Influencing Factors of Frailty in Older Patients With Chronic Heart Failure: Based on Bayesian Network

PURPOSE: Previous research has explored the factors influencing frailty in older patients with chronic heart failure (CHF), but these studies have not revealed the potential network interactions among the related factors. This study aimed to construct a Bayesian network (BN) model of frailty in older patients with CHF, analyze the predictive factors, and explore the internal relationships between these factors. METHODS: A total of 439 older patients with CHF were selected using a convenience sampling method from September 2023 to March 2024 at the cardiology department of a comprehensive tertiary hospital in Nanchang, Jiangxi, China. Multivariate logistic regression analysis was used to explore the influencing factors of frailty in older patients with CHF. The BN structure was learned using the max-min hill-climbing algorithm, with parameter estimation achieved through maximum likelihood estimation. Netica software was utilized for prediction and diagnosis. The effectiveness of the model was validated using the Receiver Operating Characteristic (ROC) curve. RESULTS: The prevalence of frailty in older patients with CHF was found to be 53.3%. After using a multivariate logistic regression analysis model that screened the variables, the nutritional risk, physical activity, depression, multimorbidity, grip strength and left atrial diameter were included into the Bayesian network model. The Bayesian network model of frailty related factors in older CHF patients showed that nutritional risk, physical activity, depression, and multimorbidity were directly related to frailty, while grip strength and left atrial diameter were indirectly related. CONCLUSION: The study results indicated that malnutrition risk, inactivity, depression, and multimorbidity were directly related to frailty, while lower grip strength and a wider left atrial diameter were indirectly related to frailty. Enhancing frailty assessment and implementing measures addressing disease, nutrition, exercise, and psychological well-being are crucial for delaying and potentially reversing the onset and progression of frailty.