Single electroencephalographic patterns as specific and time-dependent indicators of good and poor outcome after cardiac arrest

Clin Neurophysiol. 2016 Jul;127(7):2610-7. doi: 10.1016/j.clinph.2016.04.008. Epub 2016 Apr 21.

Abstract

Objective: To evaluate the prognostic value of single EEG patterns recorded at various time-frames in postanoxic comatose patients.

Methods: This retrospective study included 30-min EEGs, classified according to the definitions of continuity of background activity given by the American Clinical Neurophysiology Society. Isoelectric pattern was distinguished from other suppressed activities. Epileptiform patterns were considered separately. Outcome was dichotomised based on recovery of consciousness as good (Glasgow Outcome Scale [GOS] 3-5) or poor (GOS 1-2).

Results: We analysed 211 EEGs, categorised according to time since cardiac arrest (within 12h and around 24, 48 and 72h). In each time-frame we observed at least one EEG pattern which was 100% specific to poor or good outcome: at 12h continuous and nearly continuous patterns predicted good outcome and isoelectric pattern poor outcome; at 24h isoelectric and burst-suppression predicted poor outcome; at 48 and 72h isoelectric, burst-suppression and suppression (2-10μV) patterns predicted poor outcome.

Conclusions: The prognostic value of single EEG patterns, defined according to continuity and voltage of background activity, changes until 48-72h after cardiac arrest and in each time-frame there is at least one pattern which accurately predicts good or poor outcome.

Significance: Standard EEG can provide time-dependent reliable indicators of good and poor outcome throughout the first 48-72h after cardiac arrest.

Keywords: Cardiac arrest; Coma; EEG; EEG background activity; Postanoxic coma; Prognostication.

Publication types

  • Evaluation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Electroencephalography*
  • Female
  • Heart Arrest / complications
  • Heart Arrest / diagnosis*
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests