Nociception

Rapid sequence induction (RSI) is a standard anesthesia technique used in patients at risk of aspiration. Although tracheal intubation following RSI is a frequent and painful procedure, no study has yet evaluated nociception using the Analgesia Nociception Index (ANI) during this procedure. This monocentric prospective observational study aims to describe the impact of RSI on pain measured by ANI, and to explore early complications (desaturation, hypotension, regurgitation) and factors associated with pain and complications. 150 patients undergoing RSI in the visceral surgery operating room at CHPG Monaco will be analyzed.

The primary objective of the SEASCAPE project is to design, develop, and to apply a clinical implementation tool of a machine learning (ML) and artificial intelligence (AI)-based co-pilot system for the real-time monitoring and control of nociception during general anesthesia (GA). The ultimate clinical purpose is to optimize individualized pain management by achieving precise titration of intravenous opioids (specifically remifentanil), thereby minimizing the incidence of over- and under-dosing. This optimization is projected to enhance patient outcomes, reduce opioid-related complications, and improve overall cost-effectiveness of anesthetic procedures. The main scientific question guiding this work is: Can a novel algorithm be generated and validated to provide superior analytical precision for analgesic management by reliably differentiating genuine nociceptive responses from confounding physiological variables-such as inadequate neuromuscular blockade or changes in depth of anesthesia-thereby significantly improving the clinical decision-making framework for intraoperative nociception control? This project addresses the recognized challenge in anesthesiology: defining an objective measure to quantify nociception and antinociception during GA. Study Population: Patients scheduled for elective surgical procedures requiring general anesthesia (GA). Existing Intervention: The standard anesthetic regimen includes continuous intravenous infusion of the remifentanil for intraoperative analgesia, typically governed by a Target Controlled Infusion (TCI) system utilizing a pharmacokinetic/pharmacodynamic (PK/PD) model (Eleveld TCI model). Project Focus: The research seeks to improve the accuracy and efficacy of this existing analgesic strategy by integrating a multivariate patient data stream with the newly developed SEASCAPE co-pilot AI. This aims to refine the remifentanil dose predictions beyond the current TCI model's capabilities, personalized system.

Nociception is the encoding and processing of noxious stimulation and is considered an objective indicator for monitoring pain. Currently, a new clinically-applied medical-engineering integrated monitoring device for noxious stimulation response has emerged. Its fundamental principle is based on the monitoring of electroencephalographic (EEG) activity, incorporating two monitoring parameters: the quantitative consciousness (qCON) index and the quantitative nociceptive (qNOX) index. This device enables more precise monitoring of anesthesia depth, quantification of patients' anesthesia analgesia and stress levels, and reliable monitoring of responses to noxious stimulation. During tracheal intubation for general anesthesia, when the qCON value falls within the range of 40 to 60 and the qNOX value is between 30 and 50, it indicates that the patient is in an appropriate state of sedation and analgesia. However, there is currently no universally acknowledged standard for the optimal qNOX reference range during conscious sedation endoscopy. Therefore, this study utilizes the noxious stimulation response index (qNOX) to monitor noxious stimulation during the procedure, aiming to identify the best timing for inserting the endoscope during conscious sedation endoscopy and explore the appropriate range of qNOX for this purpose.

Nociception is the encoding and processing of noxious stimulation and is considered an objective indicator for monitoring pain. Currently, a new clinically-applied medical-engineering integrated monitoring device for noxious stimulation response has emerged. Its fundamental principle is based on the monitoring of electroencephalographic (EEG) activity, incorporating two monitoring parameters: the quantitative consciousness (qCON) index and the quantitative nociceptive (qNOX) index. However, in the context of sedation for gastrointestinal endoscopy, how the dynamic changes of the quantitative consciousness index (qCON) and the quantitative nociception index (qNOX) reflect the depth of sedation and nociceptive response remains unclear. Safe and effective sedation monitoring includes both direct visual monitoring and physiological monitoring, that is, monitoring the patient's hemodynamics and depth of sedation. This study utilizes qCON and qNOX monitoring to assess the sedation and analgesic states of patients undergoing painless gastroenterological endoscopy. By combining visual assessment (cough reflex, respiratory depression, and limb movement) with clinical physiological monitoring (vital signs monitoring and pulse oximetry), the aim is to explore the optimal sedation range for gastrointestinal endoscopy under sedation, providing new anesthesia monitoring tools for clinical use.