EEG reactivity for prognostication after cardiac arrest

Prediction of outcome (prognostication) after Cardiac Arrest (CA) is a daily faced challenge for clinicians. Early and in particular reliable prognostication has the potential to decrease uncertainties among relatives, may help in taking correct medical decisions, and could prevent unnecessary long futile care. Electroencephalographic reactivity (EEG-R), the change in brain activity in response to an external stimulus, is described as a possible marker for outcome prediction. However, clear guidelines on how to test EEG-R and how to assess the results do not exist. This thesis is a collection of investigations testing the prognostic capacity of EEG-R in patients after CA.
In a systematic review we found that methods of EEG-R testing vary widely, and that definitions are unclear. In a quest for standardization, a Delphi survey was performed with international experts on intensive care EEG. Agreement was reached on a standard stimulus protocol and a definition of EEG-R. To study the prognostic capacity of EEG-R, a prospective observational cohort study in 160 patients was performed. We found that EEG-R has limited value in prediction of poor outcome after CA: EEG-R based on visual analysis is not reliable, nor of additional value. For prediction of good outcome, EEG-R might be of additional value, especially in patients with a continuous or discontinuous EEG background. Quantitative analysis could be an alternative to visual analysis, however, for prediction of poor outcome, it is inferior to quantitative analysis of the EEG background. Use of EEG-R in prognostication after CA should be done with great restraints.