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BJA Advance Access originally published online on March 18, 2009
British Journal of Anaesthesia 2009 102(5):626-632; doi:10.1093/bja/aep043
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© The Author [2009]. Published by Oxford University Press on behalf of The Board of Directors of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournal.org

Evaluation of the predictive performance of four pharmacokinetic models for propofol

J. B. Glen1,* and F. Servin2

1 Research Department, Glen Pharma Ltd, 35A Bexton Road, Knutsford, Cheshire, UK
2 Department of Anaesthesia, University Hospital Centre, Hopital Bichat, 75877 Paris, France

* Corresponding author. E-mail: jbg{at}glenpharma.com

Background: This study has compared the predictive performance of four pharmacokinetic models, two of which are currently incorporated in commercial target-controlled infusion pumps for the administration of propofol.

Methods: Arterial propofol concentrations and patient characteristic data were available from nine patients who, in a published study, had received a standardized infusion of propofol. Predicted concentrations with ‘Diprifusor’ (Marsh), ‘Schnider’, ‘Schuttler’, and ‘White’ models were obtained by computer simulation. The predictive performance of each model was assessed overall and over the following phases: rapid infusion (1–5 min), early (1–21 min), maintenance (21-min end-infusion), and recovery (2–20 min post-infusion).

Results: The overall assessment, based on 29–36 samples from each patient, indicated that all four models were clinically acceptable. However, the negligible bias (–0.1%) with the ‘Schnider’ model was accompanied by overprediction in the rapid infusion phase and underprediction during recovery. This changing bias over time was not detected as ‘divergence’ when assessed on absolute performance error (APE), (1.4% h–1) but became significant (13.2% h–1) when based on changes in signed PE over time. The ‘Schuttler’ model performed well at most phases but overpredicted concentrations during recovery. The White model led to a marginal improvement over ‘Diprifusor’ and would be expected to reduce the positive bias usually seen with ‘Diprifusor’ systems.

Conclusions: In assessing the predictive performance of pharmacokinetic models, additional information can be obtained by analysis of bias at different phases of an infusion. The evaluation of divergence should involve linear regression analysis of both absolute and signed PEs.

Keywords: anaesthetics i.v., propofol; computer simulation; drug delivery, computerized; pharmacokinetics, models; pharmacokinetics, propofol


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