Do all sedatives promote biological sleep electroencephalogram patterns? A machine learning framework to identify biological sleep promoting sedatives using electroencephalogram.

Autor: Ramaswamy SM; Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Kuizenga MH; Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Weerink MAS; Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Vereecke HEM; Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Department of Anesthesiology and Reanimation, AZ St.-Jan Brugge Oostende AV, Brugge, Belgium., Nagaraj SB; School of Physics, Maths and Computing, Computer Science and Software Engineering, The University of Western Australia, Perth, Australia., Struys MMRF; Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Department of Basic and Applied Medical Sciences, Ghent University, Gent, Belgium.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2024 Jul 02; Vol. 19 (7), pp. e0304413. Date of Electronic Publication: 2024 Jul 02 (Print Publication: 2024).
DOI: 10.1371/journal.pone.0304413
Abstrakt: Background: Sedatives are commonly used to promote sleep in intensive care unit patients. However, it is not clear whether sedation-induced states are similar to the biological sleep. We explored if sedative-induced states resemble biological sleep using multichannel electroencephalogram (EEG) recordings.
Methods: Multichannel EEG datasets from two different sources were used in this study: (1) sedation dataset consisting of 102 healthy volunteers receiving propofol (N = 36), sevoflurane (N = 36), or dexmedetomidine (N = 30), and (2) publicly available sleep EEG dataset (N = 994). Forty-four quantitative time, frequency and entropy features were extracted from EEG recordings and were used to train the machine learning algorithms on sleep dataset to predict sleep stages in the sedation dataset. The predicted sleep states were then compared with the Modified Observer's Assessment of Alertness/ Sedation (MOAA/S) scores.
Results: The performance of the model was poor (AUC = 0.55-0.58) in differentiating sleep stages during propofol and sevoflurane sedation. In the case of dexmedetomidine, the AUC of the model increased in a sedation-dependent manner with NREM stages 2 and 3 highly correlating with deep sedation state reaching an AUC of 0.80.
Conclusions: We addressed an important clinical question to identify biological sleep promoting sedatives using EEG signals. We demonstrate that propofol and sevoflurane do not promote EEG patterns resembling natural sleep while dexmedetomidine promotes states resembling NREM stages 2 and 3 sleep, based on current sleep staging standards.
Competing Interests: M. M. R. F. Struys: His research group/department received (over the last 3 years) research grants and consultancy fees from Masimo (Irvine, CA, USA), Becton Dickinson (Eysins, Switzerland), Fresenius (Bad Homburg, Germany), Paion (Aachen, Germany), Medcaptain Europe (Andelst, The Netherlands), Baxter (Chicago, Il, USA), HanaPharm (Seoul, Republic of Korea). He receives royalties on intellectual property from Demed Medical (Sinaai, Belgium) and the Ghent University (Gent, Belgium). This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2024 Ramaswamy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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