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Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis

OBJECTIVE: It is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generati...

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Autores principales: Qu, Chunrun, Chen, Yu, Ouyang, Yuzhen, Huang, Weicheng, Liu, Fangkun, Yan, Luzhe, Lu, Ruoyu, Zeng, Yu, Liu, Zhixiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530978/
https://www.ncbi.nlm.nih.gov/pubmed/36203993
http://dx.doi.org/10.3389/fneur.2022.989280
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author Qu, Chunrun
Chen, Yu
Ouyang, Yuzhen
Huang, Weicheng
Liu, Fangkun
Yan, Luzhe
Lu, Ruoyu
Zeng, Yu
Liu, Zhixiong
author_facet Qu, Chunrun
Chen, Yu
Ouyang, Yuzhen
Huang, Weicheng
Liu, Fangkun
Yan, Luzhe
Lu, Ruoyu
Zeng, Yu
Liu, Zhixiong
author_sort Qu, Chunrun
collection PubMed
description OBJECTIVE: It is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generation sequencing (mNGS) has been increasingly adopted to improve the diagnostic yield. The present study sought to evaluate the value of mNGS in CNS infection diagnosis. METHODS: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2022 guidelines, we searched relevant articles published in seven databases, including PubMed, Web of Science, and Cochrane Library, published from January 2014 to January 2022. High-quality articles related to mNGS applications in the CNS infection diagnosis were included. The comparison between mNGS and the gold standard of CNS infection, such as culture, PCR or serology, and microscopy, was conducted to obtain true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values, which were extracted for sensitivity and specificity calculation. RESULTS: A total of 272 related studies were retrieved and strictly selected according to the inclusion and exclusion criteria. Finally, 12 studies were included for meta-analysis and the pooled sensitivity was 77% (95% CI: 70–82%, I(2) = 39.69%) and specificity was 96% (95% CI: 93–98%, I(2) = 72.07%). Although no significant heterogeneity in sensitivity was observed, a sub-group analysis was conducted based on the pathogen, region, age, and sample pretreatment method to ascertain potential confounders. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for CNS infection was 0.91 (95% CI: 0.88–0.93). Besides, Deek's Funnel Plot Asymmetry Test indicated no publication bias in the included studies (Figure 3, p > 0.05). CONCLUSION: Overall, mNGS exhibits good sensitivity and specificity for diagnosing CNS infection and diagnostic performance during clinical application by assisting in identifying the pathogen. However, the efficacy remains inconsistent, warranting subsequent studies for further performance improvement during its clinical application. STUDY REGISTRATION NUMBER: INPLASY202120002
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spelling pubmed-95309782022-10-05 Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis Qu, Chunrun Chen, Yu Ouyang, Yuzhen Huang, Weicheng Liu, Fangkun Yan, Luzhe Lu, Ruoyu Zeng, Yu Liu, Zhixiong Front Neurol Neurology OBJECTIVE: It is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generation sequencing (mNGS) has been increasingly adopted to improve the diagnostic yield. The present study sought to evaluate the value of mNGS in CNS infection diagnosis. METHODS: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2022 guidelines, we searched relevant articles published in seven databases, including PubMed, Web of Science, and Cochrane Library, published from January 2014 to January 2022. High-quality articles related to mNGS applications in the CNS infection diagnosis were included. The comparison between mNGS and the gold standard of CNS infection, such as culture, PCR or serology, and microscopy, was conducted to obtain true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values, which were extracted for sensitivity and specificity calculation. RESULTS: A total of 272 related studies were retrieved and strictly selected according to the inclusion and exclusion criteria. Finally, 12 studies were included for meta-analysis and the pooled sensitivity was 77% (95% CI: 70–82%, I(2) = 39.69%) and specificity was 96% (95% CI: 93–98%, I(2) = 72.07%). Although no significant heterogeneity in sensitivity was observed, a sub-group analysis was conducted based on the pathogen, region, age, and sample pretreatment method to ascertain potential confounders. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for CNS infection was 0.91 (95% CI: 0.88–0.93). Besides, Deek's Funnel Plot Asymmetry Test indicated no publication bias in the included studies (Figure 3, p > 0.05). CONCLUSION: Overall, mNGS exhibits good sensitivity and specificity for diagnosing CNS infection and diagnostic performance during clinical application by assisting in identifying the pathogen. However, the efficacy remains inconsistent, warranting subsequent studies for further performance improvement during its clinical application. STUDY REGISTRATION NUMBER: INPLASY202120002 Frontiers Media S.A. 2022-09-20 /pmc/articles/PMC9530978/ /pubmed/36203993 http://dx.doi.org/10.3389/fneur.2022.989280 Text en Copyright © 2022 Qu, Chen, Ouyang, Huang, Liu, Yan, Lu, Zeng and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Qu, Chunrun
Chen, Yu
Ouyang, Yuzhen
Huang, Weicheng
Liu, Fangkun
Yan, Luzhe
Lu, Ruoyu
Zeng, Yu
Liu, Zhixiong
Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis
title Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis
title_full Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis
title_fullStr Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis
title_full_unstemmed Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis
title_short Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis
title_sort metagenomics next-generation sequencing for the diagnosis of central nervous system infection: a systematic review and meta-analysis
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530978/
https://www.ncbi.nlm.nih.gov/pubmed/36203993
http://dx.doi.org/10.3389/fneur.2022.989280
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