Decision Support System for Anesthetists

NCT ID: NCT04079036

Last Updated: 2019-09-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

360 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-10-31

Study Completion Date

2020-01-31

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Anesthesia

Study Design

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Observational Model Type

CASE_CROSSOVER

Study Time Perspective

PROSPECTIVE

Study Groups

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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

No interventions assigned to this group

Healthy Weight Adult Male

Male patients with Healthy Weight BMI classification and more than 20 years old

No interventions assigned to this group

Overweight Adult Male

Male patients with OverWeight or Obese BMI classification and more than 20 years old

No interventions assigned to this group

Underweight Adult Female

Female patients with Underweight BMI classification and more than 20 years old

No interventions assigned to this group

Healthy Weight Adult Female

Female patients with Healthy Weight BMI classification and more than 20 years old

No interventions assigned to this group

Overweight Adult Female

Female patients with Overweight or Obese BMI classification and more than 20 years old

No interventions assigned to this group

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

No interventions assigned to this group

Healthy Weight children Male

Male patients less than 20 year old, and with Healthy Weight BMI classification

No interventions assigned to this group

Overweight children Male

Male patients less than 20 year old, and with Overweight or Obese BMI classification

No interventions assigned to this group

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

No interventions assigned to this group

Healthy Weight children Female

Female patients less than 20 year old, and with Overweight or Obese BMI classification

No interventions assigned to this group

Overweight children Female

Female patients less than 20 year old, and with Overweight or Obese BMI classification

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Patients under general anesthesia

Exclusion Criteria

* Cerebral Palsy patients
Minimum Eligible Age

1 Month

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of Sao Paulo

OTHER

Sponsor Role collaborator

Fundação de Amparo à Pesquisa do Estado de São Paulo

OTHER_GOV

Sponsor Role collaborator

University of Sao Paulo General Hospital

OTHER

Sponsor Role lead

Responsible Party

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Joaquim Edson Vieira

Phd Anesthesiology Professor and Principal invesigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Joaquim E Vieira, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Sao Paulo School of Medicine

Locations

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Hospital das Clínicas - Faculdade de Medicina da Universidade de Sao Paulo

São Paulo, , Brazil

Site Status

Countries

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Brazil

Central Contacts

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Bruno B Turrin, Msc

Role: CONTACT

+5511998745879

References

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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.

Reference Type BACKGROUND
PMID: 26516801 (View on PubMed)

Karl J Åström, Björn Wittenmark. Computer-Controlled Systems: Theory and Design. Dover Books on Electrical Engineering. ISBN: 0486284042. Courier Corporation, 2013

Reference Type BACKGROUND

Ahmad AM. Recent advances in pharmacokinetic modeling. Biopharm Drug Dispos. 2007 Apr;28(3):135-43. doi: 10.1002/bdd.540.

Reference Type RESULT
PMID: 17295411 (View on PubMed)

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.

Reference Type RESULT
PMID: 9768800 (View on PubMed)

Other Identifiers

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CAAE 03424918.6.0000.0068

Identifier Type: -

Identifier Source: org_study_id

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