基于sTREM-1和IL-6算法的验证,用于COVID-19的结果预测
Mathias Van Singer1, Thomas Brahier2, Jana Koch3
1Infectious Diseases Service, University Hospital of Lausanne, Lausanne, Switzerland. mathias.van-singer@chuv.ch.
BMC infectious diseases
|September 26, 2023
概括
在髓状细胞-1 (sTREM-1) 算法上表达的可溶性触发受体准确地预测了严重的COVID-19结果,显示出良好的可重复性. 介素-6 (IL-6) 算法的性能是可以接受的,但需要进一步验证.
科学领域:
- 生物化学 生化学
- 免疫学 免疫学 免疫学
- 关键护理医学 关键护理医学
背景情况:
- 以前的研究表明,可溶性触发受体表达在骨髓细胞-1 (sTREM-1) 和介质素-6 (IL-6) 算法有效预测了COVID-19患者在急诊室 (ED) 设置中的不良结果.
- 现有的算法需要在不同的临床环境中进行验证,以确认它们的预测效用.
研究的目的:
- 验证基于sTREM-1和IL-6算法的性能,用于预测COVID-19患者向ED提交的不良结果.
- 评估sTREM-1算法的30天输管或死亡率的预测准确性.
- 评估IL-6算法的性能,以预测30天的氧气需求.
主要方法:
- 一项多中心前性观察性研究,涉及三家瑞士医院急救室的PCR确诊的成年COVID-19患者.
- 来自参与中心的回顾性数据编制和合并.
- 确定30天输管/死亡率的sTREM-1算法和30天氧气需求的IL-6算法的预测精度.
主要成果:
- 验证队列包括373名患者,18%的患者在第30天死亡或输管.
- sTREM-1算法显示了30天输管/死亡率的高灵敏度 (90%) 和负预测值 (94%),与衍生队列一致.
- 对于30天的氧气需求,IL-6算法显示了可接受的灵敏度 (85%) 和负预测值 (60%),尽管低于导出队列.
结论:
- sTREM-1算法在多个中心表现出良好的可重现性,支持其临床实用性.
- 需要进一步的前性随机对照试验来评估sTREM-1算法的安全性和对医院和ICU入院率的影响.
- 在广泛实施之前,IL-6算法的有效性需要额外的多中心验证.
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