Chen YY, Guo Y, Xue XH, Pang F. Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases of the central nervous system after empirical treatment. World J Clin Cases 2022; 10(22): 7760-7771 [PMID: 36158512 DOI: 10.12998/wjcc.v10.i22.7760]
Corresponding Author of This Article
Ying-Ying Chen, PhD, Additional Professor, Department of Neurology, Liaocheng People's Hospital, No. 67 Dongchang West Road, Liaocheng 252000, Shandong Province, China. chen323232azqiqi@163.com
Research Domain of This Article
Clinical Neurology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Aug 6, 2022; 10(22): 7760-7771 Published online Aug 6, 2022. doi: 10.12998/wjcc.v10.i22.7760
Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases of the central nervous system after empirical treatment
Ying-Ying Chen, Yan Guo, Xin-Hong Xue, Feng Pang
Ying-Ying Chen, Yan Guo, Xin-Hong Xue, Department of Neurology, Liaocheng People's Hospital, Liaocheng 252000, Shandong Province, China
Feng Pang, Central Laboratory, Liaocheng People's Hospital, Liaocheng 252000, Shandong Province, China
Author contributions: Guo Y and Xue XH contributed equally to this work; Guo Y collected data, analysis and drafted the initial manuscript, and reviewed and revised the manuscript; Chen YY and Xue XH performed data analysis, drafted, and revised the manuscript; Xue XH and Pang F reviewed and revised the manuscript; and All authors read and approved the final manuscript.
Institutional review board statement: The protocol has been reviewed by the Human Research Ethics Committee of the Institutional Review Board of Liaocheng people's Hospital Medical College Hospital.
Informed consent statement: The patient has signed an informed consent form.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: The original contributions presented in the study are publicly available
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ying-Ying Chen, PhD, Additional Professor, Department of Neurology, Liaocheng People's Hospital, No. 67 Dongchang West Road, Liaocheng 252000, Shandong Province, China. chen323232azqiqi@163.com
Received: February 11, 2022 Peer-review started: February 11, 2022 First decision: April 13, 2022 Revised: April 27, 2022 Accepted: June 13, 2022 Article in press: June 13, 2022 Published online: August 6, 2022 Processing time: 160 Days and 22.5 Hours
ARTICLE HIGHLIGHTS
Research background
The value of metagenomic next-generation sequencing (mNGS) in central nervous system infectious diseases after empirical treatment has not been reported.
Research motivation
The authors evaluated the value of mNGS in cerebrospinal fluid in the diagnosis of empirically treated central nervous system (CNS) infectious diseases.
Research objectives
This study evaluated the value of mNGS in central nervous system infection and whether mNGS can be used to diagnose the pathogen of central nervous system infection
Research methods
A total of 262 empirically treated central nervous system-infected samples were analyzed by mNGS Confirmed pathogen. Using the final clinical diagnosis as the gold standard (the final cpatients were divided into CNS infection and non-CNS infection groups. Differences in continuous variables between groups were calculated using tests and χ2 tests.
Research results
mNGS is potentially advantageous in terms of speed and sensitivity. mNGS detected six rare pathogens.
Research conclusions
mNGS has a better diagnosis of CNS infection after empirical treatment, and the overall detection rate is better than that of conventional assays.
Research perspectives
mNGS has a better diagnosis of CNS infection after empirical treatment, and the overall detection rate is better than that of conventional assays. mNGS has diagnostic advantages.
