Machine Learning-Based Model for Individualized Drug Dose Prediction for Propofol

A Machine Learning-Based Model for Individualized Drug Dose Prediction for Propofol-Induced Loss of Consciousness in Patients

The goal of this observational study is to develop an individualized prediction model for drug dosage during propofol-induced loss of consciousness in anticipation of advances in research in this area. An appropriate delivery model to reduce perianesthesia complications in patients, especially in outpatient painless endoscopy patients. The main question it aims to answer is:

What type of machine learning algorithm should be used to build a drug dose prediction model that is suitable for patient awareness of anesthesia induction? 1000 participants routinely with propofol induced anesthesia loss of consciousness included in this study.

Study Overview

• Status: Completed
• Conditions: Anesthesiology Management; Anesthesiology
• Intervention / Treatment: Drug: Anesthesia induction with propofol

Detailed Description

Study Methods:

（1）Case selection： Patients requiring elective surgical treatment in the Cardiovascular and Cerebrovascular Disease Hospital of General Hospital of Ningxia Medical University.

Inclusion criteria: Patients were gender-neutral and aged ≥18 years.

（2) Clinical study protocol： Patients were admitted to the operating room to establish intravenous access, connected to ECG monitoring, EEG monitoring, 4L/min mask oxygenation, and real-time video recording of the entire anesthesia induction process using a video recorder for postoperative integration of various data. Propofol was pumped in at 100 mg/kg/h, and the anesthesiologist with propofol assessed the degree of sedation of the patient until the patient was deeply sedated and the MOAA/S score was 0, and the pumping of propofol was stopped.

(3) Observation indicators： Demographic information and general preoperative data were collected, including patients' gender, age, weight, height, ASA classification, body mass index (BMI), and past medical history (hypertension, coronary heart disease, diabetes mellitus, respiratory disease, stroke).

Systolic blood pressure, diastolic blood pressure, mean arterial pressure, heart rate, finger pulse oximetry (SPO2), electroencephalogram waveforms, the dosage of propofol administered from the start of anesthesia induction to MOAA/S = 0, and the time of administration of propofol were recorded for all the basic and extended monitoring parameters, respectively, after the patient was admitted to the operating room and at the time of the 0 score of the MOAA/S score.

(4) Evaluation methods of each item Depth of anesthesia assessment: MOAA/S depth of sedation was used for assessment, and MOAA/S score of 4-5 was classified as mild sedation, which indicated that the response to calling names in normal tone was sensitive or slow; 2-3 was classified as moderate sedation, which indicated that there was a response to calling names loudly or repeatedly, or there was a response to slight pushing and vibration; ≤1 was classified as deep sedation, which indicated that there was a response to pain stimulation; 0 was classified as general anesthesia, which indicated that there was a response to pain stimulation; 0 was classified as general anesthesia, which indicated that there was a response to pain stimulation. ≤1 is classified as deep sedation, indicating a response to painful stimuli; 0 is classified as general anesthesia, indicating no response to painful stimuli.

EEG feature extraction: use python MNE (https://mne.tools/stable/index.html) module package for analysis, MNE can read most common physiological signals in raw data format, the specific methods are as follows: ① Data extraction: import data → electrode positioning → reject useless electrodes → re-reference → filter → drop sampling rate → run ICA → batch processing → segmentation and baseline correction → interpolation of bad conductance and rejection of bad conductance → removal of noise components → rejection of bad segments; ② Data division: the data of the required EEG monitoring points are divided to include wakefulness and sedation; ③ Feature extraction: time domain, amplitude square root value, kurtosis, skewness, burst suppression rate/minute, frequency domain, and entropy index are obtained by Fourier transform.

(5) Proposed machine learning algorithm: regression analysis is a predictive modeling technique that works from a set of data to determine quantitative relational equations between certain variables, statistically test these relational equations between the variables, and identify the variables that have a significant effect from among the multiple variables that affect a particular variable.

• Study Type: Observational
• Enrollment (Actual): 1200

Contacts and Locations

Study Locations

• China
  • Ningxia
    • Yinchuan, Ningxia, China, 750004
      • General Hospital of Ningxia Medical University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Inpatients requiring elective surgery or outpatient painless endoscopic surgery； Induction of anesthesia with propofol

Description

Inclusion Criteria:

• Inpatients requiring elective surgery or outpatient painless endoscopic surgery； Induction of anesthesia with propofol； Age≥18 years old； ASA classifications I-III

Exclusion Criteria:

• Propofol allergy； Contraindication to anesthesia; Declined to participate in the study

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Drug dosage of propofol for inducing loss of consciousness in patients	Propofol was pumped at 100 mg/kg/h. The anesthesiologist assessed the patient's sedation level with the MOAA/S scale until the patient was deeply sedated and the MOAA/S score was less than or equal to 1, and pumping of propofol was stopped. Propofol Continuous Pumping Volume Recorded(mg). Record propofol pumping duration.	through study completion, an average of six months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Relevant factors that can influence the intravenous dose of propofol	Demographic information and general preoperative data were collected, including the patient's sex, age, weight, height, ASA classification, body mass index (BMI), and past medical history (hypertension, coronary artery disease, diabetes mellitus, respiratory disease, stroke).	through study completion, an average of six months
Patient's peri-anesthetic vital signs	Systolic blood pressure, diastolic blood pressure, mean arterial pressure, heart rate, and finger pulse oximetry (SPO2) were recorded after the patient was admitted to the operating room and at a MOAA/S score of 0, respectively.	through study completion, an average of six months
Characteristics of the patient's perianesthesia electroencephalogram	EEG waveforms were recorded during the patient's perianesthesia period using an EEG monitor to mark the EEG characteristics during wakefulness and MOAA/S less than or equal to 1.	through study completion, an average of six months

Collaborators and Investigators

• Sponsor: General Hospital of Ningxia Medical University

Study record dates

Study Major Dates

• Study Start (Actual): November 20, 2024
• Primary Completion (Actual): March 30, 2025
• Study Completion (Actual): July 30, 2025

Study Registration Dates

• First Submitted: November 18, 2024
• First Submitted That Met QC Criteria: November 21, 2024
• First Posted (Actual): November 25, 2024

Study Record Updates

• Last Update Posted (Actual): August 19, 2025
• Last Update Submitted That Met QC Criteria: August 16, 2025
• Last Verified: November 1, 2024

More Information

Terms related to this study

• Keywords: machine learning; propofol-induced loss of consciousness in patients; predict model
• Additional Relevant MeSH Terms: Neurologic Manifestations; Nervous System Diseases; Neurobehavioral Manifestations; Consciousness Disorders; Unconsciousness; Physiological Effects of Drugs; Central Nervous System Depressants; Hypnotics and Sedatives; Anesthetics, Intravenous; Anesthetics, General; Anesthetics; Propofol
• Other Study ID Numbers: Huiwen Zhang-2024-11

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No