University of Groningen, University Medical Center Groningengrid.4494.d, Department of Clinical Pharmacy and Pharmacology, Groningen, the Netherlands.
University of Groningen, University Medical Center Groningengrid.4494.d, Department of Critical Care, Groningen, the Netherlands.
Antimicrob Agents Chemother. 2022 Dec 20;66(12):e0111322. doi: 10.1128/aac.01113-22. Epub 2022 Nov 15.
bloodstream infections are associated with high attributable mortality, where early initiation of adequate antifungal therapy is important to increase survival in critically ill patients. The exposure variability of micafungin, a first-line agent used for the treatment of invasive candidiasis, in critically ill patients is significant, potentially resulting in underexposure in a substantial portion of these patients. The objective of this study was to develop a population pharmacokinetic model including appropriate sampling strategies for assessing micafungin drug exposure in critically ill patients to support adequate area under the concentration-time curve (AUC) determination. A two-compartment pharmacokinetic model was developed using data from intensive care unit (ICU) patients ( = 19), with the following parameters: total body clearance (CL), volume of distribution of the central compartment (V1), inter-compartmental clearance (CL12), and volume of distribution of the peripheral compartment (V2). The final model was evaluated with bootstrap analysis and the goodness-of-fit plots for the population and individual predicted micafungin plasma concentrations. Optimal sampling strategies (with sampling every hour, 24 h per day) were developed with 1- and 2-point sampling schemes. Final model parameters (±SD) were: CL = 1.03 (0.37) (L/h/1.85 m), V1 = 0.17 (0.07) (L/kg LBMc), CL12 = 1.80 (4.07) (L/h/1.85 m), and V2 = 0.12 (0.06) (L/kg LBMc). Sampling strategies with acceptable accuracy and precision were developed to determine the micafungin AUC. The developed model with optimal sampling procedures provides the opportunity to achieve quick optimization of the micafungin exposure from a single blood sample using Bayesian software and may be helpful in guiding early dose decision-making.
血流感染与高病死率相关，对于危重症患者，早期开始充分的抗真菌治疗对提高生存率至关重要。作为侵袭性念珠菌病治疗的一线药物，米卡芬净在危重症患者中的暴露变异性较大，可能导致相当一部分患者的药物暴露不足。本研究的目的是建立一个群体药代动力学模型，包括评估米卡芬净药物暴露的适当采样策略，以支持充分确定药时曲线下面积（AUC）。使用来自重症监护病房（ICU）患者的数据（n=19）建立了一个两室药代动力学模型，其中包括以下参数：总体清除率（CL）、中央室分布容积（V1）、隔室清除率（CL12）和周边室分布容积（V2）。使用群体和个体预测米卡芬净血浆浓度的自举分析和拟合优度图对最终模型进行评估。采用 1 点和 2 点采样方案开发了最佳采样策略（每小时采样 1 次，每天 24 小时采样）。最终模型参数（±SD）为：CL=1.03（0.37）（L/h/1.85 m），V1=0.17（0.07）（L/kg LBMc），CL12=1.80（4.07）（L/h/1.85 m）和 V2=0.12（0.06）（L/kg LBMc）。开发了具有可接受准确性和精密度的采样策略来确定米卡芬净 AUC。使用贝叶斯软件，通过最佳采样程序建立的模型可快速优化米卡芬净的暴露量，有助于指导早期剂量决策。
