Improving Information Extraction From EEG on Cerebral Anesthetic Drug Effects
Status:
Recruiting
Trial end date:
0000-00-00
Target enrollment:
Participant gender:
Summary
Background of the study:
Multiple electroencephalographically derived indices have been developed to measure the
cerebral hypnotic drug effect during anesthesia, using a variety of mathematical algorithms
such as bispectral index, spectral entropy and spectral edge frequency. The complexity of
the raw EEG is reduced to -an easy to interpret- number. It varies generally between 100
(fully awake patient) to 0 (an excessively sedated patient).
The anesthesiologist adjusts his dosing scheme to target a number between a predefined
range. (e.g. between 40 and 60) These monitors are currently solidly integreted in clinical
practice although they keep being hampered by several limitations. The most important
problem is that they are not extracted from a direct neuro-physiological phenomenon that is
known to be closely related to loss and return of consciousness, rather they have a
probabilistic nature, indicating whether your probability of responsivenessis is high or
low.
You are never sure which EEG phenomenon relates to the index. Also, the number that relates
to loss of consciousness rarely is the same as the number that indicates return of
consciousness, which decreases the predictive value during recovery of anesthesia.
Additionally, the dose response relationship differs on multiple parameters between each
monitors. As such the performance of one monitor cannot be extrapolated to another. Finally,
although the detection capacity of responses to verbal command is fairly good, EEG extracted
numbers perform worse on correlation with movement after a noxious stimulus. Most problems
are related to the limited understanding of the relationship between the changes in EEG and
the underlying (insufficiently understood) neurophysiological mechanism that evokes
(un)consciousness during anesthesia. Secondly, at the time of development of most monitors,
the methods of drug administration were less reproducible to allow a more rational drug
titration in a population of different demographics. The last two decades, major progress
has been made on both issues. Therefore, new insights in neuro-physiology and better drug
titration systems opens new perspectives to improve EEG derived data extraction.
Recently, Mashuire et al found a typical EEG characteristic that is correlated consistently
with the loss and return of responsiveness, independent of the anesthetic used (inhalation
or intravenous) and independent of the species tested (rats and humans). These findings do
suggest that new information can be extracted from the raw EEG that has a much closer
connection with the essential neurophysiological processes involved to evoke
consciousness/unconsciousness or responsiveness/unresponsiveness. In this study we want to
collect data that allows us to recognize these patterns on the EEG as a better measurement
of consciousness/unconsciousness.
Additionally, we have the ability to use (clinically availlable) target controlled infusion
techniques for propofol (plasma- and/or effect-site controlled) and end-tidal titrated
sevoflurane (through a Zeus Ventilator (Draeger)) If we titrate our hypnotics through these
more advanced and pharmacologically more rational titration methods, we may detect a more
relevant correlation between the dose given and the EEG behavior. By adding remifentanil, we
will also explore the alteration of performance of EEG derived information during
interaction with opioids. The obtained data may result in a breakthrough in the methodology
to titrate anesthesia in a more predictable and reproducible way, because the extracted
information relates closer to a neuro-physiological process related to (un)responsiveness.
Moreover, the index may produce more consistent results whether inhaled anesthetics or
intravenous drugs are given.