Clinical Analysis of of Influencing Factors of Phlegm-heat Syndrome in Coronary Heart Disease
CHEN Yiming
LI Ping
YANG Yang
MEN Lu
LIU Jiatao
Abstract：Objective:To explore the relationship between the formation of phlegm-heat syndrome in coronary heart disease and metabolic diseases,and to construct the corresponding prediction model.Methods:One hundred and eighty-six patients with coronary heart disease were divided into the phlegm-heat syndrome group(90 cases)and the non-phlegm-heat syndrome group(96 cases)based on phlegm-heat syndrome from October 2022 to November 2024.The general data and clinical characteristics of the two groups were collected.Univariate and multivariate Logistic regression analyses were used to screen the independent risk factors for the occurrence of phlegm-heat syndrome,and a nomogram prediction model was constructed.The predictive efficacy and clinical practicability of the model were evaluated using the receiver operating characteristic(ROC)curve,calibration curve and clinical decision curve(DCA).Results:In the univariate analysis,factors such as body mass index,smoking,smoking years,smoking quantity,drug allergy history,cardiac function classification,hypertension,hyperlipidemia,cerebral infarction,diabetes,and resting heart rate were related to the formation of phlegm-heat syndrome in coronary heart disease(P＜0.05).Multivariate Logistic regression analysis indicated that high body mass index,smoking,hypertension,hyperlipidemia and diabetes were independent risk factors for phlegm-heat syndrome in patients with coronary heart disease.The area under the ROC curve drawn based on the model was 0.803,the specificity was 0.792,and the sensitivity was 0.722.The calibration curve showed that the predicted probability of phlegm-heat syndrome in coronary heart disease showed better consistency with the actual occurrence probability(x2=10.443,P=0.235).The DCA curve showed the model with better clinical net benefit,and a net benefit 0.8.Conclusion:The formation of phlegm-heat syndrome in coronary heart disease was closely related to metabolism-related factors such as high body mass index,smoking,hypertension,hyperlipidemia and diabetes.The nomogram prediction model constructed based on the above risk factors showed better predictive efficacy and clinical application value.
Keywords：coronary heart diseasephlegm-heat syndromeLogistic regression analysismodel predictioninfluencing factors
Publication Date：2025-05-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1448-1453 )