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Modeling the Survival of Tuberculosis Patients in Eastern Zone of Tigray Regional State

Authors Geleso MG

Received 26 February 2020

Accepted for publication 9 May 2020

Published 25 May 2020 Volume 2020:13 Pages 473—481


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Marco Carotenuto

Mulugeta Geremew Geleso

Department of Statistics, Wolkite University, Wolkite, Ethiopia

Correspondence: Mulugeta Geremew Geleso Tel +251-913731672

Background: Tuberculosis (TB) is still a public health problem and amongst the top ten leading causes of death. The aim of this paper was to identify the factors that significantly affect the survival of tuberculosis patients.
Methods: A retrospective cohort study was carried out in Adigrat General and Wukro hospitals, Eastern Zone of Tigray region, Ethiopia. Data for this study were obtained from medical records of all TB cases registered from September 2016 to August 2017 in the two hospitals. Log-rank test and Kaplan–Meier plot were used to evaluate the survival pattern of TB patients. A multivariable Cox proportional regression model was employed to identify the predictors of mortality. Factors with a P-value smaller than 0.05 were taken as statistically significant facilitators of TB death.
Results: Of the 397 patients studied over the specified period, 23 (5.8%) had died. A statistically significant survival difference was observed among gender, residence, HIV status, treatment category, and age category of patients. In multivariable cox regression, lower survival rates were observed among patients aged ≥ 45 years (HR = 5.315, 95% CI: 1.231– 22.959), relapse cases (HR = 4.069, 95% CI: 1.636– 10.119), patients with extrapulmonary TB (HR = 3.054, 95% CI: 1.044– 8.940), patients from rural areas (HR = 2.834, 95% CI: 1.161– 6.916), patients with a bodyweight of ≤ 50 kg and HIV-positive patients.
Conclusion: Based on the survival experience of TB patients, advancing age, extrapulmonary TB infection, living in rural residence, lower bodyweight at beginning of treatment, HIV co-infection, and being a retreatment patient were predictors of mortality. To achieve the “End TB Strategy” goal of zero death, proper targeting of care to these vulnerable groups should be advised.

Keywords: hazard probability, mortality, tuberculosis, survival

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