用于检测初始呼吸机相关事件的自动化监测系统评估
Assessment of an automated surveillance system for detection of initial ventilator-associated events.
作者信息
Nuckchady Dooshanveer, Heckman Michael G, Diehl Nancy N, Creech Tara, Carey Darlene, Domnick Robert, Hellinger Walter C
机构信息
Division of Infectious Diseases, Mayo Clinic, Jacksonville, FL.
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL.
出版信息
Am J Infect Control. 2015 Oct 1;43(10):1119-21. doi: 10.1016/j.ajic.2015.05.040. Epub 2015 Jul 9.
Surveillance for initial ventilator-associated events (VAEs) was automated and compared with nonautomated review of episodes of mechanical ventilation. Sensitivity, specificity, positive predictive value, and negative predictive value of automated surveillance were very high (>93%), and automated surveillance reduced the time spent on detection of VAEs by >90%.
对初始呼吸机相关事件（VAE）的监测实现了自动化，并与对机械通气事件的非自动化审查进行了比较。自动化监测的敏感性、特异性、阳性预测值和阴性预测值都非常高（>93%），并且自动化监测将检测VAE所花费的时间减少了>90%。
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