| [The aim of this study]:Warfarin as a coumarin kind of vitamin K antagonists, are widely used in thrombotic diseases prevention and treatment of cardiovascular physician in patients with atrial fibrillation is mainly used for the anticoagulation. Butbecause of its safety window narrower, individual differences.Use of excessive easy cause skin mucous membrane, gastrointestinal and intracerebral hemorrhage. Underdosed nor anticoagulant effect. Lead in clinical use a tremendous limits on. How to reasonably and effectively use warfarin is the clinical needs to solve practical problems. this study through the analysis of the status quo, according to research at home and abroad of anticoagulant warfarin may influence the related factors, such as role genotyped, gender, age, merger drug and disease states, such as collection of af patients taking warfarin related material. Summarize and analyze, statistics. That the relevant factors and regression equation. For warfarin use of personalized and rationalization, provides the basis.[Methods]:select 2009 until 2011 in heart medicine hospitalization af and 86 patients taking warfarin as the research object. Every patients take warfarin INR was once before, measured after take warfarin INR was measured again later, once a week, according to INR was measured INR was adjusted warfarin dose. Acquisition of their disease status, drug and sex, age, weight and other related material. And 4ml, smoke venous blood, and extracted DNA direct DNA sequencing. Determine its CYP2C9 and VKORC1 parting. All test data processing analysis by SPSS software. The indicators of collected firstly, and then the single factor analysis of the single factor analysis has significant difference in the factor, more factors logistic regression analysis (Forward method), draw risk factors, a regression equation. Count data to constitute, mean+sd (x+s) says, continuity material measurement data than said in compares the single factor analysis of variance or independent sample t-test, discontinuity material compares the Fisher accurate inspection or X 2, p<0.05 probability method for difference have statistical significance.[Results]:the single factor analysis showed three groups of patients in the gender structure, basic diseases (high blood pressure, diabetes, cardiac insufficiency, stroke), control in heart rate was not statistically significant. In age, weight and CYP2C9 and VKORC1 genotyped had a remarkable difference. Gao min group of age groups and constitutes a higher than normal group low sensitivity, and body mass index is lower than the normal group and low sensitive group. Further to CYP2C9 and VKORC1 genotype group, found that age and weight index between in every gene group was not statistically significant. For warfarin maintenance dose VKORC1 genotypes with CYP2C9 and variance analysis showed that between CYP2C91075AA warfarin maintenance dose of the highest dose of AC type center, CC type dose doses in VKORC1-the lowest, genotype kind of also draw 1639 similar results.Multiple regression linear equations show age, weight, CYP2C91075, VKORC1-1639 for changing warfarin anticoagulant effect factors affecting the independent.[conclusion]:1 single factor analysis showed that in gao min group, the normal group and low sensitive groups of patients, age, sex, weight, gene differences differences are significant.2 multi-factor analysis indicated:age, sex, weight, CYP2C91075, VKORC1-1639 genetic differences of anticoagulant warfarin role for the influence of the independent factors.3 build multiple linear regression equation prediction warfarin dosage required for 52% of accurate value.4 this study explores the influence of anticoagulant warfarin role related factors, and established a multiple regression equation, for reasonable individual use warfarin provides some reference significance.
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