Derivation and validation of a risk stratification model to identify coronary artery disease in women who present to the emergency department with potential acute coronary syndromes

To derive and validate a model to identify women who would benefit from further evaluation of chest pain after an initial negative emergency department (ED) evaluation for acute coronary syndrome (ACS). The derivation and validation cohorts were comprised of women who presented to the ED with chest pain at two university hospitals. Patients were excluded if the initial electrocardiogram (ECG) or cardiac markers were consistent with ACS. Patients were followed for 30 days after the index visit to identify evidence of coronary artery disease (CAD), which was defined as a positive diagnostic study, myocardial infarction, or death. The authors performed a logistic regression analysis to identify significant predictors of CAD. A scoring system was developed based on the B-coefficient of these significant predictors. Levels of risk were assigned by summing and categorizing the cumulative risk score into low-, moderate-, and high-risk groups. The derivation and validation sets were comprised of 733 and 2,440 women, respectively. From the derivation set predictors of CAD (score) were history of CAD (1), age > or = 60 years (1), and high clinical suspicion (3). Low risk was defined as a score = 0, moderate risk score = 1-2, high risk score > or = 3. In the validation set, the numbers of patients with evidence of CAD were four of 1,348 (0.30%), 18 of 498 (3.6%), and 71 of 594 (11.9%) in the low-, moderate-, and high-risk groups, respectively. The risk of underlying CAD in women who present to the ED with potential ACS may be determined using a simple risk stratification score.