression models demonstrated that the internal exposure concentrations of a number of the POPs (23 PCBs, p,p'-DDE and alpha-HCH) were positively associated with childhood asthma. Some synergistic effects were observed when the children were co-exposed to the chemicals. BDE-209 was positively associated with asthma aggravation. This study indicates the potential relationships between the internal exposure concentrations of particular POPs and the development of childhood asthma. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Persistent organic pollutants Childhood asthma Internal exposure logistic regression model Positive association.

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Applications of regression models in Epidemiology 1

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2017年

作者： Erick Suárez Cynthia M. Pérez Roberto Rivera Melissa N. Martínez

ISBN: (数字)9781119212515

ISBN: (纸本)9781119212485

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: • Is based on the authors’ course notes from 20 years teaching regression modeling in public health courses • Provides exercises at the end of each chapter • Contains a solutions chapter with answers in STATA, SAS, SPSS, and R • Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of regression models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SUÁREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto

关键词： regression analysis statistical methods public health Applied regression Analysis Advanced Epidemiology Statistical Computing for Applying Statistical modeling linear regression model polynomial regression model weighted linear regression logistic regression model Poisson regression model STATA SAS SPSS R

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Analysis of Sideswipe Collision Precursors Considering the Spatial-Temporal Characteristics of Freeway Traffic

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JOURNAL OF TRANSPORTATION ENGINEERING 2016年第12期142卷 04016064-04016064页

作者： Wang, Jiangfeng Zhang, Qian Wang, Yinhai Weng, Jinxian Yan, Xuedong Beijing Jiaotong Univ MOE Key Lab Transportat Complex Syst Theory & Tec Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China Univ Washington Dept Civil & Environm Engn Seattle WA 98195 USA Shanghai Maritime Univ Coll Transport & Communicat Shanghai 201306 Peoples R China

To avoid bias caused by the high percentage of rear-end collisions in the generic models, only the observed sideswipe collisions on Highway I-5 in the central Puget Sound, Washington State, area are used to analyze the matched case-control logistic regression model. Considering the spatial-temporal characteristics of traffic flow and short-term variation of the sideswipe collision occurrence, a comprehensive analysis of sideswipe collision occurrence and its relationship with the freeway flow across lanes and detector locations are studied. The results imply that sideswipe collisions are more likely to occur at straight and level segments of multilane freeways in off-peak hours. High average occupancy and low average flow and speed variance upstream of collision location tend to increase the probability of sideswipe collision in congested scenarios. In contrast, high average speed and coefficient of variation in speed, low speed variance and coefficient of variation in occupancy, and high average absolute difference in speed between adjacent lanes downstream of collision location may decrease the likelihood of sideswipe collisions in uncongested conditions. Furthermore, the average absolute difference in occupancy and speed between upstream and downstream of the collisions location leads to an increase in the occurrence of sideswipe collisions, while standard deviation of absolute difference in occupancies and speeds exerts opposite effects. The sideswipe collision model proposed is validated using sideswipe collision data of SR 520 freeway, and both the transferability and stability of the proposed sideswipe collision model are statistically tested.

关键词： Sideswipe collision precursors logistic regression model Loop detector data Spatial-temporal character model validation

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A diagnostic of influential cases based on the information complexity criteria in generalized linear mixed models

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2016年第13期45卷 3751-3760页

作者： Shang, Junfeng Bowling Green State Univ Dept Math & Stat 450 Math Sci Bldg Bowling Green OH 43403 USA

modeling diagnostics assess models by means of a variety of criteria. Each criterion typically performs its evaluation upon a specific inferential objective. For instance, the well-known DFBETAS in linear regression models are a modeling diagnostic which is applied to discover the influential cases in fitting a model. To facilitate the evaluation of generalized linear mixed models (GLMM), we develop a diagnostic for detecting influential cases based on the information complexity (ICOMP) criteria for detecting influential cases which substantially affect the model selection criterion ICOMP. In a given model, the diagnostic compares the ICOMP criterion between the full data set and a case-deleted data set. The computational formula of the ICOMP criterion is evaluated using the Fisher information matrix. A simulation study is accomplished and a real data set of cancer cells is analyzed using the logistic linear mixed model for illustrating the effectiveness of the proposed diagnostic in detecting the influential cases.

关键词： Case-deletion Fisher information matrix GLMM ICOMP logistic regression model

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Development of injury prediction models for advanced automatic collision notification based on Japanese accident data

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INTERNATIONAL JOURNAL OF CRASHWORTHINESS 2016年第2期21卷 112-119页

作者： Yoshida, S. Hasegawa, T. Tominaga, S. Nishimoto, T. Honda Res & Dev Co Ltd Automobile R&D Ctr Utsunomiya Tochigi Japan Nihon Univ Coll Sci & Technol Tokyo 101 Japan Nihon Univ Coll Engn Fukushima Japan

In this paper, injury prediction models for estimating serious injury risk of occupants were developed based on accident data available in the Japanese statistical DB. Four types of model by crash direction (frontal crash model, near-side crash model, far-side crash model, rear-end crash model) were developed. These models were developed by using a logistic regression modelling technique based on data from Japanese ITARDA (Institute for Traffic Accident Research and Data Analysis) police-reported statistics, a large database for the last decade. Risk factors of the model are delta-V, belt use, multiple impact crash and occupant's age. Serious injury risk for four crash directions was estimated by the model. A comparison has been done between estimated serious injury risk and actual injury of Japanese ITARDA in-depth accident data (micro-data). The results show that the injury prediction model has a possibility for predicting injury risk based on onboard data and its application for post-crash safety.

关键词： Advanced automatic collision notification logistic regression model injury prediction

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