Blood Biomarkers as Prognostic Indicators for Neurological Injury in COVID-19 Patients: A Systematic Review and Meta-Analysis

Zhiwei Huang, Kassahun Haile, Lealem Gedefaw, Benson Wui Man Lau, Ling Jin, Shea Ping Yip, Chien Ling Huang

Research output: Journal article publicationReview articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Coronavirus disease 2019 (COVID-19) has been linked to various neurological complications. This meta-analysis assessed the relationship between glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) levels in the blood and neurological injury in COVID-19 patients. A comprehensive search of various databases was conducted until 18 August 2023, to find studies reporting GFAP and NfL blood levels in COVID-19 patients with neurological complications. GFAP and NfL levels were estimated between COVID-19 patients and healthy controls, and meta-analyses were performed using RevMan 5.4 software for analysis. In the 21 collected studies, it was found that COVID-19 patients had significantly higher levels of pooled GFAP (SMD = 0.52; 95% CI: 0.31, 0.73; p ≤ 0.001) and NfL (SMD = 0.60; 95% CI: 0.37, 0.82; p ≤ 0.001) when compared to the healthy controls. The pooled GFAP (SMD = 0.86; 95% CI: 0.26, 1.45; p ≤ 0.01) and NfL (SMD = 0.87; 95% CI: 0.48, 1.26; p ≤ 0.001) were significantly higher in non-survivors. These findings indicate a significant association between COVID-19 severity and elevated levels of GFAP and NfL, suggesting that GFAP and NfL could serve as potential diagnostic and prognostic markers for the early detection and monitoring of COVID-19-related neurological injuries.

Original languageEnglish
Article number15738
JournalInternational Journal of Molecular Sciences
Volume24
Issue number21
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Coronavirus disease 2019
  • glial fibrillary acidic protein
  • meta-analysis
  • neurofilament light chain
  • neurological biomarker

ASJC Scopus subject areas

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry

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