Machine-learning Algorithm to Differentiate Intraoperative Ketamine Dosing Based on Electroencephalographic Density Spectrum Array Analysis

Taipei Veterans General Hospital, Taiwan90 enrolled

Overview

Ketamine is widely used in the setting of multimodal general anesthesia, and the Electroencephalographic density spectral array (DSA) monitoring has been implemented in the practice of anesthesia. The purpose of this study is to investigate the dose-response EEG changes in patients during the perioperative period when ketamine is used. With the application of machine-learning algorithm, we aim to interpret the ketamine dosing precisely and accurately, based on the DSA obtained.

In this single-blinded randomized controlled trial, we enroll 90 patients undergoing major spine surgery, and candidates are divided into 3 groups: A (control group using sevoflurane only), B (sevoflurane + 3µg/kg ketamine infusion), C (sevoflurane + 6µg/kg/min ketamine infusion). Throughout the perioperative period, under standardized perioperative care, each patient will be monitored with EEG DSA. The data obtained will be utilized for machine-learning in the development of a algorithm to interpret the precise dosing of ketamine in respect of its effect on the EEG DSA. This study is also anticipated to boost the development of dose-response algorithm of other agents, promoting the advancement of the concept of "multimodal general anesthesia"

Study Type

OBSERVATIONAL

Enrollment

Conditions

Electroencephalographic Density Spectrum Array Analysis Density Spectrum Array Ketamine Multimodal General Anesthesia

Eligibility

Sex: ALLMin age: 20 YearsMax age: 80 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: 1. Patients undergoing elective spine surgery 2. Aged 20-80 years old Exclusion Criteria: 1. Pregnancy 2. Presence of major brain disorders: stroke, epilepsy, Parkinson's disease, etc. 3. Any of the following major organ disorders: 1. Chronic pulmonary disease (Clinically diagnosed severe chronic obstructive pulmonary disease or FEV1/FVC \<70% or FEV1 \<50%) 2. Heart failure (NYHA III or IV) 3. Chronic renal failure (eGFR\<60ml/min/1.73m2) 4. Ongoing sepsis or infection 5. Ongoing of history of CNS-acting medications/substances use (e.g.: sedatives, hypnotics, stimulants, etc.)

Outcomes

Primary Outcomes

Ketamine dosing based on EEG DSA

The DSA is obtained from raw EEG by fast Fourier transformation. By interpreting the DSA, we can obtain the trends and changes of power within different frequencies over time, in respect to different ketamine dosing.

Time frame: DSA EEG is placed before anesthesia starts, recorded throughout the operative procedure until emergence and patient is extubated. The saved EEG DSA data will be retrieved by the end of the day.

Machine-learning Algorithm to Differentiate Intraoperative Ketamine Dosing Based on Electroencephalographic Density Spectrum Array Analysis

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Central Contacts