Electroclinical biomarkers of autoimmune encephalitis

Robb Wesselingh, James Broadley, Katherine Buzzard, David Tarlinton, Udaya Seneviratne, Chris Kyndt, Jim Stankovich, Paul Sanfilippo, Cassie Nesbitt, Wendyl D'Souza, Richard Macdonell, Helmut Butzkueven, Terence J. O'Brien, Mastura Monif

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Objective: To evaluate the utility of electroencephalography (EEG) changes as diagnostic and prognostic biomarkers in acute autoimmune encephalitis (AIE). Methods: One hundred and thirty-one patients with AIE were recruited retrospectively across 7 hospitals. Clinical data were collected during admission and at 12 months. EEGs were reviewed using a standard reporting proforma. Associations between EEG biomarkers, AIE subtypes, and clinical outcomes were assessed using logistic regression modeling. Results: Presence of superimposed fast activity (OR 34.33; 95% CI 3.90, 4527.27; p < 0.001), fluctuating EEG abnormality (OR 6.60; 95% CI 1.60, 37.59; p = 0.008), and hemispheric focality (OR 28.48; 95% CI 3.14, 3773.14; p < 0.001) were significantly more common in N-methyl-D-aspartate receptor (NMDAR) antibody-associated patients with AIE compared to other AIE subtypes. Abnormal background rhythm was associated with a poor mRS (modified Rankin score) at discharge (OR 0.29; 95% CI 0.10, 0.75; p = 0.01) and improvement in mRS at 12 months compared with admission mRS (3.72; 95% CI 1.14, 15.23; p = 0.04). Significance: We have identified EEG biomarkers that differentiate NMDAR AIE from other subtypes. We have also demonstrated EEG biomarkers that are associated with poor functional outcomes.

Original languageEnglish
Article number108571
Number of pages11
JournalEpilepsy & Behavior
Publication statusPublished - Mar 2022


  • Autoimmune encephalitis
  • Biomarker
  • EEG
  • LGI-1
  • NMDA

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