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Clinical metagenomic sequencing for diagnosis of pulmonary tuberculosis.
- Source :
-
The Journal of infection [J Infect] 2020 Oct; Vol. 81 (4), pp. 567-574. Date of Electronic Publication: 2020 Aug 05. - Publication Year :
- 2020
-
Abstract
- Objectives: The aim of this study is to investigate the clinical usefulness of metagenomic Next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) samples to discriminate pulmonary tuberculosis (PTB) from Non-TB community-acquired pneumonia (CAP) in PTB suspects.<br />Methods: We investigate the performance of mNGS on BALF samples from 110 PTB suspects, in comparison with conventional microbiological testing (solid media culture, acid-fast bacilli staining (AFS), Xpert) of BALF or sputum samples and final clinical diagnosis.<br />Results: We finally clinically diagnosed 48 cases of pulmonary tuberculosis patients and 62 cases of non-tuberculosis patients. Comparing to the final clinical diagnosis, mNGS produced a sensitivity of 47.92%, which was similar to that of Xpert (45.83%) and culture (46.81%), but much higher than that of AFS (29.17%) for TB diagnosis in BALF samples. Apart from detecting Mycobacterium tuberculosis, mNGS also identified mixed infections in PTB patients, including 3 fungal cases and 1 bacteria case. Meanwhile, mNGS efficiently identified 14 of 22 (63.63%) cases of non-tuberculous mycobacteria (NTM), 7 cases of fungi, 1 case of viral infection, and other common bacterial pathogens in Non-PTB group. Finally, mNGS identified 67.23% infection cases within 3 days, while the conventional methods identified 49.58% infection cases for over 90 days.<br />Conclusion: Our data show that mNGS of BALF represents a potentially effective tool for the rapid diagnosis of PTB suspects.<br />Competing Interests: Declaration of Competing Interest We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.<br /> (Copyright © 2020 The British Infection Association. Published by Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1532-2742
- Volume :
- 81
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- The Journal of infection
- Publication Type :
- Academic Journal
- Accession number :
- 32768450
- Full Text :
- https://doi.org/10.1016/j.jinf.2020.08.004