Prospective validation of an optimal sparse plasma-sampling strategy for estimating ciprofloxacin pharmacokinetics.

Abstract

Data obtained from 23 critically ill patients treated with intravenous ciprofloxacin in two clinical trials were used to validate prospectively a previously developed maximum a posteriori (MAP)-Bayesian estimator and optimal plasma-sampling strategy (OSS). Dosages ranged from 200 mg every 12 hours to 400 mg every 8 hours. Each patient had 8-16 samples taken, either as large gold standard sampling sets or as a mix of gold standard sets and OSSs. The MAP-Bayesian estimator used a two-compartment model and identified apparent volumes of distribution of the central and peripheral compartments, distributional clearance, and the slope and intercept of the relationship between creatinine clearance and total body clearance. Fit parameters were used to derive the apparent volume of distribution at steady state and the 24-hour area under the curve. All parameters derived from the OSS using the MAP-Bayesian estimates matched up almost identically to those obtained from modeling the gold standard sets. There was no systematic bias, and good precision was seen among all the parameters. These data demonstrate the usefulness and validity of the current OSS and MAP-Bayesian estimator, and provide further evidence of the utility of optimal sampling theory.