Survival and predictors of death after successful treatment among smear positive tuberculosis: a cohort study

Background: Tuberculosis (TB) can affect patients life even after successful treatment. In this study, we aimed to determine the survival rate of patients with smear positive TB after successful treatment and identify the predictors of mortality. Methods: This was a prospective study. The source of data was the TB registry system in Iran and 964 patients were eligible for the study. The life table was used to determine the annual survival rate. Survival curves were estimated using Kaplan-Meier and were compared using the log-rank test. In order to determine the predictors of survival, four models of Cox regression, exponential, Weibull and log-logistic fitted and finally exponential model with minimum akaike information criteria and Bayesian information criterion values were selected. Then, variables with significant levels