Abstract

Background: Tuberculosis (TB) is an infectious disease and it is a public health concern due to the endemic nature of the disease. Nigeria’s health systems still rely heavily on out-dated tuberculosis diagnostic tests; including sputum smear microscopy and chest radiography. This necessitated the urgent need to explore a more reliable, effective method that can rapidly enhance simultaneous detection of Mycobacterium tuberculosis (MTB) and rifampicin (RIF) resistance. Aims: We evaluated the prevalence of MTB and rifampicin resistance and the influence of socio-demographic factors. Methods: A longitudinal, descriptive study that employs the Xpert MTB/RIF automated molecular method for rapid detection of rifampicin resistance. Secondary data were collected from the medical record from March 2017 to December 2018. Primary data were collected by direct clinical observations and analysis with gene expert machine from January 2019-March 2019. Results: Study populations were 1893 subjects pooled as secondary data at the Gene Expert laboratory, with a mean age of 44.92 years and were categorized based on sex, 1125 (59.4%) males and 768 (40.6%) females respectively. The MTB detected were 117 (15.7%) for males while 76 (9.9%) were positive for females. 948 (84.3%) were negative for males and 692 (90.1%) negative for females. Also, the categories for age were grouped into three but the older age groups (29 - 54) and (55 - 80) were more vulnerable to MTB having a p = 0.506 which is statistically non-significant; only 14 (5.5%) have RIF while 239 (94.5%) do not have RIF resistance strains. Logistic regression analysis of MTB detected showed a significant association (p 0.05) for age. The prevalence rate for RIF Resistance is 5.53%, there is a statistical difference p = 0.001 between RIF Resistance and MTB in Ilorin. Conclusion: The utilization of validated molecular technique for MTB strain identification has shown stronger epidemiological impetus for an improved care management outcome specifically in resources limited areas.

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