Seizures in autoimmune encephalitis-A systematic review and quantitative synthesis

Area of Science:

• Neurology
• Immunology
• Epileptology

Background:

• Autoimmune encephalitis (AE) is a group of immune-mediated disorders affecting the central nervous system.
• Seizures and electroencephalography (EEG) abnormalities are known clinical manifestations of AE, but their precise prevalence and association with specific AE subtypes require further elucidation.

Purpose of the Study:

• To systematically evaluate the proportion of patients experiencing seizures and exhibiting EEG abnormalities in autoimmune encephalitis.
• To analyze these occurrences in relation to the most common AE subtypes, particularly anti-NMDA receptor encephalitis.

Main Methods:

• A systematic review adhering to PRISMA standards was conducted, searching multiple databases (Medline, Embase, PsychINFO) from inception to June 2019.
• Studies reporting seizure and/or EEG data in cohorts of at least 10 AE patients were included. Data extraction and review were performed in duplicate.
• Quantitative synthesis, including logistic regression and chi-square analyses, was employed, stratified by autoantibody subtype.

Main Results:

• The review included 118 studies encompassing 3722 antibody-positive AE patients. Clinical seizures occurred in 69.9% of patients, and EEG abnormalities were present in 84.8% of those with available data.
• Anti-N-methyl-d-aspartate (NMDA) receptor encephalitis was the most frequent subtype (53.3%). In this subpopulation, seizures affected 71.8% and EEG abnormalities were found in 89.7%.
• Seizures were more prevalent in younger patients across all AE types and in the anti-NMDA receptor encephalitis group (p < .05).

Conclusions:

• This systematic review confirms a substantial burden of seizures in autoimmune encephalitis, affecting a significant majority of patients.
• EEG abnormalities are also highly prevalent in AE, underscoring the utility of EEG in diagnosis and management.
• Further prospective research is recommended to determine population-based seizure prevalence, identify associated factors, and validate EEG findings as biomarkers for AE outcomes.