Faculty of Medicine and Health Sciences, UZ Gent, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium.
Department of Anesthesiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
J Clin Monit Comput. 2022 Dec;36(6):1881-1890. doi: 10.1007/s10877-022-00842-0. Epub 2022 Mar 22.
The use of inhaled anesthetics has come under increased scrutiny because of their environmental effects. This has led to a shift where sevoflurane in O/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 (Fsevo) 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 O/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 Fsevo 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 Fsevo 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 Fsevo in O/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.
吸入麻醉剂的使用因其对环境的影响而受到越来越多的关注。这导致七氟醚在 O/空气混合气中成为维持麻醉的主要气体混合物。为了进一步减少环境影响,应使用较低的新鲜气流(FGF)。准确的七氟醚消耗模型允许我们评估和量化降低 FGF 的影响。因此,这项研究通过确定其在使用涵盖广泛 FGF 和蒸发器设置范围的方案预测七氟醚呼气末浓度(Fsevo)的能力来测试 Gas Man®模型的准确性。
在获得机构审查委员会批准后,纳入了 28 名 ASA I-II 级接受全身气管内麻醉下妇科或泌尿科手术的患者。使用 Zeus 或 FLOW-i 工作站(每组 14 名患者)以 O/空气输送七氟醚维持麻醉。每 15 分钟,将 FGF 改变为随机选择的 0.2 至 6 L/min 值,同时由麻醉师自行决定七氟醚蒸发器设置。在 1 小时内每分钟收集 Fsevo。对于每个患者,使用患者体重和在手术过程中使用的相同 FGF、蒸发器和分钟通气量设置运行 Gas Man®模拟。对于心输出量,使用 Gas Man 默认设置(= Brody 公式)。使用线性回归和 Varvel 的标准[中位数性能误差(MDPE)、中位数绝对性能误差(MDAPE)和发散]来评估 Gas Man®的性能。
额外的分析包括在冲洗期(0-15 分钟)和维持期(15-60 分钟)中分开性能。对于 FLOW-i,MDPE、MDAPE 和发散分别为 1%[-6,8]、7%[3,15]和-0.96%/h[-1.14,-0.88]。在最初的 15 分钟内,MDPE 和 MDAPE 分别为 18%[1,51]和 21%[8,51],而在最后 45 分钟内分别为 0%[-7,5]和 6%[2,10]。对于 Zeus,MDPE、MDAPE 和发散分别为 0%[-5,8]、6%[3,12]和-0.57%/h[-0.85,-0.16]。在最初的 15 分钟内,MDPE 和 MDAPE 分别为 7%[-6,28]和 13%[6,32],而在最后 45 分钟内分别为-1%[-5,5]和 5%[2,9]。
总之,Gas Man®在使用不同工作站时,在 O/空气范围内使用广泛的 FGF 和蒸发器设置来预测 Fsevo,在麻醉的前 1 小时内 MDPE 和 MDAPE<10%,在冲洗期和维持期联合使用时,模拟维持阶段的相对性能更好。作者认为,这种性能足以让 Gas Man®用于量化在冲洗和维持期的实际实践中降低 FGF 对环境的影响。