Green B, Greenwood M, Saltissi D, Westhuyzen J, Kluver L, Rowell J, Atherton J
School of Pharmacy, University of Queensland, St Lucia, Brisbane, Australia.
Br J Clin Pharmacol. 2005 Mar;59(3):281-90. doi: 10.1111/j.1365-2125.2004.02253.x.
Phase III clinical studies have confirmed that enoxaparin is superior to standard heparin in reducing the rate of recurrent ischaemic events in patients with non-ST elevation acute coronary syndromes. Patients with moderate to severe renal impairment were, however, excluded from these studies. Due to the hydrophilic disposition of enoxaparin, accumulation is likely in patients with renal dysfunction, thereby increasing the risk of haemorrhagic complications if standard weight adjusted treatment doses are used. Arbitrary dose reduction has been reported to increase the risk of ischaemic events, presumably due to inadequate enoxaparin concentrations.
The aims of this study were to investigate the influence of glomerular filtration rate (GFR) on the pharmacokinetics of subcutaneously administered enoxaparin, and to develop a practical dosing algorithm in renal impairment that can easily be used at the bedside.
Thirty-eight patients, median age 78 years (range 44-87), mean GFR 32 ml min(-1) (range 16-117) and mean weight 69 kg (range 32-95), presenting with acute coronary syndrome were recruited into the study. Approximately 10 anti-Xa concentrations were taken per patient over their period of therapy. A population pharmacokinetic model was developed using non linear mixed effects modelling techniques, utilizing the software NONMEM. Stochastic simulations were performed to identify the most suitable dosing regimen.
Three hundred and thirteen anti-Xa concentrations were collected. A two compartment, first order input model was identified as the best baseline model. Covariates found to improve model fitting were GFR as a linear function on clearance (CL) and weight as a linear function on the central volume compartment (Vc). The fraction of drug excreted unchanged (Fu) was estimated at 71%. CL and Vc from the final covariate model were estimated as; CL (l h(-1)) = 0.681 per 4.8 l hr(-1) (GFR) + 0.229 Vc (l) = 5.22 per 80 kg (total body weight)
Clearance of enoxaparin was predictably related to GFR estimated using the Cockroft and Gault equation, with ideal body weight used as the size descriptor. According to our model no dosage adjustment from the standard 1.0 mg kg(-1) 12 hourly is required for the first 48 h of treatment. Maintenance doses thereafter can be calculated using standard proportional adjustments based on Fu equal to 0.71.
III期临床研究已证实,在降低非ST段抬高急性冠状动脉综合征患者复发性缺血事件发生率方面,依诺肝素优于标准肝素。然而,中度至重度肾功能损害患者被排除在这些研究之外。由于依诺肝素具有亲水性,肾功能不全患者可能会出现药物蓄积,因此如果使用标准体重调整治疗剂量,出血并发症风险会增加。据报道,任意降低剂量会增加缺血事件风险,可能是因为依诺肝素浓度不足。
本研究旨在探讨肾小球滤过率(GFR)对皮下注射依诺肝素药代动力学的影响,并制定一种在肾功能损害患者中可在床边轻松使用的实用给药算法。
招募38例急性冠状动脉综合征患者,中位年龄78岁(范围44 - 87岁),平均GFR 32 ml·min⁻¹(范围16 - 117),平均体重69 kg(范围32 - 95)。每位患者在治疗期间大约采集10次抗Xa浓度。使用非线性混合效应建模技术,利用NONMEM软件建立群体药代动力学模型。进行随机模拟以确定最合适的给药方案。
共收集313次抗Xa浓度数据。确定二室一级输入模型为最佳基线模型。发现可改善模型拟合的协变量为:GFR作为清除率(CL)的线性函数以及体重作为中央室容积(Vc)的线性函数。药物原形排泄分数(Fu)估计为71%。最终协变量模型的CL和Vc估计如下:CL(l·h⁻¹)= 0.681 + 每4.8 l·hr⁻¹(GFR);Vc(l)= 5.22 + 每80 kg(总体重)
依诺肝素清除率与使用Cockcroft和Gault方程估算的GFR可预测相关,理想体重用作尺寸描述符。根据我们的模型,治疗的前48小时无需从标准的每12小时1.0 mg·kg⁻¹进行剂量调整。此后的维持剂量可根据Fu等于0.71使用标准比例调整来计算。