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Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya
BACKGROUND: Tuberculosis (TB) related mortality remains a serious impediment in ending TB epidemic. OBJECTIVE: To estimate survival probability and identify predictors, causes and conditions contributing to mortality among TB patients in Vihiga County. METHODS: A cohort of 291 patients from 20 purpo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Makerere Medical School
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398452/ https://www.ncbi.nlm.nih.gov/pubmed/37545936 http://dx.doi.org/10.4314/ahs.v23i1.24 |
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author | Wekunda, Paul Waliaula Aduda, Dickens S Omondi Guyah, Bernard Odongo, James |
author_facet | Wekunda, Paul Waliaula Aduda, Dickens S Omondi Guyah, Bernard Odongo, James |
author_sort | Wekunda, Paul Waliaula |
collection | PubMed |
description | BACKGROUND: Tuberculosis (TB) related mortality remains a serious impediment in ending TB epidemic. OBJECTIVE: To estimate survival probability and identify predictors, causes and conditions contributing to mortality among TB patients in Vihiga County. METHODS: A cohort of 291 patients from 20 purposively selected health facilities were prospectively considered. Data was obtained by validated questionnaires through face-to-face interviews. Survival probabilities were estimated using Kaplan-Meier method while Cox proportional hazard model identified predictors of TB mortality through calculation of hazard ratios at 95% confidence intervals. Mortality audit data was qualitatively categorized to elicit causes and conditions contributing to mortality. RESULTS: 209 (72%) were male, median age was 40 (IQR=32-53) years while TB/HIV coinfection rate was 35%. Overall, 45 (15%) patients died, majority (78% (log rank<0.001)) during intensive phase. The overall mortality rate was 32.2 (95% CI 23.5 - 43.1) deaths per 1000 person months and six months' survival probability was 0.838 (95% CI, 0.796-0.883). Mortality was higher (27%) among HIV positive than HIV negative (9%) TB patients. Independent predictors of mortality included; comorbidities (HR = 2.72, 95% CI,1.36–5.44, p< 0.005), severe illness (HR=5.06, 95% CI,1.59–16.1, p=0.006), HIV infection (HR=2.56, 95% CI,1.28–5.12, p=0.008) and smoking (HR=2.79, 95% CI,1.01–7.75, p=0.049). Independent predictors of mortality among HIV negative patients included; comorbidities (HR = 4.25, 95% CI; 1.15-15.7, p = 0.03) and being clinically diagnosed (HR = 4.8, 95% CI; 1.43-16, P = 0.01) while among HIV positive; they included smoking (HR = 4.05, 95% CI;1.03-16.0, P = 0.04), severe illness (HR = 5.84, 95% CI; 1.08-31.6, P = 0.04), severe malnutrition (HR = 4.56, 95% CI; 1.33-15.6, P = 0.01) and comorbidities (HR = 3.04, 95% CI; 1.03-8.97, p = 0.04). More than a half (52%) of mortality among HIV positive were ascribed to advanced HIV diseases while majority of (72%) of HIV negative patients died to TB related lung disease. Conditions contributing to mortality were largely patient and health system related. CONCLUSION: Risk of TB mortality is high and is attributable to comorbidities, severe illness, HIV and smoking. Causes and conditions contributing to TB mortality are multifaceted but modifiable. Improving TB/HIV care could reduce mortality in this setting. |
format | Online Article Text |
id | pubmed-10398452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Makerere Medical School |
record_format | MEDLINE/PubMed |
spelling | pubmed-103984522023-08-04 Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya Wekunda, Paul Waliaula Aduda, Dickens S Omondi Guyah, Bernard Odongo, James Afr Health Sci Articles BACKGROUND: Tuberculosis (TB) related mortality remains a serious impediment in ending TB epidemic. OBJECTIVE: To estimate survival probability and identify predictors, causes and conditions contributing to mortality among TB patients in Vihiga County. METHODS: A cohort of 291 patients from 20 purposively selected health facilities were prospectively considered. Data was obtained by validated questionnaires through face-to-face interviews. Survival probabilities were estimated using Kaplan-Meier method while Cox proportional hazard model identified predictors of TB mortality through calculation of hazard ratios at 95% confidence intervals. Mortality audit data was qualitatively categorized to elicit causes and conditions contributing to mortality. RESULTS: 209 (72%) were male, median age was 40 (IQR=32-53) years while TB/HIV coinfection rate was 35%. Overall, 45 (15%) patients died, majority (78% (log rank<0.001)) during intensive phase. The overall mortality rate was 32.2 (95% CI 23.5 - 43.1) deaths per 1000 person months and six months' survival probability was 0.838 (95% CI, 0.796-0.883). Mortality was higher (27%) among HIV positive than HIV negative (9%) TB patients. Independent predictors of mortality included; comorbidities (HR = 2.72, 95% CI,1.36–5.44, p< 0.005), severe illness (HR=5.06, 95% CI,1.59–16.1, p=0.006), HIV infection (HR=2.56, 95% CI,1.28–5.12, p=0.008) and smoking (HR=2.79, 95% CI,1.01–7.75, p=0.049). Independent predictors of mortality among HIV negative patients included; comorbidities (HR = 4.25, 95% CI; 1.15-15.7, p = 0.03) and being clinically diagnosed (HR = 4.8, 95% CI; 1.43-16, P = 0.01) while among HIV positive; they included smoking (HR = 4.05, 95% CI;1.03-16.0, P = 0.04), severe illness (HR = 5.84, 95% CI; 1.08-31.6, P = 0.04), severe malnutrition (HR = 4.56, 95% CI; 1.33-15.6, P = 0.01) and comorbidities (HR = 3.04, 95% CI; 1.03-8.97, p = 0.04). More than a half (52%) of mortality among HIV positive were ascribed to advanced HIV diseases while majority of (72%) of HIV negative patients died to TB related lung disease. Conditions contributing to mortality were largely patient and health system related. CONCLUSION: Risk of TB mortality is high and is attributable to comorbidities, severe illness, HIV and smoking. Causes and conditions contributing to TB mortality are multifaceted but modifiable. Improving TB/HIV care could reduce mortality in this setting. Makerere Medical School 2023-03 /pmc/articles/PMC10398452/ /pubmed/37545936 http://dx.doi.org/10.4314/ahs.v23i1.24 Text en © 2023 Wekunda PW et al. https://creativecommons.org/licenses/by/4.0/Licensee African Health Sciences. 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 work is properly cited. |
spellingShingle | Articles Wekunda, Paul Waliaula Aduda, Dickens S Omondi Guyah, Bernard Odongo, James Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya |
title | Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya |
title_full | Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya |
title_fullStr | Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya |
title_full_unstemmed | Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya |
title_short | Predictors of mortality and survival probability distribution among patients on tuberculosis treatment in Vihiga County, Kenya |
title_sort | predictors of mortality and survival probability distribution among patients on tuberculosis treatment in vihiga county, kenya |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398452/ https://www.ncbi.nlm.nih.gov/pubmed/37545936 http://dx.doi.org/10.4314/ahs.v23i1.24 |
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