Ignite Creation Date:
2024-05-06 @ 8:20 PM
Last Modification Date:
2024-10-26 @ 3:25 PM
Study NCT ID:
NCT06346158
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-07-05
First Post:
2024-03-08
Brief Title:
Prediction of Propofol Effect-Site Concentration Associated With Deep Anesthesia
Sponsor:
Ciusss de LEst de lÎle de Montréal
Organization:
Ciusss de LEst de lÎle de Montréal
Study Overview
Official Title:
Prediction of Propofol Effect-Site Concentration Associated With Deep Anesthesia During Induction of General Anesthesia Based on Electroencephalographic Features a Prospective Observational Study
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
PRESCOD-AI
Brief Summary:
The goal of this observational study is to explore the variability of the concentration at the effect site Ce of propofol to reach deep anesthesia DA during induction of general anesthesia in adults
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
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
Detailed Description:
Propofol is the most widely used anesthetic to induce general anesthesia GA However as opposed to volatile anesthesia propofol concentration monitoring is not directly available in humans Thus the use of a pharmacokineticpharmacodynamic PKPD model in target-controlled infusion TCI is recommended During infusion the concentration at effect-site Ce is assumed to correlate with the level of hypnosis However There is a large variability in propofol requirements in common practice The variability in propofol requirements is attributed to demographic factors genetic polymorphism procedure-related changes and individual sensitivity Previous studies have shown that EEG characteristics change with age and cognitive status
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 300mlh-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 PKPD 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
SignificanceImportance 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
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 300mlh-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 PKPD 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
SignificanceImportance 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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
True
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
None