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Abstract Details

Predicting Outcomes in Anti-NMDA Receptor Encephalitis using EEG

Background: Over the last decade there has been an increasing recognition of encephalopathy syndromes caused by autoantibodies. One of the most investigated of these are antibodies acting against the N-methyl-D-aspartate receptor (NMDAR). Outcomes from patients with anti-NMDAR encephalitis are extremely variable, with approximately 25% of patients suffering long term severe neurological deficits, or death (Dalmau et al. 2008). Patients often have abnormal EEG findings (Foff et al. 2016) and an important, yet unanswered question is whether EEG has a prognostic value in this patient group.

Method: A single centre retrospective review of patients with anti-NMDAR encephalitis over a 6-year period was employed. Patients were identified from a hospital electronic database and were included if they had confirmed anti-NMDAR antibodies with one, or more neuropsychiatric symptoms and an admission EEG. Peak power across the four main frequency bands (beta, alpha, theta, and delta) was calculated from the admission EEG using spectral analysis. The primary outcome measure was Modified Rankin Scale at last follow-up.

Results: The commonest presenting symptoms were confusion, followed by psychosis. Average time from symptom onset to EEG was 179 days and average admission length was 25 days, with an average follow up of 2.1 years. Qualitative analysis revealed generalized slowing was more common in patients with a poor outcome, whereas, electrographic seizures were more common in patients with a good outcome. Quantitative analysis revealed a statistically significant association between greater peak power in the theta and delta range and poor outcome.

Conclusion: This is the first study to demonstrate that EEG may be a potentially useful prognostic tool in patients with anti-NMDAR encephalitis. In particular, early findings suggest patients with anti-NMDAR encephalitis with greater slow wave activity on their admission EEG have worse long term outcome using either qualitative or quantitative techniques.

TitleForenamesSurnameInstitutionLead AuthorPresenter
DrGrahamBlackmanInstitute of Psychiatry, Psychology and Neuroscience
MrJohnHanrahanKings College London
MrAnthonyDalrympleKings College London
ProfAnthonyDavidInstitute of Psychiatry, Psychology and Neuroscience
Foff E.P., Taplinger D., Suski J., MBS L. and Quigg M. (2016) 'EEG findings may serve as a potential biomarker for anti-NMDA receptor encephalitis': Clin EEG Neurosci, 4, 10, pp. 1-6
Dalmau J, Gleichman AJ, Hughes EG, et al. (2008) 'Anti-NMDA-receptor encephalitis: case series and analysis of the effects of antibodies'. Lancet Neurol,7, pp. 1091-98.