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Afr. J. Clin. Exp. Microbiol ; 20(4): 324-331, 2019. ilus
Artigo em Inglês | AIM | ID: biblio-1256090

RESUMO

Background: Tuberculosis (TB) remains one of the leading public health challenges in Nigeria and the burden is still high. There is hence a need for continuous characterization of mycobacteria to obtain current data that will aid the ongoing TB prevention and control programme. The aim of this study was to phenotypically characterize mycobacteria isolates recovered from clinical specimens of patients with tuberculosis in Kaduna State, Nigeria. Methods: Two thousand, two hundred and twelve (2212) sputum samples were collected from patients clinically suspected to have TB in three different zones of Kaduna State, Nigeria, between May 2017 and October, 2018. Samples were processed by decontaminating with NaOH-Citrate N-acetyl-L-Cystein method for Ziehl Neelsen (ZN) AFB microscopy and culture on Lowenstein Jensen (LJ) slants which were incubated at 37ᵒC for 8 weeks. Positive LJ cultures were further analyzed with a rapid TB antigen assay (SD-Bioline) to differentiate Mycobacterium tuberculosis complex (MTBC) from Non Tuberculous Mycobacteria (NTM). Results: Out of the 2212 patients with suspected TB, 300 (13.6%) were positive for AFB by microscopy with Zone A (Kaduna North) having the highest AFB positive cases of 169 (15.2%). Of the 300 AFB positive samples, 272 (91.0%) were culture positive on LJ medium, 18 (6.0%) were culture negative and 10 (3.0%) were culture contaminated. Result of the distribution of mycobacteria among infected patients within the study area revealed that 219 (80.5%) were infected with MTBC, 42 (15.4%) with NTM and 11 (4.0%) with both MTBC and NTM. Conclusion: A relatively high number of TB in the study area was caused by NTM. There is need for advanced diagnostic tools that can differentiate MTBC and NTM strains among TB patients in all TB Reference Laboratories in Nigeria


Assuntos
Infecções por Mycobacterium , Nigéria , Pacientes , Tuberculose , Tuberculose/análise , Tuberculose/estatística & dados numéricos
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