Pathogen Reduction in an Endoscopy Unit Using AI-Enabled Autonomous UV-C Disinfection.

IF 2.4 3区医学 Q2 INFECTIOUS DISEASES

American journal of infection control Pub Date : 2025-09-11 DOI:10.1016/j.ajic.2025.09.006

Monique T Barakat, Mohammad Noshad, Timothy Angelotti

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引用次数: 0

Abstract

Background: Bioburden on high-touch surfaces has been identified as a contributor to Healthcare-Associated Infections. Disinfection with UV-C light robots can minimize this bioburden, but targeted disinfection can be labor intensive. This study evaluated the effectiveness of wall-mounted autonomous and targeted UV-C disinfection device powered by Artificial Intelligence (AI) in reducing bioburden in a clinical setting.

Methods: Two endoscopy rooms were evaluated in this study, a control room with standard institutional disinfection/cleaning measures and another with two autonomous UV-C (AUV) devices installed on opposite walls. To measure the potential impact on pathogenic bioburden levels, swab sampling was conducted on ten pre-selected high-touch surfaces in each room over a period of four weeks and analyzed for microbial colony counts by an independent laboratory.

Results: Autonomous, targeted UV-C disinfection inactivated pathogens within 20-60 seconds from a distance of 6-8 feet. Longer UV-C exposure time were utilized to achieve a consistent level of pathogen inactivation across the room. The AUV room had a 99.7%, 84.3% and 93.8% bioburden reduction compared to the control room (weeks 1, 2 and 4). Cumulative bioburden was 93.3% lower than that measured in the Control room.

Conclusions: These data demonstrate that this novel, autonomous and targeted UV-C disinfection approach is associated with effective surface decontamination and highlight the potential for this approach for broader use in healthcare settings.

查看原文本刊更多论文

使用人工智能自动UV-C消毒减少内窥镜装置中的病原体。

背景：高接触表面的生物负担已被确定为医疗保健相关感染的一个贡献者。使用UV-C轻型机器人进行消毒可以最大限度地减少这种生物负担，但有针对性的消毒可能是劳动密集型的。本研究评估了由人工智能（AI）驱动的壁挂式自主靶向UV-C消毒装置在减少临床环境中生物负担方面的有效性。方法：本研究对两间内窥镜室进行了评估，一间控制室采用标准的机构消毒/清洁措施，另一间控制室在相对墙壁上安装了两台自主UV-C （AUV）装置。为了测量对致病生物负荷水平的潜在影响，在四周的时间里，在每个房间预选的10个高接触表面上进行了拭子取样，并由独立实验室分析微生物菌落计数。结果：在距离6-8英尺的20-60秒内，自主，靶向UV-C消毒灭活病原体。利用较长的UV-C暴露时间来实现整个房间内病原体灭活的一致水平。与控制室（第1、2和4周）相比，AUV室的生物负荷减少了99.7%、84.3%和93.8%。累积生物负荷比控制室测量值低93.3%。结论：这些数据表明，这种新颖、自主和有针对性的UV-C消毒方法与有效的表面净化有关，并强调了这种方法在医疗保健环境中广泛应用的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

American journal of infection control 医学-传染病学

CiteScore

7.40

自引率

4.10%

发文量

479

审稿时长

24 days

期刊介绍： AJIC covers key topics and issues in infection control and epidemiology. Infection control professionals, including physicians, nurses, and epidemiologists, rely on AJIC for peer-reviewed articles covering clinical topics as well as original research. As the official publication of the Association for Professionals in Infection Control and Epidemiology (APIC)