Background The primary objective of this study was to develop a population pharmacokinetic model of meropenem, based on the population of critically ill adult patients undergoing CRRT. The secondary one was to examine the relationship between patient characteristics (covariates) and individual PK parameters. Finally, we aimed to perform Monte Carlo simulations to assess the probability of target attainment (PTA) of %T > MIC considering the uncertainty of PK parameters. Materials and methods The study population included 19 adult critically ill patients on CRRT, receiving 1 g of meropenem in 1-h infusions every 8 h. Blood samples were collected prior to (time zero) and 15, 30, 45, 60, 75, 90, 120, 180, 240 and 480 min after the start of meropenem administration. Population nonlinear mixed-effects modeling was conducted using NONMEM software, Fortran, and Wings for NONMEM. Results A two-compartment model was used to describe the available data. Typical values of the central and peripheral volume of distribution, and the CRRT and inter-compartmental clearance for a theoretical patient with 24.6 g/l albumin concertation were V 1 = 27.9 l, V 2 = 33.7 l, Cl CRRT = 15.1 l/h, and Q = 21.1 l/h. A significant covariate relationship between V 1 and albumin concentration was observed in the data that was described by a power relationship with − 2.87 exponent. Subsequently performed Monte Carlo simulations of the model allowed us to assess the impact of albumin concentration on PTA. The 40%T > 2 mg/l target was reached in more than 90% of subjects after 1-h infusion of 1000 mg q8h and steady-state conditions. The more stringent 100%T > 2 mg/l target requires higher doses and/or longer infusion durations that depend on the albumin concentration. Conclusions The population PK model was successfully developed to describe the time course of meropenem concentrations. The hypoalbuminemia was found to be associated with higher PTA in the CRRT patients after multiple short-term infusions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.