Literature DB >> 29931573

Optimizing target control of the vessel rich group with volatile anesthetics.

Christopher W Connor1,2.   

Abstract

The ability to monitor the inspired and expired concentrations of volatile anesthetic gases in real time makes these drugs implicitly targetable. However, the end-tidal concentration only represents the concentration within the brain and the vessel rich group (VRG) at steady state, and very poorly approximates the VRG concentration during common dynamic situations such as initial uptake and emergence. How should the vaporization of anesthetic gases be controlled in order to optimally target VRG concentration in clinical practice? Using a generally accepted pharmacokinetic model of uptake and redistribution, a transfer function from the vaporizer setting to the VRG is established and transformed to the time domain. Targeted actuation of the vaporizer in a time-optimal manner is produced by a variable structure, sliding mode controller. Direct mathematical application of the controller produces rapid cycling at the limits of the vaporizer, further prolonged by low fresh gas flows. This phenomenon, known as "chattering", is unsuitable for operating real equipment. Using a simple and clinically intuitive modification to the targeting algorithm, a variable low-pass boundary layer is applied to the actuation, smoothing discontinuities in the control law and practically eliminating chatter without prolonging the time taken to reach the VRG target concentration by any clinically significant degree. A model is derived for optimum VRG-targeted control of anesthetic vaporizers. An alternate and further application is described, in which deliberate perturbation of the vaporization permits non-invasive estimation of parameters such as cardiac output that are otherwise difficult to measure intra-operatively.

Entities:  

Keywords:  Anesthesia vaporizer design; Control theory; Inhalational anesthesia; Intraoperative monitoring; Pharmacokinetics of anesthetic gases; System identification

Mesh:

Substances:

Year:  2018        PMID: 29931573      PMCID: PMC6309525          DOI: 10.1007/s10877-018-0169-5

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


  24 in total

1.  Target controlled infusions: targeting the effect site while limiting peak plasma concentration.

Authors:  Guido E Van Poucke; Louis J Brandon Bravo; Steven L Shafer
Journal:  IEEE Trans Biomed Eng       Date:  2004-11       Impact factor: 4.538

Review 2.  Inhaled anesthesia: the original closed-loop drug administration paradigm.

Authors:  D K Gupta; E I Eger
Journal:  Clin Pharmacol Ther       Date:  2008-07       Impact factor: 6.875

3.  Testing computer-controlled infusion pumps by simulation.

Authors:  S L Shafer; L C Siegel; J E Cooke; J C Scott
Journal:  Anesthesiology       Date:  1988-02       Impact factor: 7.892

Review 4.  Cardiac output monitoring: a contemporary assessment and review.

Authors:  Robert H Thiele; Karsten Bartels; Tong J Gan
Journal:  Crit Care Med       Date:  2015-01       Impact factor: 7.598

Review 5.  Minimally invasive or noninvasive cardiac output measurement: an update.

Authors:  Lisa Sangkum; Geoffrey L Liu; Ling Yu; Hong Yan; Alan D Kaye; Henry Liu
Journal:  J Anesth       Date:  2016-03-09       Impact factor: 2.078

6.  Minimum alveolar anesthetic concentration: a standard of anesthetic potency.

Authors:  E I Eger; L J Saidman; B Brandstater
Journal:  Anesthesiology       Date:  1965 Nov-Dec       Impact factor: 7.892

7.  Continuous pulmonary capillary blood flow estimation from measurements of respiratory anesthetic gas concentration.

Authors:  G Akman; H Kaufman; R Roy
Journal:  IEEE Trans Biomed Eng       Date:  1985-12       Impact factor: 4.538

8.  Noninvasive cardiac output determination for children by the inert gas-rebreathing method.

Authors:  Gesa Wiegand; Gunter Kerst; Winfried Baden; Michael Hofbeck
Journal:  Pediatr Cardiol       Date:  2010-10-13       Impact factor: 1.655

9.  The effect of a model-based predictive display on the control of end-tidal sevoflurane concentrations during low-flow anesthesia.

Authors:  R Ross Kennedy; Richard A French; Sandra Gilles
Journal:  Anesth Analg       Date:  2004-10       Impact factor: 5.108

10.  Assessing the clinical or pharmaco-economical benefit of target controlled desflurane delivery in surgical patients using the Zeus anaesthesia machine.

Authors:  B Lortat-Jacob; V Billard; W Buschke; F Servin
Journal:  Anaesthesia       Date:  2009-11       Impact factor: 6.955

View more
  2 in total

1.  Context-sensitive decrement times for inhaled anesthetics in obese patients explored with Gas Man®.

Authors:  Jonas Weber; Johannes Schmidt; Steffen Wirth; Stefan Schumann; James H Philip; Leopold H J Eberhart
Journal:  J Clin Monit Comput       Date:  2020-02-17       Impact factor: 2.502

Review 2.  End of year summary 2019: anaesthesia and airway management.

Authors:  Jan F A Hendrickx; Tom Van Zundert; Andre M De Wolf
Journal:  J Clin Monit Comput       Date:  2020-01-02       Impact factor: 2.502

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.