Purpose: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is an autoimmune reaction involving Immunoglobulin G antibodies against GluN1 subunit of NMDAR. Absence of biomarkers for early diagnosis and prognosis poses a challenge. Several small case-control studies have emphasized the prospect of quantitative EEG measurements. This study aimed to analyze and identify novel scalp quantitative EEG biomarkers and their implications on outcome of NMDRA encephalitis compared with a control group.
Methods: Retrospective (2012-2021) case-control study of patients with NMDRA encephalitis and with acute/subacute encephalitis from other causes. Clinical variables and outcomes were assessed with modified Rankin Scale at admission, discharge, and follow-up. All patients underwent extensive diagnostic workup, including scalp EEG within 72 hours of admission. Quantitative EEG was calculated for Renyi, Tsalis entropy, Hjorth complexity, mean energy, and spectral power of the following frequency bands and ratios: delta (0.5-4 Hz), theta (5-8 Hz), alpha (9-14 Hz), beta (15-30 Hz), gamma (31-45 Hz), gamma-beta, beta/alpha, beta/theta, and beta/delta. Descriptive statistics, power frequency bands, complexity measures, and Wilcoxon rank sum test were used.
Results: Patients with anti-NMDAR encephalitis had significantly higher delta frequency peak power, higher beta/alpha and gamma/beta frequency ratios, lower alpha and beta peak power, and lower beta/delta frequency ratio than the control group. In patients with anti-NMDAR encephalitis, higher delta and alpha peak power had the worst clinical outcome, at discharge and follow-up, and patients with higher gamma peak power had better outcomes.
Conclusions: Quantitative EEG is a valuable tool to differentiate anti-NMDAR encephalitis from other inflammatory encephalitis and predict outcomes in patients with anti-NMDAR encephalitis.
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