Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.

Tuberculosis (TB) is the leading cause of mortality as a single infectious agent globally with increasing numbers of case notification in developing countries. This study seeks to investigate the clinical and socio-demographic factors of time to TB treatment interruption among Tuberculosis patients...

Full description

Bibliographic Details
Main Authors: Evelyn Kimani, Samuel Muhula, Titus Kiptai, James Orwa, Theresa Odero, Onesmus Gachuno
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0248820
_version_ 1818983397544951808
author Evelyn Kimani
Samuel Muhula
Titus Kiptai
James Orwa
Theresa Odero
Onesmus Gachuno
author_facet Evelyn Kimani
Samuel Muhula
Titus Kiptai
James Orwa
Theresa Odero
Onesmus Gachuno
author_sort Evelyn Kimani
collection DOAJ
description Tuberculosis (TB) is the leading cause of mortality as a single infectious agent globally with increasing numbers of case notification in developing countries. This study seeks to investigate the clinical and socio-demographic factors of time to TB treatment interruption among Tuberculosis patients in Kiambu County, 2016-2019. We retrospectively analyzed data for all treatment outcomes patients obtained from TB tracing form linked with the Tuberculosis Information Basic Unit (TIBU) of patients in Kiambu County health facilities using time to treatment interruption as the main outcome. Categorical variables were presented using frequency and percentages. Kaplan-Meir curve was used to analyze probabilities of time to treatment interruptions between intensive and continuation phases. Log-rank test statistics was used to compare the equality of the curves. Cox proportion model was used to determine determinants of treatment interruption. A total of 292 participants were included in this study. Males were 68%, with majority (35%) of the participants were aged 24-35 years; 5.8% were aged 0-14 years and 5.1% aged above 55 years. The overall treatment success rate was 66.8% (cured, 34.6%; completed 32.2%), 60.3% were on intensive phase of treatment. Lack of knowledge and relocation were the major reasons of treatment interruptions. Patients on intensive phase were 1.58 times likely to interrupt treatment compared to those on continuation phase (aHR: 1.581; 95%CI: 1.232-2.031). There is need to develop TB interventions that target men and middle aged population in order to reduce treatment interruption and increase the treatment success rates in the County and Country.
first_indexed 2024-12-20T18:02:28Z
format Article
id doaj.art-02de1a608df24e7380fc0a935a0d2e8b
institution Directory Open Access Journal
issn 1932-6203
language English
last_indexed 2024-12-20T18:02:28Z
publishDate 2021-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj.art-02de1a608df24e7380fc0a935a0d2e8b2022-12-21T19:30:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01164e024882010.1371/journal.pone.0248820Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.Evelyn KimaniSamuel MuhulaTitus KiptaiJames OrwaTheresa OderoOnesmus GachunoTuberculosis (TB) is the leading cause of mortality as a single infectious agent globally with increasing numbers of case notification in developing countries. This study seeks to investigate the clinical and socio-demographic factors of time to TB treatment interruption among Tuberculosis patients in Kiambu County, 2016-2019. We retrospectively analyzed data for all treatment outcomes patients obtained from TB tracing form linked with the Tuberculosis Information Basic Unit (TIBU) of patients in Kiambu County health facilities using time to treatment interruption as the main outcome. Categorical variables were presented using frequency and percentages. Kaplan-Meir curve was used to analyze probabilities of time to treatment interruptions between intensive and continuation phases. Log-rank test statistics was used to compare the equality of the curves. Cox proportion model was used to determine determinants of treatment interruption. A total of 292 participants were included in this study. Males were 68%, with majority (35%) of the participants were aged 24-35 years; 5.8% were aged 0-14 years and 5.1% aged above 55 years. The overall treatment success rate was 66.8% (cured, 34.6%; completed 32.2%), 60.3% were on intensive phase of treatment. Lack of knowledge and relocation were the major reasons of treatment interruptions. Patients on intensive phase were 1.58 times likely to interrupt treatment compared to those on continuation phase (aHR: 1.581; 95%CI: 1.232-2.031). There is need to develop TB interventions that target men and middle aged population in order to reduce treatment interruption and increase the treatment success rates in the County and Country.https://doi.org/10.1371/journal.pone.0248820
spellingShingle Evelyn Kimani
Samuel Muhula
Titus Kiptai
James Orwa
Theresa Odero
Onesmus Gachuno
Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.
PLoS ONE
title Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.
title_full Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.
title_fullStr Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.
title_full_unstemmed Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.
title_short Factors influencing TB treatment interruption and treatment outcomes among patients in Kiambu County, 2016-2019.
title_sort factors influencing tb treatment interruption and treatment outcomes among patients in kiambu county 2016 2019
url https://doi.org/10.1371/journal.pone.0248820
work_keys_str_mv AT evelynkimani factorsinfluencingtbtreatmentinterruptionandtreatmentoutcomesamongpatientsinkiambucounty20162019
AT samuelmuhula factorsinfluencingtbtreatmentinterruptionandtreatmentoutcomesamongpatientsinkiambucounty20162019
AT tituskiptai factorsinfluencingtbtreatmentinterruptionandtreatmentoutcomesamongpatientsinkiambucounty20162019
AT jamesorwa factorsinfluencingtbtreatmentinterruptionandtreatmentoutcomesamongpatientsinkiambucounty20162019
AT theresaodero factorsinfluencingtbtreatmentinterruptionandtreatmentoutcomesamongpatientsinkiambucounty20162019
AT onesmusgachuno factorsinfluencingtbtreatmentinterruptionandtreatmentoutcomesamongpatientsinkiambucounty20162019