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Updated: Jun 12, 2025

The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
Published on: August 11, 2008
Tuberculosis Diagnosis: Current, Ongoing, and Future Approaches
Guilherme Bartolomeu-Gonçalves1, Joyce Marinho de Souza2,3, Bruna Terci Fernandes2,4
1Programa de Pós-Graduação em Fisiopatologia Clínica e Laboratorial, Universidade Estadual de Londrina, Londrina CEP 86038-350, Paraná, Brazil.
Abstract:
Tuberculosis (TB) remains an impactful infectious disease, leading to millions of deaths every year. Mycobacterium tuberculosis causes the formation of granulomas, which will determine, through the host-pathogen relationship, if the infection will remain latent or evolve into active disease. Early TB diagnosis is life-saving, especially among immunocompromised individuals, and leads to proper treatment, preventing transmission. This review addresses different approaches to diagnosing TB, from traditional methods such as sputum smear microscopy to more advanced molecular techniques. Integrating these techniques, such as polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP), has significantly improved the sensitivity and specificity of M. tuberculosis identification. Additionally, exploring novel biomarkers and applying artificial intelligence in radiological imaging contribute to more accurate and rapid diagnosis. Furthermore, we discuss the challenges of existing diagnostic methods, including limitations in resource-limited settings and the emergence of drug-resistant strains. While the primary focus of this review is on TB diagnosis, we also briefly explore the challenges and strategies for diagnosing non-tuberculous mycobacteria (NTM). In conclusion, this review provides an overview of the current landscape of TB diagnostics, emphasizing the need for ongoing research and innovation. As the field evolves, it is crucial to ensure that these advancements are accessible and applicable in diverse healthcare settings to effectively combat tuberculosis worldwide.
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