Prediction of response to noxious stimulation during sedation-analgesia by refined multiscale entropy analysis of EEG

Abstract

The level of sedation in patients undergoing medical procedures evolves continuously since the effect of the anesthetic and analgesic agents is counteracted by noxious stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work was to analyze the capability of prediction of nociceptive responses based on refined multiscale entropy (RMSE). Functions based on RMSE and CeRemi permitted to predict different stimulation responses during sedation with better prediction probability than bispectral index.