Inference of Brain States from Frontal Electroencephalography And Pupillometry During General Anaesthesia

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dc.contributor.advisor Sleigh, Jamie
dc.contributor.advisor Voss, Logan
dc.contributor.author Gaskell, Amy Louise
dc.date.accessioned 2022-01-10T19:38:16Z
dc.date.available 2022-01-10T19:38:16Z
dc.date.issued 2021 en
dc.identifier.uri https://hdl.handle.net/2292/57906
dc.description.abstract Interindividual variability, confounding factors and measurement error hinder our ability to infer brain states from neurophysiological monitors during clinical anaesthesia. Recent monitoring advances have largely failed to translate into demonstrable benefit in clinical studies, and individualized optimization of anaesthesia and analgesia remains a significant challenge. To address these problems I examined electroencephalographic (EEG) data as a measure of cortical effects of anaesthesia and pupillometry data as a measure of brainstem effects of anaesthesia and nociception. The isolated forearm technique (IFT) was used to evaluate frontal EEG measures of cortical state during anaesthesia. Findings from three patients, who responded appropriately to a verbal command, challenge the widely held belief that the frontal alpha-delta EEG pattern is indicative of anaesthesia-induced unconsciousness. None of the frontal EEG measures evaluated (including indices in routine clinical use) reliably discriminated between IFT responders and non-responders. Episodes of connected consciousness during anaesthesia are relatively rare, which limits the positive predictive values achievable by purported awareness indices. Simulations suggested that a performance level exceeding a prediction probability (PK) of 0.92, or a two standard deviation separation, is necessary to attain satisfactory sensitivity with an acceptable burden of false positive cases. This requirement must be achieved in conditions resembling routine clinical practice. Modern causal inference techniques promise to overcome the “association ≠ causation” impasse imposed by traditional statistical dicta. Directed acyclic graphs (DAGs) are a useful tool to illustrate and understand sources of bias as pathways and to guide causal analyses. Pupil size and pupillary light reflex parameters were evaluated as potential measures of the subcortical effects of anaesthesia and intraoperative nociception using structural equation modelling to account for the causal structure of the data. The proportional amplitude of the pupillary light reflex was the best potential marker of anaesthetic effect on the brainstem, having a modest path coefficient (-0.30) with volatile anaesthetic concentration. None of the pupillometry parameters predicted early postoperative pain or sedation. Monitoring of brain state during anaesthesia remains a major challenge. Future advances will depend upon finding measures that are intimately causally linked to the brain state and that can account for between individual variability.
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof PhD Thesis - University of Auckland en
dc.relation.isreferencedby UoA en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/nz/
dc.title Inference of Brain States from Frontal Electroencephalography And Pupillometry During General Anaesthesia
dc.type Thesis en
thesis.degree.discipline Medicine
thesis.degree.grantor The University of Auckland en
thesis.degree.level Doctoral en
thesis.degree.name PhD en
dc.date.updated 2021-12-15T20:55:18Z
dc.rights.holder Copyright: The author en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en


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