Department of Anesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Saclay, Université Paris-Saclay, Hôpital Paul-Brousse, Assistance Publique Hôpitaux de Paris, Villejuif, France.
Outcomes Research Consortium, Cleveland, OH, USA.
J Clin Monit Comput. 2024 Apr;38(2):487-504. doi: 10.1007/s10877-023-01111-4. Epub 2024 Jan 6.
A closed-loop automatically controls a variable using the principle of feedback. Automation within anesthesia typically aims to improve the stability of a controlled variable and reduce workload associated with simple repetitive tasks. This approach attempts to limit errors due to distractions or fatigue while simultaneously increasing compliance to evidence based perioperative protocols. The ultimate goal is to use these advantages over manual care to improve patient outcome. For more than twenty years, clinical studies in anesthesia have demonstrated the superiority of closed-loop systems compared to manual control for stabilizing a single variable, reducing practitioner workload, and safely administering therapies. This research has focused on various closed-loops that coupled inputs and outputs such as the processed electroencephalogram with propofol, blood pressure with vasopressors, and dynamic predictors of fluid responsiveness with fluid therapy. Recently, multiple simultaneous independent closed-loop systems have been tested in practice and one study has demonstrated a clinical benefit on postoperative cognitive dysfunction. Despite their advantages, these tools still require that a well-trained practitioner maintains situation awareness, understands how closed-loop systems react to each variable, and is ready to retake control if the closed-loop systems fail. In the future, multiple input multiple output closed-loop systems will control anesthetic, fluid and vasopressor titration and may perhaps integrate other key systems, such as the anesthesia machine. Human supervision will nonetheless always be indispensable as situation awareness, communication, and prediction of events remain irreplaceable human factors.
闭环系统通过反馈原理自动控制变量。麻醉中的自动化通常旨在提高受控变量的稳定性,并减少与简单重复任务相关的工作量。这种方法旨在限制因注意力分散或疲劳而导致的错误,同时提高对基于证据的围手术期协议的遵守率。最终目标是利用这些优于手动护理的优势来改善患者的预后。二十多年来,麻醉学中的临床研究已经证明,与手动控制相比,闭环系统在稳定单一变量、减轻操作人员的工作量以及安全地实施治疗方面具有优势。这项研究集中在各种闭环系统上,这些系统将输入和输出耦合在一起,例如与丙泊酚相关的处理脑电图、与血管加压药相关的血压以及与液体治疗相关的液体反应性的动态预测器。最近,多个同时独立的闭环系统已经在实践中进行了测试,一项研究表明,这些系统对术后认知功能障碍有临床益处。尽管这些工具具有优势,但仍需要经过良好培训的操作人员保持情境意识,了解闭环系统对每个变量的反应,并在闭环系统出现故障时准备重新控制。在未来,多输入多输出闭环系统将控制麻醉、液体和血管加压药的滴定,并且可能集成其他关键系统,例如麻醉机。然而,人类监督仍然是不可或缺的,因为情境意识、沟通和事件预测仍然是不可替代的人为因素。