Clinical trial NCT05199883: The TI.VA Algorithm: A First-in-Humans Test.
Official title: The TI.VA Algorithm: Vector Analysis Applied to a Decision-Making Matrix to Model the Reactive Control Strategy During General Anesthesia: a First-in-Humans Test.
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Anesthesia
Keywords: open feedback control system
Balanced Anaesthesia
Total Intravenous Anaesthesia
Lead sponsor: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Sponsor class: OTHER
First posted: 2022-01-20
Enrollment: 5
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: This is a prospective study involving a series of consecutive patients.
Primary purpose: OTHER

Brief summary: The TI.VA algorithm is a new method to titrate the anesthetic drug concentrations whenever the planned level of anesthesia results to be not appropriate to blunt the patient's reaction to surgical stimulation.

TI.VA is a multiple inputs/multiple outputs algorithm. The control variables are the bispectral index (BIS) and the mean arterial pressure (MAP) combined in a decision-making matrix. The optimal range for the two control variables (BIS: 540-60 and MAP: 65-75 mmHg) identified the Optimal Anesthesia Zone (OAZ) at the center of the matrix. Any time one or both control variables escape from the PAZ, the algorithm proposes an intervention on the hypnotic and/or opioid levels (algorithm outputs).

A First-in-Humans study was designed to capture preliminary data on the safety and performance of the TI.VA algorithm.

Detailed description: The TI.VA algorithm is a new method to titrate the anesthetic drug concentrations whenever the planned level of anesthesia results to be not appropriate to blunt the patient's reaction to surgical stimulation.

TI.VA is a multiple inputs/multiple outputs algorithm. The control variables are the bispectral index (BIS) and the mean arterial pressure (MAP) combined in a decision-making matrix (DMM). The optimal range for the two control variables (BIS: 540-60 and MAP: 65-75 mmHg) identified the Optimal Anesthesia Zone (OAZ) at the center of the matrix. Any time one or both control variables escape from the OAZ, the algorithm quantifies the inadequacy of anesthesia level through a vector connecting the patient's current position on the DMM to the central point identified by the coordinates BIS= 50 and MAP = 75mmHg. Thereafter, the analysis of the vector main components allows the generation of two coefficients that are used to set out a balanced intervention on the hypnotic and opioid levels (algorithm outputs).

A First-in-Humans study was designed to capture preliminary data on the safety and performance of the TI.VA algorithm This is a prospective study involving a single cohort of patients without major comorbidity and candidate for minor superficial surgery. All patients received Propofol and Remifentanil administered by TCI systems as part of Total Intravenous Anaesthesia.

The algorithm was tested during maintenance of anesthesia defined as the period between skin incision and completion of surgical resection. In this step of the procedure, the titration strategy for anesthetic drug concentrations was suggested by TI.VA algorithm.

Data was collected automatically using dedicated software.

Eligibility criteria: The inclusion criteria were: :

* age 18-65 years at the time of recruitment.
* candidates for curative surgery for breast cancer.
* American Society of Anaesthesiologists (ASA) status I/II.

The exclusion criteria were:

* ASA status \> II.
* counter-indications for use of the drugs employed in this protocol.
* pregnancy or lactation.
* incapacity to understand the study explanation and sign the informed consent form.

These criteria were selected according to the risk mitigation strategy described in the protocol.

Primary outcomes:
measure: Adverse Events
timeFrame: during the surgical procedure intervention
Secondary outcomes:
measure: Stability of the Control Variables
timeFrame: during the surgical procedure intervention
measure: Performance Error analysis
timeFrame: during the surgical procedure intervention
Other outcomes:
Locations:
city: Milano
country: Italy
facility: Fondazione IRCCS Istituto Nazionale dei Tumori
Study officials:
affiliation: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
name: Emiliano Tognoli, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Brown EN, Lydic R, Schiff ND. General anesthesia, sleep, and coma. N Engl J Med. 2010 Dec 30;363(27):2638-50. doi: 10.1056/NEJMra0808281. No abstract available.
citation: A.R. Absalom, MMRF Struys. Overview on Target Controlled Infusion and Total Intravenous Anaesthesia. 2Ed. Gent, Academia Press 2019.
citation: Absalom AR, De Keyser R, Struys MM. Closed loop anesthesia: are we getting close to finding the holy grail? Anesth Analg. 2011 Mar;112(3):516-8. doi: 10.1213/ANE.0b013e318203f5ad. No abstract available.
citation: Varvel JR, Donoho DL, Shafer SL. Measuring the predictive performance of computer-controlled infusion pumps. J Pharmacokinet Biopharm. 1992 Feb;20(1):63-94. doi: 10.1007/BF01143186.