Cargando…

Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing

BACKGROUND: Due to limitations of traditional microbiological methods and the presence of the oropharyngeal normal flora, there are still many pathogens that cause lower respiratory tract infections (LRTIs) cannot be detected. Metagenomic next-generation sequencing (mNGS) has the potential capacity...

Descripción completa

Detalles Bibliográficos
Autores principales: Dong, Yulan, Chen, Qianqian, Tian, Bin, Li, Jing, Li, Jin, Hu, Zhidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896973/
https://www.ncbi.nlm.nih.gov/pubmed/36743335
http://dx.doi.org/10.2147/IDR.S387134
_version_ 1784882155516592128
author Dong, Yulan
Chen, Qianqian
Tian, Bin
Li, Jing
Li, Jin
Hu, Zhidong
author_facet Dong, Yulan
Chen, Qianqian
Tian, Bin
Li, Jing
Li, Jin
Hu, Zhidong
author_sort Dong, Yulan
collection PubMed
description BACKGROUND: Due to limitations of traditional microbiological methods and the presence of the oropharyngeal normal flora, there are still many pathogens that cause lower respiratory tract infections (LRTIs) cannot be detected. Metagenomic next-generation sequencing (mNGS) has the potential capacity to solve this problem. METHODS: This retrospective study successively reviewed 77 patients with LRTI and 29 patients without LRTI admitted to Tianjin Medical University General Hospital, China from August 2020 to June 2021. Pathogens in bronchoalveolar lavage fluid (BALF) specimens were detected adopting mNGS and traditional microbiological assays. The diagnostic performance of pathogens was compared between mNGS and BALF culture. The value of mNGS for aetiological and clinical impact investigation in LRTI was also evaluated. RESULTS: Among 77 patients with LRTI, 22.1%, 40.3%, and 65.0% of cases were detected as definite or probable pathogens by culture, all conventional microbiological tests, and mNGS, respectively. Using the final diagnosis as a gold standard, mNGS exhibited a sensitivity of 76.6% (95% confidence interval [CI], 65.6–85.5%), which was considerably superior to that of BALF culture (76.6% vs 18.2%; P < 0.01); specificity of 79.3% (95% CI, 60.3–92.0%), which was similar (79.3% vs 89.7%; P = 0.38); positive-predictive value of 90.8% (95% CI, 81.0–96.5%), and negative-predictive value of 56.1% (95% CI, 39.7–71.5%). According to our data, mNGS identified potential microorganisms in 66.7% (42/63) of culture-negative samples. Among 59 patients with pathogens identified by mNGS, conventional microbiological methods confirmed pathogenic infections in less than half (28/59) cases. Within the 77 patients, 34 (44.2%) patients received pathogen-directed therapy, 7 (9.1%) patients underwent antibiotic adjustment, and 3 (3.9%) patients stopped using antibiotics due to mNGS results. CONCLUSION: mNGS exhibits high accuracy in diagnosing LRTI, and combine with traditional microbiological tests, causative pathogens can be detected in approximately 70.0% of cases, thus yields a positive effect on antibiotic application.
format Online
Article
Text
id pubmed-9896973
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-98969732023-02-04 Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing Dong, Yulan Chen, Qianqian Tian, Bin Li, Jing Li, Jin Hu, Zhidong Infect Drug Resist Original Research BACKGROUND: Due to limitations of traditional microbiological methods and the presence of the oropharyngeal normal flora, there are still many pathogens that cause lower respiratory tract infections (LRTIs) cannot be detected. Metagenomic next-generation sequencing (mNGS) has the potential capacity to solve this problem. METHODS: This retrospective study successively reviewed 77 patients with LRTI and 29 patients without LRTI admitted to Tianjin Medical University General Hospital, China from August 2020 to June 2021. Pathogens in bronchoalveolar lavage fluid (BALF) specimens were detected adopting mNGS and traditional microbiological assays. The diagnostic performance of pathogens was compared between mNGS and BALF culture. The value of mNGS for aetiological and clinical impact investigation in LRTI was also evaluated. RESULTS: Among 77 patients with LRTI, 22.1%, 40.3%, and 65.0% of cases were detected as definite or probable pathogens by culture, all conventional microbiological tests, and mNGS, respectively. Using the final diagnosis as a gold standard, mNGS exhibited a sensitivity of 76.6% (95% confidence interval [CI], 65.6–85.5%), which was considerably superior to that of BALF culture (76.6% vs 18.2%; P < 0.01); specificity of 79.3% (95% CI, 60.3–92.0%), which was similar (79.3% vs 89.7%; P = 0.38); positive-predictive value of 90.8% (95% CI, 81.0–96.5%), and negative-predictive value of 56.1% (95% CI, 39.7–71.5%). According to our data, mNGS identified potential microorganisms in 66.7% (42/63) of culture-negative samples. Among 59 patients with pathogens identified by mNGS, conventional microbiological methods confirmed pathogenic infections in less than half (28/59) cases. Within the 77 patients, 34 (44.2%) patients received pathogen-directed therapy, 7 (9.1%) patients underwent antibiotic adjustment, and 3 (3.9%) patients stopped using antibiotics due to mNGS results. CONCLUSION: mNGS exhibits high accuracy in diagnosing LRTI, and combine with traditional microbiological tests, causative pathogens can be detected in approximately 70.0% of cases, thus yields a positive effect on antibiotic application. Dove 2023-01-30 /pmc/articles/PMC9896973/ /pubmed/36743335 http://dx.doi.org/10.2147/IDR.S387134 Text en © 2023 Dong et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Dong, Yulan
Chen, Qianqian
Tian, Bin
Li, Jing
Li, Jin
Hu, Zhidong
Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing
title Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing
title_full Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing
title_fullStr Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing
title_full_unstemmed Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing
title_short Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing
title_sort advancing microbe detection for lower respiratory tract infection diagnosis and management with metagenomic next-generation sequencing
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896973/
https://www.ncbi.nlm.nih.gov/pubmed/36743335
http://dx.doi.org/10.2147/IDR.S387134
work_keys_str_mv AT dongyulan advancingmicrobedetectionforlowerrespiratorytractinfectiondiagnosisandmanagementwithmetagenomicnextgenerationsequencing
AT chenqianqian advancingmicrobedetectionforlowerrespiratorytractinfectiondiagnosisandmanagementwithmetagenomicnextgenerationsequencing
AT tianbin advancingmicrobedetectionforlowerrespiratorytractinfectiondiagnosisandmanagementwithmetagenomicnextgenerationsequencing
AT lijing advancingmicrobedetectionforlowerrespiratorytractinfectiondiagnosisandmanagementwithmetagenomicnextgenerationsequencing
AT lijin advancingmicrobedetectionforlowerrespiratorytractinfectiondiagnosisandmanagementwithmetagenomicnextgenerationsequencing
AT huzhidong advancingmicrobedetectionforlowerrespiratorytractinfectiondiagnosisandmanagementwithmetagenomicnextgenerationsequencing