Comparison of Conventional Averaged and Rapid Averaged, Autoregressive-based Extracted Auditory Evoked Potentials for Monitoring the Hypnotic Level during Propofol Induction

Author:

Litvan Héctor1,Jensen Erik W.2,Galan Josefina3,Lund Jeppe4,Rodriguez Bernardo E.2,Henneberg Steen W.5,Caminal Pere6,Villar Landeira Juan M.7

Affiliation:

1. Head, Department of Cardiac Anesthesia.

2. Research Fellow.

3. Staff Anesthesiologist.

4. Associate Professor, Faculty of Health Sciences, Department of Anesthesia & Intensive Care, University of Southern Denmark, Odense, Denmark.

5. Associate Professor and Head, Department of Anesthesia, Rigshospitalet, Copenhagen, Denmark.

6. Professor, Center of Research in Biomedical Engineering, Polytechnic University of Catalonia, Barcelona, Spain.

7. Head, Department of Anesthesia, Hospital de la Santa Creu i Sant Pau.

Abstract

Background The extraction of the middle latency auditory evoked potentials (MLAEP) is usually done by moving time averaging (MTA) over many sweeps (often 250-1,000), which could produce a delay of more than 1 min. This problem was addressed by applying an autoregressive model with exogenous input (ARX) that enables extraction of the auditory evoked potentials (AEP) within 15 sweeps. The objective of this study was to show that an AEP could be extracted faster by ARX than by MTA and with the same reliability. Methods The MTA and ARX methods were compared with the Modified Observer's Assessment of Alertness and Sedation Scale (MOAAS) in 15 patients scheduled for cardiac surgery and anesthetized with propofol. The peak amplitudes and latencies were recorded continuously for the MTA- and ARX-extracted AEP. An index, AAI, was derived from the ARX-extracted AEP as well. Results The best predictors of the awake and anesthetized states, in terms of the prediction probability, Pk, were the AAI (Pk [SE] = 0.93 [0.01]) and Na-Pa amplitude (MTA, Pk [SE] = 0.89 [0.02]; ARX, Pk [SE] = 0.87[0.02]). When comparing the AAI at the MOAAS levels 5-3 versus 2-0, significant differences were achieved. During the transitions from awake to asleep, the ARX-extracted AEP were obtained with significantly less delay than the MTA-extracted AEP (28.4 s vs. 6 s). Conclusion The authors conclude that the MLAEP peaks and the AAI correlate well to the MOAAS, whether extracted by MTA or ARX, but the ARX method produced a significantly shorter delay than the MTA.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Anesthesiology and Pain Medicine

Reference26 articles.

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1. Midlatency auditory evoked potentials during anesthesia in children: A narrative review;Pediatric Anesthesia;2021-07-18

2. One-Class-Based Intelligent Classifier for Detecting Anomalous Situations During the Anesthetic Process;Logic Journal of the IGPL;2020-11-11

3. Modelling the hypnotic patient response in general anaesthesia using intelligent models;Logic Journal of the IGPL;2018-09-11

4. Influencia de la anestesia general sobre el tronco encefálico;Revista Española de Anestesiología y Reanimación;2017-03

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