Electroencephalogram-Based Anesthesia Indices Differently React to Modulations of Alpha-Oscillatory Activity

Thomas Kinateder; Stephan Kratzer; Cornelius Husemann; Hubert Hautmann; Paul S García; Gerhard Schneider; Matthias Kreuzer

doi:10.1213/ANE.0000000000007042

Electroencephalogram-Based Anesthesia Indices Differently React to Modulations of Alpha-Oscillatory Activity

Anesth Analg. 2024 Aug 2. doi: 10.1213/ANE.0000000000007042. Online ahead of print.

Authors

Thomas Kinateder¹, Stephan Kratzer², Cornelius Husemann¹, Hubert Hautmann³, Paul S García⁴, Gerhard Schneider¹, Matthias Kreuzer¹

Affiliations

¹ From the Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany.
² Department of Anesthesia, Critical Care and Pain Medicine, Hessing Foundation, Augsburg, Germany.
³ Department of Internal Medicine and Pneumology, Klinik Ottobeuren, Ottobeuren, Germany.
⁴ Department of Anesthesiology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.

PMID: 39093724
DOI: 10.1213/ANE.0000000000007042

Abstract

Background: The electroencephalographic (EEG) provides the anesthesiologist with information regarding the level of anesthesia. Processed EEG indices are available that reflect the level of anesthesia as a single number. Strong oscillatory EEG activity in the alpha-band may be associated with an adequate level of anesthesia and a lower incidence of cognitive sequelae. So far, we do not know how the processed indices would react to changes in the alpha-band activity. Hence, we modulated the alpha-oscillatory activity of intraoperative EEG to assess possible index changes.

Methods: We performed our analyses based on data from 2 studies. Intraoperative EEG was extracted, and we isolated the alpha-band activity by band-pass filtering (8-12 Hz). We added or subtracted this activity to the original EEG in different steps with different amplifications of the alpha signal. We then replayed these signals to the bispectral index (BIS), the Entropy Module (state entropy [SE]), the CONOX (qCON), and the SEDLine (patient state index [PSI]); and evaluated the alpha-band modulation's impact on the respective index.

Results: The indices behaved differently to the modulation. In general, indices decreased with stronger alpha-band activity, but the rate of change was different with SE showing the strongest change (9% per step) and PSI and BIS (<5% per step) showing the weakest change. A simple regression analysis revealed a decrease of 0.02 to 0.09 index points with increasing alpha amplification.

Conclusions: While the alpha-band in the intraoperative EEG seems to carry information regarding the quality of anesthesia, changes in the alpha-band activity do neither strongly nor uniformly influence processed EEG indices. Hence, to assess alpha-oscillatory activity's strength, the user needs to focus on the raw EEG or its spectral representation also displayed on the monitoring systems.