Monitoring of processed EEG under anesthesia II

Czech version

Authors: M. Horáček
Authors‘ workplace: Katedra anesteziologie a intenzivní medicíny, Institut postgraduálního vzdělávání ve zdravotnictví, Praha ; Klinika anesteziologie, resuscitace a intenzivní medicíny, 2. lékařská fakulta Univerzity Karlovy a Fakultní nemocnice v Motole, Praha
Published in: Anest. intenziv. Med., 33, 2022, č. 3-4, s. 153-160
Category: Review Article
doi: https://doi.org/10.36290/aim.2022.025

Overview

Processed EEG (pEEG) monitoring is currently used in four indications. The benefit has been demonstrated in the reduction of awakening and recovery times and in reducing the risk of accidental awareness during general anesthesia with the TIVA technique, while the indications for prevention of too deep anesthesia and personalization of anesthesia management are still questionable. Intuitively, it seems that personalized management of anesthesia using data not only from pEEG, but also from other basic monitors could improve results. The relevant studies are still ongoing. Spectrograms obtained by Fourier transformation of the raw EEG curve are suitable for personalizing anesthesia. In the spectrograms, there are significant variations between individual anesthetics, which are caused by different mechanisms of effects and various effects on neuronal circuits in the brain. Parameters such as median frequency and spectral edge frequency (SEF) are also useful. The spectrograms are shown on some monitors that are already commonly available in the Czech Republic such as SedLine Sedation Monitor, Conox or newer generation BIS devices. To titrate antinociception in anesthesia, not only pEEG, but other parameters from basic monitoring, such as respiratory system compliance, the difference between inhaled and exhaled oxygen concentration, Surgical Plethysmography Index from pulse oximetry can also be used. Aging-related EEG changes and the use of spectrograms at the beginning, during maintenance, and emergence from anesthesia will be presented in the third part of this collection of articles.

Keywords:

EEG – Anesthesia – depth of anesthesia index – spectrogram – Fourier transformation

Sources

1. Horáček M. Monitorování počítačem zpracovaného EEG v anestezii I. Anest intenziv Med. 2022;33(2):79-89.

2. Doporučený postup ČSARIM. Zásady bezpečné anesteziologické péče. Available from: https://www.csarim.cz/getmedia/bf2afe85-bd5b-4050-acd6-0cd4583aff9b/ doporuceny‑postup‑zasady‑bezpecne‑anesteziologicke‑pece- 2017.pdf.aspx (cited 11. 07. 2022)

3. Klein AA, Meek T, Allcock E, Cook TM, Mincher N, Morris C, et al. Recommendations for standards of monitoring during anaesthesia and recovery 2021: Guideline from the Association of Anaesthetists. Anaesthesia. 2021 Sep;76(9):1212-1223. doi: 10.1111/ anae.15501. PMID: 34013531.

4. Lewis SR, Pritchard MW, Fawcett LJ, Punjasawadwong Y. Bispectral index for improving intraoperative awareness and early postoperative recovery in adults. Cochrane Database Syst Rev. 2019 Sep 26;9(9):CD003843. doi: 10.1002/14651858.CD003843. pub4. PMID: 31557307.

5. Evered LA, Goldstein PA. Reducing Perioperative Neurocognitive Disorders (PND) Through Depth of Anesthesia Monitoring: A Critical Review. Int J Gen Med. 2021 Jan 14;14:153- 162. doi: 10.2147/IJGM.S242230.

6. Muhlhofer WG, Zak R, Kamal T, Rizvi B, Sands LP, Yuan M, et al.: Burst‑suppression ratio underestimates absolute duration of electroencephalogram suppression compared with visual analysis of intraoperative electroencephalogram. Br J Anaesth. 2017 May 1;118(5):755- 761. doi: 10.1093/bja/aex054. PMID: 28486575.

7. Fleischmann A, Georgii MT, Schuessler J, Schneider G, Pilge S, Kreuzer M. Always Assess the Raw Electroencephalogram: Why Automated Burst Suppression Detection May Not Detect All Episodes. Anesth Analg. 2022 Jun 3. Online ahead of print. doi: 10.1213/ ANE.0000000000006098. PMID: 35653440.

8. Kratzer S, Schneider M, Obert DP, Schneider G, García PS, Kreuzer M. Age‑Related EEG Features of Bursting Activity During Anesthetic‑Induced Burst Suppression. Front Syst Neurosci. 2020 Dec 3;14:599962. doi: 10.3389/fnsys.2020.599962. eCollection 2020. PMID: 33343307.

9. Shao YR, Kahali P, Houle TT, Deng H, Colvin C, Dickerson BC, et al. Low Frontal Alpha Power Is Associated With the Propensity for Burst Suppression: An Electroencephalogram Phenotype for a „Vulnerable Brain“. Anesth Analg. 2020 Nov;131(5):1529-1539. doi: 10.1213/ANE.0000000000004781.

