Acute Coronary Syndrome Symptom Clusters: Illustration of Results Using Multiple Statistical Methods. Journal Article

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Authors: Ryan, CJ; Vuckovic, KM; Finnegan, L; Park, CG; Zimmerman, L; Pozehl, B; Schulz, P; Barnason, S; DeVon, HA
Article Title: Acute Coronary Syndrome Symptom Clusters: Illustration of Results Using Multiple Statistical Methods.
Abstract: Researchers have employed various methods to identify symptom clusters in cardiovascular conditions, without identifying rationale. Here, we test clustering techniques and outcomes using a data set from patients with acute coronary syndrome. A total of 474 patients who presented to emergency departments in five United States regions were enrolled. Symptoms were assessed within 15 min of presentation using the validated 13-item ACS Symptom Checklist. Three variable-centered approaches resulted in four-factor solutions. Two of three person-centered approaches resulted in three-cluster solutions. -means cluster analysis revealed a six-cluster solution but was reduced to three clusters following cluster plot analysis. The number of symptoms and patient characteristics varied within clusters. Based on our findings, we recommend using (a) a variable-centered approach if the research is exploratory, (b) a confirmatory factor analysis if there is a hypothesis about symptom clusters, and (c) a person-centered approach if the aim is to cluster symptoms by individual groups.
Journal Title: Western journal of nursing research
ISSN: 1552-8456; 0193-9459
Publisher: Unknown  
Date Published: 2019