基本证候视角下的慢性心力衰竭关联因素筛选及判别模型构建:一项多中心横断面研究

Screening and constructing a discriminant model for chronic heart failure from the perspective of basic syndromes:A multicenter cross-sectional study

目的:筛选慢性心力衰竭(CHF)关联因素并构建符合中国人群特征的CHF气虚证风险判别工具。方法:本研究病例来源于2009年1月1日至2012年12月31日,西北、东北、华南、华中、华北、西南等地14家心血管重点专科成员单位收集的629例CHF患者。在前期文献研究的基础上制作了临床病例信息采集表,采用横断面调查方法在14家医院同时进行。基于Epidata软件编写数据录入系统。单因素分析采用χ2检验(Pearson法),多因素分析采用二元Logistic回归分析。结果:以是否辨证为CHF气虚证为结局变量,通过Logistic回归模型筛选出CHF气虚证患者的7个常见关联因素:心功能Ⅰ级、心功能Ⅲ级、呼吸困难、浮肿、神疲、面色萎黄和口中黏腻,系数分别为1.51、-0.57、0.63、0.66、-0.93、-0.90、0.59,常数项为0.58。结论:初步筛选并构建出符合中国人群特征的具有良好区分度和准确性的CHF气虚证风险判别模型,为后续进一步研究奠定了工作基础。

Objective:To screen the related factors of chronic heart failure(CHF)and construct a risk discriminating tool for CHF qi deficiency syndrome that meets the characteristics of Chinese population.Methods:From January1,2009 to December 31,2012,629 patients with CHF were collected from 14 key cardiovascular specialist units in northwest,northeast,South China,Central China,North China and Southwest China.On the basis of previous literature research,a clinical case information collection form was produced,which was carried out simultaneously in 14 hospitals using a cross-sectional survey method.Write data entry system based on Epidata software.Univariate analysis was performed using theχ2 test(Pearson method)and multivariate analysis using binary Logistic regression analysis.Results:Using the qi deficiency syndrome of CHF as the outcome variable,the Logistic regression model was used to screen out seven common related factors in patients with CHF qi deficiency syndrome,including cardiac function grading(gradeⅠ,Ⅲ),dyspnea,edema,fatigue,pale complexion and greasy in the mouth,with coefficients of 1.51,-0.57,0.63,0.66,-0.93,-0.90,0.59,and the constant term was 0.58.Conclusion:The risk identification tools for CHF qi deficiency syndrome with good discrimination and certain accuracy according to the characteristics of Chinese population are initially screened and constructed,which lays a working foundation for further research.