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Open Access 18-12-2023 | Propofol | Original Research

Substance-dependent EEG during recovery from anesthesia and optimization of monitoring

Authors: Marlene Lipp, Gerhard Schneider, Matthias Kreuzer, Stefanie Pilge

Published in: Journal of Clinical Monitoring and Computing | Issue 3/2024

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Abstract

The electroencephalographic (EEG) activity during anesthesia emergence contains information about the risk for a patient to experience postoperative delirium, but the EEG dynamics during emergence challenge monitoring approaches. Substance-specific emergence characteristics may additionally limit the reliability of commonly used processed EEG indices during emergence. This study aims to analyze the dynamics of different EEG indices during anesthesia emergence that was maintained with different anesthetic regimens. We used the EEG of 45 patients under general anesthesia from the emergence period. Fifteen patients per group received sevoflurane, isoflurane (+ sufentanil) or propofol (+ remifentanil) anesthesia. One channel EEG and the bispectral index (BIS A-1000) were recorded during the study. We replayed the EEG back to the Conox, Entropy Module, and the BIS Vista to evaluate and compare the index behavior. The volatile anesthetics induced significantly higher EEG frequencies, causing higher indices (AUC > 0.7) over most parts of emergence compared to propofol. The median duration of “awake” indices (i.e., > 80) before the return of responsiveness (RoR) was significantly longer for the volatile anesthetics (p < 0.001). The different indices correlated well under volatile anesthesia (rs > 0.6), with SE having the weakest correlation. For propofol, the correlation was lower (rs < 0.6). SE was significantly higher than BIS and, under propofol anesthesia, qCON. Systematic differences of EEG-based indices depend on the drugs and devices used. Thus, to avoid early awareness or anesthesia overdose using an EEG-based index during emergence, the anesthetic regimen, the monitor used, and the raw EEG trace should be considered for interpretation before making clinical decisions.
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Metadata
Title
Substance-dependent EEG during recovery from anesthesia and optimization of monitoring
Authors
Marlene Lipp
Gerhard Schneider
Matthias Kreuzer
Stefanie Pilge
Publication date
18-12-2023
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 3/2024
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-023-01103-4

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