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Review and Updates on the Diagnosis of Tuberculosis

Diagnosis of tuberculosis, and especially the diagnosis of extrapulmonary tuberculosis, still faces challenges in clinical practice. There are several reasons for this. Methods based on the detection of Mycobacterium tuberculosis (Mtb) are insufficiently sensitive, methods based on the detection of...

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Detalles Bibliográficos
Autores principales: Huang, Yi, Ai, Lin, Wang, Xiaochen, Sun, Ziyong, Wang, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570811/
https://www.ncbi.nlm.nih.gov/pubmed/36233689
http://dx.doi.org/10.3390/jcm11195826
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author Huang, Yi
Ai, Lin
Wang, Xiaochen
Sun, Ziyong
Wang, Feng
author_facet Huang, Yi
Ai, Lin
Wang, Xiaochen
Sun, Ziyong
Wang, Feng
author_sort Huang, Yi
collection PubMed
description Diagnosis of tuberculosis, and especially the diagnosis of extrapulmonary tuberculosis, still faces challenges in clinical practice. There are several reasons for this. Methods based on the detection of Mycobacterium tuberculosis (Mtb) are insufficiently sensitive, methods based on the detection of Mtb-specific immune responses cannot always differentiate active disease from latent infection, and some of the serological markers of infection with Mtb are insufficiently specific to differentiate tuberculosis from other inflammatory diseases. New tools based on technologies such as flow cytometry, mass spectrometry, high-throughput sequencing, and artificial intelligence have the potential to solve this dilemma. The aim of this review was to provide an updated overview of current efforts to optimize classical diagnostic methods, as well as new molecular and other methodologies, for accurate diagnosis of patients with Mtb infection.
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spelling pubmed-95708112022-10-17 Review and Updates on the Diagnosis of Tuberculosis Huang, Yi Ai, Lin Wang, Xiaochen Sun, Ziyong Wang, Feng J Clin Med Review Diagnosis of tuberculosis, and especially the diagnosis of extrapulmonary tuberculosis, still faces challenges in clinical practice. There are several reasons for this. Methods based on the detection of Mycobacterium tuberculosis (Mtb) are insufficiently sensitive, methods based on the detection of Mtb-specific immune responses cannot always differentiate active disease from latent infection, and some of the serological markers of infection with Mtb are insufficiently specific to differentiate tuberculosis from other inflammatory diseases. New tools based on technologies such as flow cytometry, mass spectrometry, high-throughput sequencing, and artificial intelligence have the potential to solve this dilemma. The aim of this review was to provide an updated overview of current efforts to optimize classical diagnostic methods, as well as new molecular and other methodologies, for accurate diagnosis of patients with Mtb infection. MDPI 2022-09-30 /pmc/articles/PMC9570811/ /pubmed/36233689 http://dx.doi.org/10.3390/jcm11195826 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Huang, Yi
Ai, Lin
Wang, Xiaochen
Sun, Ziyong
Wang, Feng
Review and Updates on the Diagnosis of Tuberculosis
title Review and Updates on the Diagnosis of Tuberculosis
title_full Review and Updates on the Diagnosis of Tuberculosis
title_fullStr Review and Updates on the Diagnosis of Tuberculosis
title_full_unstemmed Review and Updates on the Diagnosis of Tuberculosis
title_short Review and Updates on the Diagnosis of Tuberculosis
title_sort review and updates on the diagnosis of tuberculosis
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570811/
https://www.ncbi.nlm.nih.gov/pubmed/36233689
http://dx.doi.org/10.3390/jcm11195826
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