title: Cefepime in intensive care unit patients: validation of a population pharmacokinetic approach and influence of covariables.
abstract: OBJECTIVE
  The purpose of our study was to define and validate a population-pharmacokinetic model including the influence of patients' characteristics on the pharmacokinetics of cefepime.
  
  
  METHODS
  A total of 55 patients were randomized in Group 1 (34 patients, 320 cefepime concentrations) for the model building and Group 2 (21 patients, 196 cefepime concentrations) for the validation group. They received cefepime as 2 g A 2 or as 4 g continuously. The population pharmacokinetic analysis was carried out using NONMEM and a baseline model was constructed for studying the influence of demographic and biological variables. The model was then validated by a comparison of the predicted and observed concentrations in Group 2. A final model was elaborated from the whole population.
  
  
  RESULTS
  Total clearance (CL) was significantly correlated with the serum creatinine (CREA) and the central volume of distribution (V1) was correlated with the body weight (WT). The final model was: CL = 7.14 + (-0.0133 A CREA). V1 = (-16.8) + (0.475 A WT). Q (intercompartmental clearance) = 10.5. V2 = 18.1. The mean pharmacokinetic parameters and their individual variability were: CL (8.24 l/h, 45%), V1 (20.89 l, 60%), V2 (17.95 l, 49%), total volume (38.85 l, 42%) and Q (10.56 l/h, 9%). The bias (1.07 mg/l, IC 95% = -40.46 -+42.60), precision (21.19%) and AFE (1.15) demonstrated the performance of the model.
  
  
  CONCLUSIONS
  We have developed and validated a pharmacokinetic model to estimate cefepime concentrations. We showed that serum creatinine and body weight are factors that may influence the standard dose of cefepime. Our model enabled us to predict cefepime concentrations in other patients.
authors.affiliation: Anesthésie Réanimation, CHU Rangueil, Toulouse, France.
authors.forename: B
authors.initials: B
authors.lastname: Georges
authors.forename: J-M
authors.initials: JM
authors.lastname: Conil
authors.forename: T
authors.initials: T
authors.lastname: Seguin
authors.forename: E
authors.initials: E
authors.lastname: Dieye
authors.forename: P
authors.initials: P
authors.lastname: Cougot
authors.forename: J-F
authors.initials: JF
authors.lastname: Decun
authors.forename: M
authors.initials: M
authors.lastname: Lavit
authors.forename: K
authors.initials: K
authors.lastname: Samii
authors.forename: G
authors.initials: G
authors.lastname: Houin
authors.forename: S
authors.initials: S
authors.lastname: Saivin
mesh_terms: D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D016470:Bacteremia / Q000188:drug therapy / Q000378:metabolism; D000077723:Cefepime; D002511:Cephalosporins / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D003404:Creatinine / Q000097:blood; D003428:Cross Infection / Q000188:drug therapy / Q000378:metabolism; D005602:France; D006801:Humans; D007262:Infusions, Intravenous; D007362:Intensive Care Units; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D008954:Models, Biological; D017711:Nonlinear Dynamics; D011446:Prospective Studies
chemical_list: D000900:Anti-Bacterial Agents; D002511:Cephalosporins; D000077723:Cefepime; D003404:Creatinine