可穿戴设备可以检测出先于症状和炎症性类风湿性关节炎爆发并与之相关的生理变化
Pragya Sharma1, Matteo Danieletto1,2, Jessica K Whang3
1Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Scientific reports
|November 29, 2025
概括
可穿戴设备可以检测出预测类风湿性关节炎 (RA) 爆发的生理变化. 来自Apple Watch和Fitbit等设备的心率和步骤数据可能有助于监测RA疾病活动.
科学领域:
- 类风湿病学 类风湿病学
- 生物医学工程 生物医学工程
- 数字健康数字健康
背景情况:
- 类风湿性关节炎 (RA) 涉及生理变化.
- 监测RA疾病活动和预测爆发对于患者管理至关重要.
研究的目的:
- 调查可穿戴设备的生理指标是否可以识别和先于类风湿性关节炎 (RA) 爆发.
- 评估可穿戴技术对RA疾病监测和爆发预测的潜力.
主要方法:
- 收集了RA患者使用可穿戴设备 (Apple Watch,Fitbit,Oura Ring) 的生理数据 (心率,心率变化,步骤).
- 利用线性混合效应模型和Cosinor混合效应模型来分析生理指标和RA爆发/缓解期之间的关联.
- 采用混合效应逻辑回归来评估发作前的生理变化.
主要成果:
- 与缓解相比,在症状性RA期间观察到较低的平均步骤和更高的夜间心率 (HR).
- 每日HR,白天HR,夜间HR和休息心率 (RHR) 的升高与炎症性RA爆发相比缓解有关.
- 心率变化 (HRV) 的循环特征区分了炎症/症状爆发和缓解.
- 在所有测量的生理指标中,在炎症和症状性RA爆发前四周内检测到显著的变化.
结论:
- 来自可穿戴设备的生理数据显示,对监测类风湿性关节炎 (RA) 疾病活动有前途.
- 可穿戴技术可能提供一种非侵入性方法来预测RA爆发,从而能够及时进行干预.
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