10. Purdon PL, Sampson A, Pavone KJ, Brown EN. Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures. Anesthesiology. 2015 Oct;123(4):937-60. doi: 10.1097/ALN.0000000000000841.

11. Pavone KJ, Akeju O, Sampson AL, Ling K, Purdon PL, Brown EN. Nitrous oxide‑induced slow and delta oscillations. Clin Neurophysiol. 2016 Jan;127(1):556-564. doi: 10.1016/j.clinph.2015. 06. 001.

12. Niu B, Xiao JY, Fang Y, Zhou BY, Li J, Cao F, et al.: Sevoflurane‑ induced isoelectric EEG and burst suppression: differential and antagonistic effect of added nitrous oxide. Anaesthesia. 2017 May;72(5):570-579. doi: 10.1111/anae.13843.

13. Akeju O, Song AH, Hamilos AE, Pavone KJ, Flores FJ, Brown EN, et al. Electroencephalogram signatures of ketamine anesthesia‑ induced unconsciousness. Clin Neurophysiol. 2016 Jun;127(6):2414-22. doi: 10.1016/j.clinph.2016. 03. 005. PMID: 27178861.

14. Sleigh JW, Sanders RD. Intraoperative analgesic titration: the hunting of the snark. Anesth Analg. 2014 Aug;119(2):234-236. doi: 10.1213/ANE.0000000000000312.

15. Idei M, Seino Y, Sato N, Yoshida T, Saishu Y, Fukui K, et al. Validation of the Patient State Index for monitoring sedation state in critically ill patients: a prospective observational study. J Clin Monit Comput. 2022 Jun 4. doi: 10.1007/s10877-022-00871-9.

16. Jensen EW, Valencia JF, López A, Anglada T, Agustí M, Ramos Y, et al. Monitoring hypnotic effect and nociception with two EEG‑derived indices, qCON and qNOX, during general anaesthesia. Acta Anaesthesiol Scand. 2014 Sep;58(8):933-41. doi: 10.1111/aas.12359.

17. Muller J.N., Kreuzer M., Garcia P. S., Schneider G., Hautmann H. Monitoring depth of sedation: evaluating the agreement between the Bispectral Index, qCON and the Entropy Module’s State Entropy during flexible bronchoscopy. Minerva Anestesiol. 2017;83:563-573.

18. Ledowski T, Schneider M, Gruenewald M, Goyal RK, Teo SR, Hruby J. Surgical pleth index: prospective validation of the score to predict moderate‑ to‑ severe postoperative pain. Br J Anaesth. 2019 Aug;123(2):e328-e332. doi: 10.1016/j.bja.2018. 10. 066.

19. Sahinovic MM, Eleveld DJ, Kalmar AF, Heeremans EH, De Smet T, Seshagiri CV, et al. Accuracy of the composite variability index as a measure of the balance between nociception and antinociception during anesthesia. Anesth Analg. 2014 Aug;119(2):288- 301. doi: 10.1213/ANE.0000000000000274. PMID: 2489280.

20. Gaskell A, Pullon R, Hight D, Termaat J, Mans G, Voss L, et al. Modulation of frontal EEG alpha oscillations during maintenance and emergence phases of general anaesthesia to improve early neurocognitive recovery in older patients: protocol for a randomised controlled trial. Trials. 2019 Feb 22;20(1):146. doi: 10.1186/s13063-019-3178-x.

21. Shanker A, Abel JH, Narayanan S, Mathur P, Work E, Schamberg G, et al. Perioperative Multimodal General Anesthesia Focusing on Specific CNS Targets in Patients Undergoing Cardiac Surgeries: The Pathfinder Feasibility Trial. Front Med (Lausanne). 2021 Oct 14;8:719512. doi: 10.3389/fmed.2021.719512. eCollection 2021. PMID: 34722563.

22. Gruber BU, Girsberger V, Kusstatscher L, Funk S, Luethy A, Jakus L, et al. Comparing propofol anaesthesia guided by Bispectral Index monitoring and frontal EEG wave analysis with standard monitoring in laparoscopic surgery: protocol for the ‘EEG in General Anaesthesia - More Than Only a Bispectral Index’ Trial, a multicentre, double‑blind, randomised controlled trial. BMJ Open. 2022 Jun 10;12(6):e059919. doi: 10.1136/ bmjopen-2021-059919. PMID: 35688587.

23. Tang CJ, Jin Z, Sands LP, Pleasants D, Tabatabai S, Hong Y, et al. ADAPT-2: A Randomized Clinical Trial to Reduce Intraoperative EEG Suppression in Older Surgical Patients Undergoing Major Noncardiac Surgery. Anesth Analg. 2020 Oct;131(4):1228-1236. doi: 10.1213/ANE.0000000000004713. PMID: 32925344.