Halim M.H.A.Yusoff Y.S.Yusuf M.M.2024-05-292024-05-29201897807400000000094243X10.1063/1.50416812-s2.0-85049775689https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049775689&doi=10.1063%2f1.5041681&partnerID=40&md5=cf67ebd3bca86e02138b61dfcf2b6a8chttps://oarep.usim.edu.my/handle/123456789/9646The first 30 days after the onset of myocardial infarction (MI), also known as heart attack, is very crucial for the patients, as the risk of deaths during the period of time is considerably high. Using logistic regression, we will model the deaths within 30 days following MI, and see how the MI risk factors affect the probability of sudden deaths. A dataset for the regression consists of 28420 patients from several hospitals in Malaysia, provided by National Cardiovascular Disease Database (NCVD). The risk factors studied in this paper are age, gender, year of onset, smoking habit, BMI, diabetes, hypertension, and cholesterol level. The regression results show that the risk of sudden deaths increase with age and diabetes, while BMI, hypertension and cholesterol level have inverse effects on sudden deaths rate. There are no significant changes in the sudden deaths rate observed for different gender, smoking habits and the year of onset. � 2018 Author(s).en-USLogistic regressionMyocardial infarctionRisk factorsSudden deathConference Paper197440007