真实世界的心肺功能测量可以分层初级斯乔格伦综合征参与者持久性疲劳
概括
客观的可穿戴传感器可以在初级Sjogren综合征患者中区分持续性和非持续性疲劳. 这种数字方法提供了一种比主观患者报告更可靠的方法来评估疲劳严重程度.
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:
- 慢性疾病往往会导致衰弱的疲劳,显著降低生活质量.
- 目前的疲劳评估依赖于主观的患者报告结果 (PRO),这些结果容易产生偏见.
- 可穿戴设备提供客观,连续的生理和活动数据,可能克服PRO的局限性.
研究的目的:
- 根据使用客观,现实世界的数据,根据疲劳水平对初级Sjogren综合征 (PSS) 患者进行分层.
- 评估可穿戴传感器数据在PSS中分辨疲劳严重性的有效性.
- 探索数字生物标志物在免疫介导炎症疾病中对疲劳评估的潜力.
主要方法:
- 72名PSS参与者佩戴VitalPatch传感器,在两个7天的时间内进行持续的生理监测.
- 参与者同时完成了频繁的PRO来评估疲劳.
- 分析包括计算各种心率 (HR) 和呼吸率 (RR) 度量,并应用统计测试和机器学习分类器来区分疲劳群体.
主要成果:
- 虽然活动和呼吸速率的测量显示出有限的差异化,但64%的心率测量显著区分了持久和非持久疲劳组 (p<0.05).
- 机器学习模型在使用HR措施将疲劳持久性组分开时达到高达77%的准确性.
- 来自可穿戴设备的客观数字测量表明了通过疲劳水平对PSS患者进行分层的能力.
结论:
- 来自数字可穿戴设备的现实世界生理数据可以客观地分层PSS患者的不同疲劳水平.
- 这项研究支持开发一种客观的,单一设备的方法来识别PSS中的疲劳严重程度.
- 可穿戴技术有望改善免疫媒介炎症疾病中疲劳的评估.
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