Clinical analysis of patients with SARS-CoV-2 encephalitis confirmed by next-generation sequencing of cerebrospinal fluid
Journal Title: Chinese Journal of Nervous and Mental Diseases - Year 2024, Vol 50, Issue 9
Abstract
[Objective] To explore the clinical features, diagnostic methods, and treatment strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encephalitis confirmed through cerebrospinal fluid (CSF) analysis. [Methods] The clinical data of patients diagnosed with SARS-CoV-2 encephalitis through CSF analysis in the Neurology Intensive Care Unit of the First Affiliated Hospital of Nanchang University from March 2022 to March 2023 were collected. Additionally, the relevant literature published in both domestic and international databases was analyzed and synthesized. [Results] The main neurological manifestations of five cases included decreased consciousness (5/5), psychiatric disorder (2/5), seizures (2/5), quadriplegia (1/5), and headaches (1/5). Two cases had abnormal brain magnetic resonance imaging (MRI) changes, involving the temporal lobe, insular lobe, thalamus, hippocampus, and pons. Additionally, CSF analysis showed mildly elevated protein levels in two cases. Next-generation sequencing (NGS) of the CSF identified SARS-CoV-2 in all five cases (sequence: 41-1620), and human herpesvirus 1 in one case (sequence: 21). The treatment regimen for all cases included antiviral therapy, three were additionally treated with glucocorticoids and one received immunoglobulin therapy. All cases achieved a favorable outcome (mRS: 0-2). [Conclusion] SARS-CoV-2 has the potential to induce encephalitis/meningitis due to its neurotropic nature. The consideration of this condition is warranted in patients with relevant epidemiological history and symptoms related to the central nervous system. CSF NGS serves as a valuable tool for early diagnosis, while active antiviral therapy and immunotherapy may improve patient outcomes.
Authors and Affiliations
Chong NIE, Zheng LUO, Shiding JIANG, Gangan LIU, Daojun HONG, Lianqun WANG, Yiyi. ZHOU
Keywords
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- EP ID EP750549
- DOI 10.3969/j.issn.1002-0152.2024.09.002
- Views 82
- Downloads 0
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