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Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia

Tuberculosis is the most common opportunistic infection among HIV/AIDS patients, including those following Antiretroviral Therapy treatment. The risk of tuberculosis infection is higher in people living with HIV/AIDS than in people who are free from HIV/AIDS. Many studies focused on prevalence and d...

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Autores principales: Umeta, Abdi Kenesa, Yermosa, Samuel Fikadu, Dufera, Abdisa G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526740/
https://www.ncbi.nlm.nih.gov/pubmed/36182998
http://dx.doi.org/10.1038/s41598-022-20872-7
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author Umeta, Abdi Kenesa
Yermosa, Samuel Fikadu
Dufera, Abdisa G.
author_facet Umeta, Abdi Kenesa
Yermosa, Samuel Fikadu
Dufera, Abdisa G.
author_sort Umeta, Abdi Kenesa
collection PubMed
description Tuberculosis is the most common opportunistic infection among HIV/AIDS patients, including those following Antiretroviral Therapy treatment. The risk of tuberculosis infection is higher in people living with HIV/AIDS than in people who are free from HIV/AIDS. Many studies focused on prevalence and determinants of tuberculosis in HIV/AIDS patients without taking into account the censoring aspects of the time to event data. Therefore, this study was undertaken with aim to model time to tuberculosis co-infection of HIV/AIDS patients under follow-up at Jimma Medical Center, Ethiopia using Bayesian parametric survival models. A data of a retrospective cohort of 421 HIV/AIDS patients under follow-up from January 2016 to December 2020 until active tuberculosis was diagnosed or until the end of the study was collected from Jimma Medical Center, Ethiopia. The analysis of the data was performed using R-INLA software package. In order to identify the risk factors which have association with tuberculosis co-infection survival time, Bayesian parametric accelerated failure time survival models were fitted to the data using Integrated Nested Laplace Approximation methodology. About 26.37% of the study subjects had been co-infected with tuberculosis during the study period. Among the parametric accelerated failure time models, the Bayesian log-logistic accelerated failure time model was found to be the best fitting model for the data. Patients who lived in urban areas had shorter tuberculosis co-infection free survival time compared to those who lived in rural areas with an acceleration factor of 0.2842. Patients who smoke and drink alcohol had also shorter tuberculosis co-infection survival time than those who do not smoke and drink alcohol respectively. Patients with advanced WHO clinical stages(Stage III and IV), bedridden functional status, low body mass index and severe anemic status had shorter tuberculosis co-infection survival time. Place of residence, smoking, drinking alcohol, larger family size, advanced clinical stages(Stage III and Stage IV), bedridden functional status, CD4 count ([Formula: see text] 200 cells/mm(3) and 200–349 cells/mm(3)), low body mass index and low hemoglobin are the factors that lead to shorter tuberculosis co-infection survival time in HIV/AIDS patients. The findings of the study suggested us to forward the recommendations to modify patients’ life style, early screening and treatment of opportunistic diseases like anemia , as well as effective treatment and management of tuberculosis and HIV co-infection are important to prevent tuberculosis and HIV co-infection.
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spelling pubmed-95267402022-10-03 Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia Umeta, Abdi Kenesa Yermosa, Samuel Fikadu Dufera, Abdisa G. Sci Rep Article Tuberculosis is the most common opportunistic infection among HIV/AIDS patients, including those following Antiretroviral Therapy treatment. The risk of tuberculosis infection is higher in people living with HIV/AIDS than in people who are free from HIV/AIDS. Many studies focused on prevalence and determinants of tuberculosis in HIV/AIDS patients without taking into account the censoring aspects of the time to event data. Therefore, this study was undertaken with aim to model time to tuberculosis co-infection of HIV/AIDS patients under follow-up at Jimma Medical Center, Ethiopia using Bayesian parametric survival models. A data of a retrospective cohort of 421 HIV/AIDS patients under follow-up from January 2016 to December 2020 until active tuberculosis was diagnosed or until the end of the study was collected from Jimma Medical Center, Ethiopia. The analysis of the data was performed using R-INLA software package. In order to identify the risk factors which have association with tuberculosis co-infection survival time, Bayesian parametric accelerated failure time survival models were fitted to the data using Integrated Nested Laplace Approximation methodology. About 26.37% of the study subjects had been co-infected with tuberculosis during the study period. Among the parametric accelerated failure time models, the Bayesian log-logistic accelerated failure time model was found to be the best fitting model for the data. Patients who lived in urban areas had shorter tuberculosis co-infection free survival time compared to those who lived in rural areas with an acceleration factor of 0.2842. Patients who smoke and drink alcohol had also shorter tuberculosis co-infection survival time than those who do not smoke and drink alcohol respectively. Patients with advanced WHO clinical stages(Stage III and IV), bedridden functional status, low body mass index and severe anemic status had shorter tuberculosis co-infection survival time. Place of residence, smoking, drinking alcohol, larger family size, advanced clinical stages(Stage III and Stage IV), bedridden functional status, CD4 count ([Formula: see text] 200 cells/mm(3) and 200–349 cells/mm(3)), low body mass index and low hemoglobin are the factors that lead to shorter tuberculosis co-infection survival time in HIV/AIDS patients. The findings of the study suggested us to forward the recommendations to modify patients’ life style, early screening and treatment of opportunistic diseases like anemia , as well as effective treatment and management of tuberculosis and HIV co-infection are important to prevent tuberculosis and HIV co-infection. Nature Publishing Group UK 2022-10-01 /pmc/articles/PMC9526740/ /pubmed/36182998 http://dx.doi.org/10.1038/s41598-022-20872-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Umeta, Abdi Kenesa
Yermosa, Samuel Fikadu
Dufera, Abdisa G.
Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia
title Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia
title_full Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia
title_fullStr Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia
title_full_unstemmed Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia
title_short Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients at Jimma Medical Center, Ethiopia
title_sort bayesian parametric modeling of time to tuberculosis co-infection of hiv/aids patients at jimma medical center, ethiopia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526740/
https://www.ncbi.nlm.nih.gov/pubmed/36182998
http://dx.doi.org/10.1038/s41598-022-20872-7
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