Literature DB >> 22127991

A direct dynamic dose-response model of propofol for individualized anesthesia care.

Jin-Oh Hahn1, Guy A Dumont, J Mark Ansermino.   

Abstract

In an effort to open up new opportunities in individualized anesthesia care, this paper presents a dynamic dose-response model of propofol that relates propofol dose (i.e., infusion rate) directly to a clinical effect. The proposed model consists of a first-order equilibration dynamics plus a nonlinear Hill equation model, each representing the transient distribution of propofol dose from the plasma to the effect site and the steady-state dose-effect relationship. Compared to traditional pharmacokinetic-pharmacodynamic (PKPD) models, the proposed model has structural parsimony and comparable predictive capability, making it more attractive than its PKPD counterpart for identifying an individualized dose-response model in real-time. The efficacy of the direct dynamic dose-response model over a traditional PKPD model was assessed using a mixed effects modeling analysis of the electroencephalogram (EEG)-based state entropty (SE) response to intravenous propofol administration in 34 pediatric subjects. An improvement in the mean-squared error and r(2) value of individual prediction, as well as the Akaike's information criterion (AIC) was seen with the direct dynamic dose-response model.
© 2011 IEEE

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Year:  2011        PMID: 22127991     DOI: 10.1109/TBME.2011.2177497

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

Review 1.  Automation of anaesthesia: a review on multivariable control.

Authors:  Jing Jing Chang; S Syafiie; Raja Kamil; Thiam Aun Lim
Journal:  J Clin Monit Comput       Date:  2014-06-25       Impact factor: 2.502

Review 2.  Regulatory Considerations for Physiological Closed-Loop Controlled Medical Devices Used for Automated Critical Care: Food and Drug Administration Workshop Discussion Topics.

Authors:  Bahram Parvinian; Christopher Scully; Hanniebey Wiyor; Allison Kumar; Sandy Weininger
Journal:  Anesth Analg       Date:  2018-06       Impact factor: 5.108

3.  Feedback control for clinicians.

Authors:  Guy A Dumont
Journal:  J Clin Monit Comput       Date:  2013-04-12       Impact factor: 2.502

  3 in total

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