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群体药代动力学研究及比较 8 种药代动力学模型在预测重症监护患者持续输注美罗培南中的性能

Population pharmacokinetics and evaluation of the predictive performance of pharmacokinetic models in critically ill patients receiving continuous infusion meropenem: a comparison of eight pharmacokinetic models.

机构信息

Department of Intensive Care Medicine, Ghent University Hospital, Ghent, Belgium.

Department of Pharmacy, Mount Sinai West Hospital, New York, NY, USA.

出版信息

J Antimicrob Chemother. 2019 Feb 1;74(2):432-441. doi: 10.1093/jac/dky434.

Abstract

BACKGROUND

Several population pharmacokinetic (PopPK) models for meropenem dosing in ICU patients are available. It is not known to what extent these models can predict meropenem concentrations in an independent validation dataset when meropenem is infused continuously.

PATIENTS AND METHODS

A PopPK model was developed with concentration-time data collected from routine care of 21 ICU patients (38 samples) receiving continuous infusion meropenem. The predictability of this model and seven other published PopPK models was studied using an independent dataset that consisted of 47 ICU patients (161 samples) receiving continuous infusion meropenem. A statistical comparison of imprecision (mean square prediction error) and bias (mean prediction error) was conducted.

RESULTS

A one-compartment model with linear elimination and creatinine clearance as a covariate of clearance best described our data. The mean ± SD parameter estimate for CL was 9.89 ± 3.71 L/h. The estimated volume of distribution was 48.1 L. The different PopPK models showed a bias in predicting serum concentrations from the validation dataset that ranged from -8.76 to 7.06 mg/L. Imprecision ranged from 9.90 to 42.1 mg/L.

CONCLUSIONS

Published PopPK models for meropenem vary considerably in their predictive performance when validated in an external dataset of ICU patients receiving continuous infusion meropenem. It is necessary to validate PopPK models in a target population before implementing them in a therapeutic drug monitoring program aimed at optimizing meropenem dosing.

摘要

背景

有几个关于 ICU 患者美罗培南剂量的群体药代动力学(PopPK)模型。当美罗培南持续输注时,这些模型在独立验证数据集中预测美罗培南浓度的程度尚不清楚。

患者和方法

我们使用来自 21 名接受连续输注美罗培南的 ICU 患者(38 个样本)常规治疗中收集的浓度-时间数据,开发了一个 PopPK 模型。使用包含 47 名接受连续输注美罗培南的 ICU 患者(161 个样本)的独立数据集,研究了该模型和其他七个已发表的 PopPK 模型的可预测性。进行了精度(均方预测误差)和偏差(平均预测误差)的统计比较。

结果

一个具有线性消除和肌酐清除率作为清除率的协变量的单室模型最好地描述了我们的数据。CL 的平均±SD 参数估计值为 9.89 ± 3.71 L/h。估计的分布体积为 48.1 L。不同的 PopPK 模型在预测验证数据集血清浓度时存在偏差,范围从-8.76 到 7.06 mg/L。精度范围从 9.90 到 42.1 mg/L。

结论

在接受连续输注美罗培南的 ICU 患者的外部数据集验证时,发表的美罗培南 PopPK 模型在预测性能上存在很大差异。在实施旨在优化美罗培南剂量的治疗药物监测计划之前,有必要在目标人群中验证 PopPK 模型。

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