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J Shahrekord Univ Med Sci. 2019;21(4): 169-174.
doi: 10.34172/jsums.2019.30
  Abstract View: 1541
  PDF Download: 551

Original Article

Factors affecting time until myocardial infarction in hypertension patients using truncated Cox regression

Abolfazl Hosseinnataj 1 ORCID logo, Jamshid Yazdani-Charati 2* ORCID logo, Hossein Mohsenipouya 1 ORCID logo, Ali Ghaemian 4, Roja Nikaein 5, Mohammad Bagheri 6

1 PhD Candidate, Student Research Center, Mazandaran University of Medical Sciences, Sari, Iran
2 Department of Biostatistics, Cardiovascular Research Center, School of Health, Mazandaran University of Medical Sciences, Sari, Iran
3 Health Education and Promotion, Faculty of Nursing, Mazandaran University of Medical Sciences, Sari, Iran
4 Department of Cardiovascular Disease, School of Medicine, Cardiovascular Research Center, Mazandaran University of Medical Sciences, Sari, Iran
5 School of Health, Mazandaran University of Medical Sciences, Sari, Iran
6 Mazandaran University of Medical Sciences, Sari, Iran
*Corresponding Author: *Corresponding Author: Jamshid Yazdani-Charati, Faculty of Health, Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran, Tel: 0033242001, Email: , Email: Jamshid.charati@gmail.com

Abstract

Background and aims: Hypertension is one of the most common and important risk factors of cardiovascular diseases. This phenomenon, if not cured, causes lots of problems in vital organs of the body like kidneys, brain, eyes, and heart. The aim of the current study was to identify factors which affect the time until myocardial infarction (MI) in hypertension patients using truncated Cox regression.

Methods: This study was a population retrospective cohort and its statistical population included patients with hypertension symptoms, who had MI for the first time in Sari. A decision was made based on continuing the study as a nested case and control study because the number of MI incidents was low (7%) in the studied sample. In addition, the Cox’s model and truncated Cox were used for determining the factors affecting the patients’ survival.

Results: The median and mean survival times in this sample were equal to 57 and 66.44 months, respectively. Considering time truncation, family history (HR=1.70) and the age at diagnosis (HR=0.99) were statistically significant in the Cox’s model (P< 0.05).

Conclusion: Overall, using the Akaike criterion for comparing the survival time without the effect of truncation, the Cox’s model demonstrated better fitness by controlling the truncation effect. These results show the importance of controlling the truncation in those diseases in which it is impossible to distinguish the time of the appearance from the symptoms. 

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Submitted: 02 Sep 2018
Accepted: 17 Mar 2019
ePublished: 30 Aug 2019
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