呼吸道病毒感染的可计算表型在"我们所有人"研究计划中
Bennett J Waxse1,2, Fausto Andres Bustos Carrillo1, Tam C Tran1,2,3,4
1National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
medRxiv : the preprint server for health sciences
|January 27, 2025
概括
从电子健康记录 (EHR) 中开发可计算的表型可以有效地识别呼吸道病毒感染. 这种综合方法加强了疾病监测和对宿主遗传学和健康差异的研究.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 计算生物学 计算生物学
背景情况:
- 电子健康记录 (EHR) 为传染病研究提供了有价值的时间数据.
- 在电子健康系统中识别感染的最佳方法仍在开发中.
- 呼吸系统病毒对公共卫生构成重大挑战,需要强有力的识别策略.
研究的目的:
- 使用EHR数据开发和验证可计算的表型,用于识别呼吸道病毒感染.
- 评估综合计费代码,处方和实验室结果用于疾病表型化的有效性.
- 为了实现对宿主遗传学,健康差异和与偶发性传染病相关的临床结果的大规模研究.
主要方法:
- 使用了"我们所有人"研究计划数据集,包括265,222名参与者.
- 通过在90天内整合计费代码,处方和实验室结果来开发可计算的表型.
- 分析了各种呼吸道病毒的队列大小,包括腺病毒和SARS-CoV-2.
主要成果:
- 现型成功生成了多种病毒的队列,范围从238 (腺病毒) 到28,729 (SARS-CoV-2) 病例.
- 特定于病毒的计费代码显示了可变的灵敏度 (8-67%),但具有高的积极预测值 (90-97%).
- 与CDC数据相比,鉴定的感染与预期的季节性模式和比例保持一致,表明方法的有效性.
结论:
- 综合EHR数据方法优于单个组件,用于识别偶发性传染病.
- 开发的方法有效地识别严重感染,并支持大规模的流行病学研究.
- 这种表型化策略促进了对宿主遗传学,健康差异和各种情节性疾病的临床结果的研究.
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