摘要
针对临床用麻醉监测告警系统采用的硬阈值算法对绝对血容量不足等并发症评价指标单一,误报率达75%的问题,研制了1个新的实时智能监测告警系统(real-time smart alarms foranesthesia monitoring,RTSAAM)。新系统包含2个诊断模块,一是血压变化告警模块(SPV模块),另一个是基于新算法的统计告警模块,该模块综合了血压、心率、脉量和呼气末CO2浓度等指标,能够提供足够的诊断支持信息,并可随时调节系统灵敏度。通过Kappa分析,在线和离线状态下新系统与麻醉师的诊断结果一致性分别为76%和81%,说明新系统对诊断术中的绝对血容量不足有效。
Patient monitoring in the operating theatre requires a high level of vigilance by anesthetists.The aim of this paper is to report the design of a clinically useful diagnostic system called real-time smart alarms for absolute hypovolemia in anesthesia monitoring（RTSAAM）.The system provides decision support to the anesthetist by presenting the diagnostic results on an integrative,ergonomic display that is hoped to enhance patient safety.The performance of the system is assessed by both offline testing and real-time testing in the operation theatre.When detecting absolute hypovolemia（AHV） a satisfactory level of agreement（up to 81%） is observed between RTSAAM and the anesthetist.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第8期43-47,65,共6页
Journal of Chongqing University
基金
国家自然科学基金资助项目(60971016)
关键词
麻醉
智能监测
血压变化检测
血容量不足
anesthesiology
intelligent monitoring
blood pressure
absolute hypovolemia
