Analysis of influencing factors of sarcopenia in elderly patients with chronic heart failure and establishment of the nomogram prediction model

Wang Lihui; Xie Jing; Ma Bei; Xu Qing; Du Chaosheng; Liu Li

doi:10.3760/j.issn.1673-4777.2025.11.005

Abstract：Objective To explore the influencing factors of sarcopenia in elderly patients with chronic heart failure(CHF),and to construct a nomogram prediction model for predicting the risk of sarcopenia.Methods A total of 200 elderly patients with CHF admitted to the Ninth Medical Center of Chinese PLA General Hospital from July 2023 to January 2025 were selected.According to the occurrence of sarcopenia,patients were divided into sarcopenia group(50 cases)and non-sarcopenia group(150 cases),and the data were collected and recorded.LASSO regression analysis and multivariate Logistic regression analysis were used to screen the independent predictors of sarcopenia in elderly CHF patients.A model was constructed based on LASSO-Logistic regression analysis,and a nomogram was drawn by R software.The calibration curve and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the nomogram model calibration.The receiver operating characteristic(ROC)curve was used to evaluate the discrimination of the nomogram model.Clinical decision curve analysis was used to evaluate the clinical validity of the nomogram model.Results There were significant differences in age,body mass index,proportion of hyper-tension,diabetes mellitus,left ventricular ejection fraction,New York Heart Association(NYHA)classification,albumin,hemoglobin,appendicular skeletal muscle mass,6 m pace and grip strength between the non-sarcopenia group and the sarcopenia group(all P＜0.05).LASSO-Logistic regression analysis showed that age ≥75 years,lower body mass index,diabetes mellitus,NYHA grade Ⅲ-Ⅳ and lower albumin were independent predictors of sarcopenia in elderly patients with CHF.According to the above factors,a nomogram model for predicting sarcopenia in elderly patients with CHF was constructed.The calibration curve showed that the consistency between the observed value and the predicted value was high,and the Hosmer-Lemeshow goodness of fit test showed x2=0.427,P=0.600.ROC curve results showed that the area under the curve of the model was 0.958(95％confidence interval:0.934-0.982),and the calibration and discrimination of the model were good.Clinical decision curve analysis was used to evaluate the clinical effectiveness of the nomogram model.When the threshold probability range was set to 0.03-0.95,patients could benefit from the nomogram model.Conclusion Age ≥75 years,lower body mass index,diabetes mellitus,NYHA grade Ⅲ-Ⅳ and lower albumin are independent predictors of sarcopenia in elderly CHF patients.The nomogram model based on the above factors can effectively predict the risk of sarcopenia in elderly CHF patients.