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利用经验证的群体药代动力学模型为危重症成年患者推荐持续输注哌拉西林的剂量。

Using a Validated Population Pharmacokinetic Model for Dosing Recommendations of Continuous Infusion Piperacillin for Critically Ill Adult Patients.

机构信息

Faculty of Pharmacy, Université de Montréal, Pavillon Jean-Coutu, 2940 Chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada.

Laboratoire de Suivi Thérapeutique Pharmacologique et Pharmacocinétique, Faculty of Pharmacy, Université de Montréal, Montreal, QC, Canada.

出版信息

Clin Pharmacokinet. 2022 Jun;61(6):895-906. doi: 10.1007/s40262-022-01118-1. Epub 2022 Mar 28.

Abstract

UNLABELLED

BACKGROUND AND OBJECTIVE: Piperacillin is a broad-spectrum β-lactam antibiotic commonly prescribed in intensive care units. Many piperacillin population pharmacokinetic models have been published, but few underwent an external evaluation. External evaluation is an important process to determine a model's capability of being generalized to other hospitals. We aimed to assess the predictive performance of these models with an external validation dataset.

METHODS

Six models were evaluated with a dataset consisting of 30 critically ill patients (35 samples) receiving piperacillin by continuous infusion. Models were subject to prediction-based (bias and imprecision) and simulation-based evaluations. When a model had an acceptable evaluation, it was used for dosing simulations to evaluate the probability of target attainment.

RESULTS

Bias and imprecision ranged from - 35.7 to 295% and from 22.7 to 295%, respectively. The models of Klastrup et al. and of Udy et al. were acceptable according to our criteria and were used for dosing simulations. Simulations showed that a loading dose of 4 g followed by a maintenance dose of 16 g/24 h of piperacillin infused continuously was necessary to remain above a pharmacokinetic-pharmacodynamic target set as a minimal inhibitory concentration of 16 mg/L in 90% of patients, for a median patient with a creatinine clearance of 76 mL/min.

CONCLUSIONS

Despite the considerable variation in the predictive performance of the models with the external validation dataset, this study was able to validate two of these models and led to the elaboration of a dosing nomogram for piperacillin by continuous infusion that can be used by clinicians in intensive care units.

摘要

背景与目的

哌拉西林是一种在重症监护病房中常用的广谱β-内酰胺类抗生素。已经发表了许多哌拉西林群体药代动力学模型,但很少有经过外部评估。外部评估是确定模型是否能够推广到其他医院的重要过程。我们旨在使用外部验证数据集评估这些模型的预测性能。

方法

使用包含 30 名接受连续输注哌拉西林的重症患者(35 个样本)的数据集评估了 6 个模型。模型接受基于预测的(偏差和不准确性)和基于模拟的评估。当模型评估结果可以接受时,使用其进行剂量模拟以评估目标达成的概率。

结果

偏差和不准确性范围分别为 -35.7%至 295%和 22.7%至 295%。根据我们的标准,Klastrup 等人和 Udy 等人的模型是可以接受的,并用于剂量模拟。模拟结果表明,对于肌酐清除率为 76mL/min 的中位数患者,需要给予 4g 的负荷剂量,然后连续输注 16g/24h 的维持剂量,才能使哌拉西林的浓度保持在 16mg/L 的最低抑菌浓度以上,从而使 90%的患者达到目标。

结论

尽管这些模型在外部验证数据集中的预测性能存在很大差异,但本研究能够验证其中的两个模型,并制定了连续输注哌拉西林的剂量图表,可供重症监护病房的临床医生使用。

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