首页> 外文期刊>The journal of alternative and complementary medicine: research on paradigm, practice, and policy >A Quantitative Diagnostic Method for Phlegm and Blood Stasis Syndrome in Coronary Heart Disease Using Tongue, Face, and Pulse Indexes: An Exploratory Pilot Study
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A Quantitative Diagnostic Method for Phlegm and Blood Stasis Syndrome in Coronary Heart Disease Using Tongue, Face, and Pulse Indexes: An Exploratory Pilot Study

机译:舌头,面部和脉冲指标冠心病痰和血瘀综合征的定量诊断方法:探索试验研究

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Objectives:The aim of this study was to establish a quantitative syndrome differentiation model with logistic regression analysis for phlegm and blood stasis syndrome (PBSS) in coronary heart disease (CHD) to offer methodology guidance for the quantitative syndrome differentiation of Traditional Chinese Medicine (TCM). Design:Tongue, face, and pulse information of each subject was obtained using the TCM-intelligent diagnosis instruments. Logistic regression model was used to construct the syndrome diagnosis model. The area under receiver operating characteristic curve (ROC-AUC) was used to evaluate the diagnostic value of the model. Subjects:Among the 141 subjects, 83 belonged to the PBSS group, and 58 belonged to the non-PBSS group. Results:The independent indexes used to predict PBSS in patients with CHD were length of the crack (LC) (p = 0.002), number of ecchymosis (NE) (p < 0.001), length of philtrum (LEP) (p = 0.022), and right hand pulse h1 (Rh-1) (p = 0.021). The expression of combining predictor L in this study was L = LC +57.58 NE +4.53 LEP +2.68 Rh-1. The ROC curve analysis indicated that the AUC values of LC, NE, LEP, and Rh(1)were 0.646, 0.710, 0.619, and 0.613, respectively. The AUC = 0.825 of the syndrome diagnosis model was the largest. Conclusions:The quantitative study of TCM syndrome based on logistic regression analysis provides a good method for the objective analysis and application of TCM syndrome.
机译:目的:本研究的目的是建立一种定量综合征分化模型,具有冠心病(CHD)中痰和血瘀综合征(PBSS)的逻辑回归分析,为中药定量综合征分化提供方法指导(TCM )。设计:使用TCM智能诊断仪器获得每个受试者的舌头,面和脉冲信息。 Logistic回归模型用于构建综合征诊断模型。接收器操作特性曲线(ROC-AUC)下的区域用于评估模型的诊断值。主题:在141个受试者中,83个属于PBSS组,58个属于非PBSS组。结果:用于预测CHD患者患者PBSS的独立指标是裂缝(LC)的长度(P = 0.002),生成数(NE)(P <0.001),腓特朗(LEP)(P = 0.022) ,右手脉冲H1(RH-1)(P = 0.021)。在本研究中组合预测器L的表达是L = LC + 57.58 NE + 4.53Lep +2.68 rh-1。 ROC曲线分析表明,LC,NE,LEP和RH(1)的AUC值分别为0.646,0.710,0.619和0.613。 AUC = 0.825的综合征诊断模型是最大的。结论:基于逻辑回归分析的TCM综合征的定量研究提供了TCM综合征的客观分析和应用的良好方法。

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