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Classifying subgroups of patients with symptoms of acute coronary syndromes: A cluster analysis
Author(s) -
DeVon Holli A.,
Ryan Catherine J.,
Rankin Sally H.,
Cooper Bruce A.
Publication year - 2010
Publication title -
research in nursing and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 85
eISSN - 1098-240X
pISSN - 0160-6891
DOI - 10.1002/nur.20395
Subject(s) - medicine , chest pain , cluster (spacecraft) , latent class model , acute coronary syndrome , physical therapy , myocardial infarction , statistics , computer science , programming language , mathematics
The purpose of the study was to identify subgroups of patients presenting with acute coronary syndromes based on symptom clusters. Two hundred fifty‐six patients completed a symptom assessment in their hospital rooms. Latent class cluster analysis and analysis of variance were used to classify subgroups of patients according to selected clinical characteristics. Four subgroups were identified and labeled as Heavy Symptom Burden, Chest Pain Only, Sweating and Weak, and Short of Breath and Weak (model fit χ 2 [130,891, n = 256] = 867.5, p = 1.00). The largest group of patients experienced classic symptoms of chest pain and shortness of breath but not sweating. Younger patients were more likely to cluster in the Heavy Symptom Burden group ( F = 5.08, p = .002). Interpretation of the clinical significance of these groupings requires further study. © 2010 Wiley Periodicals, Inc. Res Nurs Health 33:386–397, 2010