![]() MREC waived informed patient consent for NCVD. The NCVD registry was approved by the Medical Review & Ethics Committee (MREC), Ministry of Health (MOH) Malaysia in 2007 (Approval Code: NMRR-07-20-250). We used retrospective data from the Malaysian National Cardiovascular Database (NCVD-ACS) registry collected between 2006 until 2016. The study aims to identify factors and develop an ML model risk calculator that predicts short and long-term mortality in a heterogeneous South-East Asian population. To our knowledge, the development, and application of ML algorithms to predict short- and long-term mortality post-STEMI in a heterogeneous Asian population has yet to be reported. ML has been shown to outperform the conventional risk scoring model in population-specific mortality studies, post-STEMI, in countries like China, Israel and Korea. Ĭurrent evidence supporting the use of ML over statistically-based models in mortality predictions include Logistic Regression (LR), Support Vector Machine (SVM) and Random Forest (RF). There is a need to develop models which consider these multiple risk factors and outcomes, including the use of machine learning (ML) algorithms. This discrepancy is difficult to explain especially in the context of a higher disease burden amongst Asian patients.Ĭonventional cardiovascular disease (CVD) risk assessment models assume that risk factors have a linear relationship to clinical outcomes, leading to the oversimplification of a truly complex correlation. Studies using TIMI scores amongst Asians revealed a higher incidence of STEMI when compared to their Caucasian counterpart with somewhat similar mortality risk. TIMI scoring, unlike the GRACE score, was derived from patients with ST-segment elevation myocardial infarction (STEMI) only. The TIMI risk score is widely used due to its simplicity in calculation and accuracy in STEMI patients. Conventional risk scores may not be able to account for nuances related to the individual region in terms of disease burden, healthcare resources and available interventions. South-East Asia in particular is unique because of its heterogeneity due to inherent genetic variations in an already diverse group of multi-ethnic communities. Asian countries tend to have younger patients with myocardial infarction, a higher burden of diabetes melitus, hypertension and renal failure as well as higher rates of delayed presentation for medical care. These scores are extrapolated from studies with predominantly Caucasian patients with limited participation from Asia. Prediction of mortality risks associated with the acute coronary syndrome (ACS) is often evaluated using risk scores such as the Thrombolysis in Myocardial Infarction (TIMI) or Global Registry of Acute Cardiac Events (GRACE) scores. Half of the global burden related to ischemic heart disease occurs within the Asia-Pacific region. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. Data are however available from NHAM upon request using or email them at Any findings from the data need to be reported and permission needs to be obtained from the NHAM committee before publication.įunding: This work was supported by the University of Malaya Internal grant (Project No: GPF013B- 2018). ![]() The data belongs to the individual ministry of health universities hospitals and private hospitals that require multiple institutional agreements for data release to third parties hence ethical approval is needed for analysis. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: The data that support the findings of this study are available from the National Heart Association of Malaysia (NHAM) but restrictions apply to the availability of these data, and so are not publicly available. Received: JanuAccepted: JPublished: August 2, 2021Ĭopyright: © 2021 Aziz et al. PLoS ONE 16(8):Įditor: Yoshihiro Fukumoto, Kurume University School of Medicine, JAPAN (2021) Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach. Citation: Aziz F, Malek S, Ibrahim KS, Raja Shariff RE, Wan Ahmad WA, Ali RM, et al. ![]()
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