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Core symptoms in the cardiac rehabilitation phase of patients with chronic heart failure: A symptom network analysis study

作者
Fengfei Zhou,Bailing Zhang,Yi Lu,Qingqing Yang
出处
期刊:Medicine [Ovid Technologies (Wolters Kluwer)]
卷期号:104 (42): e45204-e45204
标识
DOI:10.1097/md.0000000000045204
摘要

This study investigates the composition characteristics of symptom clusters in patients with chronic heart failure (CHF) during the cardiac rehabilitation phase, constructs their symptom network structure, and identifies core symptoms, thereby providing a foundation for optimizing the precise management plan for symptoms during the rehabilitation period. A convenience sampling method was employed. From January 2023 to May 2025, 550 patients with CHF undergoing cardiac rehabilitation at the Department of Cardiology of Nantong Sixth People’s Hospital were selected for a cross-sectional survey. The patients’ symptom experiences were assessed using a general information questionnaire and the Chinese version of the Memorial Heart Failure Symptom Assessment Scale for Heart Failure. The analysis primarily focused on the degree of symptom distress, and exploratory factor analysis was conducted to extract symptom clusters. The R 4.3.1 software was utilized to construct a symptom network model, and node strength and closeness centrality were calculated to identify core symptoms and their interrelationships. The identification of symptom clusters through exploratory factor analysis revealed 5 distinct clusters that accounted for 63.75% of the variance. These clusters include: cardiopulmonary function limitation, fluid retention imbalance, fatigue-nutritional disorder, gastrointestinal symptoms, and neuropsychological disorders. Notably, shortness of breath following activity (r_s = 4.618), fatigue (r_s = 4.752), and anxiety (r_s = 4.752) emerged as the core hubs of the network, with fatigue exhibiting a predictability of up to 69%. Medical staff should prioritize intervening in the 3 core symptoms, paying attention to their cross-group correlations, and implementing precise management strategies based on the symptom network structure to effectively reduce the symptom burden during the recovery period, promote functional recovery, and improve the quality of life.
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