医学
生活质量(医疗保健)
星团(航天器)
抑郁症状
胸痛
心力衰竭
物理疗法
萧条(经济学)
横断面研究
可视模拟标度
不利影响
内科学
焦虑
精神科
护理部
病理
计算机科学
经济
宏观经济学
程序设计语言
作者
Seongkum Heo,JungHee Kang,Mi‐Seung Shin,Young‐Hyo Lim,Sun Hwa Kim,Sangsuk Kim,Minjeong An,JinShil Kim
标识
DOI:10.1097/jcn.0000000000001043
摘要
Background Physical and psychological symptoms are prevalent in patients with heart failure (HF) and are associated with poor quality of life (QOL) and high hospitalization rates. Thus, it is critical to identify symptom clusters to better manage patients with high-risk symptom cluster(s) and to reduce adverse effects. Objective The aims of this study were to identify clusters of physical HF symptoms (ie, dyspnea during daytime, dyspnea when lying down, fatigue, chest pain, edema, sleeping difficulty, and dizziness) and depressive symptoms and to examine their association with QOL in patients with HF. Methods In this secondary analysis of a cross-sectional study, data on physical HF symptoms (Symptom Status Questionnaire), depressive symptoms (Patient Health Questionnaire-9), and general QOL (European Quality of Scale-Visual Analog Scale) were collected. We identified clusters based on the physical HF symptoms and depressive symptoms using 2-step and k -means cluster analysis methods. Results Chest pain was removed from the model because of the low importance value. Two clusters were revealed (cluster 1, severe symptom cluster, vs cluster 2, less severe symptom cluster) based on the 7 symptoms. In cluster 1, all of the 7 symptoms were more severe, and QOL was poorer than those in cluster 2 (all P s < .001). All the mean and median scores of the 7 symptoms in cluster 1 were higher than those in cluster 2. Conclusions Patients with HF were clearly divided into 2 clusters based on physical HF symptoms and depressive symptoms, which were associated with QOL. Clinicians should assess these symptoms to improve patient outcomes.
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