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Estimation of country-specific tuberculosis resistance antibiograms using pathogen genomics and machine learning.

Avika DixitLuca FreschiRoger VargasMatthias I GröschelMaria NakhoulSabira TahseenS M Masud AlamS M Mostofa KamalAlena SkrahinaRamon P BasilioDodge R LimNazir Ahmed IsmailMaha R Farhat
Published in: BMJ global health (2024)
can be reliably estimated using public WGS and phenotypic resistance prediction for key antibiotics, but public WGS data demonstrates oversampling of isolates with higher resistance levels than MDR. Nevertheless, our results raise concerns about the empiric use of short-course fluoroquinolone regimens for drug-susceptible TB in South Asia and indicate underutilisation of ethionamide in MDR treatment.
Keyphrases
  • machine learning
  • mycobacterium tuberculosis
  • healthcare
  • multidrug resistant
  • mental health
  • adverse drug
  • big data
  • electronic health record
  • single cell
  • hiv aids
  • human immunodeficiency virus