Target controlled infusion of rocuronium: analysis of effect data to select a pharmacokinetic model

We aimed to evaluate whether area under the curve (AUC) analysis of pharmacodynamic data can be used to compare pharmacokinetic models taken from the literature, during a target controlled infusion (TCI) of rocuronium. Seventy-two patients scheduled for orthopaedic surgery received a TCI of rocuroni...

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Veröffentlicht in:British journal of anaesthesia : BJA 2003-02, Vol.90 (2), p.183-188
Hauptverfasser: Vermeyen, K. M., Hoffmann, V. L., Saldien, V.
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Sprache:eng
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Zusammenfassung:We aimed to evaluate whether area under the curve (AUC) analysis of pharmacodynamic data can be used to compare pharmacokinetic models taken from the literature, during a target controlled infusion (TCI) of rocuronium. Seventy-two patients scheduled for orthopaedic surgery received a TCI of rocuronium (Stanpump) based on one of four pharmacokinetic models: those described by Szenohradszky, Alvarez-Gomez, Wierda, and Cooper. The resulting theoretical plasma concentration versus time curve was calculated for all patients based on all four pharmacokinetic models. Predicted effect versus time curves were calculated following the pharmacokinetic–pharmacodynamic link model (Sheiner and colleagues). Neuromuscular block was evaluated acceleromyographically. The difference between the area under the observed effect (AUCOE) and predicted effect (AUCPE) versus time curves was used for comparison. AUCPE differed significantly from AUCOE in the Szenohradszky and Alvarez-Gomez models, both with the reference link-pharmacodynamic data and with altered link-pharmacodynamic variables. AUCPE and AUCOE were comparable for the Wierda and Cooper models. The mean AUCOE was 25.1 (sd 11.9)% block×h. AUCPE–AUCOE was significantly larger in the Szenohradszky model when compared with all other pharmacokinetic models. This difference remained when link or pharmacodynamic variables were modified. The smallest AUCPE–AUCOE difference was found with the Wierda model. It was possible to use AUC analysis for identification of the pharmacokinetic model that best predicted the pharmacodynamic characteristics of our patients.
ISSN:0007-0912
1471-6771
DOI:10.1093/bja/aeg043