一个电子算法来识别与万科米辛相关的急性损伤
Jerald P Cherian1, George F Jones1, Preetham Bachina1
1Department of Medicine, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Open forum infectious diseases
|June 29, 2023
概括
这项研究开发了一种电子算法,用于识别与万科米辛相关的急性损伤 (V-AKI). 该算法准确地检测V-AKI,有助于了解其发生率并告知干预措施.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 药物监督 药物监督 药物监督
- 医疗信息学 医疗信息学
背景情况:
- 由于缺乏系统的监测,不完全了解与万科米辛相关的急性损伤 (V-AKI) 的负担.
- 开发可靠的方法来识别V-AKI对于患者安全和有效治疗至关重要.
研究的目的:
- 开发和验证一种电子算法,用于识别与菌素相关的急性损伤 (V-AKI).
- 为了确定V-AKI在医疗保健系统中的发病率.
主要方法:
- 使用V-AKI评估框架开发了一种电子算法,并与手动图表审查进行验证.
- 统计指标包括百分比协议,卡帕系数,灵敏度和特异性.
- 对48小时或更长时间的万科米辛疗程进行了发病率评估.
主要成果:
- 电子算法显示了与图表审查的高度一致 (92.5%一致,0.95卡帕).
- 该算法在检测可能或可能的V-AKI时显示出出色的灵敏度 (89.7%) 和特异性 (98.2%).
- 在11,073个万科米辛疗程 (≥48小时) 中,可能或可能发生V-AKI的发病率为14.0%.
结论:
- 一个电子算法有效地识别V-AKI具有高准确性,可与手动图表检查相提并论.
- 这种经过验证的算法可以成为未来的研究和干预措施的宝贵工具,旨在减少V-AKI.
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