Design and Development of Multi-modal Intelligent Anesthesia Monitoring System

NCT06317025 | Completed

• 1 other identifier: SHOUFA2022-2Z-2039
• Study Type: observational
• Target: 330
• Locations: 1 country
• Sites: 1

Brief Summary

This project integrates the characteristics of electroencephalo-graph（EEG）, cerebral oxygen, blood pressure, heart rate, etc., based on nonlinear theory and multi-modal monitoring system suitable for domestic patients, taking into neural oscillation, large sample data and machine learning theory, to develop a account changes in sedation, analgesia, cerebral hemodynamics and other factors, regardless of patient age and type of general anesthesia drugs.

Conditions

Anesthesia

Keywords

Anesthesia monitoring; Near infrared reflectance spectroscopy（NIRS）; electroencephalogram（EEG）; multimodal; Age dependent; Machine learning

Outcome Measures

Primary Outcomes (1)

• the depth of anesthesia (too deep or too shallow)

  PRST score system, combined with BIS index for comprehensive judgment

  During general anesthesia

Secondary Outcomes (2)

• EEG characteristics of loss of consciousness induced by different general anesthesia drugs

  During general anesthesia

• Characteristics of perioperative neurovascular coupling

  Perioperative

Study Arms (1)

Patients undergoing general anaesthesia who were prospectively enrolled for multimodal physiological

Monitoring depth of anaesthesia using PRST （P：pressure， T：tear，R：rate， S：sweat）score developed by Evans and bispectral index

Diagnostic Test: Multi-modal Intelligent Anesthesia Monitoring System

Interventions

Multi-modal Intelligent Anesthesia Monitoring System DIAGNOSTIC_TEST

To evaluate the sensitivity and specificity of self-developed anesthesia monitoring systems in diagnosing the depth of anesthesia (too deep or too shallow)

Patients undergoing general anaesthesia who were prospectively enrolled for multimodal physiological

Eligibility Criteria

• Age: 0 Years - 65 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients undergoing non-cardiac surgery under general anesthesia in Beijing Chaoyang Hospital, Capital Medical University

You may qualify if:

• Age: 0-65 years old
• ASA: Level I-III
• Patients undergoing non cardiac surgery under general anesthesia
• Informed consent of the patient or legal representative

You may not qualify if:

• Previous history of severe neurological disorders
• History of mental illness and related medication use
• Individuals who are unable to cooperate in completing cognitive function tests
• Severe hearing or visual impairment
• Preoperative delirium in patients
• Individuals who have experienced severe adverse reactions such as cardiac arrest and cardiopulmonary resuscitation during surgery
• Those who require neurosurgery, head and facial surgery
• Individuals who are allergic to EEG and fNIRS electrodes

Sponsors & Collaborators

• Beijing Chao Yang Hospital: lead

Study Sites (1)

Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University

Beijing, Beijing Municipality, 100020, China

Location

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 21, 2024
• First Posted: March 19, 2024
• Study Start: April 1, 2024
• Primary Completion: March 28, 2026
• Study Completion: March 28, 2026
• Last Updated: September 8, 2026

Record last verified: 2026-09

Data Sharing

• IPD Sharing: Will share
• Shared Documents: SAP
• Time Frame: Beginning after publication of the relevant study results and for a period consistent with institutional data-retention and sharing policies.
• Access Criteria: Data will be made available to qualified researchers who submit a scientifically sound proposal. Requests will be reviewed by the corresponding author and relevant institutional authorities, and access will be subject to ethics approval, institutional requirements, applicable data-protection regulations, and execution of an appropriate data-use agreement where required.

Locations

CN (1)