一个具有活动跟踪的数字平台,用于长期COVID中的能源管理支持:一个随机对照试验
Nilihan Em Sanal-Hayes1, Lawrence D Hayes2, Jacqueline L Mair3,4,5
1School of Health and Society, University of Salford, Salford, UK.
Nature communications
|February 2, 2026
概括
长期COVID (LC) 的即时能源管理应用程序干预显示对后炼不适 (PEM) 的影响很小. 未来的研究应该在具有较低自发恢复率的条件下探索这种方法,例如慢性疲劳综合征 (CFS).
科学领域:
- 康复医学 康复医学 康复医学
- 数字健康数字健康
- 慢性疾病管理 慢性疾病管理
背景情况:
- 长期COVID (LC) 经常表现为衰弱的运动后不适 (PEM),影响日常功能.
- 有效的能源管理策略对于患有LC症状的人来说至关重要.
- 目前对LC的干预往往缺乏针对能源监管的定制,实时支持.
研究的目的:
- 评估在长期COVID的成年人中进行能源管理的即时数字干预措施的有效性.
- 将"Pace Me"应用程序与可穿戴活动追踪器与标准护理对运动后不适的影响进行比较.
主要方法:
- 一个为期6个月的实用随机对照试验 (RCT) 涉及250名长期COVID的成年人.
- 干预小组收到了"Pace Me"应用程序,可穿戴的追踪器,以及用于能源管理的即时消息.
- 对照组接受了一个带有数据输入屏幕的应用程序;主要结果是通过DePaul症状问卷-PEM (DSQ-PEM) 测量PEM.
主要成果:
- 对于初级结果 (DSQ-PEM),没有观察到按组时间的显著相互作用,这表明干预的效果是微不足道的 (p=0.614, η2p=0.002).
- 干预组和对照组都显示了从基线到随访的PEM得分没有显著变化.
- 在DSQ-PEM中,没有个体症状问题表明了群体之间的显著相互作用效应.
结论:
- 在这项试验中",Pace Me"即时干预证明了在长期COVID患者中管理PEM的标准护理相比,额外的额外益处很小.
- 在LC群体中高自发康复率和广泛的纳入标准可能会混结果,可能掩盖干预效应.
- 能源管理框架要求在自然恢复较少的条件下进行进一步的研究,例如慢性疲劳综合征 (CFS).
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