Decision Support System for Anesthetists (Serenity)

Decision Support System for Anesthetists for In-room Monitoring of the Level of Consciousness, Neuro-muscular Blocking and Nociception Employing Data Fusion and Artificial Intelligence

The balanced anesthesia process contains three main parts: the control of hypnosis, analgesia, and neuromuscular blockade. For the induction phase, the anesthesiologist performs protocols based on prior planning specific to each patient and usually performs these controls by monitoring the classic vital signs and other clinical signs for the maintenance phase.

In a way, this professional is the controller in a control system that acts on the plant (the patient) through the infusion of hypnotic drugs, analgesics and neuromuscular blockers. In addition, the anesthesiologist estimates the state of consciousness, the level of analgesia and the level of neuromuscular blockage through other indirect measures, as well as a state observer.

There are different techniques for direct monitoring of these three anesthesia variables (DoA, NMB and NoL), such as BIS and Narcotrend, but all have some disadvantages, especially when the anesthesia process combines different drugs. This work proposes a new way of evaluating DoA, NMB and NoL using data fusion techniques to combine classical clinical signs with advanced EEG monitoring techniques to provide a decision support system for the anesthesiologist.

Study Overview

• Status: Unknown
• Conditions: Anesthesia

Detailed Description

The balanced anesthesia process contains three main parts: the control of hypnosis, the analgesia and neuromuscular blockade. For the induction phase, the anesthesiologist performs protocols based on prior planning specific to each patient. Normally, the anesthesiologist controls the process by monitoring the classical vital signs and other clinical most common signs during the maintenance phase. In a way, this professional is the controller in a control system that acts on the plant (the patient) through the infusion of hypnotic and analgesic drugs and neuromuscular blockers.

In addition, the anesthesiologist estimates the the level of consciousness, of nociception and the level of neuromuscular blockade through these indirect measurements, just as a state observer in a control system would do.

There are different techniques for the direct monitoring of these three variables of anesthesia (DoA, NMB and NoL), such as BIS and Narcotrend, but all of them present a few disadvantages and mis-measurements, especially when the anesthesia process combines different drugs.

This work proposes a new way of evaluating DoA, NMB and NoL, using techniques to combine classical clinical signs with advanced EEG monitoring, to provide a decision support system for the anesthesiologist.

For this, we will perform data acquisition from the equipment usually used in surgical procedures with general anesthesia, such as ECG, EEG, blood pressure, mechanical ventilation, among others.

In short, all data of the patient's vital signs during the procedure and the actions taken by the anesthesiologist and surgeons.

The data will be concentrated on a specific equipment, and will be analyzed together with the data of other patients to improve the mathematical models involved in the process.

• Study Type: Observational
• Enrollment (Anticipated): 360

Contacts and Locations

• Study Contact: Name: Bruno B Turrin, Msc; Phone Number: +5511998745879; Email: bbturrin@usp.br

Study Locations

• Brazil
  • São Paulo, Brazil, 01246-903
    • Hospital das Clínicas - Faculdade de Medicina da Universidade de Sao Paulo

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 1 month to 80 years (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Patients undergoing surgical procedures with general anesthesia

Description

Inclusion Criteria:

• Patients under general anesthesia

Exclusion Criteria:

• Cerebral Palsy patients

Study Plan

How is the study designed?

Number of groups / cohorts

12

Cohorts and Interventions

Group / Cohort
Underweight Adult Male; Male patients with Underweight BMI classification and more than 20 years old https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html
Healthy Weight Adult Male; Male patients with Healthy Weight BMI classification and more than 20 years old
Overweight Adult Male; Male patients with OverWeight or Obese BMI classification and more than 20 years old
Underweight Adult Female; Female patients with Underweight BMI classification and more than 20 years old
Healthy Weight Adult Female; Female patients with Healthy Weight BMI classification and more than 20 years old
Overweight Adult Female; Female patients with Overweight or Obese BMI classification and more than 20 years old
Underweight children Male; Male patients less than 20 year old, and with Underweight BMI classification https://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html
Healthy Weight children Male; Male patients less than 20 year old, and with Healthy Weight BMI classification
Overweight children Male; Male patients less than 20 year old, and with Overweight or Obese BMI classification
Underweight children Female; Male patients less than 20 year old, and with Underweight BMI classification https://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html
Healthy Weight children Female; Female patients less than 20 year old, and with Overweight or Obese BMI classification
Overweight children Female; Female patients less than 20 year old, and with Overweight or Obese BMI classification

