Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia

Mvocardial infarction (MI), which also known as heart attack, has been the top cause of death worldwide. High rates of mortality were also reported within the first 30 days alter a heart attack. The mortality within a short span of' time also called as sudden death. Using logistic regression...

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Main Author:	Muhammad Hazrani bin Abdul Halim
Format:	Thesis
Language:	English
Subjects:	Heart Diseases > complications. Cardiology myocardial infraction, risk factors, sudden death
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spelling	my-usim-ddms-125512024-05-29T04:19:24Z Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia Muhammad Hazrani bin Abdul Halim Mvocardial infarction (MI), which also known as heart attack, has been the top cause of death worldwide. High rates of mortality were also reported within the first 30 days alter a heart attack. The mortality within a short span of' time also called as sudden death. Using logistic regression, we investigate the relationship between the risk of' sudden death following MI and various risk factors and Annulate a probability model to predict sudden death. The dataset used in the study consist of 28.412 observations from 19 hospitals and medical institutions, which was provided by National Cardiovascular Disease Database (NCVD). Regression results show that year of' MI event, gender. and smoking habit have the least impact on the probability of' sudden death. Elderlies, diabetic, and non-hypertensive Ml patients have a higher risk of sudden death. BMI and cholesterol level were observed to have an inverse-J-shaped relationship with sudden death, which means people in middle classes have higher survival chance. The overall performance of the logistic model suggests that the model can be used to predict the outcome MI patients after 30 days of onset. Keywords: Iogistic regression, mortaIity prediction, myocardial infraction, risk factors, sudden death Universiti Sains Islam Malaysian 2018-08 Thesis en https://oarep.usim.edu.my/handle/123456789/12551 https://oarep.usim.edu.my/bitstreams/d8e67215-c6ae-4b15-a6d5-61c09374409f/download 8a4605be74aa9ea9d79846c1fba20a33 https://oarep.usim.edu.my/bitstreams/0dc576df-9dcf-44bc-96d2-a9e4050261e8/download 62abdaccafcf020389b1dce37e651313 https://oarep.usim.edu.my/bitstreams/d2aff72b-c5ca-4751-a0b6-3df4d4b2a75c/download e81b0c3f3c80041b4ea531232392ecdd https://oarep.usim.edu.my/bitstreams/f3502996-4299-4ba5-9bd1-e7ad474b7b7c/download 99d14e51849fe0d1e7edeb0c01ea0254 https://oarep.usim.edu.my/bitstreams/fa569abe-f277-422a-b3bc-8250e0b7151d/download 59223d6f1dfd872f9d775556eb5c13b7 https://oarep.usim.edu.my/bitstreams/fc398db8-b7f5-4955-923c-f850d6ee3068/download e9949e4cca59329c478e2a3700accd15 https://oarep.usim.edu.my/bitstreams/3d11a479-cdd2-4048-a82d-3f6d90f4e329/download 7368e20c2452015c5cd9f5cf59868f93 https://oarep.usim.edu.my/bitstreams/b4d267c7-88eb-4bbc-9670-f5ae3b852bac/download 9310f264fc6ebc3d0a13bc8c58b1154a https://oarep.usim.edu.my/bitstreams/a9f5863b-9742-4403-8f64-e98b926e0bd6/download a371d6baf13136657933fc234f6e1385 Heart Diseases--complications. Cardiology myocardial infraction, risk factors, sudden death
institution	Universiti Sains Islam Malaysia
collection	USIM Institutional Repository
language	English
topic	Heart Diseases--complications. Cardiology myocardial infraction, risk factors, sudden death
spellingShingle	Heart Diseases--complications. Cardiology myocardial infraction, risk factors, sudden death Muhammad Hazrani bin Abdul Halim Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia
description	Mvocardial infarction (MI), which also known as heart attack, has been the top cause of death worldwide. High rates of mortality were also reported within the first 30 days alter a heart attack. The mortality within a short span of' time also called as sudden death. Using logistic regression, we investigate the relationship between the risk of' sudden death following MI and various risk factors and Annulate a probability model to predict sudden death. The dataset used in the study consist of 28.412 observations from 19 hospitals and medical institutions, which was provided by National Cardiovascular Disease Database (NCVD). Regression results show that year of' MI event, gender. and smoking habit have the least impact on the probability of' sudden death. Elderlies, diabetic, and non-hypertensive Ml patients have a higher risk of sudden death. BMI and cholesterol level were observed to have an inverse-J-shaped relationship with sudden death, which means people in middle classes have higher survival chance. The overall performance of the logistic model suggests that the model can be used to predict the outcome MI patients after 30 days of onset. Keywords: Iogistic regression, mortaIity prediction, myocardial infraction, risk factors, sudden death
format	Thesis
author	Muhammad Hazrani bin Abdul Halim
author_facet	Muhammad Hazrani bin Abdul Halim
author_sort	Muhammad Hazrani bin Abdul Halim
title	Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia
title_short	Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia
title_full	Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia
title_fullStr	Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia
title_full_unstemmed	Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia
title_sort	modelling and predicting sudden death following myocardial infarction in malaysia
granting_institution	Universiti Sains Islam Malaysian
_version_	1812444719193522176

Modelling And Predicting Sudden Death Following Myocardial Infarction In Malaysia

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