Physical Symptoms, Depressive Symptoms, and Quality of Life in Patients With Heart Failure: Cluster Analysis
- Authors
- Heo, Seongkum; Kang, JungHee; Shin, Mi-Seung; Lim, Young-Hyo; Kim, Sun Hwa; Kim, Sangsuk; An, Minjeong; Kim, JinShil
- Issue Date
- Jan-2024
- Publisher
- Lippincott Williams & Wilkins Ltd.
- Keywords
- cluster analysis; depression; heart failure; signs and symptoms
- Citation
- Journal of Cardiovascular Nursing, v.39, no.1, pp 31 - 37
- Pages
- 7
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- Journal of Cardiovascular Nursing
- Volume
- 39
- Number
- 1
- Start Page
- 31
- End Page
- 37
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/194308
- DOI
- 10.1097/JCN.0000000000001043
- ISSN
- 0889-4655
1550-5049
- Abstract
- 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 Ps <.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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