Detection and species diversity of nontuberculous mycobacteria among patients investigated for tuberculosis at the National Tuberculosis Reference Laboratory, Maputo, Mozambique

Nontuberculous mycobacteria (NTM) can mimic tuberculosis, particularly in immunocompromised individuals, complicating diagnosis in high tuberculosis-burden settings. Laboratory detection of NTM may result in diagnostic uncertainty when species-level identification and clinical correlation are limited. This study assessed the detection rate and species diversity of NTM in clinical specimens referred to the National Tuberculosis Reference Laboratory (NTRL) of Mozambique. A retrospective cross-sectional analytical study was conducted using laboratory-based secondary data. A total of 334 records from 2015 to 2020 with interpretable molecular identification results were included after screening the DISA Laboratory Information System. Records with inconclusive or uninterpretable molecular results were excluded; individual demographic, geographic, or specimen variables that were unavailable were retained as unspecified/unknown. Data were analysed using IBM SPSS Statistics version 20. NTM were identified using the GenoType Mycobacterium CM and AS line probe assays and classified operationally according to their established clinical relevance in the literature. NTM were detected in 34.4% (115/334; 95% CI, 29.5–39.7) of specimens, while 65.6% (219/334) had no NTM detected. Clinically relevant NTM accounted for 24.3% (81/334), NTM of low/limited clinical relevance for 0.9% (3/334), and 9.3% (31/334) were reported as Mycobacterium spp. without species-level identification. Nine NTM species or species groups were identified, with M. intracellulare (11.4%) and M. fortuitum (5.7%) predominating, followed by M. scrofulaceum (2.7%) and M. abscessus complex (2.1%). Most specimens were pulmonary (311/334) and originated from males (193/334) aged 15–60 years (263/334), mainly from Maputo City and Province. NTM detection was significantly associated with TB classification at referral ( p < 0.001) and age group ( p = 0.005), but not with sex, or specimen type. A substantial proportion of specimens yielded diverse NTM species. However, limited clinical and longitudinal data precluded distinguishing colonization or contamination from NTM disease. Molecular species-level diagnostics could improve NTM-MTBC differentiation and support appropriate clinical management in tuberculosis-endemic settings.

Authors

Institutions

Publication Details

Journal
Discover Public Health
Published
2026-10-14
DOI
https://doi.org/10.1186/s12982-026-03125-0
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detection and species diversity of nontuberculous mycobacteria among patients investigated for tuberculosis at the National Tuberculosis Reference Laboratory, Maputo, Mozambique

Alberto Sineque, Alcina Zitha, Mateus F. Aini, Carla Maria D. G. Madeira
Discover Public Health
Mycobacterium research and diagnosis
article

Detection and species diversity of nontuberculous mycobacteria among patients investigated for tuberculosis at the National Tuberculosis Reference Laboratory, Maputo, Mozambique

Alberto Sineque, Alcina Zitha, Mateus F. Aini, Carla Maria D. G. Madeira
article en

Abstract

Nontuberculous mycobacteria (NTM) can mimic tuberculosis, particularly in immunocompromised individuals, complicating diagnosis in high tuberculosis-burden settings. Laboratory detection of NTM may result in diagnostic uncertainty when species-level identification and clinical correlation are limited. This study assessed the detection rate and species diversity of NTM in clinical specimens referred to the National Tuberculosis Reference Laboratory (NTRL) of Mozambique. A retrospective cross-sectional analytical study was conducted using laboratory-based secondary data. A total of 334 records from 2015 to 2020 with interpretable molecular identification results were included after screening the DISA Laboratory Information System. Records with inconclusive or uninterpretable molecular results were excluded; individual demographic, geographic, or specimen variables that were unavailable were retained as unspecified/unknown. Data were analysed using IBM SPSS Statistics version 20. NTM were identified using the GenoType Mycobacterium CM and AS line probe assays and classified operationally according to their established clinical relevance in the literature. NTM were detected in 34.4% (115/334; 95% CI, 29.5–39.7) of specimens, while 65.6% (219/334) had no NTM detected. Clinically relevant NTM accounted for 24.3% (81/334), NTM of low/limited clinical relevance for 0.9% (3/334), and 9.3% (31/334) were reported as Mycobacterium spp. without species-level identification. Nine NTM species or species groups were identified, with M. intracellulare (11.4%) and M. fortuitum (5.7%) predominating, followed by M. scrofulaceum (2.7%) and M. abscessus complex (2.1%). Most specimens were pulmonary (311/334) and originated from males (193/334) aged 15–60 years (263/334), mainly from Maputo City and Province. NTM detection was significantly associated with TB classification at referral ( p < 0.001) and age group ( p = 0.005), but not with sex, or specimen type. A substantial proportion of specimens yielded diverse NTM species. However, limited clinical and longitudinal data precluded distinguishing colonization or contamination from NTM disease. Molecular species-level diagnostics could improve NTM-MTBC differentiation and support appropriate clinical management in tuberculosis-endemic settings.

Discover Public HealthVol. 23(1)
Eduardo Mondlane University (MZ), University of Coimbra (PT)
Good health and well-being
Openalex Percentile: Top 12%
Mycobacterium research and diagnosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.