A predictive model using myocardial contrast echocardiography for patients presenting to the emergency department with chest pain and a nondiagnostic electrocardiogram.

Abstract

Risk stratification of patients presenting to an emergency department (ED) with suspected cardiac chest pain (CP) and an undifferentiated electrocardiogram (ECG) is difficult. We hypothesized that a risk score incorporating clinical, ECG, Rand contrast echocardiography variables [regional function (RF) and myocardial perfusion (MP)] obtained at the bedside would accurately predict adverse events in occurring within 48 h of ED presentation. A logistic risk model was developed in the initial 1166 patients (cohort 1), and validated in another 720 patients (cohort 2). Any abnormality or ST‐T changes on ECG (OR 2.5, 95% CI:1.4–4.5, p=0.002, and OR 2.9, 95% CI:1.7–4.8, p=0.001, respectively), abnormal RF with normal MP (OR 3.5, 95% CI:1.8–6.5, p=0.001), and abnormal RF with abnormal MP (OR 9.6, 95% CI:5.8–16.0, p=0.001) were found to be significant multivariate predictors of nonfatal myocardial infarction or cardiac death. The estimate of the probability of concordance for the risk model was 0.82 for cohort 1. Likewise, in cohort 2, the c‐index for the risk model was 0.83. In conclusion, a model based on variables obtained at the patient’s bedside can be used to accurately risk stratify patients presenting to the ED with suspected cardiac CP and a nondiagnostic ECG. Its application could enhance care of CP patients in the ED.