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Quality of Life Research
Gepubliceerd in:

01-12-2007

Cluster analysis: a useful technique to identify elderly cardiac patients at risk for poor quality of life

Auteurs: Yoshimi Fukuoka, Teri G. Lindgren, Sally H. Rankin, Bruce A. Cooper, Diane L. Carroll

Gepubliceerd in: Quality of Life Research | Uitgave 10/2007

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Abstract

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 ≥ 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.
vorige artikel Respondent satisfaction regarding SF-36 and EQ-5D, and patients’ perspectives concerning health outcome assessment within routine health care
volgende artikel Marker states and a health state prompt provide modest improvements in the reliability and validity of the standard gamble and rating scale in prostate cancer patients
Voetnoten
1
Note that some researchers might use the pragmatic approach of dichotomizing continuous scores into extreme groups, or at the median, in order to find groups of observations with similar classifications of the dichotomies—as this would be done in a multi-way contingency table. This practice of dichotomizing variables “wastes” variance and could lead to serious errors in estimation [19, 20] .
 
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Metagegevens
Titel
Cluster analysis: a useful technique to identify elderly cardiac patients at risk for poor quality of life
Auteurs
Yoshimi Fukuoka
Teri G. Lindgren
Sally H. Rankin
Bruce A. Cooper
Diane L. Carroll
Publicatiedatum
01-12-2007
Uitgeverij
Springer Netherlands
Gepubliceerd in
Quality of Life Research / Uitgave 10/2007
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-007-9272-7

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