Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an <i>AUC</i><sub><i>24</i></sub> Target in Critically Ill Patients

万古霉素 加药 医学 药代动力学 治疗药物监测 非金属 人口 病危 指南 重症监护医学 药理学 生物 环境卫生 病理 细菌 遗传学 金黄色葡萄球菌
作者
Zhi Rao,Siming Guo,Yanming Wei
出处
期刊:Chemotherapy [Karger Publishers]
卷期号:69 (1): 49-55 被引量:1
标识
DOI:10.1159/000531638
摘要

<b><i>Introduction:</i></b> Monitoring of <i>AUC</i><sub><i>24</i></sub> was updated recommendation in the guideline for the therapeutic drug monitoring (TDM) of vancomycin in Chinese pharmacological society published in 2020. Vancomycin pharmacokinetic profiles are diverse and unique in critically ill patients because of the drastic variability of the patients’ physiological parameters, while the study for population pharmacokinetic (PPK) models in Chinese critically ill patients has been rarely reported. The objectives of this study were to construct a PPK model to describe the pharmacokinetic characteristics of vancomycin in critically ill patients and to individualize vancomycin dosing by model-informed Bayesian estimation for maintenance of <i>AUC</i><sub><i>24</i></sub> target at 400–650 mg h/L recommended by the 2020 guideline. <b><i>Methods:</i></b> Vancomycin with different dosing was administered intravenously over 1 h for critically ill patients, TDM was started at 48 h or 72 h since initiation of vancomycin therapy for patients. Blood samples were collected from patients for trough concentrations or C<sub><i>max</i></sub>. Vancomycin concentrations were determined by high-performance liquid chromatography method with ultraviolet detection. PPK model was performed using the nonlinear mixed-effect model (NONMEM<sup>®</sup>). Individual PK parameters for critically ill patients treated with vancomycin were estimated using a post hoc empirical Bayesian method based on the final PPK model. <i>AUC</i><sub><i>24</i></sub> was calculated as the total daily dose divided by the clearance (L/h). <b><i>Results:</i></b> The PPK of vancomycin was determined by a one-compartment model with creatinine clearance as fixed effects. The PK estimates in the final model generally agreed with the median estimates and were contained within the 95% CI generated from the bootstrap results, indicating good precision and stability in the final model. The visual predictive check plots showed the adequate predictive performance of the final PK model and supported a good model fit. The model-informed Bayesian estimation was used to predict the <i>AUC</i><sub><i>24</i></sub> of critically ill patient by the acquired TDM results, and the dosing adjustment by maintenance of <i>AUC</i><sub><i>24</i></sub> at 400–650 mg h/L had made a great therapeutic effect for the case. <b><i>Conclusion:</i></b> This study established a PPK model of vancomycin in Chinese critically ill patients, and individualized dosing of vancomycin by model-informed Bayesian estimation to maintain an <i>AUC</i><sub><i>24</i></sub> target at 400–650 mg h/L has been successfully applied in clinic. This result supports the continued use of model-informed Bayesian estimation to vancomycin treatment in critically ill patients.
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