ArticleBJA open2023
Using the TI.VA algorithm to titrate the depth of general anaesthesia: a first-in-humans study.
Article in BJA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05199883 (The TI.VA Algorithm), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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.
Who cites it
0 citing papers in PubMed, 2 citations in OpenAlex.
No citing paper in PubMed yet.
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The dose of anaesthetic and opioid drugs must be continuously adjusted after the induction of general anaesthesia to maintain an adequate depth of anaesthesia. The TI.VA algorithm is a multiple-input/multiple-output algorithm designed to optimise the balance between anaesthetic and opioid concentrations during general anaesthesia. It applies vector analysis to a two-dimensional matrix to quantify any inadequacy of the depth of anaesthesia at any given moment and determine any drug dose adjustments required to achieve an adequate depth of anaesthesia. This study aimed to capture preliminary data on the performance and safety of the TI.VA algorithm during total i.v. anaesthesia in patients. Methods: This prospective study enrolled nine patients with breast cancer scheduled to undergo surgery. General anaesthesia was induced under manual control using propofol and remifentanil. Anaesthesia was guided using the TI.VA algorithm from skin incision until surgical resection was completed. The quality of anaesthesia was assessed through an analysis of performance errors. A bispectral index global score (GS Results: All nine procedures were completed without any adverse events and none of the patients recalled any intraoperative event. Overall, we analysed 3417 monitoring points corresponding to 285 min of surgery. All patients presented a GS Conclusions: The TI.VA algorithm provides adequate control of clinical anaesthesia. A more sophisticated prototype needs to be developed before the trial is expanded to include larger patient populations. Clinical trial registration: NCT05199883.
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