Brunner J X, Westenskow D R, Zelenkov P
Department of Anesthesiology, University of Utah, Salt Lake City 84132.
J Clin Monit. 1989 Apr;5(2):90-9. doi: 10.1007/BF01617881.
An alarm algorithm was developed to monitor the ventilator on the National Aeronautics and Space Administration space station. The algorithm automatically identifies and interprets critical events so that an untrained user can manage the mechanical ventilation of a critically injured crew member. The algorithm was tested in two healthy volunteers by simulating 260 critical events in each volunteer while the volunteer breathed via the ventilator. Thirteen critical events were induced eight times in random order, for the five different modes of ventilation. These events included various ventilator tubing disconnects, leaks, and occlusions, as well as power and gas supply failures. The algorithm identified the critical events and generated alarms in response to 99.2% (516 of 520, total) of the events. The alarm textual messages were correct 98% (505 of 516 messages) of the time. The alarm algorithm is an improvement over current alarms found on most ventilators because its alarm messages specifically identify failures in the patient breathing circuit or ventilator. The system may improve patient care by helping critical care personnel respond more rapidly and correctly to critical events.
开发了一种警报算法，用于监测美国国家航空航天局空间站上的呼吸机。该算法能自动识别并解读关键事件，以便未经培训的用户能够管理重伤机组人员的机械通气。通过让两名健康志愿者通过呼吸机呼吸，同时在每名志愿者身上模拟260次关键事件，对该算法进行了测试。针对五种不同的通气模式，以随机顺序对13种关键事件各诱发8次。这些事件包括各种呼吸机管道断开、泄漏和堵塞，以及电源和气体供应故障。该算法识别出了关键事件，并针对99.2%（共520次事件中的516次）的事件生成了警报。警报文本信息在98%（516条信息中的505条）的情况下是正确的。与大多数呼吸机上现有的警报相比，该警报算法有所改进，因为其警报信息能具体识别患者呼吸回路或呼吸机中的故障。该系统可通过帮助重症护理人员更快速、正确地应对关键事件来改善患者护理。