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Heart Rate	HR - Heart Rate - unit: [bpm], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Arterial blood pressure	P_INV - Invasive blood pressure - unit: [mmHg], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Mean Arterial Pressure	MAP - Mean Arterial Pressure - unit: [mmHg], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Non Invasive Blood pressure	P_NINV - Non Invasive blood pressure - unit: [mmHg/mmHg], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Conscience Level	CL - Consciousnesses Level (through BIS) - unit: [u 0-100] will be stored in real time during the surgical procedure.	2 to 3 months of diferent surgical procedures
Inspired anesthetic concentration	FiAA - Inspired fraction of anesthetic agent - unit: [% of Volume], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Inspired carbon dioxide concentration	FiCO2 - CO2 inspired Fraction - unit: [% of Volume], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Inspired Nitrous Oxide concentration	FiN2O - N2O inspired Fraction - unit: [% of Volume], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Blood oxygen saturation	SpO2 - Peripheral capillary oxygen saturation - unit: [%], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Exhaled Carbon Dioxide concentration	EtCO2 - End-tidal CO2 concentration (CO2 Exhaled Fraction) - unit: [% of Volume], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Exhaled Anesthetic concentration	EtAA - Anesthetic agents Exhaled Fraction - unit: [% of Volume], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Anesthetic agent infusion rate	IR_Anes - Infusion Rate of anesthetic agent - unit: [mg/hr], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Analgesic agent infusion rate	IR_Analg - Infusion rate of Analgesic agent - unit: [mg/hr], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Neuro-muscular Block agent infusion rate	IR_NMB - Infusion rate of neuro-muscular block agent - unit: [mg/hr], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Ventilation respiratory rate	RR - Respiratory Rate - unit: [bpm], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Ventilation Tidal volume	Vt - Tidal Volume - unit: [mL], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Ventilation Minute Volume	Vm - Minute Volume - unit: [L/min], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Ventilation maximum pressure per cycle	Pmax - Maximum pressure during the inspiration cycle - unit: [cmH2O], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Ventilation Plateau pressure	Pplateau - Plateau pressure during the inspiration cycle - unit: [cmH2O], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Ventilation PEEP	PEEP - Positive end of expiration pressure - unit: [cmH2O], will be stored in real time during the surgical procedure.	2 to 3 months of different surgical procedures
Primary anesthesia Data - related to the manual infusion of drugs	Every monitored clinical variable, related to the manual infusion of drugs, will be stored in real time during the surgical procedure. Every infusion made manually by the anesthesiologist during the procedure should be recorded, always considering the total amount infused and the time it occurred.	2 to 3 months of different surgical procedures
Preoperative patient medical records - General state of the patient in ASA.	Anesthesia related preoperative information from the patient, such as prior use of opioids, ASA and METS indexes. ASA - Physical state of the patient - unit: [u] P1 to P5	2 to 3 months of different surgical procedures
Preoperative patient medical records - General state of the patient in METS.	Anesthesia related preoperative information from the patient, such as prior use of opioids, ASA and METS indexes. METS - Functional state of the patient - unit: [u]	2 to 3 months of different surgical procedures
Preoperative patient medical records - Clinical state of the patient - Age	Anesthesia related preoperative information from the patient, such as: I - Age - unit: [years]	2 to 3 months of different surgical procedures
Preoperative patient medical records - Clinical state of the patient - gender	Anesthesia related preoperative information from the patient, such as: G - Gender - unit: Male or Female	2 to 3 months of different surgical procedures
Preoperative patient medical records - Clinical state of the patient - Weight	Anesthesia related preoperative information from the patient, such as: P - Weight - unit: [Kg]	2 to 3 months of different surgical procedures
Preoperative patient medical records - Clinical state of the patient - Height	Anesthesia related preoperative information from the patient, such as: A - Height - unit: [cm]	2 to 3 months of different surgical procedures

Collaborators and Investigators

• Sponsor: University of Sao Paulo General Hospital
• Collaborators: University of Sao Paulo; Fundação de Amparo à Pesquisa do Estado de São Paulo

Publications and helpful links

General Publications

• Schnider TW, Minto CF, Struys MM, Absalom AR. The Safety of Target-Controlled Infusions. Anesth Analg. 2016 Jan;122(1):79-85. doi: 10.1213/ANE.0000000000001005.
• Karl J Åström, Björn Wittenmark. Computer-Controlled Systems: Theory and Design. Dover Books on Electrical Engineering. ISBN: 0486284042. Courier Corporation, 2013
• Ahmad AM. Recent advances in pharmacokinetic modeling. Biopharm Drug Dispos. 2007 Apr;28(3):135-43. doi: 10.1002/bdd.540.
• Iselin-Chaves IA, Flaishon R, Sebel PS, Howell S, Gan TJ, Sigl J, Ginsberg B, Glass PS. The effect of the interaction of propofol and alfentanil on recall, loss of consciousness, and the Bispectral Index. Anesth Analg. 1998 Oct;87(4):949-55. doi: 10.1097/00000539-199810000-00038.

Study record dates

Study Major Dates

• Study Start (Anticipated): October 1, 2019
• Primary Completion (Anticipated): December 1, 2019
• Study Completion (Anticipated): January 1, 2020

Study Registration Dates

• First Submitted: July 10, 2019
• First Submitted That Met QC Criteria: September 4, 2019
• First Posted (Actual): September 6, 2019

Study Record Updates

• Last Update Posted (Actual): September 6, 2019
• Last Update Submitted That Met QC Criteria: September 4, 2019
• Last Verified: September 1, 2019

More Information

Terms related to this study

• Keywords: General Anesthesia; Anesthesia Awareness; Anesthesia overdose
• Other Study ID Numbers: CAAE 03424918.6.0000.0068

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

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