Literature DB >> 27294779

Adaptive pharmacokinetic and pharmacodynamic modelling to predict propofol effect using BIS-guided anesthesia.

I Martín-Mateos1, J A Méndez Pérez2, J A Reboso Morales3, J F Gómez-González1.   

Abstract

BACKGROUND AND
OBJECTIVE: Propofol is widely used for hypnosis induction and maintenance of general anesthesia. Its effect can be assessed using the bispectral index (BIS). Many automatic infusion systems are based in pharmacokinetics (PK) and pharmacodynamics (PD) models to predict the response of the patient to the drug. However, all these models do not take into account intra and inter-patient variability. An adjusted intraoperative drug administration allows faster recovery and provides post-operative side-effect mitigation
METHODS: BIS evolution and surgery-recorded propofol infusion data of a group of 60 adult patients (30 males/30 females) with ASA I/II physical status were used to test a real time PK/PD compartmental model. This new algorithm tunes three model parameters (ce50, γ and ke0), minimizing a performance function online.
RESULTS: The error in the BIS signal predicted by the real time PK/PD model was smaller than the error measured with fixed parameter equations. This model shows that ce50, γ and ke0 change with time and patients, given a mean (95% confidence interval) of 3.89 (3.52-4.26)mg/l, 4.63 (4.13-5.13) and 0.36 (0.31-0.4)min(-1), respectively.
CONCLUSIONS: The real time PK/PD model proposed provides a closer description of the patient real state at each sample time. This allows for greater control of the drug infusion, and thus the quantity of drug administered can be titrated to achieve the desired effect for the desired duration, and reduce unnecessary waste or post-operative effects.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Anesthesia modelling; Bispectral Index; Compartmental model; Pharmacokinetics and pharmacodynamics model; Propofol; Real time

Mesh:

Substances:

Year:  2016        PMID: 27294779     DOI: 10.1016/j.compbiomed.2016.06.007

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  3 in total

Review 1.  Power spectrum and spectrogram of EEG analysis during general anesthesia: Python-based computer programming analysis.

Authors:  Teiji Sawa; Tomomi Yamada; Yurie Obata
Journal:  J Clin Monit Comput       Date:  2021-10-29       Impact factor: 1.977

2.  Control strategy with multivariable fault tolerance module for automatic intravenous anesthesia.

Authors:  Bhavina Patel; Hirenkumar Patel; Divyang Shah; Alpesh Sarvaia
Journal:  Biomed Eng Lett       Date:  2020-08-16

Review 3.  A Review of Modern Control Strategies for Clinical Evaluation of Propofol Anesthesia Administration Employing Hypnosis Level Regulation.

Authors:  Muhammad Ilyas; Muhammad Fasih Uddin Butt; Muhammad Bilal; Khalid Mahmood; Ali Khaqan; Raja Ali Riaz
Journal:  Biomed Res Int       Date:  2017-03-30       Impact factor: 3.411

  3 in total

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