Empirical models for dosage optimization of four beta-lactams in critically ill septic patients based on therapeutic drug monitoring of amikacin

Abstract

Objectives: The study aims to develop empirical models able to predict the pharmacokinetics (PK) of four beta-lactams using the amikacin (AMK) therapeutic drug monitoring (TDM), in order to optimize their dosage regimens.

Design and methods: 69 critically ill septic patients were included. All received a first dose of AMK combined with piperacillin/tazobactam, ceftazidime, cefepime or meropenem. A multivariate analysis was performed to predict the beta-lactam PK using AMK PK parameters estimated from TDM and using pathophysiological variables.

Results: An optimal prediction model was identified for each PK parameter of each beta-lactam. The best predictor of each model was one of the AMK PK parameters estimated from TDM. Other variables included colloid solution, renal and hepatic biomarkers, age and body weight.

Conclusion: PK of the four beta-lactams could be easily and rapidly predicted in critically ill septic patients using the AMK TDM. These predictions could improve the beta-lactam dosages in clinical practice.