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Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol

BACKGROUND: We investigated how one pharmacokinetic (PK) model differed in prediction of plasma (C(p)) and effect-site concentration (C(eff)) using a reproducing simulation of target-controlled infusion (TCI) with another PK model of propofol. METHODS: Sixty female patients were randomly assigned to...

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Autores principales: Kim, Jong-Yeop, Kim, Dae-Hee, Lee, A-Ram, Moon, Bong-Ki, Min, Sang-Kee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Anesthesiologists 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3337375/
https://www.ncbi.nlm.nih.gov/pubmed/22558495
http://dx.doi.org/10.4097/kjae.2012.62.4.309
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author Kim, Jong-Yeop
Kim, Dae-Hee
Lee, A-Ram
Moon, Bong-Ki
Min, Sang-Kee
author_facet Kim, Jong-Yeop
Kim, Dae-Hee
Lee, A-Ram
Moon, Bong-Ki
Min, Sang-Kee
author_sort Kim, Jong-Yeop
collection PubMed
description BACKGROUND: We investigated how one pharmacokinetic (PK) model differed in prediction of plasma (C(p)) and effect-site concentration (C(eff)) using a reproducing simulation of target-controlled infusion (TCI) with another PK model of propofol. METHODS: Sixty female patients were randomly assigned to TCI using Marsh PK (Group M) and TCI using Schnider PK (Group S) targeting 6.0 µg/ml of C(p) of propofol for induction of anesthesia, and loss of responsiveness (LOR) was evaluated. Total and separate cross-simulation were investigated using the 2 hr TCI data (Marsh TCI and Schnider TCI), and we investigated the reproduced predicted concentrations (MARSH(SCH) and SCHNIDER(MAR)) using the other model. The correlation of the difference with covariates, and the influence of the PK parameters on the difference of prediction were investigated. RESULTS: Group M had a shorter time to LOR compared to Group S (P < 0.001), but C(eff) at LOR was not different between groups. Reproduced simulations showed different time courses of C(p). MARSH(SCH) predicted a higher concentration during the early phase, whereas SCHNIDER(MAR) was maintained at a higher concentration. Volume and clearance of the central compartment were relevant to the difference of prediction, respectively. Body weight correlated well with differences in prediction between models (R(sqr) = 0.9821, P < 0.001). CONCLUSIONS: We compared two PK models to determine the different infusion behaviors during TCI, which resulted from the different parameter sets for each PK model.
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spelling pubmed-33373752012-05-03 Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol Kim, Jong-Yeop Kim, Dae-Hee Lee, A-Ram Moon, Bong-Ki Min, Sang-Kee Korean J Anesthesiol Clinical Research Article BACKGROUND: We investigated how one pharmacokinetic (PK) model differed in prediction of plasma (C(p)) and effect-site concentration (C(eff)) using a reproducing simulation of target-controlled infusion (TCI) with another PK model of propofol. METHODS: Sixty female patients were randomly assigned to TCI using Marsh PK (Group M) and TCI using Schnider PK (Group S) targeting 6.0 µg/ml of C(p) of propofol for induction of anesthesia, and loss of responsiveness (LOR) was evaluated. Total and separate cross-simulation were investigated using the 2 hr TCI data (Marsh TCI and Schnider TCI), and we investigated the reproduced predicted concentrations (MARSH(SCH) and SCHNIDER(MAR)) using the other model. The correlation of the difference with covariates, and the influence of the PK parameters on the difference of prediction were investigated. RESULTS: Group M had a shorter time to LOR compared to Group S (P < 0.001), but C(eff) at LOR was not different between groups. Reproduced simulations showed different time courses of C(p). MARSH(SCH) predicted a higher concentration during the early phase, whereas SCHNIDER(MAR) was maintained at a higher concentration. Volume and clearance of the central compartment were relevant to the difference of prediction, respectively. Body weight correlated well with differences in prediction between models (R(sqr) = 0.9821, P < 0.001). CONCLUSIONS: We compared two PK models to determine the different infusion behaviors during TCI, which resulted from the different parameter sets for each PK model. The Korean Society of Anesthesiologists 2012-04 2012-04-23 /pmc/articles/PMC3337375/ /pubmed/22558495 http://dx.doi.org/10.4097/kjae.2012.62.4.309 Text en Copyright © the Korean Society of Anesthesiologists, 2012 http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Research Article
Kim, Jong-Yeop
Kim, Dae-Hee
Lee, A-Ram
Moon, Bong-Ki
Min, Sang-Kee
Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
title Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
title_full Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
title_fullStr Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
title_full_unstemmed Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
title_short Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
title_sort cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol
topic Clinical Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3337375/
https://www.ncbi.nlm.nih.gov/pubmed/22558495
http://dx.doi.org/10.4097/kjae.2012.62.4.309
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