• Esther Candries, Andre M De Wolf, and HendrickxJan F AJFADepartment of Anesthesiology, OLV Hospital, Aalst, Belgium.Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium.Department of Anesthesiology, UZ Leuven, Leuven, Belgium.Department of Cardiovascular Sciences.
• Faculty of Medicine and Health Sciences, UZ Gent, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium. Esther.Candries@UGent.be.
• J Clin Monit Comput. 2022 Dec 1; 36 (6): 188118901881-1890.

AbstractThe use of inhaled anesthetics has come under increased scrutiny because of their environmental effects. This has led to a shift where sevoflurane in O2/air has become the predominant gas mixture to maintain anesthesia. To further reduce environmental impact, lower fresh gas flows (FGF) should be used. An accurate model of sevoflurane consumption allows us to assess and quantify the impact of the effects of lowering FGFs. This study therefore tested the accuracy of the Gas Man® model by determining its ability to predict end-expired sevoflurane concentrations (FETsevo) in patients using a protocol spanning a wide range of FGF and vaporizer settings. After IRB approval, 28 ASA I-II patients undergoing a gynecologic or urologic procedure under general endotracheal anesthesia were enrolled. Anesthesia was maintained with sevoflurane in O2/air, delivered via a Zeus or FLOW-i workstation (14 patients each). Every fifteen min, FGF was changed to randomly selected values ranging from 0.2 to 6 L/min while the sevoflurane vaporizer setting was left at the discretion of the anesthesiologist. The FETsevo was collected every min for 1 h. For each patient, a Gas Man® simulation was run using patient weight and the same FGF, vaporizer and minute ventilation settings used during the procedure. For cardiac output, the Gas Man default setting was used (= Brody formula). Gas Man®'s performance was assessed by comparing measured with Gas Man® predicted FETsevo using linear regression and Varvel's criteria [median performance error (MDPE), median absolute performance error (MDAPE), and divergence]. Additional analysis included separating performance for the wash-in (0-15 min) and maintenance phase (15-60 min). For the FLOW-i, MDPE, MDAPE and divergence were 1% [- 6, 8], 7% [3, 15] and - 0.96%/h [- 1.14, - 0.88], respectively. During the first 15 min, MDPE and MDAPE were 18% [1, 51] and 21% [8, 51], respectively, and during the last 45 min 0% [- 7, 5] and 6% [2, 10], respectively. For the Zeus, MDPE, MDAPE and divergence were 0% [- 5, 8], 6% [3, 12] and - 0.57%/h [- 0.85, - 0.16], respectively. During the first 15 min, MDPE and MDAPE were 7% [- 6, 28] and 13% [6, 32], respectively, and during the last 45 min - 1% [- 5, 5] and 5% [2, 9], respectively. In conclusion, Gas Man® predicts FETsevo in O2/air in adults over a wide range of FGF and vaporizer settings using different workstations with both MDPE and MDAPE < 10% during the first hour of anesthesia, with better relative performance for simulating maintenance than wash-in. In the authors' opinion, this degree of performance suffices for Gas Man® to be used to quantify the environmental impact of FGF reduction in real life practice of the wash-in and maintenance period combined.© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

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