Prognostic and diagnostic value of EEG signal coupling measures in coma

Clin Neurophysiol. 2016 Aug;127(8):2942-2952. doi: 10.1016/j.clinph.2015.08.022. Epub 2015 Oct 24.

Abstract

Objective: Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients.

Methods: In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians.

Results: Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946).

Conclusions: EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma.

Significance: Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

Keywords: Bayes classifier; Coma; Prognostication; Quantitative EEG; Synchronization.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Brain / physiopathology*
  • Coma / diagnosis*
  • Coma / physiopathology
  • Electroencephalography / methods*
  • Female
  • Glasgow Coma Scale
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Retrospective Studies
  • Signal Processing, Computer-Assisted
  • Young Adult