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Factors Affecting Length of Stay in the Pediatric Emergency Department

PEDIATRICS AND NEONATOLOGY 2013年第3期54卷 179-187页

作者： Li, Sung-Tse Chiu, Nan-Chang Kung, Wen-Chuan Chen, Juei-Chao Hsinchu Mackay Mem Hosp Dept Pediat Hsinchu 30070 Taiwan Taoyuan Innovat Inst Technol Dept Early Childhood Care & Educ Chungli Taiwan Mackay Med Nursing & Management Coll Taipei Taiwan Mackay Mem Hosp Dept Pediat Taipei Taiwan Hsinchu Mackay Mem Hosp Dept Nursing Hsinchu 30070 Taiwan Fu Jen Catholic Univ Coll Management Dept Stat & Informat Sci Taipei Taiwan

Background: A large volume of visits can cause an emergency department (ED) to become overcrowded, resulting in a longer length of stay (LOS). The objective of this study was to analyze factors affecting the LOS in the pediatric ED. Methods: Records of all visits to the pediatric ED of the study hospital, from July 1, 2006 to June 31, 2007, were retrospectively retrieved. Data were collected from the hospital's computerized records system. Eta-squared correlation ratio and Cramer's V test evaluated the associations between variables. Two-thirds of the database was randomized for the classification and regression tree (CART) model-building dataset, and one-third was used for the validation dataset. Results: A total of 29,035 patients visited the pediatric ED during the evaluation period. Of the total visits, 61.1% were due to complaints of fever. The mean LOS was 2.6 +/- 4.67 hours, and 74.3% of visits had an LOS of shorter than 2 hours. The CART analysis selected five factors (waiting time for hospitalization, laboratory tests, door-to-physician time, gastrointestinal symptoms, and patient outcome) to produce a total of nine subgroups of patients. The mean LOS of the model-building dataset closely correlated with that of the validation dataset (r(2) = 0.999). Conclusion: Patients who were waiting for hospitalization for less than 8 hours or were not admitted, those without any laboratory tests, those having door-to-physician time less than 60 minutes, and those without any gastrointestinal symptoms had the shortest LOS. Patients who waited for hospitalization for more than 16 hours had the longest LOS. Copyright (C) 2012, Taiwan Pediatric Association. Published by Elsevier Taiwan LLC. All rights reserved.

关键词： classification and regression tree length of stay pediatric emergency department

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Prediction of financial crises using statistic model and intelligent technologies in ubiquitous environments

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INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY 2013年第2期48卷 173-183页

作者： Senoguchi, Junsuke Kurahashi, Setsuya Univ Tsukuba Grad Sch Business Sci Bunkyo Ku 3-29-1 Ootsuka Tokyo 1120012 Japan

A large number of earlier studies partially revealed the mechanism of the financial crises in recent years. However, no study has yet conducted the variable selection from the mounds of factors including the critical component of key macro financial statistics. This study, using a traditional logistic model and intelligent system technologies, explored some key influential factors on the occurrence of the financial crises. As a result, the cyclical component of the current account as percentages of GDP and the cyclical component of the domestic loan as percentages of GDP have been proven a key factor to predict a financial crisis. In the present, China and Malaysia can be classified as a crises group with 77% of possibilities.

关键词： intelligent technologies classification and regression tree CART variable selection artificial intelligence

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Multi-Loci Analysis Reveals the Importance of Genetic Variations in Sensitivity of Platinum-Based Chemotherapy in Non-Small-Cell Lung Cancer

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MOLECULAR CARCINOGENESIS 2013年第12期52卷 923-931页

