Population pharmacokinetics of amikacin in intensive care unit patients studied by NPEM algorithm |
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Authors: | J. Debord,C. Pessis,JC Voultoury,P. Marquet,H. Lotfi,L. Merle,and G. Lachâ tre |
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Affiliation: | Service de Pharmacologie-Toxicologie, Hôpital Dupuytren, 2, avenue Martin Luther King, 87042 Limoges;Service de Réanimation Polyvalente, Hôpital Dupuytren, 2, avenue Martin Luther King, 87042 Limoges;Laboratoire de Toxicologie, Facultéde Pharmacie, 2, rue du Docteur Marcland, 87025 Limoges, France |
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Abstract: | Summary— The population pharmacokinetics of amikacin was studied in 40 intensive care unit patients (212 plasma concentrations) by NPEM algorithm using a one-compartment model. The population was best characterized by the following pharmacokinetic parameters: renal clearance relative to creatinine clearance (Cs = 0.96 ± 0.33), and either the total volume of distribution (Vd = 23.9 ± 7.0 I) or the volume of distribution relative to body weight (Vs = 0.36 ± 0.10 1·kg−1. The volume of distribution was increased with respect to the usual value of 0.25 1·kg−1. The statistical distribution of these pharmacokinetic parameters was approximately gaussian, with no significant correlation between volume of distribution and clearance. The medians and standard deviations of Cs and Vs were used as reference population values to estimate the pharmacokinetics of amikacin in a second group of 29 patients by the bayesian method, with two blood samples per patient. For each patient, the fitted parameters were able to predict the plasma concentrations of amikacin during the next 72 h with no significant bias and good precision (2.9 mg·1−1 for peaks and 0.5 mg·1−1 for troughs). This study confirms the ability of the NPEM algorithm to provide reference population values for use in bayesian monitoring of aminoglycoside therapy. |
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Keywords: | amikacin population pharmacokinetics NPEM algorithm bayesian estimation predictive performance |
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