全麻诱导后，麻醉和阿片类药物的剂量必须持续调整，以保持充分的麻醉深度。TI.VA算法是一种多输入/多输出算法，旨在优化全麻期间麻醉和阿片类药物浓度之间的平衡。它应用向量分析于二维矩阵，以量化麻醉深度在任何给定时刻的不足，并确定所需的药物剂量调整，以实现充分的麻醉深度。本研究旨在收集有关TI.VA算法在全i.v.麻醉患者中的性能和安全性的初步数据。该前瞻性研究纳入了9例乳腺癌患者并计划接受手术。使用丙泊酚和雷米芬太尼手动控制诱导全麻。从皮肤切口到手术切除完成，使用TI.VA算法来指导麻醉。通过分析绩效错误评估麻醉质量。双频指数全局评分(GSBIS) <50被认为是算法性能的可接受目标。所有9个手术程序均在无任何不良事件的情况下完成，并且没有患者回忆起任何术中事件。总体而言，我们分析了3417个监测点，相当于285分钟的手术时间。所有患者的GSBIS值都低于50的截断值。TI.VA算法提供了对临床麻醉的充分控制。在扩大试验范围以包括更多患者群体之前，需要开发更复杂的原型。NCT05199883.© 2023作者。

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.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 (GSBIS) <50 was considered an acceptable target for algorithm performance.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 GSBIS below the cut-off value of 50.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.NCT05199883.© 2023 The Authors.