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Cluster analysis: a useful technique to identify elderly cardiac patients at risk for poor quality of life
Yoshimi Fukuoka1, Teri G Lindgren, Sally H Rankin
1School of Nursing, University of California San Francisco, San Francisco, CA 94143, USA. Yoshimi.Fukuoka@nursing.ucsf.edu
Insights
Elderly patients one year after heart surgery or heart attack often fall into distinct symptom groups. The "Weary" group shows poorer quality of life and higher psychological distress, requiring targeted interventions.
Area of Science:
- Cardiology
- Geriatrics
- Psychology
Background:
- Elderly patients undergoing acute myocardial infarction (AMI) or coronary artery bypass surgery (CABG) face unique challenges.
- Assessing long-term cardiac symptom frequency and its impact on quality of life is crucial for this demographic.
Purpose of the Study:
- To determine the frequency of cardiac symptoms in elderly patients one year post-AMI and/or CABG.
- To identify distinct patient subgroups based on cardiac symptom profiles.
- To investigate variations in health-related quality of life and psychological distress among these subgroups.
Main Methods:
- Telephone interviews with 206 elderly, unpartnered patients (≥65 years) one year after AMI and/or CABG.
- Measurement of cardiac symptoms, SF-36 (health-related quality of life), POMS (psychological distress), and QOL-I.
- Hierarchical cluster analysis to identify patient subgroups based on cardiac symptoms.
Main Results:
- Three patient subgroups were identified: Weary (19.4%), Diffuse symptom (68.4%), and Breathless (12.2%).
- The Weary group exhibited significantly lower SF-36 scores (except social functioning) and higher POMS scores (except Anger/hostility and Confusion/Bewilderment) compared to the Diffuse symptom group.
Conclusions:
- Cluster analysis effectively identified a subgroup of elderly patients with poorer recovery post-cardiac events.
- The 'Weary' subgroup requires focused attention and tailored intervention strategies to enhance their health outcomes.
Objective:
The purposes of this study are (1) to examine the frequency of cardiac symptoms in elderly people one year after acute myocardial infarction (AMI) and/or coronary artery bypass surgery (CABG); (2) to identify patient subgroups (cluster solutions) based on cardiac symptoms after cardiac events and (3) to determine if these subgroups vary based on health related quality of life and psychological distress.
Methods:
A sample of 206 elderly, unpartnered, patients (age > or = 65) were interviewed one year after AMI and/or CABG by telephone. Cardiac symptoms, SF-36, POMS, and QOL-I were measured. A hierarchical cluster analysis was used to identify patient subgroups based on cardiac symptoms, using a combination of dendrograms and stopping rules.
Results:
Three subgroups were identified: (1) the Weary (19.4%), (2) the Diffuse symptom (68.4%), and (3) the Breathless groups (12.2%). The Weary group had significantly lower scores on all of SF-36 subscales (except for social functioning) and higher scores on all of POMS subscales (except for Anger/hostility and Confusion/Bewilderment) compared to the Diffuse symptom group.
Conclusions:
The cluster analysis was useful to identify the subgroup with poorer recovery. Patients in the Weary group need more attention and intervention strategies to improve their health.
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