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The TI.VA Algorithm: A First-in-Humans Test.

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.

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05199883
Acronym
TIVAly
Enrollment
5
Registered
2022-01-20
Start date
2020-12-01
Completion date
2021-01-31
Last updated
2022-02-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Anesthesia

Keywords

open feedback control system, Balanced Anaesthesia, Total Intravenous Anaesthesia

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.

Interventions

OTHERTI.VA algorithm: decision support system

TI.VA algorithm uses BIS and MAP values as control variables to suggest the intervention on propofol and remifentanil levels.

Sponsors

Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE

Intervention model description

This is a prospective study involving a series of consecutive patients.

Eligibility

Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No

Inclusion 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.

Design outcomes

Primary

MeasureTime frameDescription
Adverse Eventsduring the surgical procedure interventionAn adverse event is defined as any untoward medical occurrence in the study period. Intra-operative adverse events were reported using the institutional incident reporting system. Data was collected in the time between skin incision and the completion of surgical resection.

Secondary

MeasureTime frameDescription
Stability of the Control Variablesduring the surgical procedure interventionTo characterize the patient's repose to surgery, the TI.VA algorithm uses a Decision-Making Matrix drawn by crossing BIS (Min-max: 0-100, optimal range 40-60 ) and Mean Arterial Pressure (Min-max: 0-150mmHg. Optimal range 65-75mmHg). The Optimal anesthesia zone is defined as the area of the Decision-Making Matrix identify by the optimal range for the two control variables (BIS and MAP). The stability of the control variables during anesthesia was quantified by the percentage of monitoring points registered in the Optimal Anaesthesia Zone during anesthesia. A monitoring point is understood as a value of BIS and MAP recorded at the same time. The system records a monitoring point every 5 seconds. Data was collected in the time between skin incision and the completion of surgical resection.
Performance Error analysisduring the surgical procedure interventionThe performance of the algorithm was assessed using the performance error (PE), median PE (MDPE), median absolute PE (MDAPE), and wobble according to the method of Performance Error. Data was collected in the time between skin incision and the completion of surgical resection.

Countries

Italy

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 11, 2026