痰热郁肺型慢性阻塞性肺疾病急性加重期患者证候特点及理化指标的Logistic回归分析

Logistic regression analysis on symptoms and physicochemical indexes in AECOPD patients with heat phlegm obstructing lung syndrome

目的探讨慢性阻塞性肺疾病急性加重期(acute exacerbation of chronic obstructive pulmonary disease,AECOPD)痰热郁肺型患者的临床证候特点及实验室指标的变化,为AECOPD的中医分型诊断提供方法学依据。方法回顾性收集815例AECOPD患者的临床资料,其中中医辨证分为痰热郁肺型者467例,非痰热郁肺型者348例,采用Logistic回归法对痰热郁肺型AECOPD的中医证候特点和实验室指标进行分析并建立回归模型,总结影响痰热郁肺AECOPD诊断的主要证候特点及理化因素。结果在纳入研究的14个自变量中,高血清同型半胱氨酸(OR=1.111,P=0.004)、发热(OR=13.061,P=0.008)、怕热(OR=2.425,P=0.016)、苔黄(OR=124.061,P=0.000)均为痰热郁肺的阳性诊断指标,这四个变量拟合的回归方程用于预测AECOPD的中医分型,正确率为98.4%。结论高血清同型半胱氨酸、发热、怕热、苔黄对痰热郁肺型AECOPD的辨证和诊断更具价值。

Objective To investigate the features of clinical symptom and laboratory parameters in acute exacerbation of chronic obstructive pulmonary disease （AECOPD） patients with heat phlegm obstructing lung syndrome, and to provide a methodological approach for the classificatory diagnosis of this disease. Methods Clinical data from 815 AECOPD patients, which were differentiated between heat phlegm obstructing lung syndrome （467 individuals） and non-heat phlegm obstructing lung syndrome （348 individuals） by the principle of TCM, were collected retrospectively. The characteristic of TCM clinical symptoms and laboratory parameters in AECOPD patients were explored by Logistic regression analysis. Logistic equation and ROC curve were used for depicting the prediction value of regression model. Results Logistic regression analysis indicated that 4 of 14 independent variables were statistically significant in this study, that high level of serum homocysteine （ OR = 1. 111, P = 0. 004） , fever （ OR = 13. 061, P=0.008） , intolerance of heat （ OR = 2. 425, P = 0. 016） and yellow tongue fur （ OR = 124. 061, P=0.000） were positive indicators for the diagnosis of heat phlegm obstructing lung syndrome. The prediction accuracy of Logistic equation was 98.4% and the area under ROC curve was 0. 992. Conclusion Serum Hcy, fever, intolerance of heat and yellow tongue fur are four valuable factors for the syndrome differentiation and diagnosis in AECOPD patients.