作者： Liu, Li Wu, Jing Zhong, Rong Wu, Chen Zou, Li Yang, Beifang Chen, Wei Zhu, Beibei Duan, Shengyu Yu, Dianke Tan, Wen Nie, Shaofa Lin, Dongxin Miao, Xiaoping Huazhong Univ Sci & Technol Tongji Med Coll Sch Publ Hlth Dept Epidemiol & Biostat Wuhan 430030 Peoples R China Huazhong Univ Sci & Technol Tongji Med Coll Sch Publ Hlth Key Lab Environm & HlthMinist Educ Wuhan 430030 Peoples R China Chinese Acad Med Sci Canc Inst & Hosp State Key Lab Mol Oncol Beijing 100730 Peoples R China Chinese Acad Med Sci Canc Inst & Hosp Dept Etiol & Carcinogenesis Beijing 100730 Peoples R China Peking Union Med Coll Beijing 100021 Peoples R China

Polymorphisms in DNA repair and apoptotic pathways may cause variations in chemosensitivity of non-small-cell lung cancer (NSCLC) through complex gene-gene and gene-environment interactions. A total of 200 advanced NSCLC patients who received platinum-based chemotherapies were recruited. The short-term clinical outcomes were classified as chemosensitive group, including complete remission (CR) and partial remission (PR), and chemoresistant group, namely stable disease (SD) and progression disease (PD) at the end of treatment. We applied multifactor dimensionality reduction (MDR), classification and regression tree (CART) and traditional logistic regression (LR) to explore high-order gene-gene and gene-environment interactions among 11 functional single nucleotide polymorphisms (SNPs), smoking status, cancer stages and treatment regimens in the response to chemotherapy. Multi-loci analyses consistently indicated that interactions among XRCC1 Arg194Trp, XPC PAT, FAS G-1377A, and FASL T-844C were associated with sensitivity to platinum-based chemotherapy. In MDR analysis, the four-factor model yielded the highest test accuracy of 0.72 (permutation P=0.001). In CART analysis, these four SNPs were the determinant nodes of the growth of regression tree. Patients carrying XRCC1 Arg194Arg, FAS-1377GG, and FASL-844T allele displayed completely no response to platinum, whereas patients with XRCC1 194Trp allele and XPC PAT +/+ had 68.8% response rate to platinum. In LR analysis, a significant gene-dosage effect was detected along with the increasing number of favorable genotypes of these four polymorphisms (P-trend=0.00002). Multi-loci analysis reveals the importance of genetic variations involved in DNA repair and apoptotic pathways in sensitivity of platinum-based chemotherapy in NSCLC. (c) 2012 Wiley Periodicals, Inc.

关键词： classification and regression tree multifactor dimensionality reduction single nucleotide polymorphism

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The Utility of Serum Hepcidin as a Biomarker for Late-Onset Neonatal Sepsis

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JOURNAL OF PEDIATRICS 2013年第1期162卷 67-71页

作者： Wu, Tai-Wei Tabangin, Meredith Kusano, Ryosuke Ma, Yan Ridsdale, Ross Akinbi, Henry Univ So Calif Keck Sch Med Div Neonatol Los Angeles CA 90033 USA Keio Univ Sch Med Dept Pediat Tokyo Japan Cincinnati Childrens Hosp Med Ctr Div Biostat & Epidemiol Cincinnati OH 45229 USA Cincinnati Childrens Hosp Med Ctr Div Neonatol Cincinnati OH 45229 USA

Objective To assess the utility of hepcidin, a potent regulator of host defense and inflammation, in the diagnosis of late-onset sepsis in very low birth weight infants. Study design We compared the diagnostic performance of hepcidin with C-reactive protein from the serum concentrations in acute and convalescent blood specimens obtained from 44 infants suspected of late-onset sepsis. The predictive accuracies were assessed from the areas under receiver operating characteristic curves and the cutoffs that differentiated infants with and without sepsis were identified using classification and regression tree analysis. Results Seventeen of the enrolled infants in this study were bacteremic and/or received antibiotics for neonatal sepsis for days (infants with sepsis). The concentrations of hepcidin were increased 4-fold in infants with compared with infants without sepsis (P < .0001) and returned to similar levels following therapy. The areas under receiver operating characteristic curves of hepcidin was 0.93 compared with 0.83 for C-reactive protein, P = .06. Hepcidin concentration >92.2 ng/mL correctly classified 91% of all infants (positive predictive value: 100%, negative predictive value: 87%, specificity: 100%, and sensitivity: 76%). Conclusion Serum hepcidin concentration may be a useful adjunct test, in addition to blood culture and other markers of infection, in the evaluation of late-onset sepsis in very low birth weight infants. (J Pediatr 2013;162:67-71).

