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吸入麻醉的药代动力学特殊方面。

Special aspects of pharmacokinetics of inhalation anesthesia.

作者信息

Hendrickx J F A, De Wolf A

机构信息

Department of Anesthesiology and Intensive Care, OLV Hospital, Moorselbaan 164, 9300, Aalst, Belgium.

出版信息

Handb Exp Pharmacol. 2008(182):159-86. doi: 10.1007/978-3-540-74806-9_8.

Abstract

Recent interest in the use of low-flow or closed circuit anesthesia has rekindled interest in the pharmacokinetics of inhaled anesthetics. The kinetic properties of inhaled anesthetics are most often modeled by physiologic models because of the abundant information that is available on tissue solubilities and organ perfusion. These models are intuitively attractive because they can be easily understood in terms of the underlying anatomy and physiology. The use of classical compartment modeling, on the other hand, allows modeling of data that are routinely available to the anesthesiologist, and eliminates the need to account for every possible confounding factor at each step of the partial pressure cascade of potent inhaled agents. Concepts used to describe IV kinetics can readily be applied to inhaled agents (e.g., context-sensitive half-time and effect site concentrations). The interpretation of the F(A)/F(I) vs time curve is expanded by reintroducing the concept of the general anesthetic equation-the focus is shifted from "how F(A) approaches F(I)" to "what combination of delivered concentration and fresh gas flow (FGF) can be used to attain the desired F(A)." When the desired F(A) is maintained with a FGF that is lower than minute ventilation, rebreathing causes a discrepancy between the concentration delivered by the anesthesia machine (=selected by the anesthesiologist on the vaporizer, F(D)) and that inspired by the patient. This F(D)-F(I) discrepancy may be perceived as "lack of control" and has been the rationale to use a high FGF to ensure the delivered matched the inspired concentration. Also, with low FGF there is larger variability in F(D) because of interpatient variability in uptake. The F(D)-F(I) discrepancy increases with lower FGF because of more rebreathing, and as a consequence the uptake pattern seems to be more reflected in the F(D) required to keep F(A) constant. The clinical implication for the anesthesiologist is that with high FGF few F(D) adjustments have to be made, while with a low FGF F(D) has to be adjusted according to a pattern that follows the decreasing uptake pattern in the body. The ability to model and predict the uptake pattern of the individual patient and the resulting kinetics in a circle system could therefore help guide the anesthesiologist in the use of low-flow anesthesia with conventional anesthesia machines. Several authors have developed model-based low FGF administration schedules, but biologic variability limits the performance of any model, and therefore end-expired gas analysis is obligatory. Because some fine-tuning based on end-expired gas analysis will always be needed, some clinicians may not be inclined to use very low FGF in a busy operating room, considering the perceived increase in complexity. This practice may be facilitated by the development of anesthesia machines that use closed circuit anesthesia (CCA) with end-expired feedback control--they "black box" these issues (see Chapter 21). In this chapter, we first explore how and why the kinetic properties of intravenous and inhaled anesthetics have been modeled differently. Next, we will review the method most commonly used to describe the kinetics of inhaled agents, the F(A)/F(I) vs time curve that describes how the alveolar (F(A)) approaches the inspired (F(I)) fraction (in the gas phase, either "fraction," "concentration," or "partial pressure" can be used). Finally, we will reintroduce the concept of the general anesthetic equation to explain why the use of low-flow or closed circuit anesthesia has rekindled interest in the modeling of pharmacokinetics of inhaled anesthetics. Clinical applications of some of these models are reviewed. A basic understanding of the circle system is required, and will be provided in the introduction.

摘要

最近对低流量或闭环麻醉的关注重新点燃了人们对吸入麻醉药药代动力学的兴趣。由于在组织溶解度和器官灌注方面有丰富的信息,吸入麻醉药的动力学特性最常通过生理模型来模拟。这些模型直观上很有吸引力,因为从基础解剖学和生理学角度很容易理解。另一方面,经典房室模型的使用允许对麻醉医生常规可获得的数据进行建模,并且无需在强效吸入药物分压级联的每个步骤中考虑每一个可能的混杂因素。用于描述静脉内动力学的概念可以很容易地应用于吸入药物(例如,上下文敏感半衰期和效应部位浓度)。通过重新引入全身麻醉方程的概念,对F(A)/F(I)与时间曲线的解释得到了扩展——重点从“F(A)如何接近F(I)”转移到“可以使用何种输送浓度和新鲜气体流量(FGF)的组合来达到所需的F(A)”。当用低于分钟通气量的FGF维持所需的F(A)时,再呼吸会导致麻醉机输送的浓度(=麻醉医生在蒸发器上选择的,F(D))与患者吸入的浓度之间出现差异。这种F(D)-F(I)差异可能被视为“缺乏控制”,这也是使用高FGF以确保输送浓度与吸入浓度匹配的理论依据。此外,由于患者间摄取的变异性,低FGF时F(D)的变异性更大。由于更多的再呼吸,F(D)-F(I)差异随FGF降低而增加,因此摄取模式似乎更多地反映在维持F(A)恒定时所需的F(D)中。对麻醉医生的临床意义在于,高FGF时几乎无需调整F(D),而低FGF时必须根据体内摄取降低模式调整F(D)。因此,能够对个体患者的摄取模式及其在循环系统中的药代动力学进行建模和预测,有助于指导麻醉医生在使用传统麻醉机进行低流量麻醉时的操作。几位作者已经制定了基于模型的低FGF给药方案,但生物变异性限制了任何模型的性能,因此呼气末气体分析是必不可少的。由于总是需要基于呼气末气体分析进行一些微调,一些临床医生可能不愿意在繁忙的手术室中使用非常低的FGF,因为他们认为复杂性增加了。使用带有呼气末反馈控制的闭环麻醉(CCA)的麻醉机的开发可能会促进这种做法——它们将这些问题“黑箱化”(见第21章)。在本章中,我们首先探讨静脉内和吸入麻醉药的动力学特性为何以及如何以不同方式建模。接下来,我们将回顾描述吸入药物动力学最常用的方法,即F(A)/F(I)与时间曲线,该曲线描述了肺泡(F(A))如何接近吸入(F(I))分数(在气相中,可以使用“分数”“浓度”或“分压”)。最后,我们将重新引入全身麻醉方程的概念,以解释为什么低流量或闭环麻醉的使用重新点燃了人们对吸入麻醉药药代动力学建模的兴趣。还将回顾其中一些模型的临床应用。需要对循环系统有基本的了解,将在引言中提供。

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