Document Type

Article

Publication Date

10-1-2013

Comments

This article has been peer reviewed. It is the authors' final version prior to publication in American Journal of Emergency Medicine.

Volume 31, Issue 10, October 2013, Pages 1479-85.

The published version is available at DOI: 10.1016/j.ajem.2013.08.001. Copyright © Elsevier Inc.

Abstract

OBJECTIVE: The objective of the study is to evaluate cardiac risk factors and risk scores for prediction of coronary artery disease (CAD) and adverse outcomes in an emergency department (ED) population judged to be at low to intermediate risk for acute coronary syndrome.

METHODS: Informed consent was obtained from consecutive ED patients who presented with chest pain and were evaluated with coronary computed tomography angiography (cCTA). Cardiac risk factors, clinical presentation, electrocardiogram, and laboratory studies were recorded; the Thrombolysis in Myocardial Infarction (TIMI) and Global Registry of Acute Coronary Events (GRACE) scores were tabulated. Coronary computed tomography angiography findings were rated on a 6-level plaque burden scale and classified for significant CAD (stenosis ≥50%). Adverse cardiovascular outcomes were recorded at 30 days.

RESULTS: Among 250 patients evaluated by cCTA, 143 (57%) had no CAD, 64 (26%) demonstrated minimal plaque (70% stenosis). Six patients developed adverse cardiovascular outcomes. Among traditional cardiac risk factors, only age (older) and sex (male) were significant independent predictors of CAD. Correlation with CAD was poor for the TIMI (r = 0.12) and GRACE (r = 0.09-0.23) scores. The TIMI and GRACE scores were not useful to predict adverse outcomes. Coronary computed tomography angiography identified severe CAD in all subjects with adverse outcomes.

CONCLUSION: Among ED patients who present with chest pain judged to be at low to intermediate risk for acute coronary syndrome, traditional risk factors are not useful to stratify risk for CAD and adverse outcomes. Coronary computed tomography angiography is an excellent predictor of CAD and outcome.

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