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Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.

Background: Identifying risk factors associated with mortality is important in providing better prognosis to patients. Consistent with that, Bayesian approach offers a great advantage where it rests on the assumption that all model parameters are random quantities and hence can incorporate prior kno...

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Main Authors: Juhan, N., Zubairi, Y. Z., Khalid, Z. M., Mahmood Zuhdi, A. S.
Format: Article
Published: Iranian Journal of Public Health 2020
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/93335/
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spelling my.utm.933352021-11-19T03:15:46Z http://eprints.utm.my/id/eprint/93335/ Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis. Juhan, N. Zubairi, Y. Z. Khalid, Z. M. Mahmood Zuhdi, A. S. QA Mathematics Background: Identifying risk factors associated with mortality is important in providing better prognosis to patients. Consistent with that, Bayesian approach offers a great advantage where it rests on the assumption that all model parameters are random quantities and hence can incorporate prior knowledge. Therefore, we aimed to develop a reliable model to identify risk factors associated with mortality among ST-Elevation Myocardial Infarction (STEMI) male patients using Bayesian approach. Methods: A total of 7180 STEMI male patients from the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry for the years 2006-2013 were enrolled. In the development of univariate and multivariate logistic regression model for the STEMI patients, Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied. The performance of the model was assessed through convergence diagnostics, overall model fit, model calibration and discrimination. Results: A set of six risk factors for cardiovascular death among STEMI male patients were identified from the Bayesian multivariate logistic model namely age, diabetes mellitus, family history of CVD, Killip class, chronic lung disease and renal disease respectively. Overall model fit, model calibration and discrimination were considered good for the proposed model. Conclusion: Bayesian risk prediction model for CVD male patients identified six risk factors associated with mortality. Among the highest risks were Killip class (OR=18.0), renal disease (2.46) and age group (OR=2.43) respectively. Iranian Journal of Public Health 2020 Article PeerReviewed Juhan, N. and Zubairi, Y. Z. and Khalid, Z. M. and Mahmood Zuhdi, A. S. (2020) Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis. Iranian Journal of Public Health, 49 (9). ISSN 2251-6085
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Juhan, N.
Zubairi, Y. Z.
Khalid, Z. M.
Mahmood Zuhdi, A. S.
Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.
description Background: Identifying risk factors associated with mortality is important in providing better prognosis to patients. Consistent with that, Bayesian approach offers a great advantage where it rests on the assumption that all model parameters are random quantities and hence can incorporate prior knowledge. Therefore, we aimed to develop a reliable model to identify risk factors associated with mortality among ST-Elevation Myocardial Infarction (STEMI) male patients using Bayesian approach. Methods: A total of 7180 STEMI male patients from the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry for the years 2006-2013 were enrolled. In the development of univariate and multivariate logistic regression model for the STEMI patients, Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied. The performance of the model was assessed through convergence diagnostics, overall model fit, model calibration and discrimination. Results: A set of six risk factors for cardiovascular death among STEMI male patients were identified from the Bayesian multivariate logistic model namely age, diabetes mellitus, family history of CVD, Killip class, chronic lung disease and renal disease respectively. Overall model fit, model calibration and discrimination were considered good for the proposed model. Conclusion: Bayesian risk prediction model for CVD male patients identified six risk factors associated with mortality. Among the highest risks were Killip class (OR=18.0), renal disease (2.46) and age group (OR=2.43) respectively.
format Article
author Juhan, N.
Zubairi, Y. Z.
Khalid, Z. M.
Mahmood Zuhdi, A. S.
author_facet Juhan, N.
Zubairi, Y. Z.
Khalid, Z. M.
Mahmood Zuhdi, A. S.
author_sort Juhan, N.
title Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.
title_short Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.
title_full Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.
title_fullStr Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.
title_full_unstemmed Risk factors of mortality among male patients with cardiovascular disease in Malaysia using Bayesian analysis.
title_sort risk factors of mortality among male patients with cardiovascular disease in malaysia using bayesian analysis.
publisher Iranian Journal of Public Health
publishDate 2020
url http://eprints.utm.my/id/eprint/93335/
_version_ 1717093454636384256
score 13.211869

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