h Population pharmacokinetic analyses can be applied to predict optimized dosages for individual patients. The aim of this study was to compare the prediction performance of the published population pharmacokinetic models for meropenem in critically ill patients. We coded the published population pharmacokinetic models with covariate relationships into dosing software to predict unbound meropenem concentrations measured in a separate cohort of critically ill patients. The agreements between the observed and predicted concentrations were evaluated with Bland-Altman plots. The absolute and relative bias and precision of the models were determined. The clinical implications of the results were evaluated according to whether dose adjustments were required from the predictions to achieve a meropenem concentration of >2 mg/liter throughout the dosing interval. A total of 157 free meropenem concentrations from 56 patients were analyzed. Eight published population pharmacokinetic models were compared. The models showed an absolute bias in predicting the unbound meropenem concentrations from a mean percent difference (95% confidence interval [CI]) of ؊108.5% (؊119.9% to ؊97.3%) to 19.9% (7.3% to 32.7%), while absolute precision ranged from ؊249.1% (؊263.4% to ؊234.8%) to 31.9% (17.6% to 46.2%) and ؊178.9% (؊196.9% to ؊160.9%) to 175.0% (157.0% to 193.0%). A dose change was required in 44% to 64% of the concentration results. Seven of the eight equations evaluated underpredicted free meropenem concentrations. In conclusion, the overall accuracy of these models supports their inclusion in dosing software and application for individualizing meropenem doses in critically ill patients to increase the likelihood of achievement of optimal antibiotic exposures.
Meropenem, a carbapenem antibiotic with broad-spectrum activities against both Gram-positive and Gram-negative bacteria, is commonly used in critically ill patients with life-threatening infections. Vital to the success of this treatment is early and appropriate antibiotic therapy. Selecting the correct dose is as important, but this process is highly challenging in critically ill patients because of the variable and difficult-to-predict pharmacokinetics in these patients (1, 2). Dose optimization of meropenem should be considered imperative because suboptimal antibiotic exposures might jeopardize the clinical outcomes and potentially increase the emergence of antibiotic resistance (3).Meropenem is a time-dependent antibiotic: its clinical and microbiological efficacy is related to the percentage of the dosing interval in which the free drug concentration remains above the MIC of the pathogenic organism (fT ϾMIC ) (4, 5). The in vitro bactericidal activity of carbapenems is optimal at an fT ϾMIC of Ն40%; however, a target fT ϾMIC of 100% has been suggested in critically ill patients (6). Population pharmacokinetic models that quantify the effect of demographic, pathophysiological, and other drug-related factors on drug disposition should be considered valuable in the crit...