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万古霉素在大型重症监护病房患者队列中的群体药代动力学模型的外部评估。

External Evaluation of Population Pharmacokinetic Models of Vancomycin in Large Cohorts of Intensive Care Unit Patients.

机构信息

Department of Intensive Care Medicine, Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Amsterdam Medical Data Science (AMDS), Research VUmc Intensive Care (REVIVE), Amsterdam Cardiovascular Sciences (ACS), Amsterdam, The Netherlands

Department of Pharmacy, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands.

出版信息

Antimicrob Agents Chemother. 2019 Apr 25;63(5). doi: 10.1128/AAC.02543-18. Print 2019 May.

Abstract

Dosing of vancomycin is often guided by therapeutic drug monitoring and population pharmacokinetic models in the intensive care unit (ICU). The validity of these models is crucial, as ICU patients have marked pharmacokinetic variability. Therefore, we set out to evaluate the predictive performance of published population pharmacokinetic models of vancomycin in ICU patients. The PubMed database was used to search for population pharmacokinetic models of vancomycin in adult ICU patients. The identified models were evaluated in two independent data sets which were collected from two large hospitals in the Netherlands (Amsterdam UMC, Location VUmc, and OLVG Oost). We also tested a one-compartment model with fixed values for clearance and volume of distribution, in which a clinical standard dosage regimen (SDR) was mimicked to assess its predictive performance. Prediction error was calculated to assess the predictive performance of the models. Six models plus the SDR model were evaluated. The model of Roberts et al. (J. A. Roberts, F. S. Taccone, A. A. Udy, J.-L. Vincent, F. Jacobs, and J. Lipman, Antimicrob Agents Chemother 55:2704-2709, 2011, https://doi.org/10.1128/AAC.01708-10) performed satisfactorily, with mean and median values of prediction error of 5.1% and -7.5%, respectively, for Amsterdam UMC, Location VUmc, patients, and -12.6% and -17.2% respectively, for OLVG Oost patients. The other models, including the SDR model, yielded high mean values (-49.7% to 87.7%) and median values (-56.1% to 66.1%) for both populations. In conclusion, only the model of Roberts et al. was able to validly predict the concentrations of vancomycin for our data, whereas other models and standard dosing were largely inadequate. Extensive evaluation should precede the adoption of any model in clinical practice for ICU patients.

摘要

万古霉素的给药通常由重症监护病房(ICU)中的治疗药物监测和群体药代动力学模型指导。这些模型的有效性至关重要,因为 ICU 患者的药代动力学变化很大。因此,我们着手评估已发表的 ICU 患者万古霉素群体药代动力学模型的预测性能。我们使用 PubMed 数据库搜索成人 ICU 患者的万古霉素群体药代动力学模型。在两个独立的数据集中评估所识别的模型,这些数据来自荷兰的两家大医院(阿姆斯特丹 UMC,VUmc 地点和 OLVG 东部)。我们还测试了一个具有固定清除率和分布容积的单室模型,模拟临床标准剂量方案(SDR)以评估其预测性能。计算预测误差以评估模型的预测性能。评估了六个模型加 SDR 模型。Roberts 等人的模型(J. A. Roberts,F. S. Taccone,A. A. Udy,J.-L. Vincent,F. Jacobs 和 J. Lipman,Antimicrob Agents Chemother 55:2704-2709,2011,https://doi.org/10.1128/AAC.01708-10)表现令人满意,对于阿姆斯特丹 UMC,VUmc 地点的患者,平均和中位数预测误差值分别为 5.1%和-7.5%,对于 OLVG 东部的患者,分别为-12.6%和-17.2%。其他模型,包括 SDR 模型,对于两个群体的平均和中位数预测误差值均很高(-49.7%至 87.7%)。总之,只有 Roberts 等人的模型能够有效地预测我们数据的万古霉素浓度,而其他模型和标准剂量方案则远远不够。在将任何模型应用于 ICU 患者的临床实践之前,应进行广泛的评估。

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