Acute Coronary Syndrome Symptom Clusters: Illustration of Results Using Multiple Statistical Methods. (July 2019)

• Record Type: Journal Article
• Authors: Ryan, Catherine J.; Vuckovic, Karen M.; Finnegan, Lorna; Park, Chang G.; Zimmerman, Lani; Pozehl, Bunny; Schulz, Paula; Barnason, Susan; DeVon, Holli A.
• Is Part Of: Western journal of nursing research. Volume 41:Number 7(2019)
• Page Start: 1032
• Page End: 1055
• Publication Date: 2019-07
• Subjects: cluster analysis -- symptom clusters -- symptoms -- latent class analysis -- acute coronary syndrome; Nursing -- Research -- Periodicals; Nursing -- Periodicals; Nursing -- Research -- West (U.S.) -- Periodicals; Nursing -- West (U.S.) -- Periodicals; Nursing -- Periodicals; Nursing Research -- Periodicals; Soins infirmiers -- Recherche -- Périodiques; Soins infirmiers -- Périodiques; Soins infirmiers -- Recherche -- États-Unis (Ouest) -- Périodiques; Soins infirmiers -- États-Unis (Ouest) -- Périodiques; Soins infirmiers; Recherche; États-Unis (Ouest); Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 610.730702
• DOI: 10.1177/0193945918822323
• Languages: English
• ISSNs: 0193-9459

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. 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.