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Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya

BACKGROUND: Despite robust Tuberculosis (TB) program with effective chemotherapy and high coverage, treatment interruption remains a serious problem. Interrupting TB treatment means that patients remain infectious for longer time and are at risk of developing drug resistance and death. This study wa...

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Autores principales: Wekunda, Paul Waliaula, Aduda, Dickens S. Omondi, Guyah, Bernard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638988/
https://www.ncbi.nlm.nih.gov/pubmed/34855844
http://dx.doi.org/10.1371/journal.pone.0260669
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author Wekunda, Paul Waliaula
Aduda, Dickens S. Omondi
Guyah, Bernard
author_facet Wekunda, Paul Waliaula
Aduda, Dickens S. Omondi
Guyah, Bernard
author_sort Wekunda, Paul Waliaula
collection PubMed
description BACKGROUND: Despite robust Tuberculosis (TB) program with effective chemotherapy and high coverage, treatment interruption remains a serious problem. Interrupting TB treatment means that patients remain infectious for longer time and are at risk of developing drug resistance and death. This study was conducted to identify and describe predictors of TB treatment interruption. METHODS: A cohort of 291 notified TB patients from 20 selected health facilities in Vihiga County were enrolled in to the study and followed up until the end of treatment. Patient characteristics that potentially predict treatment interruption were recorded during treatment initiation using structured questionnaires. Patients who interrupted treatment were traced and reasons for stoppage of treatment recorded. Kaplan Meier method was used to estimate probabilities of treatment interruption by patient characteristics and determine time intervals. The Log rank test for the equality of survival distributions analyzed significance of survival differences among categorical variables. For multivariable analysis, Cox proportional hazard model, was fitted to identify predictors of TB treatment interruption through calculation of hazard ratios with 95% Confidence Intervals (CIs). For variable analysis, statistical significance was set at P ≤ 0.05. Reasons for treatment interruption were categorized according to most recurrent behavioral or experiential characteristics. RESULTS: Participants’ median age was 40 years (IQR = 32–53) and 72% were male. Of the 291 patients, 11% (n = 32) interrupted treatment. Incidences of treatment interruption significantly occurred during intensive phase of treatment. Independent predictors of treatment interruption included alcohol consumption (HR = 9.2, 95% CI; 2.6–32.5, p < 0.001), being female (HR = 5.01, 95% CI; 1.68–15.0, p = 0.004), having primary or lower education level (HR = 3.09, 95% CI; 1.13–8.49, p < 0.029) and having a treatment supporter (HR = 0.33, 95% CI; 0.14–0.76, p = 0.009). Reasons for interrupting treatment were categorized as: alcoholism, feeling better after treatment initiation, associated TB stigma, long distance to health facility, lack of food, perception of not having TB and pill burden. CONCLUSION: TB treatment interruption was high and largely associated with patients’ socio-demographic and behavioral characteristics. These multidimensional factors suggest the need for interventions that not only target individual patients but also environment in which they live and receive healthcare services.
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spelling pubmed-86389882021-12-03 Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya Wekunda, Paul Waliaula Aduda, Dickens S. Omondi Guyah, Bernard PLoS One Research Article BACKGROUND: Despite robust Tuberculosis (TB) program with effective chemotherapy and high coverage, treatment interruption remains a serious problem. Interrupting TB treatment means that patients remain infectious for longer time and are at risk of developing drug resistance and death. This study was conducted to identify and describe predictors of TB treatment interruption. METHODS: A cohort of 291 notified TB patients from 20 selected health facilities in Vihiga County were enrolled in to the study and followed up until the end of treatment. Patient characteristics that potentially predict treatment interruption were recorded during treatment initiation using structured questionnaires. Patients who interrupted treatment were traced and reasons for stoppage of treatment recorded. Kaplan Meier method was used to estimate probabilities of treatment interruption by patient characteristics and determine time intervals. The Log rank test for the equality of survival distributions analyzed significance of survival differences among categorical variables. For multivariable analysis, Cox proportional hazard model, was fitted to identify predictors of TB treatment interruption through calculation of hazard ratios with 95% Confidence Intervals (CIs). For variable analysis, statistical significance was set at P ≤ 0.05. Reasons for treatment interruption were categorized according to most recurrent behavioral or experiential characteristics. RESULTS: Participants’ median age was 40 years (IQR = 32–53) and 72% were male. Of the 291 patients, 11% (n = 32) interrupted treatment. Incidences of treatment interruption significantly occurred during intensive phase of treatment. Independent predictors of treatment interruption included alcohol consumption (HR = 9.2, 95% CI; 2.6–32.5, p < 0.001), being female (HR = 5.01, 95% CI; 1.68–15.0, p = 0.004), having primary or lower education level (HR = 3.09, 95% CI; 1.13–8.49, p < 0.029) and having a treatment supporter (HR = 0.33, 95% CI; 0.14–0.76, p = 0.009). Reasons for interrupting treatment were categorized as: alcoholism, feeling better after treatment initiation, associated TB stigma, long distance to health facility, lack of food, perception of not having TB and pill burden. CONCLUSION: TB treatment interruption was high and largely associated with patients’ socio-demographic and behavioral characteristics. These multidimensional factors suggest the need for interventions that not only target individual patients but also environment in which they live and receive healthcare services. Public Library of Science 2021-12-02 /pmc/articles/PMC8638988/ /pubmed/34855844 http://dx.doi.org/10.1371/journal.pone.0260669 Text en © 2021 Wekunda et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wekunda, Paul Waliaula
Aduda, Dickens S. Omondi
Guyah, Bernard
Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya
title Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya
title_full Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya
title_fullStr Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya
title_full_unstemmed Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya
title_short Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya
title_sort determinants of tuberculosis treatment interruption among patients in vihiga county, kenya
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638988/
https://www.ncbi.nlm.nih.gov/pubmed/34855844
http://dx.doi.org/10.1371/journal.pone.0260669
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