A predictive instrument using contrast echocardiography in patients presenting to the emergency department with chest pain and without ST-segment elevation

Abstract

Objective: Risk stratification of patients presenting to the emergency department (ED) with suspected cardiac chest pain (CP) and an undifferentiated electrocardiogram (ECG) is difficult. We hypothesized that in these patients a risk score incorporating clinical, ECG, and myocardial contrast echocardiography (MCE) variables would accurately predict adverse events occurring within the next 48 hours.

Methods: Patients with CP lasting for 30 minutes or more who did not have ST-segment elevation on the ECG, were enrolled. Regional function (RF) and myocardial perfusion (MP) were assessed by MCE. A risk model was developed in the initial 1166 patients (cohort 1) and validated in subsequent 720 patients (cohort 2). Any abnormality or ST changes on ECG (odds ratio [OR] 2.5; 95% confidence interval [CI], 1.4-4.5, P = .002, and OR 2.9, 95% CI, 1.7-4.8, P < .001, respectively), abnormal RF with normal MP (OR 3.5, 95% CI, 1.8-6.5, P < .001), and abnormal RF with abnormal MP (OR 9.6, 95% CI, 5.8-16.0, P < .001) were found to be significant multivariate predictors of nonfatal myocardial infarction or cardiac death.

Results: The estimate of the probability of concordance for the risk model was 0.82 for cohort 1 and 0.83 for cohort 2. The risk score in both cohorts stratified patients into 5 distinct risk groups with event rates ranging from 0.3% to 58%.

Conclusion: A simple predictive instrument has been developed from clinical, ECG, and MCE findings obtained at the bedside that can accurately predict events occurring within 48 hours in patients presenting to the ED with suspected cardiac CP and an ECG that is not diagnostic for acute ischemic injury. Its application could enhance care of patients with CP in the ED. For instance, patients with a risk score of 0 could be discharged from the ED without further workup. However, this needs to be validated in a multicenter study.

Copyright 2010 American Society of Echocardiography. Published by Mosby, Inc. All rights reserved.

Figures

Figure 1

The 14-segment myocardial model for regional function and myocardial perfusion analyses. Individual segments were grouped into 3 coronary territories. See text for details.

Figure 2

Proportion of cohort 1 patients with a cardiac event and average of predicted probabilities for a cardiac event based on logistic regression model. The numbers above each pair of bars indicate the number of individuals with that risk score. Abbreviations: obs=observed proportion, pre=average of predicted probabilities from model.

Figure 3

Proportion of cohort 2 patients with a cardiac event and average of predicted probabilities for a cardiac event based on logistic regression model. The numbers above each pair of bars indicate the number of individuals with that risk score. Abbreviations: same as in Figure 2.