Bailey J M
Department of Anesthesiology, Emory University School of Medicine, Atlanta, Georgia 30322, USA.
Anesthesiology. 1995 Nov;83(5):1095-103. doi: 10.1097/00000542-199511000-00024.
Several recent studies have analyzed the relationship between pharmacokinetic parameters and the rate of decrease in concentration after discontinuation of a continuous drug infusion. Although these studies have clarified our understanding of those aspects of pharmacokinetics most relevant to anesthesia practice, they do not directly address the issue of the duration of drug effect, which will be a function of both pharmacokinetic and pharmacodynamic variables. This paper extends these concepts by presenting a method to unify pharmacokinetics and pharmacodynamics in a measure of duration of drug effect that is applicable when the drug effect is assessed in a binary, response/no response fashion.
The parameter proposed to quantify duration of drug effect is the area under the curve expressing probability of drug effect as a function of time after the agent is discontinued. This parameter is denoted the mean effect time. It is calculated using the logistic (or Hill) equation to relate the probability of drug effect to drug concentration, which in turn can be calculated as a function of time by pharmacokinetic simulation. Mean effect times were calculated for sufentanil, alfentanil, propofol, and midazolam using the logistic equation describing recovery and by assuming that drug blood concentrations during maintenance of anesthesia were sufficient to reduce the probability of responsiveness to surgical stimulation to 10% (C90). Published pharmacokinetic and pharmacodynamic parameters were used for these calculations. These results were compared to the relevant decrement times (as defined in this paper, the time required for the concentration to decrease from C90 to the concentration at which 50% of patients are responsive and/or able to maintain adequate ventilation, denoted C50). It was assumed that C90 and C50 were independent variables.
Mean effect times for midazolam and propofol, for which the steepness parameter delta for recovery (responsiveness and adequate ventilation) is less than 4, are significantly greater than the decrement time. Mean effect times for sufentanil and alfentanil (delta = 6 and 10, respectively) are close to decrement times. The discrepancy between mean effect time and decrement time becomes greater as the duration of drug administration increases. The incorporation of pharmacokinetic variability into the calculations had little effect on the results.
Context-sensitive half-times or other decrement times have been shown to be the most useful measures of the kinetics of drug concentrations. Mean effect time may be a useful concept for understanding the recovery from drug effects.
最近的几项研究分析了药代动力学参数与持续药物输注停止后浓度下降速率之间的关系。尽管这些研究阐明了我们对药代动力学中与麻醉实践最相关方面的理解,但它们并未直接解决药物作用持续时间的问题,而药物作用持续时间将是药代动力学和药效学变量的函数。本文通过提出一种方法来扩展这些概念,该方法在以二元的、有反应/无反应方式评估药物作用时,将药代动力学和药效学统一在一个药物作用持续时间的度量中。
用于量化药物作用持续时间的参数是曲线下面积,它表示药物停止使用后药物作用概率随时间的变化。该参数称为平均效应时间。它使用逻辑(或希尔)方程计算,将药物作用概率与药物浓度相关联,而药物浓度又可以通过药代动力学模拟作为时间的函数来计算。使用描述恢复的逻辑方程并假设麻醉维持期间的药物血药浓度足以将对手术刺激的反应概率降低到10%(C90),计算了舒芬太尼、阿芬太尼、丙泊酚和咪达唑仑的平均效应时间。这些计算使用已发表的药代动力学和药效学参数。将这些结果与相关的下降时间(如本文所定义,浓度从C90下降到50%的患者有反应和/或能够维持足够通气的浓度所需的时间,称为C50)进行比较。假设C90和C50是独立变量。
咪达唑仑和丙泊酚的平均效应时间,其恢复(反应性和足够通气)的陡度参数δ小于4,显著大于下降时间。舒芬太尼和阿芬太尼的平均效应时间(分别为δ = 6和10)接近下降时间。随着药物给药持续时间的增加,平均效应时间与下降时间之间的差异变得更大。将药代动力学变异性纳入计算对结果影响很小。
情境敏感半衰期或其他下降时间已被证明是药物浓度动力学最有用的度量。平均效应时间可能是理解药物作用恢复的一个有用概念。