基于宏、中、微观对冠心病血瘀证前证相关因素的二元logistic回归分析

Binary Logistic Regression Analysis Based on Macro-,Meso-,and Micro-Levels of the Factors Associated with the Pre-Existing Evidence of Coronary Heart Disease Blood Stasis Evidence

目的基于中医状态学宏、中、微观健康状态表征参数体系探讨冠心病血瘀证前证发展过程中的相关保护/危险因素。方法收集湖南中医药大学各附属医院就诊于心内科门诊及住院部冠心病待查对象253例,按照宏观、中观、微观3个维度制定调查问卷,对采集的参数用Python软件进行分类整理,将患者诊断为冠心病血瘀证前证(150例)和冠心病血瘀证(100例),用频次分析、χ^(2)检验及Logistic回归等方法进行统计分析。结果(1)单因素分析结果显示:年龄、BMI、吸烟史、饮酒史、高血压史、糖尿病史、月平均高温、空气质量、季节、职业类型、社会环境、冠脉造影狭窄、舒张压、收缩压、肌酐、尿酸、总胆固醇等指标在冠心病血瘀证前证和冠心病血瘀证之间存在差异,差异均有统计学意义(P<0.05)。(2)二元Logistic回归分析显示:年龄、BMI、饮酒史、职业类型、冠脉造影狭窄、舒张压、肌酐、暗红舌是其独立危险因素。建立预测模型:P=1/[1+exp(16.522-1.427×年龄-0.975×BMI-3.55×饮酒史+1.982×月平均高温+0.709×季节-1.827×职业类型-1.1×冠脉造影狭窄-0.072×舒张压-0.076×肌酐+2.398×头晕-4.108×暗红舌+4.169×脉涩)],模型预测率为90.5%。结论冠心病血瘀证logistic回归模型与临床诊断良好,为冠心病已病与未病之间的状态探索奠定基础,为亚健康理论提供重要的基础数据。

Objective To explore the relevant protective/risk factors during the development of coronary heart disease blood stasis evidence in the process of pre-existing evidence based on the macro-,meso-,and micro-health state characterization parameter system of Chinese medicine state science.Methods 253 cases of coronary heart disease to be investigated were collected from the outpatient and inpatient departments of the Department of Cardiology in the hospitals affiliated to Hunan University of Traditional Chinese Medicine,and questionnaires were formulated according to the three dimensions of macro,meso,and micro,and the collected parameters were categorized with Python software,and the patients were diagnosed as pre-coronary heart disease blood stasis evidence(150 cases)and coronary heart disease blood stasis evidence(100 cases),and statistical analyses were performed with frequency analysis,χ^(2)test,and Logistic regression and other methods for statistical analysis.Results①The results of univariate analysis showed that:age,BMI,history of smoking,history of alcohol consumption,history of hypertension,history of diabetes mellitus,average monthly high temperature,air quality,season,type of occupation,social environment,coronary artery angiographic stenosis,diastolic blood pressure,systolic blood pressure,creatinine,uric acid and total cholesterol differed between patients diagnosed as pre-Coronary artery disease blood stasis evidence and those diagnosed as Coronary artery disease blood stasis evidence,and all the differences were statistically significant(P<0.05).②Binary logistic regression analysis showed that age,BMI,history of alcohol consumption,type of occupation,coronary angiographic stenosis,diastolic blood pressure,creatinine,and dark red tongue were independent risk factors.A prediction model was established:P=1/[1+exp(16.522-1.427×age-0.975×BMI-3.55×drinking history+1.982×monthly average high temperature+0.709×season-1.827×occupational type-1.1×coronary angiographic stenosis-0.072×diastolic blood pressure-0.076×creatinine+2.398×dizziness-4.108×dark red tongue+4.169×pulse asthenia)],the model prediction rate was 90.5%.Conclusion The logistic regression model of coronary heart disease with blood stasis evidence is good with clinical diagnosis,which lays the foundation for the exploration of the state between the already diseased and undiseased of coronary heart disease,and provides important basic data for the theory of subhealth.