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  • 1
    ISSN: 1573-8744
    Keywords: pefloxacin ; population pharmacokinetics ; intensive care unit ; Bayesian estimation ; NONMEM
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract The pharmacokinetics of pefloxacin (PF) were investigated in a population of 74 intensive care unit patients receiving 400 mg bid as 1-hr infusion using (i) Bayesian estimation (BE) of individual patient parameters followed by multiple linear regression (MLR) analysis and (ii) NONMEM analysis. The data consisted of 3 to 9 PF plasma levels per patient measured over 1 to 3 dosage intervals (total 113) according to four different limited (suboptimal) sampling 3-point protocols. Twenty-nine covariates (including 15 comedications) were considered to explain the interpatient variability. Predicted PFCLfor a patient with median covariates values was similar in both BE/ MLR and NONMEM analysis (4.02 and 3.92 L/hr, respectively). Bilirubin level and age were identified as the major determinants of PFCLby both approaches with similar predicted magnitude of effects (about 40 and 30% decrease of median CL,respectively). Confounding effects were observed between creatinine clearance (26% decrease of PF CLin the BE/MLR model), simplified acute physiology score (a global score based on 14 biological and clinical variables) (18% decrease of median CLin the NONMEM model) and age (entered in both models) which were highly correlated in our data base. However, both models predicted similar PF CLfor actual subpopulations by using actual covariate values. Finally, the NONMEM analysis allowed identification of an effect of weight on CL(decrease of CL for weight 〈65 kg) whereas the BE/MLR analysis predicted an increase of CLin patients treated with phenobarbital. In conclusion, both approaches allowed identification of the major risk factors of PF pharmacokinetics in ICU patients. Their potential use at different stages of drug development is discussed.
    Type of Medium: Electronic Resource
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