Boonstra J M, Märtson A G, Sandaradura I, Kosterink J G W, van der Werf T S, Marriott D J E, Zijlstra J G, Touw D J, Alffenaar J W C
University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, the Netherlands.
The University of Sydney, Faculty of Medicine and Health, School of Pharmacy, Sydney, Australia.
Antimicrob Agents Chemother. 2021 Feb 17;65(3). doi: 10.1128/AAC.01554-20.
The efficacy of fluconazole is related to the area under the plasma concentration-time curve (AUC) over the MIC of the microorganism. Physiological changes in critically ill patients may affect the exposure of fluconazole, and therefore dosing adjustments might be needed. The aim of this study was to evaluate variability in fluconazole drug concentration in intensive care unit (ICU) patients and to develop a pharmacokinetic model to support personalized fluconazole dosing. A prospective observational pharmacokinetic study was performed in critically ill patients receiving fluconazole either as prophylaxis or as treatment. The association between fluconazole exposure and patient variables was studied. Pharmacokinetic modeling was performed with a nonparametric adaptive grid (NPAG) algorithm using R package Pmetrics. Data from 33 patients were available for pharmacokinetic analysis. Patients on dialysis and solid organ transplant patients had a significantly lower exposure to fluconazole. The population was best described with a one-compartment model, where the mean volume of distribution was 51.52 liters (standard deviation [SD], 19.81) and the mean clearance was 0.767 liters/h (SD, 0.46). Creatinine clearance was tested as a potential covariate in the model, but was not included in the final population model. A significant positive correlation was found between the fluconazole exposure (AUC) and the trough concentration (). Substantial variability in fluconazole plasma concentrations in critically ill adults was observed, where the majority of patients were underexposed. Fluconazole therapeutic drug monitoring (TDM)-guided dosing can be used to optimize therapy in critically ill patients. (This study has been registered at ClinicalTrials.gov under identifier NCT02491151.).
氟康唑的疗效与血浆浓度 - 时间曲线下面积（AUC）相对于微生物的最低抑菌浓度（MIC）有关。重症患者的生理变化可能会影响氟康唑的暴露量，因此可能需要调整剂量。本研究的目的是评估重症监护病房（ICU）患者氟康唑药物浓度的变异性，并建立一个药代动力学模型以支持氟康唑的个体化给药。对接受氟康唑预防或治疗的重症患者进行了一项前瞻性观察性药代动力学研究。研究了氟康唑暴露量与患者变量之间的关联。使用R包Pmetrics中的非参数自适应网格（NPAG）算法进行药代动力学建模。有33例患者的数据可用于药代动力学分析。接受透析的患者和实体器官移植患者的氟康唑暴露量显著较低。用单室模型能最好地描述该群体，其中平均分布容积为51.52升（标准差[SD]，19.81），平均清除率为0.767升/小时（SD，0.46）。肌酐清除率在模型中作为潜在协变量进行了测试，但未纳入最终的群体模型。氟康唑暴露量（AUC）与谷浓度之间存在显著的正相关。观察到重症成年患者氟康唑血浆浓度存在很大变异性，其中大多数患者暴露不足。氟康唑治疗药物监测（TDM）指导下的给药可用于优化重症患者的治疗。（本研究已在ClinicalTrials.gov上注册，标识符为NCT02491151。）