关键词： CRP C-reactive protein CART classification and regression tree CV Coefficient of variation ln Natural logarithmic NPV Negative predictive value PPV Positive predictive value VLBW Very low birth weight

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A novel tree kernel partial least squares for modeling the structure-activity relationship

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JOURNAL OF CHEMOMETRICS 2013年第3-4期27卷 43-49页

作者： Huang, Xin Cao, Dong-Sheng Xu, Qing-Song Liang, Yi-Zeng Cent South Univ Sch Math & Stat Changsha 410075 Hunan Peoples R China Hunan City Univ Dept Math Yiyang 413000 Peoples R China Cent South Univ Res Ctr Modernizat Tradit Chinese Med Changsha 410083 Hunan Peoples R China

Kernel partial least squares (KPLS) has become a popular technique for regression and classification of complex data sets, which is a nonlinear extension of linear PLS in which training samples are transformed into a feature space via a nonlinear mapping. The PLS algorithm can then be carried out in the feature space. In the present study, we attempt to develop a novel tree KPLS (TKPLS) classification algorithm by constructing an informative kernel on the basis of decision tree ensembles. The constructed tree kernel can effectively discover the similarities of samples and select informative features by variable importance ranking in the process of building the kernel. Simultaneously, TKPLS can also handle nonlinear relationships in the structureactivity relationship data by such a kernel. Finally, three data sets related to different categorical bioactivities of compounds are used to evaluate the performance of TKPLS. The results show that the TKPLS algorithm can be regarded as an alternative and promising classification technique. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： kernel partial least squares structureactivity relationship kernel methods decision tree classification and regression tree

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A threshold analysis of dengue transmission in terms of weather variables and imported dengue cases in Australia

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EMERGING MICROBES & INFECTIONS 2013年第12期2卷 e87-e93页

作者： Huang, Xiaodong Clements, Archie C. A. Williams, Gail Milinovich, Gabriel Hu, Wenbiao Univ Queensland Infect Dis Epidemiol Unit Sch Populat Hlth Brisbane Qld 4006 Australia Queensland Univ Technol Inst Hlth & Biomed Innovat Sch Publ Hlth & Social Work Brisbane Qld 4006 Australia

Dengue virus (DENV) transmission in Australia is driven by weather factors and imported dengue fever (DF) cases. However, uncertainty remains regarding the threshold effects of high-order interactions among weather factors and imported DF cases and the impact of these factors on autochthonous DF. A time-series regression tree model was used to assess the threshold effects of natural temporal variations of weekly weather factors and weekly imported DF cases in relation to incidence of weekly autochthonous DF from 1 January 2000 to 31 December 2009 in Townsville and Cairns, Australia. In Cairns, mean weekly autochthonous DF incidence increased 16.3-fold when the 3-week lagged moving average maximum temperature was < 32 degrees C, the 4-week lagged moving average minimum temperature was >= 24 degrees C and the sum of imported DF cases in the previous 2 weeks was > 0. When the 3-week lagged moving average maximum temperature was >= 32 degrees C and the other two conditions mentioned above remained the same, mean weekly autochthonous DF incidence only increased 4.6-fold. In Townsville, the mean weekly incidence of autochthonous DF increased 10-fold when 3-week lagged moving average rainfall was >= 27 mm, but it only increased 1.8-fold when rainfall was < 27 mm during January to June. Thus, we found different responses of autochthonous DF incidence to weather factors and imported DF cases in Townsville and Cairns. Imported DF cases may also trigger and enhance local outbreaks under favorable climate conditions.

