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优化个体化患者万古霉素给药的创新方法。

Innovative approaches to optimizing the delivery of vancomycin in individual patients.

机构信息

Albany College of Pharmacy and Health Sciences, Albany, NY, USA.

University of Southern California, Keck School of Medicine, Los Angeles, CA, USA; Laboratory of Applied Pharmacokinetics and Bioinformatics (LAPKB), Children's Hospital of Los Angeles, Los Angeles, CA, USA.

出版信息

Adv Drug Deliv Rev. 2014 Nov 20;77:50-7. doi: 10.1016/j.addr.2014.05.016. Epub 2014 Jun 5.

Abstract

The delivery of personalized antimicrobial therapy is a critical component in the treatment of patients with invasive infections. Vancomycin, the drug of choice for infections due to methicillin-resistant Staphylococcus aureus, requires the use of therapeutic drug monitoring (TDM) for delivery of optimal therapy. Current guidance on vancomycin TDM includes the measurement of a trough concentration as a surrogate for achieving an AUC to minimum inhibitory concentration (MIC) by broth microdilution (AUC/MICBMD) ratio≥400. Although trough-only monitoring has been widely integrated into clinical practice, there is a high degree of inter-individual variability between a measured trough concentration and the actual AUC value. The therapeutic discordance between AUC and trough may lead to suboptimal outcomes among patients with infections due to less susceptible pathogens or unnecessarily increase the probability of acute kidney injury (AKI) in others. Given the potentially narrow vancomycin AUC range for optimal effect and minimal AKI, clinicians need a "real-time" system to predict accurately the AUC with limited pharmacokinetic (PK) sampling. This article reviews two innovative approaches for calculating the vancomycin AUC in clinical practice based on one or two drug concentrations. One such approach involves the use of Bayesian computer software programs to estimate the "true" vancomycin AUC value with minimal PK sampling and provide AUC-guided dosing recommendations at the bedside. An alternative involves use of two concentrations (peak and trough) and simple analytic equations to estimate AUC values. Both approaches provide considerable improvements over the current trough-only concentration monitoring method.

摘要

个体化抗菌治疗的实施是治疗侵袭性感染患者的关键环节。对于耐甲氧西林金黄色葡萄球菌感染,万古霉素是治疗的首选药物,需要进行治疗药物监测(TDM)以实现最佳治疗效果。目前关于万古霉素 TDM 的指南包括测量谷浓度作为通过肉汤微量稀释(AUC/MICBMD)比值≥400 来实现 AUC 至最低抑菌浓度(MIC)的替代指标。尽管仅进行谷浓度监测已广泛整合到临床实践中,但测量的谷浓度与实际 AUC 值之间存在很大的个体间差异。AUC 与谷浓度之间的治疗差异可能导致对敏感性较低的病原体感染患者的治疗效果不佳,或者在其他患者中不必要地增加急性肾损伤(AKI)的概率。鉴于最佳效果和最小 AKI 的万古霉素 AUC 范围较窄,临床医生需要一种“实时”系统,以便在有限的药代动力学(PK)采样的情况下准确预测 AUC。本文综述了两种基于一个或两个药物浓度计算临床实践中万古霉素 AUC 的创新方法。其中一种方法涉及使用贝叶斯计算机软件程序,通过最小 PK 采样来估计“真实”万古霉素 AUC 值,并在床边提供 AUC 指导的给药建议。另一种方法涉及使用两个浓度(峰浓度和谷浓度)和简单的分析方程来估算 AUC 值。这两种方法均显著优于目前仅进行谷浓度监测的方法。

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