Objective: Augmented renal clearance (ARC) can occur in critically-ill pediatric patients receiving aminoglycosides such as gentamicin and tobramycin, yet optimal dosing strategies for ARC are undefined. We evaluated the probability of achieving efficacious or toxic exposures in pediatrics.
Methods: Parallel population modeling of concentration strategies were pursued using Pmetrics v1.5.2 (non-parametric) and Monolix v2019R2 (parametric). Bayesian exposures were used to classify ARC based on total CL. The effect of SCR, CRCL, TBW, post-natal age (PNA), and ARC were explored as covariates. Probabilities of target attainment (PTA) (i.e., Cmax/MIC, AUC:MIC) and of toxic exposure (PTE) (i.e., Cmin>2 mcg/mL) were calculated according to PNA and ARC.
Results: 123 patients (1-21yrs, 56%female) contributed 304 concentrations. A two-compartment was superior to a one-compartment model in both approaches. Bayesian posterior predicted concentrations from the non-parametric base model fitted the data well (R2=0.96) and classified 34 patients as having ARC (28%). Both the non-parametric and parametric approaches resulted in allometrically scaling of TBW on V and CL. ARC modified CL and central V. CRCL and a maturation function modified CL. ARC was associated with a 1.49- vs. 1.66-fold increase in CL and a 1.56- vs 1.66-fold increase in the central V (non-parametric vs. parametric). High dose of 12 mg/kg/day was required to achieve adequate PTA when MIC were 1-2 mcg/mL; ARC lowered achievable MICs. When PNA< 2 years, PTE was increased.
Conclusions: Aminoglycoside monotherapy should be avoided in critically-ill pediatric patients with ARC when MICs exceed 1 mcg/mL, as optimal exposures are unachievable with standard dosing.
Augmented Renal Clearance Using Vancomycin Population-Based Pharmacokinetic Modeling With Bayesian Estimation in Critically-Ill Pediatric Patients
