Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis

Anne G. Rosenfeld; Elizabeth P. Knight; Alana Steffen; Larisa Burke; Mohamud Daya; Holli A. DeVon

doi:10.1016/j.hrtlng.2015.05.008

Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis

Anne G. Rosenfeld
, Elizabeth P. Knight
, Alana Steffen
, Larisa Burke
, Mohamud Daya
, Holli A. DeVon

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

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)
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	https://doi.org/10.1016/j.hrtlng.2015.05.008
State	Published - Sep 1 2015

Funding

This study is funded by NIH : R01 NR012012 (DeVon, PI).

Funders	Funder number
Author National Institutes of Health National Institutes of Health National Institutes of Health National Institutes of Health The Bev Hartig Huntington's Disease Foundation National Institutes of Health
National Institute of Nursing Research	R01NR012012

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

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10.1016/j.hrtlng.2015.05.008

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Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis. / Rosenfeld, Anne G.; Knight, Elizabeth P.; Steffen, Alana et al.
In: Heart and Lung: Journal of Acute and Critical Care, Vol. 44, No. 5, 01.09.2015, p. 368-375.

Research output: Contribution to journal › Article › peer-review

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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.",

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AU - Knight, Elizabeth P.

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AU - Burke, Larisa

AU - Daya, Mohamud

AU - DeVon, Holli A.

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AB - 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.

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KW - Diagnosis

KW - Latent class analysis

KW - Race

KW - Sex

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Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis

Abstract

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Keywords

ASJC Scopus subject areas

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