来自一项纵向多组学研究的COVID-19严重程度的短期预测因子,用于重症监护病房的实践应用
Sabine Kugler1, Lisa Hahnefeld2, Jan Andreas Kloka3
1Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven 1, St. Augustin, Germany.
Talanta
|October 22, 2023
概括
研究人员开发了一种多omics预测器,可以提前五天预测COVID-19患者的恶化情况. 该工具有助于重症监护室 (ICU) 的资源管理和在流行病期间的临床决策.
科学领域:
- 发现生物标志物的发现.
- 密集护理医学是密集护理的医学.
- 流行病的准备情况.
背景情况:
- 在全球范围内,COVID-19大流行使ICU资源受到压力.
- 现有的预测因素侧重于长期结果,而不是短期的ICU规划.
- 需要工具来预测急性疾病的进展,以便更好地分配资源.
研究的目的:
- 建立工作流程,以确定ICU中COVID-19进展的短期预测因素.
- 为临床决策开发基于多omics的预测器.
- 帮助管理资源和药物在严重疾病的急性阶段.
主要方法:
- 招募了32名入住ICU的SARS-CoV-2患者.
- 收集的连续血样本用于蛋白质组,代谢组和脂质组分析.
- 利用统计分析和机器学习来识别进展预测因素.
主要成果:
- 确定了两种与疾病恶化相关的蛋白质 (CCL7,CA14) 和一种脂质 (hexosylceramide).
- 开发了一种具有79-84%准确度的预测器,用于预测未来3-5天的恶化.
- 预测器的表现补充了临床医生的评估.
结论:
- 建立了一个基于omics的生物标志物发现工作流.
- 成功开发了COVID-19症状恶化的短期预测剂.
- 方法可以适应未来的流行病准备和小型队列研究.
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