Mortality During Treatment For Tuberculosis; A Review Of Surveillance Data In A Rural County In Kenya

PLOS ONE(2019)

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摘要
BackgroundGlobally in 2016, 1.7 million people died of Tuberculosis (TB). This study aimed to estimate all-cause mortality rate, identify features associated with mortality and describe trend in mortality rate from treatment initiation.MethodA 5-year (2012-2016) retrospective analysis of electronic TB surveillance data from Kilifi County, Kenya. The outcome was all-cause mortality within 180 days after starting TB treatment. The risk factors examined were demographic and clinical features at the time of starting anti-TB treatment. We performed survival analysis with time at risk defined from day of starting TB treatment to time of death, lost-to-follow-up or completing treatment. To account for 'lost-to-follow-up' we used competing risk analysis method to examine risk factors for all-cause mortality.Results10,717 patients receiving TB treatment, median (IQR) age 33 (24-45) years were analyzed; 3,163 (30%) were HIV infected. Overall, 585 (5.5%) patients died; mortality rate of 12.2 (95% CI 11.3-13.3) deaths per 100 person-years (PY). Mortality rate increased from 7.8 (95% CI 6.4-9.5) in 2012 to 17.7 (95% CI 14.9-21.1) in 2016 per 100PY (P-trend <0.0001). 449/585 (77%) of the deaths occurred within the first three months after starting TB treatment. The median time to death (IQR) declined from 87 (40-100) days in 2012 to 46 (18-83) days in 2016 (P-trend = 0. 04). Mortality rate per 100PY was 7.3 (95% CI 6.5-7.8) and 23.1 (95% CI 20.8-25.7) among HIV-uninfected and HIV-infected patients respectively. Age, being a female, extrapulmonary TB, being undernourished, HIV infected and year of diagnosis were significantly associated with mortality.ConclusionsWe found most deaths occurred within three months and an increasing mortality rate during the time under review among patients on TB treatment. Our results therefore warrant further investigation to explore host, disease or health system factors that may explain this trend.
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