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穿戴式传感器数据的长期变化在有和没有长期Covid的人身上

Jennifer M Radin¹, Julia Moore Vogel², Felipe Delgado²

¹Scripps Research Translational Institute, La Jolla, CA, 92037, USA. Jennifer.radin@modernatx.com.

NPJ digital medicine

|September 13, 2024

概括

长期COVID显著改变了每日可穿戴的数据,包括休息心率和活动水平,长达感染后的一年. 这些变化,以及人口统计因素,可以帮助识别长期COVID并发症风险较高的个体.

科学领域:

数字健康数字健康
传染病流行病学传染病流行病学
心血管生理学心血管生理学

背景情况:

长期COVID的特征是SARS-CoV-2感染后30天以上的持续症状,这对公众健康构成了重大挑战.
了解与长期COVID相关的客观生理变化对于诊断和管理至关重要.
可穿戴传感器数据为实时监测健康状况和疾病进展提供了一个有希望的途径.

研究的目的:

研究长期COVID和没有长期COVID的个体中可穿戴传感器数据 (步数,静止心率,睡眠量) 的纵向变化.
确定与长期COVID发展和持续相关的客观生物标志物.
探索长期COVID的人口统计和急性阶段症状预测因素.

主要方法:

一项队列研究将279名长期COVID患者与274名对照人进行比较,分析SARS-CoV-2感染后长达一年的可穿戴数据与感染前的基线.
利用可穿戴设备的步数,静止心率 (RHR) 和睡眠量数据.
收集人口统计信息,疫苗接种情况和急性阶段症状数据.

主要成果:

与对照人群相比,长期COVID患者的静止心率和活动轨迹显著不同.
女性,年轻人,未接种疫苗的人,以及那些报告更急性阶段症状的人更有可能患上长期COVID.
从可穿戴设备获得的客观数据显示,在研究期间,长期COVID组中存在明显的模式.

结论:

穿戴式传感器数据为长期COVID的生理影响提供了客观的见解.
人口统计和急性阶段症状数据可以帮助早期识别患有长期COVID风险的个人.
客观数据跟踪可能对评估未来长期COVID干预措施的有效性有价值.

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