Prediction of Propofol Effect-Site Concentration Associated With Deep Anesthesia
NCT ID: NCT06346158
Last Updated: 2026-01-16
Study Results
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Basic Information
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RECRUITING
110 participants
OBSERVATIONAL
2025-04-07
2027-01-31
Brief Summary
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The investigators hypothesized that there is a great variability in this Ce that could be precisely explained by
* Electroencephalographic (EEG) features available prior to induction of anesthesia
* Cognitive performance
* Patients characteristics Participants will undergo preoperative cognitive testing and awake EEG. Then, induction of general anesthesia will be performed using continuous infusion of propofol. The Ce at which Deep anesthesia is observed will be recorded.
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Detailed Description
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Hypothesis : There is a large interindividual variability in patients' sensitivity to propofol which can be precisely modeled using clinical, demographic, and electroencephalographic (EEG) features available prior to induction of general anesthesia. The investigators also hypothesise that this sensitivity to propofol may identify vulnerable brain phenotype related to poor cognitive performance.
Specific objectives: Primary: to investigate the variability of Ce propofol at which deep anesthesia (DA) occurs during induction of general anesthesia (CeDA). Secondary: to explore the relationship between demographics, cognitive performance, and EEG variables with the independent CeDA variable. Tertiary: to develop and validate a machine learning algorithm to predict CeDA based on clinical, demographic and EEG features obtained prior the induction of general anesthesia.
Methods: This prospective monocentric observational study will include 110 participants of 18 years of age or older scheduled for surgery under general anesthesia. Baseline cognitive performance will be assessed using the Montreal Cognitive Assessment. Induction of GA will be performed using 300ml.h-1 of 1% propofol until DA (Defined as a Patient State Index (PSI) \< 30) is observed. The primary endpoint will be the Ce propofol at which deep anesthesia (CeDA) occurs as calculated by the Eleveld PK/PD model for propofol. Preoperative raw EEG waveforms from the SedLine monitor will be used to extract statistical, entropic, and spectral features. High-density EEG (128 channels) will also be recorded in a subsample of 40 patients to extract brain functional connectivity features. These features will be entered in a generalized additive model to predict CeDA. We will also develop and validate a machine learning algorithm to predict CeDA based on these features.
Significance/Importance: The results of this study could provide a better understanding of the determinants of the inter-individual variability observed in the pharmacodynamic effect of anesthetic agents. Moreover, the prediction of CeDA may help clinicians in setting the right and safe target in target-controlled infusion of propofol during induction of general anesthesia and further limit the occurrence of deep anesthesia during surgery. Finally, the knowledge of the link between EEG characteristics, sensitivity to anesthetics and cognitive performance may lead to more personalized anesthesia delivery.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Cognitive testing
Preoperative cognitive battery test
electroencephalogram
Preoperative 24 channel EEG
High density electroencephalogram
preoperative 128-channel electroencephalogram
General anesthesia
induction of general anesthesia using propofol 1%
Eligibility Criteria
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Inclusion Criteria
* Adults
Exclusion Criteria
* Known allergy or intolerance or other medical condition that precludes the use of prescribed general anesthesia protocol for this study,
* Patients requiring rapid sequence induction,
* Anticipated or known difficult intubation patient,
* Anticipated or known difficult ventilation patient,
* Body mass index ≥ 35 kg.m-2.
18 Years
ALL
No
Sponsors
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Centre Integre Universitaire de Sante et Services Sociaux du Nord de l'ile de Montreal
OTHER
Ciusss de L'Est de l'Île de Montréal
OTHER
Responsible Party
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Principal Investigators
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Louis Morisson, MD, MSc
Role: PRINCIPAL_INVESTIGATOR
CIUSSS de l'Est de l'Ile de Montréal
Locations
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Hopital Maisonneuve-Rosemont
Montreal, Quebec, Canada
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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2024-3615
Identifier Type: -
Identifier Source: org_study_id
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