Purpose: Vancomycin (VCM) concentration is often out of therapeutic range (10-20 μg/ml) in patients receiving continuous renal replacement therapy (CRRT). The purposes of this study were to develop a practical VCM population pharmacokinetic (PPK) model and to evaluate the potential of Bayesian prediction-based therapeutic drug monitoring (Bayes-TDM) in VCM dose individualization for patients receiving CRRT.
Methods: We developed a VCM PPK model using 80 therapeutic concentrations in 17 patients receiving CRRT. Bayes-TDM with the VCM PPK model was evaluated in 23 patients after PPK modeling.
Results: We identified the covariates reduced urine output (RUO, <0.5 ml/kg/h) and effluent flow rate of CRRT for the VCM PPK model. The mean VCM non CRRT clearance (CLnonCRRT) was 2.12 l/h. RUO lowered CLnonCRRT to 0.34 l/h. The volume of distribution was 91.3 l/70 kg. The target concentration attainment rate by Bayes-TDM was higher (87.0%) than that by the PPK modeling period (53.8%, P = 0.046). The variance of the second measured concentrations by the Bayes-TDM was lower (11.5, standard deviation: 3.4 μg/ml) than that by the PPK modeling period (50.5, standard deviation: 7.1 μg/ml, P = 0.003).
Conclusions: Bayes-TDM could be a useful tool for VCM dose individualization in patients receiving CRRT.
Keywords: Bayesian; Vancomycin; continuous renal replacement therapy; population pharmacokinetics; therapeutic drug monitoring.