Objective:To construct and validate a clinical prediction model for Qi-Yin deficiency syndrome in coronary heart disease,aiming to assist in clinical syndrome differentiation and provide a reference for the diagnosis and treatment of Qi-Yin deficiency syndrome in coronary heart disease.Methods:A retrospective collection of clinical data from 176 coronary heart disease patients who visited Dongying Hospital Affiliated to Shandong University of Traditional Chinese Medicine from January 2022 to January 2024 was conducted.The model was constructed using the Lasso-Multifactorial Logistic Regression method and evaluated by plotting the receiver operating characteristic curve(ROC),calibration curve,and decision curve analysis dynamic(DCA).Results:The Lasso-Multifactorial Logistic Regression analysis identified age,diabetes,left ventricular ejection fraction,and fasting blood glucose as characteristics included in the model.Advanced age,diabetes,and high fasting blood glucose were risk factors for the diagnosis of Qi-Yin deficiency syndrome,while a high left ventricular ejection fraction was a protective factor.The area under the curve(AUC)of the model in the training group was 0.829[95％CI(0.755,0.903)],and the AUC in the validation group was 0.775[95％CI(0.631,0.918)].The calibration curve showed that the model's predictive curve was close to the actual observed curve,and the DCA indicated that the model could provide clinical benefits to patients at a decision threshold below 0.8.Conclusion:The clinical prediction model for Qi-Yin deficiency syndrome in coronary heart disease constructed in this study has good performance,and can provide a certain reference for the syndrome differentiation and treatment of Qi-Yin deficiency syndrome in coronary heart disease.
关键词
冠心病/气阴两虚证/列线图/临床预测模型
Key words
coronary heart disease/Qi-Yin deficiency syndrome/nomogram/clinical prediction model
维普
万方数据