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

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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.

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Notes

  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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Acknowledgements

We would like to acknowledge support from the NINR R01 NR005205 for Drs. Rankin and Carroll, NIH T32 NR07088 symptom management postdoctoral fellowships for Drs. Lindgren and Fukuoka and support from NICHD 9K12 HD052163-06 and UCSF’s Office of Research on Women’s Health for Dr. Fukuoka.

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Authors and Affiliations

  1. School of Nursing, University of California San Francisco, San Francisco, CA, 94143, USA

    Yoshimi Fukuoka, Teri G. Lindgren, Sally H. Rankin & Bruce A. Cooper

  2. Yvonne L. Munn Center for Nursing Research Institute for Patient Care, Massachusetts General Hospital, Boston, MA, 02114, USA

    Diane L. Carroll

Authors
  1. Yoshimi Fukuoka
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  2. Teri G. Lindgren
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  3. Sally H. Rankin
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  4. Bruce A. Cooper
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  5. Diane L. Carroll
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Correspondence to Yoshimi Fukuoka.

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Fukuoka, Y., Lindgren, T.G., Rankin, S.H. et al. Cluster analysis: a useful technique to identify elderly cardiac patients at risk for poor quality of life. Qual Life Res 16, 1655–1663 (2007). https://doi.org/10.1007/s11136-007-9272-7

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  • DOI: https://doi.org/10.1007/s11136-007-9272-7

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