Purpose To evaluate the optimal dosing regimens of meropenem against extended-spectrum beta-lactamase-producing Escherichia coli (ESBL E. coli ) in critically ill patients with varying degrees of renal function using Monte Carlo simulation (MCS). Methods The MCS was performed using the minimum inhibitory concentration (MIC) data from Right Laboratory and Health Screen in Naypyitaw, Myanmar, as well as reported meropenem pharmacokinetic parameters in the target population and the pharmacokinetic-pharmacodynamic index. For each dosing regimen, 10,000 virtual patients were generated to assess the probability of target attainment (PTA) and the cumulative fraction of response (CFR). The most effective dosage regimens were determined using PTA and a CFR of 90%. Results ESBL E. coli made up 93 of the 396 clinical E. coli isolates, and they are all multidrug-resistant, with resistance to at least five antibiotic classes. The MIC 50 and MIC 90 were determined to be 0.25 μg/mL. The PTA was affected by five factors: creatinine clearance (CLcr), vasopressor usage, MIC, infusion time, and dosage fractionation. In patients who did not receive vasopressors, the current regimens (US-FDA and EMA) were ineffective in all renal function for MIC >0.25μg/mL. In the subset group of CLcr >80 mL/min for MIC 2μg/mL, the maximum total daily dose of 6g/day (2g q 8hr; 3hr infusion) was still ineffective, but 4g/day (1g q 6hr; 3hr infusion) achieved 98.96% PTA. Almost majority of the simulated regimens produced >90% PTA in vasopressor-dependent patients with all levels of renal function, resulting in a decreased total daily dose requirement. Conclusion For high MIC (>1μg/mL) patients who do not use vasopressors and have a CLcr >80 mL/min, a combination of dosage fractionation and the extended infusion was considered as an effective technique to maximize target attainment. Neither prolonged infusion nor dosage fractionation should be explored in patients using vasopressors.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.