Literature DB >> 29210791

Design and Evaluation of a Closed-Loop Anesthesia System With Robust Control and Safety System.

Nicholas West1, Klaske van Heusden2, Matthias Görges1,3, Sonia Brodie1, Aryannah Rollinson1, Christian L Petersen1, Guy A Dumont2,3, J Mark Ansermino1,3, Richard N Merchant1,4.   

Abstract

BACKGROUND: Closed-loop control of anesthesia involves continual adjustment of drug infusion rates according to measured clinical effect. The NeuroSENSE monitor provides an electroencephalographic measure of depth of hypnosis (wavelet-based anesthetic value for central nervous system monitoring [WAVCNS]). It has previously been used as feedback for closed-loop control of propofol, in a system designed using robust control engineering principles, which implements features specifically designed to ensure patient safety. Closed-loop control of a second drug, remifentanil, may be added to improve WAVCNS stability in the presence of variable surgical stimulation. The objective of this study was to design and evaluate the feasibility of a closed-loop system for robust control of propofol and remifentanil infusions using WAVCNS feedback, with an infusion safety system based on the known pharmacological characteristics of these 2 drugs.
METHODS: With Health Canada authorization, research ethics board approval, and informed consent, American Society of Anesthesiologists I-III adults, requiring general anesthesia for elective surgery, were enrolled in a 2-phase study. In both phases, infusion of propofol was controlled in closed loop during induction and maintenance of anesthesia, using WAVCNS feedback, but bounded by upper- and lower-estimated effect-site concentration limits. In phase I, remifentanil was administered using an adjustable target-controlled infusion and a controller was designed based on the collected data. In phase II, remifentanil was automatically titrated to counteract rapid increases in WAVCNS.
RESULTS: Data were analyzed for 127 patients, of median (range) age 64 (22-86) years, undergoing surgical procedures lasting 105 (9-348) minutes, with 52 participating in phase I and 75 in phase II. The overall control performance indicator, global score, was a median (interquartile range) 18.3 (14.2-27.7) in phase I and 14.6 (11.6-20.7) in phase II (median difference, -3.25; 95% confidence interval, -6.35 to -0.52). The WAVCNS was within ±10 of the setpoint for 84.3% (76.6-90.6) of the maintenance of anesthesia in phase I and 88.2% (83.1-93.4) in phase II (median difference, 3.7; 95% confidence interval, 0.1-6.9). The lower propofol safety bound was activated during 30 of 52 (58%) cases in phase I and 51 of 75 (68%) cases in phase II.
CONCLUSIONS: Adding closed-loop control of remifentanil improved overall controller performance. This controller design offers a robust method to optimize the control of 2 drugs using a single sensor. The infusion safety system is an important component of a robust automated anesthesia system, but further research is required to determine the optimal constraints for these safe conditions.

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Year:  2018        PMID: 29210791     DOI: 10.1213/ANE.0000000000002663

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


  4 in total

1.  Optimizing Robust PID Control of Propofol Anesthesia for Children: Design and Clinical Evaluation.

Authors:  Klaske van Heusden; Kristian Soltesz; Erin Cooke; Sonia Brodie; Nicholas West; Matthias Gorges; J Mark Ansermino; Guy A Dumont
Journal:  IEEE Trans Biomed Eng       Date:  2019-02-08       Impact factor: 4.538

Review 2.  Intelligent automated drug administration and therapy: future of healthcare.

Authors:  Richa Sharma; Dhirendra Singh; Prerna Gaur; Deepak Joshi
Journal:  Drug Deliv Transl Res       Date:  2021-01-14       Impact factor: 4.617

Review 3.  Artificial intelligence and anesthesia: a narrative review.

Authors:  Valentina Bellini; Emanuele Rafano Carnà; Michele Russo; Fabiola Di Vincenzo; Matteo Berghenti; Marco Baciarello; Elena Bignami
Journal:  Ann Transl Med       Date:  2022-05

4.  Pain Detection with Bioimpedance Methodology from 3-Dimensional Exploration of Nociception in a Postoperative Observational Trial.

Authors:  Martine Neckebroek; Mihaela Ghita; Maria Ghita; Dana Copot; Clara M Ionescu
Journal:  J Clin Med       Date:  2020-03-04       Impact factor: 4.241

  4 in total

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