Development of a diagnostic algorithm for identification of non-tuberculous mycobacteria species and drug sensitivity
Diagnosis and management of non-tuberculous mycobacterial (NTM) infections remain formidable due to their nonspecific clinical presentation, environmental persistence and adaptability, and intrinsic drug resistance to existing treatments. The diverse species exhibiting variable drug susceptibility and lacking standardised treatment regimens make the precise identification of NTM species more critical. Therefore, precise and prompt species-level identification is paramount to confirm diagnosis, suggest appropriate therapeutics to improve patient outcomes. NTM infections often mimic tuberculosis, leading to frequent misdiagnosis, inappropriate therapy, and increased morbidity. Compounding this, advanced molecular tools required for precise identification are limited inresource-constrained setups. Moreover, no robust diagnostic algorithm exists for accurately identifying NTM at the species level.
