Suppr超能文献

使用TI.VA算法滴定全身麻醉深度:首例人体研究。

Using the TI.VA algorithm to titrate the depth of general anaesthesia: a first-in-humans study.

作者信息

Tognoli Emiliano, Luigi Mariani

机构信息

Department of Anaesthesiology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.

Unit of Clinical Epidemiology and Trial Organisation, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.

出版信息

BJA Open. 2023 Jun 16;7:100203. doi: 10.1016/j.bjao.2023.100203. eCollection 2023 Sep.

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) <50 was considered an acceptable target for algorithm performance.

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 below the cut-off value of 50.

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.

摘要

背景

全身麻醉诱导后,必须持续调整麻醉药和阿片类药物的剂量,以维持足够的麻醉深度。TI.VA算法是一种多输入/多输出算法,旨在优化全身麻醉期间麻醉药和阿片类药物浓度之间的平衡。它将向量分析应用于二维矩阵,以量化任何给定时刻麻醉深度的不足,并确定实现足够麻醉深度所需的任何药物剂量调整。本研究旨在获取TI.VA算法在患者全静脉麻醉期间的性能和安全性的初步数据。

方法

这项前瞻性研究纳入了9例计划接受手术的乳腺癌患者。使用丙泊酚和瑞芬太尼在手动控制下诱导全身麻醉。从皮肤切开到手术切除完成,使用TI.VA算法指导麻醉。通过对性能误差的分析来评估麻醉质量。双谱指数全局评分(GS)<50被认为是算法性能的可接受目标。

结果

所有9例手术均顺利完成,无任何不良事件,所有患者均未回忆起任何术中事件。总体而言,我们分析了与285分钟手术相对应的3417个监测点。所有患者的GS均低于50的临界值。

结论

TI.VA算法可提供足够的临床麻醉控制。在试验扩大到包括更多患者群体之前,需要开发更复杂的原型。

临床试验注册

NCT05199883。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b052/10457467/b9d403b9dd09/gr1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验