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Acute Coronary Syndrome Symptom Clusters: Illustration of Results Using Multiple Statistical MethodsRyan, Catherine J.; Vuckovic, Karen M.; Finnegan, Lorna; Park, Chang G.; Zimmerman, Lani; Pozehl, Bunny; Schulz, Paula; Barnason, Susan; DeVon, Holli A.
Western journal of nursing research, 07/2019, Letnik: 41, Številka: 7Journal Article
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. K-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.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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