Influence of Clinical Diagnosis in the Population Pharmacokinetics of Amikacin in Intensive Care Unit Patients

Abstract

The aim of the present study was to analyse the pharmacokinetic behaviour of amikacin in intensive care unit (ICU) patients using a mixed-effect model and sparse data collected during routine clinical care. The patient population comprised 158 medical ICU patients divided into two groups: one for computing the population model (n = 120) and the other for validation (n = 38). A 1-compartment model was used and the following covariates were tested for their influence on clearance (CL) and volume of distribution (Vd): age, gender, weight, parenteral nutrition, creatinine clearance, duration of therapy and clinical diagnosis. The nonlinear mixed-effect model (NONMEM) was used to assess the population pharmacokinetic model of amikacin in this patient population. In this study, the final population model accounting for amikacin pharmacokinetics in ICU patients was: CL = 0.93 CL(CR) (1 + 0.22 Trauma), Vd = 0.39 TBW (1 + 0.24 Sepsis), where CL(CR) and TBW corresponded to the patients' creatinine clearance and total bodyweight, respectively. The 'Trauma' and 'Sepsis' variables referred to the clinical diagnosis of the patients. This model was subsequently used to predict amikacin serum levels obtained in the validation population by a priori and Bayesian methods. The predictive performance was adequate for clinical purposes, pointing to the feasibility of our population model to provide reference values for a priori prediction as well as the Bayesian approach for individualisation of amikacin therapy in ICU patients.