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Optimizing Vancomycin Dosing in Chronic Kidney Disease by Deriving and Implementing a Web-Based Tool Using a Population Pharmacokinetics Analysis.

作者信息

Dorajoo Sreemanee Raaj, Winata Chrystal Leandra, Goh Jessica Hui Fen, Ooi Say Tat, Somani Jyoti, Yeoh Lee Ying, Lee Siok Ying, Yap Chun Wei, Chan Alexandre, Chae Jung-Woo

机构信息

Department of Pharmacy, National University of Singapore, Singapore, Singapore.

Department of Pharmacy, Khoo Teck Puat Hospital, Singapore, Singapore.

出版信息

Front Pharmacol. 2019 Jun 11;10:641. doi: 10.3389/fphar.2019.00641. eCollection 2019.

DOI:10.3389/fphar.2019.00641
PMID:31244657
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6581063/
Abstract

Chronic kidney disease (CKD) patients requiring intravenous vancomycin bear considerable risks of adverse outcomes both from the infection and vancomycin therapy itself, necessitating especially precise dosing to avoid sub- and supratherapeutic vancomycin exposure. In this retrospective study, we performed a population pharmacokinetic analysis to construct a vancomycin dose prediction model for CKD patients who do not require renal replacement therapy. The model was externally validated on an independent cohort of patients to assess its prediction accuracy. The pharmacokinetic parameter estimates and the equations were productized into a Web application (VancApp) subsequently implemented in routine care. The association between VancApp-based dosing and time-to-target concentration attainment, 30-day mortality, and nephrotoxicity were assessed postimplementation. The model constructed from an initial cohort (n = 80) revealed a population clearance and volume of distribution of 1.30 L/h and 1.23 L/kg, respectively. External model validation (n = 112) demonstrated a mean absolute prediction error of 1.25 mg/L. Following 4 months of clinical implementation of VancApp as an optional alternative to usual care [VancApp (n = 22) vs. usual care (n = 21)], patients who had received VancApp-based dosing took a shorter time to reach target concentrations (median: 66 vs. 102 h, p = 0.187) and had fewer 30-day mortalities (14% vs. 24%, p = 0.457) compared to usual care. While statistical significance was not achieved, the clinical significance of these findings appear promising. Clinical implementation of a population pharmacokinetic model for vancomycin in CKD can potentially improve dosing precision in CKD and could serve as a practical means to improve vital clinical outcomes.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/0629d7d44b49/fphar-10-00641-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/a8b6e30ef930/fphar-10-00641-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/75b7ffb83ed9/fphar-10-00641-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/0629d7d44b49/fphar-10-00641-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/a8b6e30ef930/fphar-10-00641-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/75b7ffb83ed9/fphar-10-00641-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e019/6581063/0629d7d44b49/fphar-10-00641-g003.jpg

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Implementing Clinical Prediction Models: Pushing the Needle Towards Precision Pharmacotherapy.实施临床预测模型:推动精准药物治疗。
Clin Pharmacol Ther. 2018 Feb;103(2):180-183. doi: 10.1002/cpt.752. Epub 2017 Jul 19.
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External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients.
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