Teketelew, Girma and Medhin, Gimay and Fenta, Teferi Gedif (2022) Survival and Its Predictors among Tuberculosis Patients on Treatment in Selected Health Centers of Addis Ababa, Ethiopia: A Retrospective Cohort Study. Open Journal of Preventive Medicine, 12 (10). pp. 223-238. ISSN 2162-2477
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Abstract
Tuberculosis is one of the leading causes of morbidity and mortality globally. Although different strategies have been designed and implemented to combat it, it has continuously increased in the past five years, resulting in 10 million new cases and 1.6 million deaths. This study aims to estimate survival and predictors among tuberculosis patients on treatment in selected health centers in Addis Ababa, Ethiopia. The study employed a retrospective cohort design where data were collected by reviewing medical records of tuberculosis patients who were registered from May 2016 to May 2017 on treatment in 20 selected health centers in Addis Ababa. Independent predictors were identified, and the strength of association between dependent and independent predictors was determined using the Weibull regression model. Before computing Weibull regression analysis, Cox proportional assumption, model diagnosis, and fitness were checked. The hazard ratio was calculated to indicate the strength of association. Of 371 TB patients, about 136 (36.7%) died during the treatment period. Most TB deaths occurred during the intensive phase, and the overall estimated median survival time was 157 days. In the multivariable Weibull model, age (HR = 0.98), baseline weight (HR = 0.96, P = 0.03), tuberculosis treatment phase (continuation phase, HR = 0.48), and tuberculosis type (pulmonary negative TB, HR = 19.92) were found to be independent predictors of time to death of tuberculosis patients. Finally, the study concluded that the survival time to death of the patients is high. The health care providers should give special attention and follow up for pulmonary negative and underweight TB patients.
Item Type: | Article |
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Subjects: | STM Digital Library > Medical Science |
Depositing User: | Unnamed user with email support@stmdigitallib.com |
Date Deposited: | 17 Feb 2023 09:57 |
Last Modified: | 24 Jun 2024 04:35 |
URI: | http://archive.scholarstm.com/id/eprint/397 |