A new risk stratification score for patients with suspected cardiac chest pain in emergency departments based on machine learning

摘要

: Chest pain is one of the most common complaints for patients attending emergency departments (EDs) globally. It is important to accurately stratify risk of possible acute coronary syndrome (ACS) for these patients. Several risk stratification scores such as thrombolysis in myocardial infarction (TIMI), global registry for acute coronary events (GRACE), Banach and HEART are helpful. Previous research in our setting compared these four scores and found that the HEART score, with a C-statistic of 0.731, was the best for predicting 7-day major adverse cardiac events (MACE).