Literature DB >> 18806028

The accuracy and clinical feasibility of a new bayesian-based closed-loop control system for propofol administration using the bispectral index as a controlled variable.

Tom De Smet1, Michel M R F Struys, Martine M Neckebroek, Kristof Van den Hauwe, Sjoert Bonte, Eric P Mortier.   

Abstract

BACKGROUND: Closed-loop control of the hypnotic component of anesthesia has been proposed in an attempt to optimize drug delivery. Here, we introduce a newly developed Bayesian-based, patient-individualized, model-based, adaptive control method for bispectral index (BIS) guided propofol infusion into clinical practice and compare its accuracy and clinical feasibility under direct observation of an anesthesiologist versus BIS guided, effect compartment controlled propofol administration titrated by the anesthesiologist during ambulatory gynecological procedures.
METHODS: Forty ASA patients were randomly allocated to the closed-loop or manual control group. All patients received midazolam 1 mg IV and alfentanil 0.5 mg IV before induction. In the closed-loop control group, propofol was administered using the previously described closed-loop control system to reach and maintain a target BIS of 50. In the manual control group, the propofol effect-site concentration was adapted at the discretion of the anesthesiologist to reach and maintain a BIS as close as possible to 50. Induction characteristics, performance, and robustness during maintenance and recovery times were compared. Hemodynamic and respiratory stability were calculated as clinical feasibility parameters.
RESULTS: The closed-loop control system titrated propofol administration accurately resulting in BIS values close to the set point. The closed-loop control system was able to induce the patients within clinically accepted time limits and with less overshoot than the manual control group. Automated control resulted in beneficial recovery times. Our closed-loop control group showed similar acceptable clinical performance specified by similar hemodynamic, respiratory stability, comparable movement rates, and quality scores than the manual control group.
CONCLUSIONS: The Bayesian-based closed-loop control system for propofol administration using the BIS as a controlled variable performed accurate during anesthesia for ambulatory gynecological procedures. This control system is clinical feasibility and can be further validated in clinical practice.

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Year:  2008        PMID: 18806028     DOI: 10.1213/ane.0b013e31817bd1a6

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  14 in total

1.  [Feedback control of depth of anesthesia during propofol administration. Bispectral index as the controlled variable].

Authors:  M Janda; J Bajorat; O Simanski; R Kähler; B Pohl; G F E Nöldge-Schomburg; R Hofmockel
Journal:  Anaesthesist       Date:  2010-07       Impact factor: 1.041

2.  Dynamic behavior of BIS, M-entropy and neuroSENSE brain function monitors.

Authors:  Stéphane Bibian; Guy A Dumont; Tatjana Zikov
Journal:  J Clin Monit Comput       Date:  2010-12-05       Impact factor: 2.502

3.  Rocuronium: automatic infusion versus manual administration with TOF monitorisation.

Authors:  Fatma Gulcin Ozturk Arikan; Guldem Turan; Asu Ozgultekin; Zubeyir Sivrikaya; Bekir Cem Cosar; Dondu Nisa Onder
Journal:  J Clin Monit Comput       Date:  2015-08-18       Impact factor: 2.502

4.  A novel system for automated propofol sedation: hybrid sedation system (HSS).

Authors:  Cedrick Zaouter; Riccardo Taddei; Mohamad Wehbe; Erik Arbeid; Shantale Cyr; Francesco Giunta; Thomas M Hemmerling
Journal:  J Clin Monit Comput       Date:  2016-03-12       Impact factor: 2.502

5.  Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective.

Authors:  Hamzeh Khazaei; Nadja Mench-Bressan; Carolyn McGregor; James Edward Pugh
Journal:  IEEE J Transl Eng Health Med       Date:  2015-10-01       Impact factor: 3.316

6.  A closed-loop anesthetic delivery system for real-time control of burst suppression.

Authors:  Max Y Liberman; Shinung Ching; Jessica Chemali; Emery N Brown
Journal:  J Neural Eng       Date:  2013-06-07       Impact factor: 5.379

7.  Robust control of burst suppression for medical coma.

Authors:  M Brandon Westover; Seong-Eun Kim; ShiNung Ching; Patrick L Purdon; Emery N Brown
Journal:  J Neural Eng       Date:  2015-05-28       Impact factor: 5.379

8.  Real-time closed-loop control in a rodent model of medically induced coma using burst suppression.

Authors:  ShiNung Ching; Max Y Liberman; Jessica J Chemali; M Brandon Westover; Jonathan D Kenny; Ken Solt; Patrick L Purdon; Emery N Brown
Journal:  Anesthesiology       Date:  2013-10       Impact factor: 7.892

9.  A brain-machine interface for control of medically-induced coma.

Authors:  Maryam M Shanechi; Jessica J Chemali; Max Liberman; Ken Solt; Emery N Brown
Journal:  PLoS Comput Biol       Date:  2013-10-31       Impact factor: 4.475

Review 10.  Medical devices for the anesthetist: current perspectives.

Authors:  Jerry Ingrande; Hendrikus Jm Lemmens
Journal:  Med Devices (Auckl)       Date:  2014-03-25
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