关键词： Aedes aegypti autochthonous dengue classification and regression tree dengue fever imported dengue

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Feature extraction for defect classification and yield enhancement in color filter and micro-lens manufacturing: An empirical study

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2013年第8期30卷 510-517页

作者： Chen, Ying-Jen Lin, Tzu-Hsiang Chang, Kuo-Hao Chien, Chen-Fu Natl Tsing Hua Univ Dept Ind Engn & Engn Management 101Sect 2Kuang Fu Rd Hsinchu 30013 Taiwan

Yield improvement is an important issue in semiconductor-manufacturing supply chains, including color filter and micro-lens manufacturing. In the color filter and micro-lens processes, it is critical to quickly identify the defect pattern through the defect pictures and then take corrective actions to avoid greater yield loss. Until now, defect pattern recognition heavily relies on domain experts' knowledge, which easily causes inconsistent classification results from person to person and unsatisfactory performance. In this study, a framework is proposed to achieve automatic defect detection and classification in color filter and micro-lens manufacturing to enhance the decision quality of pattern recognition. In particular, the proposed framework integrates Canny edge detection and classification and regression tree methodology. To validate the viability of the proposed framework in real settings, an empirical study was conducted in collaboration with a leading complementary metal oxide semiconductor image sensor foundry in Taiwan. The results not only showed the effectiveness of the proposed framework but also demonstrated the practical values.

关键词： surface defect detection color filter and micro-lens processes classification and regression tree feature extraction yield enhancement

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Genetics of biliary lithiasis from an ethnic perspective

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CLINICS AND RESEARCH IN HEPATOLOGY AND GASTROENTEROLOGY 2013年第2期37卷 119-125页

作者： Krawczyk, Marcin Francisco Miquel, Juan Stokes, Caroline S. Zuniga, Silvia Hampe, Jochen Mittal, Balraj Lammert, Frank Univ Saarland Dept Med 2 Med Ctr D-66421 Homburg Germany Pontificia Univ Catolica Chile Fac Med Dept Gastroenterol Santiago Chile Univ Kiel Dept Internal Med 1 Univ Hosp Schleswig Holstein Kiel Germany Sanjay Gandhi Post Grad Inst Med Sci Dept Genet Lucknow Uttar Pradesh India

Gallstone disease represents one of the most common gastroenterological disorders worldwide. Gallstones affect over 15% of adults in Europe and 25-30% of Hispanic populations in Central and South America. The heritability of gallstones varies considerably according to ethnicity, with Native Americans and Hispanics with Amerindian admixture being the most susceptible populations. Genetic factors have been shown to account for 25-30% of total gallstone risk in Europe, however, in Hispanic populations, this risk percentage may increase to 45-65%. Recent genome-wide association and candidate gene studies have identified common polymorphisms in enterohepatic transporters (ABCG5/8, SLC10A2) and the Gilbert syndrome UGT1A1 variant as genetic determinants of gallstone formation. Together, these polymorphisms cover a significant proportion of the previously predicted genetic background of gallstones in European populations. New lithogenic genes need to be discovered in future studies in high-risk populations. In this review, we address the latest developments in the genetic analysis of gallstones and discuss the ethnic background of this condition in European, Central and South American and Asian populations. (C) 2012 Elsevier Masson SAS. All rights reserved.

关键词： ABCG5/8 Hepatobiliary cholesterol transporter ApoB100 Apolipoprotein B100 ApoE4 Apolipoprotein E4 CI Confidence interval CYP7A1 Cholesterol 7-alpha hydroxylase FOXO1 Forkhead box O1 FXR Farnesoid X receptor GSD Gallstone disease GWAS Genome-wide association study NPL Non-parametric linkage OR Odds ratio p. Protein PAR Population attributable risk SAFGS San Antonio Family Gallbladder Study SLC10A2 Solute carrier 10A2 SNP Single nucleotide polymorphism SRB1 Scavanger receptor B1 UGT1A1 UDP-glucuronosyl transferase 1 LPAC Low-phospholipid associated cholelithiasis ESR1 Estrogen receptor 1 ESR2 Estrogen receptor 2 PGR Progesterone receptor LR Logistic regression CART classification and regression tree MDR Multifactor dimensionality reduction

