Abstract
Objectives: To identify classes of individuals presenting to the ED for suspected ACS who shared similar symptoms and clinical characteristics. Background: Describing symptom clusters in undiagnosed patients with suspected ACS is a novel and clinically relevant approach, reflecting real-world emergency department evaluation procedures. Methods: Symptoms were measured using a validated 13-item symptom checklist. Latent class analysis was used to describe symptom clusters. Results: The sample of 874 was 37% female with a mean age of 59.9 years. Four symptom classes were identified: Heavy Symptom Burden (Class 1), Chest Symptoms and Shortness of Breath (Class 2), Chest Symptoms Only (Class 3), and Weary (Class 4). Patients with ACS were more likely to cluster in Classes 2 and 3. Women and younger patients were more likely to group in Class 1. Conclusions: Further research is needed to determine the value of symptom clusters in the ED triage and management of suspected ACS.
Original language | English (US) |
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Pages (from-to) | 368-375 |
Number of pages | 8 |
Journal | Heart and Lung: Journal of Acute and Critical Care |
Volume | 44 |
Issue number | 5 |
DOIs | |
State | Published - Sep 1 2015 |
Keywords
- Acute coronary syndrome
- Age
- Diagnosis
- Latent class analysis
- Race
- Sex
- Symptom clusters
ASJC Scopus subject areas
- Pulmonary and Respiratory Medicine
- Critical Care and Intensive Care Medicine
- Cardiology and Cardiovascular Medicine