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| Name | Class |
|---|---|
| University of Sao Paulo | OTHER |
| Fundação de Amparo à Pesquisa do Estado de São Paulo | OTHER_GOV |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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 |
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| 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. |
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Inclusion Criteria:
Exclusion Criteria:
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Patients undergoing surgical procedures with general anesthesia
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Bruno B Turrin, Msc | Contact | +5511998745879 | bbturrin@usp.br |
| Name | Affiliation | Role |
|---|---|---|
| Joaquim E Vieira, MD, PhD | University of Sao Paulo School of Medicine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hospital das ClÃnicas - Faculdade de Medicina da Universidade de Sao Paulo | São Paulo | 01246-903 | Brazil |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26516801 | Background | 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. | |
| Background | Karl J Åström, Björn Wittenmark. Computer-Controlled Systems: Theory and Design. Dover Books on Electrical Engineering. ISBN: 0486284042. Courier Corporation, 2013 | ||
| 17295411 |
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| ID | Term |
|---|---|
| D058926 | Intraoperative Awareness |
| ID | Term |
|---|---|
| D007431 | Intraoperative Complications |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| 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 |
| 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 |
| Result |
| Ahmad AM. Recent advances in pharmacokinetic modeling. Biopharm Drug Dispos. 2007 Apr;28(3):135-43. doi: 10.1002/bdd.540. |
| 9768800 | Result | 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. |