title: Population pharmacokinetics of propofol in Chinese patients.
abstract: OBJECTIVE
  To analyze population pharmacokinetics of propofol in Chinese surgical patients using a nonlinear mixed-effect model (NONMEM) program and to quantitate the effects of covariance of gender, age, and body weight.
  
  
  METHODS
  The population pharmacokinetics of propofol was investigated in 76 selective surgical patients (37 males and 39 females aged 19-77 a, weighing 39-86 kg). A total of 1439 blood samples were analyzed using NONMEM (NONMEM Project Group, University of California, San Francisco, CA). Interindividual variability was estimated for clearances and distribution volumes. The effects of age, body weight, and gender were investigated.
  
  
  RESULTS
  The pharmacokinetics of propofol in Chinese patients was best described by a three-compartment pharmacokinetic model. Body weight was found to be a significant factor for the elimination clearance, the two inter-compartmental clearances, and the volume of the central compartment. The volumes of the shallow peripheral compartment and deep peripheral compartment remain constant for all individuals. The estimates of these parameters for a 60-kg adult were 1.56 L/min, 0.737 L/min, 0.360 L/min, 12.1 L, 43 L, and 213 L, respectively. For old patients, the elimination clearance and volume of the central compartment decreased.
  
  
  CONCLUSIONS
  The pharmacokinetics of propofol in Chinese patients can be well described by a standard three-compartment pharmacokinetic model. Inclusion of age and body weight as covariances significantly improved the model. Adjusting pharmacokinetics to the individual patients should improve the precision of target-controlled infusion system.
authors.affiliation: The School of Life Science, Nanjing University, Nanjing 210093, China. Xujguo@hotmail.com
authors.forename: Yu-Hong
authors.initials: YH
authors.lastname: Li
authors.forename: Jian-Zhong
authors.initials: JZ
authors.lastname: Rui
authors.forename: Yong-Gang
authors.initials: YG
authors.lastname: Zhou
authors.forename: Li-Qin
authors.initials: LQ
authors.lastname: Wang
authors.forename: Su-E
authors.initials: SE
authors.lastname: Fu
authors.forename: Jian-Jun
authors.initials: JJ
authors.lastname: Yang
authors.forename: Fu-Kun
authors.initials: FK
authors.lastname: Liu
authors.forename: Shu-Ya
authors.initials: SY
authors.lastname: Hu
authors.forename: Quan
authors.initials: Q
authors.lastname: Wen
authors.forename: Jian-Guo
authors.initials: JG
authors.lastname: Xu
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D018686:Anesthetics, Intravenous / Q000493:pharmacokinetics*; D044466:Asian People; D001835:Body Weight; D002681:China; D005260:Female; D006801:Humans; D008297:Male; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D017711:Nonlinear Dynamics; D015742:Propofol / Q000493:pharmacokinetics*
chemical_list: D018686:Anesthetics, Intravenous; D015742:Propofol