Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zurich, Switzerland.
Institute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland.
Antimicrob Resist Infect Control. 2024 Mar 6;13(1):30. doi: 10.1186/s13756-024-01375-8.
Hospital-acquired pneumonia (HAP) and its specific subset, non-ventilator hospital-acquired pneumonia (nvHAP) are significant contributors to patient morbidity and mortality. Automated surveillance systems for these healthcare-associated infections have emerged as a potentially beneficial replacement for manual surveillance. This systematic review aims to synthesise the existing literature on the characteristics and performance of automated nvHAP and HAP surveillance systems.
We conducted a systematic search of publications describing automated surveillance of nvHAP and HAP. Our inclusion criteria covered articles that described fully and semi-automated systems without limitations on patient demographics or healthcare settings. We detailed the algorithms in each study and reported the performance characteristics of automated systems that were validated against specific reference methods. Two published metrics were employed to assess the quality of the included studies.
Our review identified 12 eligible studies that collectively describe 24 distinct candidate definitions, 23 for fully automated systems and one for a semi-automated system. These systems were employed exclusively in high-income countries and the majority were published after 2018. The algorithms commonly included radiology, leukocyte counts, temperature, antibiotic administration, and microbiology results. Validated surveillance systems' performance varied, with sensitivities for fully automated systems ranging from 40 to 99%, specificities from 58 and 98%, and positive predictive values from 8 to 71%. Validation was often carried out on small, pre-selected patient populations.
Recent years have seen a steep increase in publications on automated surveillance systems for nvHAP and HAP, which increase efficiency and reduce manual workload. However, the performance of fully automated surveillance remains moderate when compared to manual surveillance. The considerable heterogeneity in candidate surveillance definitions and reference standards, as well as validation on small or pre-selected samples, limits the generalisability of the findings. Further research, involving larger and broader patient populations is required to better understand the performance and applicability of automated nvHAP surveillance.
医院获得性肺炎（HAP）及其特定亚组，即非呼吸机相关性医院获得性肺炎（nvHAP），是导致患者发病率和死亡率升高的重要原因。针对这些医院获得性感染的自动化监测系统已成为一种有潜力的替代手动监测的方法。本系统评价旨在综合现有关于自动化 nvHAP 和 HAP 监测系统的特征和性能的文献。
我们对描述 nvHAP 和 HAP 自动化监测的文献进行了系统检索。我们的纳入标准涵盖了描述完全和半自动系统的文章，且对患者人口统计学特征或医疗保健环境没有限制。我们详细介绍了每项研究中的算法，并报告了针对特定参考方法进行验证的自动化系统的性能特征。使用了两个已发表的指标来评估纳入研究的质量。
我们的综述共确定了 12 项符合条件的研究，这些研究共描述了 24 个不同的候选定义，其中 23 个用于完全自动化系统，1 个用于半自动系统。这些系统仅在高收入国家使用，且大多数是在 2018 年后发表的。这些算法通常包括放射学、白细胞计数、体温、抗生素使用和微生物学结果。经过验证的监测系统的性能存在差异，完全自动化系统的灵敏度范围为 40%至 99%，特异性为 58%至 98%，阳性预测值为 8%至 71%。验证通常是在小的、预先选择的患者人群中进行的。
近年来，有关 nvHAP 和 HAP 自动化监测系统的出版物数量急剧增加，这提高了效率并减少了手动工作量。然而，与手动监测相比，完全自动化监测的性能仍然中等。候选监测定义和参考标准的显著异质性，以及在小样本或预先选择的样本上进行验证，限制了研究结果的普遍性。需要进一步研究，涉及更大和更广泛的患者人群，以更好地了解自动化 nvHAP 监测的性能和适用性。
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