Yinyi Hu1,2, Jiaoming Jiang1, Liyuan Xu1, Cui Wang3, Pengxiao Wang4, Biwen Yang4, Ming Tao5. 1. School of Nursing, Zunyi Medical University, Zunyi, China. 2. Department of Nursing, Fourth People's Hospital of Guiyang, Guiyang, China. 3. Department of Pediatric Orthopedics, Affiliated Hospital of Zunyi Medical University, Zunyi, China. 4. Department of Cardiology, Affiliated Hospital of Zunyi Medical University, Zunyi, China. 5. Department of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Abstract
AIM: This study aimed to identify symptom clusters among patients with chronic heart failure (HF) and examine their independent relationships with quality of life (QoL). METHODS: A descriptive cross-sectional design was adopted, and 201 Chinese participants were recruited. Their symptom profiles and QoL were assessed using the Memorial Symptom Assessment Scale-Heart Failure and Minnesota Living with Heart Failure Questionnaire. Exploratory factor analysis was used to identify the symptom clusters. Pearson's correlation analysis and multiple regression analysis were conducted to examine their independent relationships with QoL. RESULTS: Six distinct symptom clusters were identified: the fatigue, dyspneic, discomfort, congestive, ischemic, and emotional symptom clusters. These six symptom clusters accounted for 57.508% of the variance in patient symptom experiences and were positively related to their overall QoL. Moreover, the fatigue (β = .317, p < .001), dyspneic (β = .228, p < .001), congestive (β = .363, p < .001), and emotional (β = .200, p < .001) symptom clusters independently predicted QoL. CONCLUSION: The six symptom clusters that were identified in this study and the relationships that they shared with QoL are expected to inform future approaches to symptom management. Interventions that target these symptom clusters will improve the QoL of patients with HF.
AIM: This study aimed to identify symptom clusters among patients with chronic heart failure (HF) and examine their independent relationships with quality of life (QoL). METHODS: A descriptive cross-sectional design was adopted, and 201 Chinese participants were recruited. Their symptom profiles and QoL were assessed using the Memorial Symptom Assessment Scale-Heart Failure and Minnesota Living with Heart Failure Questionnaire. Exploratory factor analysis was used to identify the symptom clusters. Pearson's correlation analysis and multiple regression analysis were conducted to examine their independent relationships with QoL. RESULTS: Six distinct symptom clusters were identified: the fatigue, dyspneic, discomfort, congestive, ischemic, and emotional symptom clusters. These six symptom clusters accounted for 57.508% of the variance in patient symptom experiences and were positively related to their overall QoL. Moreover, the fatigue (β = .317, p < .001), dyspneic (β = .228, p < .001), congestive (β = .363, p < .001), and emotional (β = .200, p < .001) symptom clusters independently predicted QoL. CONCLUSION: The six symptom clusters that were identified in this study and the relationships that they shared with QoL are expected to inform future approaches to symptom management. Interventions that target these symptom clusters will improve the QoL of patients with HF.