Cedrick Zaouter1, Thomas M Hemmerling, Romain Lanchon, Emanuela Valoti, Alain Remy, Sébastien Leuillet, Alexandre Ouattara. 1. From the *CHU de Bordeaux, Service d Anesthésie-Réanimation II, Bordeaux, France; †Division of Experimental Surgery, Department of Anaesthesia, Arnold and Blema Steinberg Simulation Centre, McGill University, Montreal, Canada; ‡Servizio di Anestesia Rianimazione e terapia intensiva, Università degli Studi di Pavia, Dip. Scienze Clinico-Chirurgiche Diagnostiche e Pediatriche, Unità di Anestesiologia - Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; and §Biofortis, Mérieux NutriSciences Company, Saint-Herblain, France.
Abstract
BACKGROUND: In this pilot study, we tested a novel automatic anesthesia system for closed-loop administration of IV anesthesia drugs for cardiac surgical procedures with cardiopulmonary bypass. This anesthesia drug delivery robot integrates all 3 components of general anesthesia: hypnosis, analgesia, and muscle relaxation. METHODS: Twenty patients scheduled for elective cardiac surgery with cardiopulmonary bypass were enrolled. Propofol, remifentanil, and rocuronium were administered using closed-loop feedback control. The main objective was the feasibility of closed-loop anesthesia defined as successful automated cardiac anesthesia without manual override by the attending anesthesiologist. Secondary qualitative observations were clinical and controller performances. The clinical performance of hypnosis control was the efficacy to maintain a bispectral index (BIS) of 45. To evaluate the hypnosis performance, BIS values were stratified into 4 categories: "excellent," "good," "poor," and "inadequate" hypnosis control defined as BIS values within 10%, ranging from 11% to 20%, ranging from 21% to 30%, or >30% of the target value, respectively. The clinical performance of analgesia was the efficacy to maintain NociMap values close to 0. The analgesia performance was assessed classifying the NociMap values in 3 pain control groups: -33 to +33 representing excellent pain control, -34 to -66 and +34 to +66 representing good pain control, and -67 to -100 and +67 to +100 representing insufficient pain control. The controller performance was calculated using the Varvel parameters. RESULTS: Robotic anesthesia was successful in 16 patients, which is equivalent to 80% (97.5% confidence interval [CI], 53%-95%) of the patients undergoing cardiac surgery. Four patients were excluded from the final analysis because of technical problems with the automated anesthesia delivery system. The secondary qualitative observations revealed that the clinical performance of hypnosis allowed an excellent and good control during 70% (97.5% CI, 63%-76%) of maintenance time and an insufficient clinical performance of analgesia for only 3% (97.5% CI, 1%-6%) of maintenance time. CONCLUSIONS: The completely automated closed-loop system tested in this investigation could be used successfully and safely for cardiac surgery necessitating cardiopulmonary bypass. The results of the present trial showed satisfactory clinical performance of anesthesia control.
BACKGROUND: In this pilot study, we tested a novel automatic anesthesia system for closed-loop administration of IV anesthesia drugs for cardiac surgical procedures with cardiopulmonary bypass. This anesthesia drug delivery robot integrates all 3 components of general anesthesia: hypnosis, analgesia, and muscle relaxation. METHODS: Twenty patients scheduled for elective cardiac surgery with cardiopulmonary bypass were enrolled. Propofol, remifentanil, and rocuronium were administered using closed-loop feedback control. The main objective was the feasibility of closed-loop anesthesia defined as successful automated cardiac anesthesia without manual override by the attending anesthesiologist. Secondary qualitative observations were clinical and controller performances. The clinical performance of hypnosis control was the efficacy to maintain a bispectral index (BIS) of 45. To evaluate the hypnosis performance, BIS values were stratified into 4 categories: "excellent," "good," "poor," and "inadequate" hypnosis control defined as BIS values within 10%, ranging from 11% to 20%, ranging from 21% to 30%, or >30% of the target value, respectively. The clinical performance of analgesia was the efficacy to maintain NociMap values close to 0. The analgesia performance was assessed classifying the NociMap values in 3 pain control groups: -33 to +33 representing excellent pain control, -34 to -66 and +34 to +66 representing good pain control, and -67 to -100 and +67 to +100 representing insufficient pain control. The controller performance was calculated using the Varvel parameters. RESULTS: Robotic anesthesia was successful in 16 patients, which is equivalent to 80% (97.5% confidence interval [CI], 53%-95%) of the patients undergoing cardiac surgery. Four patients were excluded from the final analysis because of technical problems with the automated anesthesia delivery system. The secondary qualitative observations revealed that the clinical performance of hypnosis allowed an excellent and good control during 70% (97.5% CI, 63%-76%) of maintenance time and an insufficient clinical performance of analgesia for only 3% (97.5% CI, 1%-6%) of maintenance time. CONCLUSIONS: The completely automated closed-loop system tested in this investigation could be used successfully and safely for cardiac surgery necessitating cardiopulmonary bypass. The results of the present trial showed satisfactory clinical performance of anesthesia control.
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
Authors: Johannes Boltze; Jaroslaw A Aronowski; Jerome Badaut; Marion S Buckwalter; Mateo Caleo; Michael Chopp; Kunjan R Dave; Nadine Didwischus; Rick M Dijkhuizen; Thorsten R Doeppner; Jens P Dreier; Karim Fouad; Mathias Gelderblom; Karen Gertz; Dominika Golubczyk; Barbara A Gregson; Edith Hamel; Daniel F Hanley; Wolfgang Härtig; Friedhelm C Hummel; Maulana Ikhsan; Miroslaw Janowski; Jukka Jolkkonen; Saravanan S Karuppagounder; Richard F Keep; Inga K Koerte; Zaal Kokaia; Peiying Li; Fudong Liu; Ignacio Lizasoain; Peter Ludewig; Gerlinde A S Metz; Axel Montagne; Andre Obenaus; Alex Palumbo; Monica Pearl; Miguel Perez-Pinzon; Anna M Planas; Nikolaus Plesnila; Ami P Raval; Maria A Rueger; Lauren H Sansing; Farida Sohrabji; Charlotte J Stagg; R Anne Stetler; Ann M Stowe; Dandan Sun; Akihiko Taguchi; Mickael Tanter; Sabine U Vay; Raghu Vemuganti; Denis Vivien; Piotr Walczak; Jian Wang; Ye Xiong; Marietta Zille Journal: Front Aging Neurosci Date: 2021-01-28 Impact factor: 5.750