ReviewDiagnostics (Basel, Switzerland)2026
Tuberculosis in Pregnancy: An Updated Narrative Review.
Review in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
8 authors.
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Abstract
Tuberculosis remains one of the leading infectious causes of morbidity and mortality worldwide, disproportionately affecting women of reproductive age, particularly in low- and middle-income countries. Tuberculosis during pregnancy represents a major clinical challenge, as physiological and immunological changes associated with pregnancy may obscure symptoms, delay diagnosis, and contribute to adverse maternal and perinatal outcomes. This narrative review provides an updated and clinically oriented overview of tuberculosis during pregnancy, with particular emphasis on diagnostic challenges, imaging strategies, microbiological testing, maternal-fetal complications, and therapeutic management. Key topics include symptom-based screening, tuberculin skin test and interferon gamma release assays, as well as molecular diagnostic methods such as GeneXpert Mycobacterium tuberculosis/Rifampicin (MTB/RIF) and Xpert MTB/RIF Ultra, chest radiography, computed tomography, and emerging biomarkers. We also discuss the impact of tuberculosis on pregnancy outcomes, including prematurity, low birth weight, maternal morbidity, and neonatal complications, as well as the particular challenges posed by human immunodeficiency virus HIV coinfection and multidrug-resistant tuberculosis. Current treatment strategies, preventive approaches, postpartum care, neonatal management, and Bacille Calmette-Guérin vaccination are reviewed in light of contemporary evidence and international recommendations. Finally, we highlight practical diagnostic algorithms, current evidence gaps, and priorities for future research aimed at improving maternal and neonatal outcomes in both high- and low-resource settings.
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