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靶控输注与新的药代动力学模型的未来。

The future of target-controlled infusion and new pharmacokinetic models.

作者信息

Absalom Anthony R, Schnider Thomas W

机构信息

Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Kantonsspital St. Gallen, St. Gallen, Switzerland.

出版信息

Curr Opin Anaesthesiol. 2025 May 26;38(4):375-81. doi: 10.1097/ACO.0000000000001529.

Abstract

PURPOSE OF REVIEW

To summarize recent developments in the understanding of the pharmacology of the hypnotic and opioid drugs, with relevance to target-controlled infusions and newer pharmacokinetic models.

RECENT FINDINGS

General-purpose models have been developed for propofol, remifentanil, and dexmedetomidine, suitable for use in a wide variety of patients, but still not universally applicable. A validation study of the predictive performance of the Eleveld propofol model showed reasonable performance in children, healthy adults, and obese adults but poorer performance in elderly patients. Observational studies show that complications during total intravenous anesthesia often arise from omission of basic safety checks and inadequate knowledge, rather than model misspecification. Specifically, there is a lack of understanding of the influence of the clinical situation on the pharmacodynamics of hypnotic drugs. Artificial intelligence is likely to produce useful drug infusion rate advisory systems, or even closed-loop control systems that could potentially provide better patient-individualized titration of anesthetic drugs.

SUMMARY

Further efforts to develop new models are unlikely to be clinically beneficial. Efforts should rather be made to ensure better education and a better appreciation of variability in pharmacodynamics and the need for better ways of tailoring drug doses to individual patient needs.

摘要

综述目的

总结在催眠药和阿片类药物药理学认识方面的最新进展,及其与靶控输注和新的药代动力学模型的相关性。

最新发现

已开发出适用于丙泊酚、瑞芬太尼和右美托咪定的通用模型,适用于多种患者,但仍未普遍适用。一项对Eleveld丙泊酚模型预测性能的验证研究表明,该模型在儿童、健康成年人和肥胖成年人中表现合理,但在老年患者中表现较差。观察性研究表明,全静脉麻醉期间的并发症往往源于基本安全检查的遗漏和知识不足,而非模型设定错误。具体而言,人们对临床情况对催眠药物药效学的影响缺乏了解。人工智能可能会产生有用的药物输注速率咨询系统,甚至可能提供更好的患者个体化麻醉药物滴定的闭环控制系统。

总结

进一步开发新模型不太可能在临床上带来益处。相反,应努力确保更好的教育,并更好地认识药效学的变异性以及根据个体患者需求调整药物剂量的更好方法的必要性。

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