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丙泊酚的靶控输注:近期结果的系统评价

Target-Controlled Infusion of Propofol: A Systematic Review of Recent Results.

作者信息

Šafránková Pavla, Bruthans Jan

机构信息

Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, nám. Sítná 3105, Kladno, CZ-272 01, Czech Republic.

Department of Anesthesiology and Intensive Care, General University Hospital, U Nemocnice 499/2, Prague, CZ-128 08, Czech Republic.

出版信息

J Med Syst. 2025 Apr 28;49(1):54. doi: 10.1007/s10916-025-02187-y.

Abstract

This study presents a systematic review conducted according to the PRISMA 2020 guidelines, evaluating pharmacokinetic-pharmacodynamic (PK-PD) models for target-controlled infusion (TCI) of propofol. A structured search was performed across PubMed, Summon, Google Scholar, Web of Science, and Scopus, identifying 427 sources, of which 17 met the inclusion criteria. The analysis revealed that nine studies compared existing models, six focused on the development of new PK-PD models, and two explored broader implications of TCI in anesthesia. Comparative studies indicate that while the Eleveld model generally offers superior predictive accuracy, it does not consistently outperform the Marsh and Schnider models across all populations. The Schnider model demonstrated better bias control in elderly patients, while the Eleveld model improved drug clearance estimation in obese patients. However, inconsistencies remain in predicting brain concentrations of propofol. Newly proposed models introduce adaptive dosing strategies, incorporating allometric scaling, lean body weight, and machine learning techniques, yet require further external validation. The results highlight ongoing challenges in achieving universal applicability of TCI models, underscoring the need for future research in refining precision dosing and personalized anesthesia management.

摘要

本研究呈现了一项根据PRISMA 2020指南进行的系统评价,评估用于丙泊酚靶控输注(TCI)的药代动力学-药效学(PK-PD)模型。在PubMed、Summon、谷歌学术、科学网和Scopus数据库中进行了结构化检索,共识别出427个来源,其中17个符合纳入标准。分析表明,9项研究比较了现有模型,6项专注于新PK-PD模型的开发,2项探讨了TCI在麻醉中的更广泛意义。比较研究表明,虽然Eleveld模型通常具有更高的预测准确性,但在所有人群中它并不总是优于Marsh模型和Schnider模型。Schnider模型在老年患者中表现出更好的偏差控制,而Eleveld模型在肥胖患者中改善了药物清除率估计。然而,在预测丙泊酚的脑浓度方面仍存在不一致性。新提出的模型引入了自适应给药策略,纳入了异速生长标度、瘦体重和机器学习技术,但仍需要进一步的外部验证。结果突出了TCI模型实现普遍适用性方面持续存在的挑战,强调了未来在优化精准给药和个性化麻醉管理方面进行研究的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f27/12034585/f285f95a20ad/10916_2025_2187_Fig1_HTML.jpg

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