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Cruise Passengers in a Homeport: A Market Analysis

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TOURISM GEOGRAPHIES 2013年第1期15卷 68-87页

作者： Brida, Juan Gabriel Pulina, Manuela Riano, Eugenia Zapata Aguirre, Sandra Free Univ Bolzano Sch Econ & Management Competence Ctr Tourism Management & Tourism Econ I-39100 Bolzano Italy Univ Sassari Econ Dept DiSEA I-07100 Sassari Italy Univ Sassari CRENoS I-07100 Sassari Italy Inst Univ Colegio Mayor Antioquia Fac Management GIET Res Grp Medellin Colombia

The aim of this study is to examine cruise passengers' characteristics, preferences and their overall experience in a port of call. Based on 1,361 survey data collected from passengers in the port of call of Cartagena, during the third quarter of 2009, a three-step multivariate market segment analysis is employed. First, a correspondence analysis is run to reveal the underlying factors in the data;second, based on the correspondence analysis, a hierarchical cluster investigation is performed to segment the sample into homogeneous groups;third, a decision tree is computed to characterise each group. The cluster analysis identifies six distinct market segments differentiated by nationality, satisfaction, safety perception and expenditure. The findings imply several policy directions. In particular, institutions should enhance the perception of safety in Cartagena to guarantee repeated visits, an ad hoc marketing policy may encourage revisit by young South Americans, and managers should extend the inland visiting time that is likely to produce local multiplier effects.

关键词： Cruise tourism customer segmentation hierarchical cluster classification and regression tree market analysis policy implications South America Colombia

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Statistical strategies for constructing health risk models with multiple pollutants and their interactions: possible choices and comparisons

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ENVIRONMENTAL HEALTH 2013年第2013期12卷 85-85页

作者： Sun, Zhichao Tao, Yebin Li, Shi Ferguson, Kelly K. Meeker, John D. Park, Sung Kyun Batterman, Stuart A. Mukherjee, Bhramar Univ Michigan Sch Publ Hlth Dept Biostat Ann Arbor MI 48109 USA Univ Michigan Sch Publ Hlth Dept Environm Hlth Sci Ann Arbor MI 48109 USA

Background: As public awareness of consequences of environmental exposures has grown, estimating the adverse health effects due to simultaneous exposure to multiple pollutants is an important topic to explore. The challenges of evaluating the health impacts of environmental factors in a multipollutant model include, but are not limited to: identification of the most critical components of the pollutant mixture, examination of potential interaction effects, and attribution of health effects to individual pollutants in the presence of multicollinearity. Methods: In this paper, we reviewed five methods available in the statistical literature that are potentially helpful for constructing multipollutant models. We conducted a simulation study and presented two data examples to assess the performance of these methods on feature selection, effect estimation and interaction identification using both cross-sectional and time-series designs. We also proposed and evaluated a two-step strategy employing an initial screening by a tree-based method followed by further dimension reduction/variable selection by the aforementioned five approaches at the second step. Results: Among the five methods, least absolute shrinkage and selection operator regression performs well in general for identifying important exposures, but will yield biased estimates and slightly larger model dimension given many correlated candidate exposures and modest sample size. Bayesian model averaging, and supervised principal component analysis are also useful in variable selection when there is a moderately strong exposureresponse association. Substantial improvements on reducing model dimension and identifying important variables have been observed for all the five statistical methods using the two-step modeling strategy when the number of candidate variables is large. Conclusions: There is no uniform dominance of one method across all simulation scenarios and all criteria. The performances differ according

关键词： Bayesian model averaging classification and regression tree Collinearity Interaction effect Model selection Multiple pollutants Principal component analysis Shrinkage Variable selection

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