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万古霉素群体药代动力学模型在临床应用中的预测性能的评估

庞惠媚 刘滔滔 韦文兴 覃小玲 经力 郭晴 陆华 程道海

中国临床药理学杂志2018,Vol.34Issue(6):710-712,724,4.
中国临床药理学杂志2018,Vol.34Issue(6):710-712,724,4.DOI:10.13699/j.cnki.1001-6821.2018.06.029

万古霉素群体药代动力学模型在临床应用中的预测性能的评估

Evaluation of the predictive performance for a vancomycin population pharmacokinetic model

庞惠媚 1刘滔滔 1韦文兴 1覃小玲 1经力 1郭晴 1陆华 1程道海1

作者信息

  • 1. 广西医科大学第一附属医院药学部,南宁 530021
  • 折叠

摘要

Abstract

Objective To evaluate the predictive performance of a vancomycin population pharmacokinetic (PPK) model in clinical application.Methods Adult inpatients who received intravenous vancomycin treatment were collected in the First Affiliated Hospital of Guangxi Medical University.Individual predictive values (IPRED) of steady-state trough concentrations (Ctrough) and peak concentrations (Cpeak) at a given dose were estimated by bayesian feedback method basing on a PPK model.The predictive performance was evaluated by comparing the IPRED with the measured values.Results A total of 271 patients with 697 samples were included,including 417 Ctrough and 280 Cpeak.The mean Ctrough and its mean IPRED were (11.85 ±7.14) and (11.08 ±6.81)mg · L-1;the mean Cpeak and its mean IPRED were (18.42 ±9.61) and (17.61 ±7.37) mg · L-1.The mean error,mean relative error,mean absolute error and root mean square error were-0.77 mg · L-1,-2.53%,1.63 mg · L-1 and 2.38 mg · L-1 for Ctrough,and-0.81 mg · L-1,1.53%,2.28 mg · L-1 and 3.32 mg · L-1 for Cpeak,respectively.About 92% of the concentrations had a relative error within ± 30%.Conclusion Previously established vancomycin PPK model has an excellent predictive performance in the clinical application,which is useful for individualized administration of vancomycin in adult patients.

关键词

万古霉素/群体药代动力学模型/预测性能/临床应用

Key words

vancomycin/population pharmacokinetic model/predictive performance/clinical application

分类

医药卫生

引用本文复制引用

庞惠媚,刘滔滔,韦文兴,覃小玲,经力,郭晴,陆华,程道海..万古霉素群体药代动力学模型在临床应用中的预测性能的评估[J].中国临床药理学杂志,2018,34(6):710-712,724,4.

基金项目

国家自然科学基金资助项目(81460569) (81460569)

中国临床药理学杂志

OA北大核心CSCDCSTPCD

1001-6821

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