Polard E, Le Bouquin V, Le Corre P, Kérebel C, Trout H, Feuillu A, Le Verge R, Mallédant Y
Department of Biopharmaceutics and Clinical Pharmacy, Université de Rennes 1, France.
Ther Drug Monit. 1999 Aug;21(4):395-403. doi: 10.1097/00007691-199908000-00003.
The pharmacokinetics of vancomycin was investigated in adult ICU patients after the first administration and at steady state. Then the predictive performance of a two-compartment Bayesian forecasting program was assessed in these patients by using population-based parameters and three non steady state vancomycin concentrations as feedback information. Finally a prospective investigation was carried out to search potential covariates. At steady state, a significant decrease (around 30%) in clearance (CL) was observed, while creatinine clearance (CLcr) was stable and a significant increase (around 30%) in volume of distribution (V(SS)) was observed. A two-fold increase in elimination half-life was found. CL was weakly correlated with CLcr at onset of therapy and at steady state. The Bayesian program tended to overpredict vancomycin peak and trough concentrations. A larger mean prediction error and a poorer precision were observed when population-based parameter estimates were used (no feedback) compared to feedback prediction, but the differences were not significant. Mechanical ventilation and concurrent opioid therapy may be pertinent covariates of vancomycin pharmacokinetics. The current work has shown that vancomycin pharmacokinetics in ICU patients displayed a significant variability and a significant change in both clearance and distribution during the course of therapy. Further investigation is necessary to clarify these findings. Moreover, the use of the Bayesian forecasting PKS program in our patients led to a prediction with low bias but rather poor precision. This outcome highlights the need to implement a population modeling approach, to determine the vancomycin pharmacokinetic parameters and covariates in our ICU patients, and to apply this information to provide more accurate concentration predictions.
在成年重症监护病房(ICU)患者首次给药后及稳态时研究了万古霉素的药代动力学。然后,通过使用基于群体的参数和三个非稳态万古霉素浓度作为反馈信息,评估了两室贝叶斯预测程序在这些患者中的预测性能。最后进行了一项前瞻性研究以寻找潜在的协变量。在稳态时,观察到清除率(CL)显著降低(约30%),而肌酐清除率(CLcr)稳定,且分布容积(V(SS))显著增加(约30%)。发现消除半衰期增加了两倍。在治疗开始时和稳态时,CL与CLcr呈弱相关。贝叶斯程序倾向于高估万古霉素的峰浓度和谷浓度。与反馈预测相比,使用基于群体的参数估计(无反馈)时观察到更大的平均预测误差和更低的精度,但差异不显著。机械通气和同时使用阿片类药物治疗可能是万古霉素药代动力学的相关协变量。目前的研究表明,ICU患者中万古霉素的药代动力学表现出显著的变异性,并且在治疗过程中清除率和分布均发生了显著变化。需要进一步研究以阐明这些发现。此外,在我们的患者中使用贝叶斯预测PKS程序导致预测偏差较低但精度相当差。这一结果凸显了实施群体建模方法的必要性,以确定我们ICU患者中万古霉素的药代动力学参数和协变量,并应用这些信息以提供更准确的浓度预测。