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Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection

INTRODUCTION: We aimed to explore the real-world clinical application value and challenges of metagenomic next-generation sequencing (mNGS) for pulmonary infection diagnosis. METHODS: We retrospectively reviewed the results of mNGS and conventional tests from 140 hospitalized patients with suspected...

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Autores principales: Xie, Guijuan, Zhao, Bo, Wang, Xun, Bao, Liang, Xu, Yiming, Ren, Xian, Ji, Jiali, He, Ting, Zhao, Hongqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322361/
https://www.ncbi.nlm.nih.gov/pubmed/34117999
http://dx.doi.org/10.1007/s40121-021-00476-w
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author Xie, Guijuan
Zhao, Bo
Wang, Xun
Bao, Liang
Xu, Yiming
Ren, Xian
Ji, Jiali
He, Ting
Zhao, Hongqing
author_facet Xie, Guijuan
Zhao, Bo
Wang, Xun
Bao, Liang
Xu, Yiming
Ren, Xian
Ji, Jiali
He, Ting
Zhao, Hongqing
author_sort Xie, Guijuan
collection PubMed
description INTRODUCTION: We aimed to explore the real-world clinical application value and challenges of metagenomic next-generation sequencing (mNGS) for pulmonary infection diagnosis. METHODS: We retrospectively reviewed the results of mNGS and conventional tests from 140 hospitalized patients with suspected pulmonary infections from January 2019 to December 2020. The sample types included bronchoalveolar lavage fluid, lung tissue by transbronchial lung biopsy, pleural effusion, blood, and bronchial sputum. Apart from the mNGS reports that our patients received, an extra comprehensive and thorough literature search was conducted. RESULTS: Significant differences were noticed in the positive detection rates of pathogens between mNGS and conventional diagnostic testing (115/140, 82.14% vs 50/140, 35.71%, P < 0.05). The percentage of mNGS-positive patients was significantly higher than that of conventional testing-positive patients with regard to bacterial detection (P < 0.01), but no significant differences were found with regard to fungal detection (P = 0.67). Significant statistical differences were found between mixed infection cases (15, 22.70%) and single infection cases (4, 7.84%) in terms of diabetes (P = 0.03). The most frequent pattern of mixed infection was bacteria and fungi mixed infection (40, 40/89 = 44.94%), followed by bacteria mixed infection (29, 29/89 = 32.58%). The sensitivity of mNGS in pulmonary infection diagnosis was much higher than that of conventional test (89.17% vs 50.00%; P < 0.01), but the specificity was the opposite (75.00% vs 81.82%; P > 0.05). CONCLUSION: mNGS is a valuable tool for the detection of pulmonary infections, especially mixed pulmonary infections. The most common combinations we found were bacterial–fungal coinfection and bacterial–bacterial coinfection. Still, there are many challenges in the clinical application of mNGS in the diagnosis of pulmonary infections. There is still a lot of work to be done in interpreting the mNGS reports, because both clinical judgment and literature analysis strategy need to be refined.
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spelling pubmed-83223612021-08-19 Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection Xie, Guijuan Zhao, Bo Wang, Xun Bao, Liang Xu, Yiming Ren, Xian Ji, Jiali He, Ting Zhao, Hongqing Infect Dis Ther Original Research INTRODUCTION: We aimed to explore the real-world clinical application value and challenges of metagenomic next-generation sequencing (mNGS) for pulmonary infection diagnosis. METHODS: We retrospectively reviewed the results of mNGS and conventional tests from 140 hospitalized patients with suspected pulmonary infections from January 2019 to December 2020. The sample types included bronchoalveolar lavage fluid, lung tissue by transbronchial lung biopsy, pleural effusion, blood, and bronchial sputum. Apart from the mNGS reports that our patients received, an extra comprehensive and thorough literature search was conducted. RESULTS: Significant differences were noticed in the positive detection rates of pathogens between mNGS and conventional diagnostic testing (115/140, 82.14% vs 50/140, 35.71%, P < 0.05). The percentage of mNGS-positive patients was significantly higher than that of conventional testing-positive patients with regard to bacterial detection (P < 0.01), but no significant differences were found with regard to fungal detection (P = 0.67). Significant statistical differences were found between mixed infection cases (15, 22.70%) and single infection cases (4, 7.84%) in terms of diabetes (P = 0.03). The most frequent pattern of mixed infection was bacteria and fungi mixed infection (40, 40/89 = 44.94%), followed by bacteria mixed infection (29, 29/89 = 32.58%). The sensitivity of mNGS in pulmonary infection diagnosis was much higher than that of conventional test (89.17% vs 50.00%; P < 0.01), but the specificity was the opposite (75.00% vs 81.82%; P > 0.05). CONCLUSION: mNGS is a valuable tool for the detection of pulmonary infections, especially mixed pulmonary infections. The most common combinations we found were bacterial–fungal coinfection and bacterial–bacterial coinfection. Still, there are many challenges in the clinical application of mNGS in the diagnosis of pulmonary infections. There is still a lot of work to be done in interpreting the mNGS reports, because both clinical judgment and literature analysis strategy need to be refined. Springer Healthcare 2021-06-12 2021-09 /pmc/articles/PMC8322361/ /pubmed/34117999 http://dx.doi.org/10.1007/s40121-021-00476-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Xie, Guijuan
Zhao, Bo
Wang, Xun
Bao, Liang
Xu, Yiming
Ren, Xian
Ji, Jiali
He, Ting
Zhao, Hongqing
Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection
title Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection
title_full Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection
title_fullStr Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection
title_full_unstemmed Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection
title_short Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection
title_sort exploring the clinical utility of metagenomic next-generation sequencing in the diagnosis of pulmonary infection
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322361/
https://www.ncbi.nlm.nih.gov/pubmed/34117999
http://dx.doi.org/10.1007/s40121-021-00476-w
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