4.5 Article

Capability of processed EEG parameters to monitor conscious sedation in endoscopy is similar to general anaesthesia

期刊

UNITED EUROPEAN GASTROENTEROLOGY JOURNAL
卷 9, 期 3, 页码 354-361

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/2050640620959153

关键词

Neuromonitoring; conscious sedation; endoscopy; nurse administered propofol sedation; processed EEG

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This study aimed to differentiate consciousness in endoscopic propofol sedation using EEG parameters, with complexity and optimised frequency domain parameters yielding the best results. While these findings are not sufficient for clinical application, prediction capability may be increased with further optimisation and modelling.
Background Reliable and safe sedation is a prerequisite for endoscopic interventions. The current standard is rather safe, yet, an objective device to measure sedation depth is missing. To date, anaesthesia monitors based on processed electroencephalogram (EEG) have not been utilised in conscious sedation. Objective To investigate EEG parameters to differentiate consciousness in endoscopic propofol sedation. Methods In total, 171 patients aged 21-83 years (ASA I-III) undergoing gastrointestinal and bronchial endoscopy were enrolled. Standard monitoring and a frontotemporal 2-channel-EEG were recorded. The state of consciousness was identified by repeated requests to squeeze the investigator's hand. Results In total, 1132 state of consciousness transitions were recorded in procedures ranging from 5 to 69 minutes. Thirty-four EEG parameters from the frequency domain, time-frequency domain and complexity measures were calculated. Area under the curve ranged from 0.51 to 0.82 with complexity and optimised frequency domain parameters yielding the best results. Conclusion Prediction of the state of consciousness with processed EEG parameters is feasible, and results for sedation in endoscopic procedures are similar to those reported from general anaesthesia. These results are insufficient for a clinical application, but prediction capability may be increased with optimisation and modelling.

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