Predicting complications in emergency department patients with acute coronary syndrome – Existing risk scores versus a new logistic regression model
Background Patients with acute coronary syndrome (ACS) are often admitted to monitored wards due to the risk of complications. Several risk prediction scores exist, but their use in the emergency department (ED) is limited. We aimed to compare the ability of existing risk scores with a new logistic regression model in predicting complications in ACS patients. Methods This was a secondary analysis
