Impact of symptom prevalence and symptom burden on quality of life in patients with heart failure

Eur J Cardiovasc Nurs. 2005 Sep;4(3):198-206. doi: 10.1016/j.ejcnurse.2005.03.010.


Background: Heart failure is an escalating health problem around the world. Despite significant scientific advances, heart failure patients experience multiple physical and psychological symptoms that can impact the quality of life.

Aims: To determine the (1) symptom prevalence, severity, distress and symptom burden in patients with heart failure; (2) impact of age and gender on symptom prevalence, severity, distress and symptom burden; and (3) impact of symptom prevalence and symptom burden on health-related quality of life (HRQOL) in patients with heart failure.

Methods: A convenience sample of 53 heart failure patients participated in this descriptive, cross-sectional design. Symptoms and HRQOL were measured using the Memorial Symptom Assessment Scale-Heart Failure and the Minnesota Living with Heart Failure Questionnaire.

Results: Patients experienced a mean of 15.1+/-8.0 symptoms. Shortness of breath and lack of energy were the most prevalent. Difficulty sleeping was the most burdensome symptom. Lower age, worse functional status, total symptom prevalence and total symptom burden predicted 67% of the variance in HRQOL.

Conclusion: Patients with heart failure experience a high level of symptoms and symptom burden. Nurses should target interventions to decrease frequency, severity, distress and overall symptom burden and improve HRQOL.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptation, Psychological
  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Chronic Disease
  • Cohort Studies
  • Cross-Sectional Studies
  • Depressive Disorder / diagnosis
  • Depressive Disorder / epidemiology
  • Female
  • Follow-Up Studies
  • Heart Failure / diagnosis*
  • Heart Failure / epidemiology
  • Heart Failure / psychology*
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prevalence
  • Probability
  • Quality of Life*
  • Regression Analysis
  • Risk Assessment
  • Severity of Illness Index
  • Sex Distribution
  • Sickness Impact Profile
  • Socioeconomic Factors
  • Stress, Psychological