A novel multivariate STeady-state index during general ANesthesia (STAN).

The assessment of the adequacy of general anesthesia for surgery, namely the nociception/anti-nociception balance, has received wide attention from the scientific community. Monitoring systems based on the frontal EEG/EMG, or autonomic state reactions (e.g. heart rate and blood pressure) have been developed aiming to objectively assess this balance. In this study a new multivariate indicator of patients' steady-state during anesthesia (STAN) is proposed, based on wavelet analysis of signals linked to noxious activation. A clinical protocol was designed to analyze precise noxious stimuli (laryngoscopy/intubation, tetanic, and incision), under three different analgesic doses; patients were randomized to receive either remifentanil 2.0, 3.0 or 4.0 ng/ml. ECG, PPG, BP, BIS, EMG and [Formula: see text] were continuously recorded. ECG, PPG and BP were processed to extract beat-to-beat information, and [Formula: see text] curve used to estimate the respiration rate. A combined steady-state index based on wavelet analysis of these variables, was applied and compared between the three study groups and stimuli (Wilcoxon signed ranks, Kruskal-Wallis and Mann-Whitney tests). Following institutional approval and signing the informed consent thirty four patients were enrolled in this study (3 excluded due to signal loss during data collection). The BIS index of the EEG, frontal EMG, heart rate, BP, and PPG wave amplitude changed in response to different noxious stimuli. Laryngoscopy/intubation was the stimulus with the more pronounced response [Formula: see text]. These variables were used in the construction of the combined index STAN; STAN responded adequately to noxious stimuli, with a more pronounced response to laryngoscopy/intubation (18.5-43.1 %, [Formula: see text]), and the attenuation provided by the analgesic, detecting steady-state periods in the different physiological signals analyzed (approximately 50 % of the total study time). A new multivariate approach for the assessment of the patient steady-state during general anesthesia was developed. The proposed wavelet based multivariate index responds adequately to different noxious stimuli, and attenuation provided by the analgesic in a dose-dependent manner for each stimulus analyzed in this study.