BACKGROUND: The aim of this study is to derive a propofol pharmacokinetic (PK) pharmaco-dynamic (PD) model to perform effect-site target-controlled infusion (TCI) in obese patients, and to analyze its performance along with that of other available PK models. METHODS: In the first step of the study, a 3-compartment PK model linked to a sigmoidal inhibitory E-max PD model by a first-order rate constant (keo) was used to fit propofol concentration-bispectral index (BIS) data. Population modeling analysis was performed by nonlinear mixed effects regression in NONMEM (ICON, Dublin, Ireland). PK data from 3 previous studies in obese adult patients (n = 47), including PD (BIS) data from 1 of these studies (n = 20), were pooled and simultaneously analyzed. A decrease in NONMEM objective function (Delta OBJ) of 3.84 points, for an added parameter, was considered significant at the 0.05 level. In the second step of the study, we analyzed the predictive performance (median predictive errors [MDPE] and median absolute predictive errors [MDAPE]) of the current model and of other available models using an independent data set (n = 14). RESULTS: Step 1: The selected PKPD model produced an adequate fit of the data. Total body weight resulted in the best size scalar for volumes and clearances (Delta OBJ, -18.173). Empirical allometric total body weight relationships did not improve model fit (Delta OBJ, 0.309). A lag time parameter for BIS response improved the fit (Delta OBJ, 89.593). No effect of age or gender was observed. Step 2: Current model MDPE and MDAPE were 11.5% (3.7-25.0) and 26.8% (20.7-32.6) in the PK part and 0.4% (-10.39 to 3.85) and 11.9% (20.7-32.6) in the PD part. The PK model developed by Eleveld et al resulted in the lowest PK predictive errors (MDPE = < 10% and MDAPE = < 25%). CONCLUSIONS: We derived and validated a propofol PKPD model to perform effect-site TCI in obese patients. This model, derived exclusively from obese patient's data, is not recommended for TCI in lean patients because it carries the risk of underdosing.
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Ajou Univ, Sch Med, Dept Anesthesiol & Pain Med, 164 World Cup Ro, Suwon 16499, South KoreaAjou Univ, Sch Med, Dept Anesthesiol & Pain Med, 164 World Cup Ro, Suwon 16499, South Korea
Min, Sang Kee
Choi, Gyubin
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Ajou Univ, Sch Med, Dept Anesthesiol & Pain Med, 164 World Cup Ro, Suwon 16499, South KoreaAjou Univ, Sch Med, Dept Anesthesiol & Pain Med, 164 World Cup Ro, Suwon 16499, South Korea
Choi, Gyubin
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Kim, Ji Eun
Kim, Ha Yeon
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Ajou Univ, Sch Med, Dept Anesthesiol & Pain Med, 164 World Cup Ro, Suwon 16499, South KoreaAjou Univ, Sch Med, Dept Anesthesiol & Pain Med, 164 World Cup Ro, Suwon 16499, South Korea
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Univ Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, PortugalUniv Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, Portugal
Bras, S.
Bressan, N.
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Univ Porto, Fac Engn, Oporto, PortugalUniv Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, Portugal
Bressan, N.
Ribeiro, L.
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Hosp Vet Porto, Oporto, PortugalUniv Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, Portugal
Ribeiro, L.
Ferreira, D. A.
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Univ Tras os Montes & Alto Douro, CECAV, Vila Real, PortugalUniv Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, Portugal
Ferreira, D. A.
Antunes, L.
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机构:Univ Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, Portugal
Antunes, L.
Nunes, C. S.
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Kings Coll London, Div Engn, London WC2R 2LS, EnglandUniv Porto, Inst Ciencias Biomed Abel Salazar, Hosp Geral Santo Antonio, Serv Anestesiol, Oporto, Portugal