Neuroprognostication After Cardiac Arrest Using Glial Fibrillary Acidic Protein: A Systematic Review and Meta-Analysis

OBJECTIVES: To evaluate the prognostic accuracy of glial fibrillary acidic protein (GFAP) levels in predicting poor neurologic outcomes in adult patients after cardiac arrest, across different post-resuscitation timepoints. DATA SOURCES: PubMed, Scopus, Web of Science, and Google Scholar were systematically searched up to June 12, 2025. STUDY SELECTION: Eligible studies included randomized controlled or observational studies enrolling adult or pediatric patients with in- or out-of-hospital cardiac arrest who achieved return of spontaneous circulation (ROSC), measured GFAP in any biofluid, and reported neurologic outcomes. DATA EXTRACTION: Three independent reviewers extracted data on study design, population, arrest characteristics, GFAP sampling methods, outcome definitions, and prognostic performance. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. DATA SYNTHESIS: Twenty studies were included in the systematic review; 12 contributed to meta-analyses. Median GFAP levels were significantly higher in patients with poor neurologic outcomes at 24 hours (Δ = 138.1 pg/mL), 48 hours (Δ = 471.1 pg/mL), and 72 hours (Δ = 745.7 pg/mL) post-ROSC. Summary area under the curve values for prognostic accuracy improved over time: 0.76 at 24 hours, 0.84 at 48 hours, and 0.88 at 72 hours. Subgroup analyses limited to 6-month outcomes and out-of-hospital arrests showed consistent results. Quality assessment revealed low applicability concerns but moderate risk of bias in patient selection and flow/timing. CONCLUSIONS: GFAP demonstrates time-dependent prognostic utility in predicting poor neurologic outcomes after cardiac arrest in adults, with optimal performance at 48-72 hours post-ROSC. These findings support suggest that GFAP shows potential as a time-dependent biomarker but remains investigational. Further prospective studies are needed to validate its clinical utility and to determine standardized cutoff values before routine implementation.