Back

Molecular Detection of Multi-drug resistant tuberculosis in clinical isolates from two urban centres in Malawi

Sikwese, T. D.; Msosa, T.; Twabi, H.; Dzunda, S.; Chaima, D.; Banda, B.; Kanamazina, Y.; Nyenje, M.; Nliwasa, M.; Musopole, A.; Ndhlovu, V. S.

2024-09-22 infectious diseases
10.1101/2024.09.19.24313870 medRxiv
Show abstract

IntroductionSuboptimal chemotherapy allows Mycobacterium tuberculosis to develop drug resistance owing to development of resistant mutants in the mycobacterial population. Early diagnosis of TB and identification of drug-resistance is of particular importance in human immunodeficiency virus (HIV)-infected individuals, as delay of therapy and subsequent development of drug-resistant TB can be devastating due to compromised immune systems. MethodologyWe conducted a cross-sectional evaluation study using presumptive M. tuberculosis positive clinical isolates at two urban sites in Malawi (Blantyre and Lilongwe) to assess the presence of mutant genes on first and second line TB drugs using Line Probe Assay (LPA) and the gold standard drug susceptibility test (DST) ResultsFor the Lilongwe site, the incidence of MDR-TB by Line Probe Assay (LPA) was found to be 14.06% (95% CI: 8%-20%) whereas that for Rif mono-resistance was 6.25% (95% CI: 2%-10%). Contrastingly, MDR-TB by DST was 23.44% (95 CI:16% - 21%) while mono-resistance was 6.25% (95% CI:2% -10). There was a substantial agreement on the detection of MDR-TB (kappa statistic was 0.75 with 95% CI of 0.62-0.88). Blantyre site, at 9.5% confidence interval, the point estimate for MDR-TB was 0% while for INH mono-resistance TB was 3.3%. ConclusionsThere is high incidence of MDR-TB among patients whose samples are sent to the Lilongwe site than previously thought. A short turnaround time to diagnosis, and the ability to simultaneously detect rifampicin and isoniazid resistance, makes LPA a reliable tool for the early detection of multidrug-resistant tuberculosis.

Published in Archives of Clinical and Biomedical Research · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.