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Year : 2012  |  Volume : 44  |  Issue : 3  |  Page : 393-397

Propofol pharmacokinetics in China: A multicentric study

1 Department of Pharmacology, Jinling Hospital, Nanjing city, Jiangsu, China
2 Department of Anesthesiology, First Affiliated Hospital of Xinjiang Medical University, Urlumgi city, Xinjiang, China
3 Department of Anesthesiology, Liuhuaqiao Hospital, Guangzhou city, Guangdong, China
4 Department of Anesthesiology, the Third affiliated Hospital, SUN-Yat-sen University, Guangzhou city, Guangdong, China
5 Department of Pharmacy, The first Affiliated Hospital of Guangzhou Medical College, Guangzhou city, Guandong, China
6 Department of Anesthesiology, Jinling Hospital, Nanjing city, Jiangsu, China

Correspondence Address:
Jian-zhong Rui
Department of Pharmacology, Jinling Hospital, Nanjing city, Jiangsu
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0253-7613.96346

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Objective : A multicenter population pharmacokinetics study of propofol was performed to establish a new population model. Materials and Methods : Three thousand two hundred and fifty-nine blood samples of 220 participants were measured by HPLC-UV or HPLC-FLU or GC-MS. Target-controlled infusion after single bolus or continuous infusion was applied for propofol anesthesia. The samples were taken from 2 to 1500 min. The concentration-time profiles were analyzed by nonlinear mixed effect model (NONMEM) with first order estimation method. The inter-individual variability and the residual variability were described by exponential model and constant coefficient variation model. The stepwise modeling strategy using PsN was applied for covariate modeling. The criteria of forward addition and backward elimination were (α = 0.01 and α = 0.005, χ2, df = 1). The final model was evaluated by bootstrap using PDx and visual predictive check using PsN. 500 bootstraps and 1000 simulation were run. Result : The propofol population model was described by 3-compartment model with inter-individual variability of CL, V 1 , Q 2, and Q 3 describing by exponential model. The inter-individual variability of V 2 , V 3 were not included because it is reported that the parameter was near its boundary. The typical value of CL, V1, Q2, V2, Q3 and V3 were 1.28 L · min-1 , 10.1 × (age/44)-0.465 × (1 + 0.352 × sex) L, 0.819 L · min-1 , 36.0 L, 0.405 × (bodyweight/60)1.58 L · min-1 and 272 L, respectively. Coefficients of inter-individual variability of CL, V1, Q2 and Q3 were 30.5%, 35.6%, 43.7% and 66.9%, respectively, and the coefficients of variation of HPLC-UV, GC-MS and HPLC-FLU were 13.3%, 16.9% and 24.2%, respectively. The bootstrap evaluation showed that the final model parameter estimates were within ± 3.39% compared with bootstrap median. The curves of observations percentiles were distributed within the corresponding 95 prediction percentiles by the visual predictive check. Conclusion: The three-compartment model with first-order elimination could describe the pharmacokinetics of propofol fairly well. The involved fixed effects are age, body weight and sex. The population model was evaluated to be stable by bootstrap and visual predictive check.


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