| Objectives:investigate the risk factors which may lead to liver cirrhosis esophageal varices bleeding in atmospheric temperature switch (Cold) in NANCHANG region and create a risk predictive model.Methods:(1) object investigated:cirrhosis patients with esophageal varices bleeding (case group) and esophageal varices (control group) who hospitalized in the Fist Affiliated Hospital of Nan Chang University from January to March 2008, December 2008 to March 2009 and December 2009 to March 2010, these periods were in extremely cold climate. (2) Items investigated:general information, past medical history, personal hobby, diet habits, physical characteristics, psychological characteristics, serum biochemistry profile, endoscopy and ultrasonic diagnosis results, etc. (3) Investigation methods:design questionnaires, collected the relevant information from medical records, at the same time inquired the patients enrolled in the study by face to face or telephone enquiries. (4) Data storing and management: all data were inputted into Excel electronic forms for categorizing and statistical analyzing. (5) Data analysis software:SPSS 13.0 was applied to finish above Logistic regression analyses. Firstly,univariate conditional Logistic regression analyses were performed, secondly, according to the above analysis results, multivariate conditional Logistic regression analysis were conducted in different blocks with the items about a same topic. With those analyses, the roles of all the factors were observed and key factors were screened, finally, created a risk predictive model.Results:(1) Clinical data:total 272 patients enrolled in the study, including males 210 (77.2%) and females 62 (22.8%), with ages ranging from 22 to 83, averaging 52.0. There were no differences in the age compositions (P=0.383),but sex ratio of patients were differences (P=0.031) between the case group and the control group. (2) Among the total 272 patients,the univariate conditional logistic regression analysis show that the following factors are positive for BEV (OR=1.187-21.117, P =0.000~0.049):bleeding history of EV, clear causes, good appetite, insomnia, Irascible temper, reasonable or perceptual style in treating thing, fuzzy vessels structural in ultrasonic diagnosis, severe,full,snaky EV, RC sign, high ALB and A/G. The following factors are negative for BEV(OR=0.000-0.999,P= 0.049~0.000):female, daily longer time of sleep,high ALT,AST.TBIL,DBIL.IBIL AKP,GLB,APTT,PT, ascites. The multivariate Logistic regression analysis showed that the following factors are the positive for BEV (OR=5.576~14.362,P= 0.003~0.000):bleeding history of EV, RC sign and snaky EV. The following factors are negative for BEV (OR=0.115~0.174, P=0.033~0.002):high GLB,AKP and ascites. (3) The BEV risk model and its assessment:The following factors enter the Logistic regression equation model:ascites, temper characteristics, AST,AKP,GLB,APTT. The established Logistic regression equation is:Logit(P)=1.391+2.692 bleeding history of EV-1.260 ascites+1.199 temper characteristics +0.014 AST 0.138 GLB-0.007 AKP-0.059 APTT. The predictive performance of the model is as follows:Sensitivity 87.5%, specificity 86.8%, accuracy 87.2%.Conclusions:The following factors for liver cirrhosis esophageal varices bleeding in atmospheric temperature switch (Cold) in NANCHANG region:(1) Key risk factors for liver cirrhosis esophageal varices bleeding in cold climate:include bleeding history of EV, clear causes, good appetite, insomnia, Irascible temper, reasonable or perceptual style in treating thing, fuzzy vessels structural under ultrasonic diagnosis, severe,full,snaky EV, RC sign, high ALB and A/G.(2) Key protective factors for liver cirrhosis esophageal varices bleeding in cold climate:include female, daily longer time of sleep,high ALT,AST,TBIL,DBIL IBIL,AKP,GLB,APTT,PT, ascites.(3) The predictive performance of the model is very good. |