AMIKACIN BAYESIAN FORECASTING IN CRITICALLY ILL PATIENTS WITH SEPSIS AND CIRRHOSIS

This study was designed to determine the population pharmacokinetic pa rameters of amikacin in two subpopulations of intensive care unit pati ents with sepsis and cirrhosis and sepsis without cirrhosis, The autho rs evaluated the usefulness of the obtained parameters to forecast the serum amikacin concentrations in a validation group of patients with sepsis and cirrhosis when used as a priori distribution in a Bayesian forecaster. The population parameters were estimated by a nonparametri c expectation maximization algorithm (NPEM), and the accuracy of the p redictions were evaluated through a prediction error analysis. Signifi cant differences (p < 0.05) were found in Vd (0.668 versus 0.470 l/kg) and K (0.0701 versus 0.161 h(-1)) between subpopulations of patients with and without cirrhosis. The model derived for patients with cirrho sis used as a priori distribution, with and without feedback, was supe rior to the model derived for patients with sepsis in forecasting amik acin serum concentrations. The results show the relevance of using the specific model for the subgroup with cirrhosis as a priori distributi on in a Bayesian forecaster to obtain a nonbiased prediction with an a cceptable precision.