Electroclinical biomarkers of autoimmune encephalitis

Epilepsy Behav. 2022 Mar:128:108571. doi: 10.1016/j.yebeh.2022.108571. Epub 2022 Jan 29.

Abstract

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.

Keywords: Autoimmune encephalitis; Biomarker; EEG; LGI-1; NMDA.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Anti-N-Methyl-D-Aspartate Receptor Encephalitis* / complications
  • Biomarkers
  • Electroencephalography
  • Hashimoto Disease* / complications
  • Hashimoto Disease* / diagnosis
  • Humans
  • Retrospective Studies

Substances

  • Biomarkers