A sex-based predictive model for acute coronary syndrome in patients calling an emergency center demonstrated good accuracy for men (AUC 0.77) but poor, non-validated accuracy for women (AUC 0.67).
Cohort (n=3,727)
Yes
Does a sex-based predictive model accurately predict acute coronary syndrome in men and women calling an emergency medical communication centre for chest pain?
A predictive model for acute coronary syndrome based on phone interviews accurately identifies risk in men but performs poorly in women, highlighting sex disparities in ACS presentation.
Effect estimate: AUC 0.77 (men) and 0.67 (women) (95% CI 0.73-0.80 (men), 0.60-0.74 (women))
BACKGROUND: Chest pain is a frequent reason for calls in emergency medical communication centre (EMCC). Detecting a coronary origin by phone is a challenge. This is especially so as the presentations differ according to gender. We aimed to establish and validate a sex-based model to predict a coronary origin of chest pain in patients calling an EMCC. METHODS: This prospective cohort study enrolled patients at 18 years of age or older who called the EMCC because of non-traumatic chest pain. The main outcome was the diagnosis of acute coronary syndrome (ACS) determined by expert evaluation of patient files. RESULTS: During 18 months, 3727 patients were enrolled: 2097 (56%) men and 1630 (44%) women. ACS was diagnosed in 508 (24%) men and 139 (9%) women. For men, independent factors associated with an ACS diagnosis were age, tobacco use, severe and permanent pain; retrosternal, breathing non-related and radiating pain; and additional symptoms. The area under the receiver operating characteristic curve (AUC) was 0.76 (95% confidence interval CI 0.73-0.79) for predicting ACS. The accuracy of the male model to predict ACS was validated in a validation dataset (Hosmer-Lemeshow test: p = 0.554); the AUC was 0.77 (95%CI 0.73-0.80). For women, independent factors associated with an ACS diagnosis were age ≥ 60 years, personal history of coronary artery disease, and breathing non-related and radiating pain. The AUC was 0.79 (95%CI 0.75-0.83). The accuracy of the female model to predict ACS was not validated in the validation dataset (Hosmer-Lemeshow test: p = 0.035); the AUC was 0.67 (95%CI 0.60-0.74). CONCLUSIONS: Predictors of an ACS diagnosis in patients calling an EMCC for chest pain differ between men and women. We developed an accurate predictive model for men, but for women, the accuracy was poor. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov ( NCT02042209 ).
Reuter et al. (Thu,) conducted a cohort in Non-traumatic chest pain (n=3,727). Sex-based predictive model was evaluated on Diagnosis of acute coronary syndrome (ACS) (AUC 0.77 (men) and 0.67 (women), 95% CI 0.73-0.80 (men), 0.60-0.74 (women)). A sex-based predictive model for acute coronary syndrome in patients calling an emergency center demonstrated good accuracy for men (AUC 0.77) but poor, non-validated accuracy for women (AUC 0.67).