The Nature of EEG reactivity to light, sound and pain stimulation in neurosurgical comatose patients evaluated by a quantitative method

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Abstract

EEG reactivity (EEG-R) is regarded as an important parameter in coma prognosis but knowledge is sparse on the nature of EEG changes due to different kinds of stimulation and their prognostic significance. EEG-R was quantified in a study of 39 comatose neurosurgical patients. Six 30-second standardized visual, auditory, and painful stimulations were applied. EEG-R in the delta, theta, alpha, and beta band was normalized in z-scores as the power of a stimulation epoch relative to average power of 6 resting epochs. Outcome measure was 3 months Glasgow Outcome Scale. Increase in EEG activity was related to poor outcome, was more common (13.4% of tests), and grew continuously during the 30-second stimulation epoch. Decrease in EEG activity was related to good outcome, was rarer (2.5%), and peaked around 15 seconds. Pain was the most provocative stimulation (20.4%) followed by sound (8.7%) and eye-opening (6.7%). Discrimination between good (n = 6) and poor (n = 33) outcome was best in the theta and alpha bands for pain stimulation in the first 10-20 seconds and for sound stimulation in the first 5 to 10 seconds, eye-opening did not discriminate. Increase in activity predicted poor outcome with a high specificity 100% (CI = 52%-100%) and a modest sensitivity of 39% (CI = 23%-58%). Decrease in activity predicted good outcome with a high specificity of 100% (CI = 87%-100%) and a modest sensitivity of 33% (CI = 6%-76%). This quantitative study reveals new knowledge about the nature of EEG-R, which contribute to the development of more reliable and objective clinical procedures for outcome prediction.

Original languageEnglish
JournalClinical E E G and Neuroscience
Volume48
Issue6
Pages (from-to)428-437
Number of pages10
ISSN1550-0594
DOIs
Publication statusPublished - 1 Nov 2017

Keywords

  • EEG prognosis
  • EEG reactivity
  • coma prognosis
  • neurosurgical intensive care
  • quantitative EEG

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