Effect of Symptom Clusters on Quality of Life in Patients with Heart Failure

• Published in: The Journal of heart and lung transplantation Vol. 32; no. 4; pp. S126 - S127
• Main Authors: Salyer, J, Flattery, M.P, Lyon, D.E
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.04.2013
• Subjects: Surgery
• ISSN: 1053-2498; 1557-3117
• DOI: 10.1016/j.healun.2013.01.276

Purpose Heart failure (HF) is a progressive, symptomatic illness with reports suggesting that pts. experience 2 to 9 symptoms. Symptom clusters (SCs) are symptoms that co-occur, are related, and influence outcomes. Thus, the purpose of this study was to examine 9 prevalent symptoms of HF, identify SCs, and examine the effects on quality of life (QOL). Methods and Materials This study was conducted at a health sciences center with a HF/HTx Program. We studied 117 HF pts. (age=56; 62% male; 50% AA) and examined prevalence and severity of 9 symptoms: anxiety, depression, dyspnea, fatigue, pain, swelling, daytime sleepiness, cognitive dysfunction, and GI disturbances. Instruments were valid and reliable and had acceptable psychometric properties. Descriptive statistics were used to describe the sample, co-morbidities, and symptoms. Principle components analysis (PCA) was used to extract related symptoms, aggregate components, and calculate SC scores. Multiple regression was used to examine effects of SCs on QOL. Results Approx. 51% of pts. were NYHA Class III/IV and had an EF of 25%. Over half (62%) had an ICD and 9% were receiving IV inotropes. The most prevalent symptoms included: dyspnea in the past 2 weeks (100%), decreased hunger (95%), decreased appetite (85%), daytime sleepiness (54%), fatigue (73%), swelling (73%), and pain (62%). Least frequently occurring included depression (21%). Three SCs were extracted in a PCA: Sickness Behavior (anxiety, depression, daytime sleepiness, cognitive dysfunction, fatigue), Discomforts (dyspnea, edema, pain), and GI Disturbamces (appetite/hunger). Sickness Behavior was the only predictor (β=-0.635; p=<0.0001) of QOL. Approximately 40% of the variance in QOL was explained by this symptom cluster (F=75.12; p=0.0001; R2=.404). Conclusions Sickness Behaviors had a significant negative effect on QOL and suggests that incorporating an evaluation of each of these symptoms may facilitate identification and treatment of symptoms having an additive and detrimental impact on QOL. Future studies to examine the stability of the cluster are warranted.