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宏基因组下一代测序在经验性治疗后中枢神经系统感染性疾病诊断中的应用。

Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases of the central nervous system after empirical treatment.

作者信息

Chen Ying-Ying, Guo Yan, Xue Xin-Hong, Pang Feng

机构信息

Department of Neurology, Liaocheng People's Hospital, Liaocheng 252000, Shandong Province, China.

Central Laboratory, Liaocheng People's Hospital, Liaocheng 252000, Shandong Province, China.

出版信息

World J Clin Cases. 2022 Aug 6;10(22):7760-7771. doi: 10.12998/wjcc.v10.i22.7760.

Abstract

BACKGROUND

The diagnostic value of metagenomic next-generation sequencing (mNGS) in central nervous system (CNS) infectious diseases after empirical treatment has not been reported.

AIM

To investigate the diagnostic value of mNGS of cerebrospinal fluid (CSF) in the empirically treated CNS infectious diseases.

METHODS

A total of 262 CSF samples from patients with suspected CNS infections were collected between August 2020 and December 2021. Both mNGS and conventional methods were used for testing. The conventional methods included microbial culture, smear, polymerase chain reaction,

RESULTS

Among 262 suspected cases, 183 cases (69.84%) were diagnosed as CNS infection, including 86 cases of virus infection (47.00%), 70 cases of bacterial infection (38.25%) and 27 cases of fungal infection (14.76%). The sensitivity and specificity of mNGS were 65.6% (95%CI: 58.2%-72.3%) and 89.6% (95%CI: 79.1%-95.3%), respectively. The PPV of mNGS was 94.5% (95%CI: 88.6%-97.6%), and the NPV was 48.8% (95%CI: 39.7%-57.9%). The pathogen detective sensitivity and accuracy of mNGS were higher than those of conventional methods (Sensitivity: 65.6% 37.2%; < 0.001; Accuracy: 72.0% 50%, < 0.001). The results showed that compared with conventional methods, mNGS technology was a more sensitive method for the diagnosis of CNS infection after empirical treatment.

CONCLUSION

mNGS can be a better method applied in the diagnosis of CNS infection after empirical treatment.

摘要

背景

宏基因组下一代测序(mNGS)在经验性治疗后中枢神经系统(CNS)感染性疾病中的诊断价值尚未见报道。

目的

探讨脑脊液(CSF)的mNGS在经验性治疗的中枢神经系统感染性疾病中的诊断价值。

方法

2020年8月至2021年12月期间共收集了262例疑似中枢神经系统感染患者的脑脊液样本。同时采用mNGS和传统方法进行检测。传统方法包括微生物培养、涂片、聚合酶链反应。

结果

262例疑似病例中,183例(69.84%)被诊断为中枢神经系统感染,其中病毒感染86例(47.00%),细菌感染70例(38.25%),真菌感染27例(14.76%)。mNGS的敏感性和特异性分别为65.6%(95%CI:58.2%-72.3%)和89.6%(95%CI:79.1%-95.3%)。mNGS的阳性预测值为94.5%(95%CI:88.6%-97.6%),阴性预测值为48.8%(95%CI:39.7%-57.9%)。mNGS的病原体检测敏感性和准确性高于传统方法(敏感性:65.6%对37.2%,P<0.001;准确性:72.0%对50%,P<0.001)。结果表明,与传统方法相比,mNGS技术是经验性治疗后诊断中枢神经系统感染更敏感的方法。

结论

mNGS可作为经验性治疗后诊断中枢神经系统感染的更好方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/207d/9372857/4a53df66f5d8/WJCC-10-7760-g001.jpg

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本文引用的文献

5
Performance of Metagenomic Next-Generation Sequencing for the Diagnosis of Viral Meningoencephalitis in a Resource-Limited Setting.
Open Forum Infect Dis. 2020 Feb 8;7(3):ofaa046. doi: 10.1093/ofid/ofaa046. eCollection 2020 Mar.
7
[A Seven-Year Evaluation of Viral Central Nervous System Infections].
Mikrobiyol Bul. 2019 Oct;53(4):434-441. doi: 10.5578/mb.68012.
8
Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid.
Genome Res. 2019 May;29(5):831-842. doi: 10.1101/gr.238170.118. Epub 2019 Apr 16.
9
Detection of pediatric bacterial meningitis pathogens from cerebrospinal fluid by next-generation sequencing technology.
J Infect. 2019 Apr;78(4):323-337. doi: 10.1016/j.jinf.2018.12.001. Epub 2018 Dec 12.
10

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