Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach.

Background: Conventional risk score for predicting short and long-term mortality following an ST-segment elevation myocardial infarction (STEMI) is often not population specific.

Objective: Apply machine learning for the prediction and identification of factors associated with short and long-term mortality in Asian STEMI patients and compare with a conventional risk score.

Methods: The National Cardiovascular Disease Database for Malaysia registry, of a multi-ethnic, heterogeneous Asian population was used for in-hospital (6299 patients), 30-days (3130 patients), and 1-year (2939 patients) model development.

Impact of cardiac care variation on ST-elevation myocardial infarction outcomes in Malaysia.

Developing countries face challenges in providing the best reperfusion strategy for patients with ST-segment elevation myocardial infarction because of limited resources. This causes wide variation in the provision of cardiac care. The aim of this study was to assess the impact of variation in cardiac care provision and reperfusion strategies on patient outcomes in Malaysia.

An Asian validation of the TIMI risk score for ST-segment elevation myocardial infarction.

Background: Risk stratification in ST-elevation myocardial infarction (STEMI) is important, such that the most resource intensive strategy is used to achieve the greatest clinical benefit. This is essential in developing countries with wide variation in health care facilities, scarce resources and increasing burden of cardiovascular diseases. This study sought to validate the Thrombolysis In Myocardial Infarction (TIMI) risk score for STEMI in a multi-ethnic developing country.