alexa Identifying Some Risk Factors of Time to Recurrent Relapses in Bipolar I Disorder Patients using Frailty Model of Survival Analysis
ISSN: 2378-5756

Journal of Psychiatry
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Research Article

Identifying Some Risk Factors of Time to Recurrent Relapses in Bipolar I Disorder Patients using Frailty Model of Survival Analysis

Seyede Solmaz Taheri1, Mohammad Reza Khodaie Ardakani2, Masoud Karimlou1 and Mehdi Rahgozar1*

1Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

2Department of Psychiatry, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

*Corresponding Author:
Mehdi Rahgozar
Department of Biostatistics
University of Social Welfare and Rehabilitation Sciences
Tehran, Iran
Tel: +98-21-22180146
E-mail: [email protected]

Received Date: March 19, 2016; Accepted Date: June 28, 2016; Published Date: July 05, 2016

Citation: Taheri SS, Ardakani MRK, Karimlou M, Rahgozar M (2016) Identifying Some Risk Factors of Time to Recurrent Relapses in Bipolar I Disorder Patients using Frailty Model of Survival Analysis J Psychiatry 19:376. doi:10.4172/ jop.1000376

Copyright: © 2016 Taheri SS, et al. 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.

 

Abstract

Objective: Bipolar I disorder patients often experience relapse once and even more with no limit on number of relapses. The time to relapses of these patients are rarely studied particularly considering heterogeneity across individuals. The aim of this study was to identify some risk factors of time to recurrent relapses in bipolar I disorder patients with a recurrent event model in survival analysis.
Methods: In a retrospective longitudinal study, data of medical records of 526 bipolar I disorder patients who had referred to Razi Psychiatric hospital in Tehran from 1993 to 2011 with at least one relapse, with-out relapse in other hospitals or home in this duration, were investigated and time to recurrent relapses were collected in months. Semiparametric penalized frailty model which consider whit-in subject correlation and heterogeneity across individuals, was applied to identify the risk factors of recurrent time to relapses.
Results: Significant frailty parameter (p<0.001) prove presence of heterogeneity among data. In frailty model the effects of substance abuse (p=0.041), regular fluctuation (p=0.002) and marital status (p=0.009) were significant on the hazard of recurrent times to relapses but other variables showed no significant effect.
Conclusions: Substance abuse, marital status and RF are important risk factors in order to plan for postpone the time to next relapses. More studies are required to clear out the effect of other covariates with this model.

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