Combination of Entropy and Electroencephalograpy for Deep of Hypnosis Monitoring Improvement during General Anesthesia

Author(s): Alberto Martinez Ruiz, Blanca Escontrela, Itxaso Merino Julian

Background: Deep of hypnosis monitoring based on electroencephalogram (EEG) and end tidal anesthetic concentration (ETAC) of volatile agents are a standard of care in patients under general anesthesia. Entropy and ETAC could reflected the effects of volatile agents as evidence had been showed, but its accuracy for hypnosis monitoring during nociceptive stimulation in patients under neuromuscular block and emergence is controversial.

Methods: Prospective, single-group, double-blinded and observational study was conducted in young female patients scheduled for minor gynecological surgery under general anesthesia. A standard protocol was administered to all patients and deep of hypnosis monitoring using entropy and quantitative EEG (qEEG) was blind to anesthesiologist in charge. Primary outcomes were described changes and discrimination capacity of hypnosis depth of entropy, qEEG and ETAC from induction to emergence. Secondary outcome was described an equation of hypnosis state prediction using entropy, qEEG and ETAC based on its discrimination capacity of hypnosis depth.

Results: 42 patients scheduled for minor gynecological surgery under general anesthesia were included. Combination of frontal electromyogram (fEMG), Response Entropy (RE), delta and theta activities showed an excellent prediction capacity of hypnosis state. Entropy and fEMG showed an excellent discrimination capacity of hypnosis depth from induction to emergence. Delta activity showed a good discrimination capacity of hypnosis state during emergence. Electroencephalogram amplitude during maintenance and median Frequency (MF) during emergence showed an acceptable discrimination capacity of hypnosis depth. Beta/Delta ratio (B/D) during induction and emergence showed an acceptable discrimination capacity of hypnosis depth. During maintenance Burst Suppression corrected for Spectral Edge Frequency ratio (BcSEF) and Beta/Theta ratio (B/T) showed an acceptable discrimination capacity of hypnosis depth. ETAC showed a good discrimination capacity from laryngoscopy to emergence. ETAC variability was poorly explained for entropy. Entropy variability was poorly explained for ETAC and EEG variables.

Conclusions: Our study described an equation for hypnosis state prediction combining fast, intermediate and slow activity. An interesting finding of the present study was that delta activity, MF, amplitude and corrected variables probably reflecting the balance between slow and fast activity could improve deep of hypnosis monitoring, but limitations related to little size and design of this study warrants further validation.