临床表现 临床表现
Emilie V Brotherhood1,2, Coty Chen1, Claire J Cadwallader1
1Memory and Aging Center, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 24, 2025
概括
FitbitTM活动数据揭示了前叶退行症 (FTLD) 患者的明显模式. 这些休息活动模式与轻度认知障碍或健康个体的休息活动模式有很大不同.
科学领域:
- 神经科学是一个神经科学.
- 老年学是指老年学的学科.
- 生物医学工程 生物医学工程
背景情况:
- 阿尔茨海默病和相关痴呆症 (ADRD) 显著影响睡眠-清醒周期.
- 商业可穿戴设备为现实世界监控提供可扩展的被动动动图.
- 描述休息活动模式可以揭示健康成年人和ADRD队列之间的差异.
研究的目的:
- 使用FitbitTM数据来描述连续休息活动模式.
- 为了检查健康成年人和各种ADRD队列之间的这些模式的差异.
- 调查活动模式与认知/功能衰退之间的关联.
主要方法:
- 收集了健康成年人,轻度认知障碍 (MCI),阿尔茨海默氏病 (AD) 和前叶退化 (FTLD) 队列的三轴动图,临床,认知,功能和情绪数据.
- 使用休息活动总和分钟级步数特征的量化活动模式.
- 应用主要组件分析 (PCA) 来减少数据,并确定了解释>85%的差异的五个组件.
主要成果:
- 主要组件1 (PC1),代表活动变化和振幅,与认知和功能下降得分 (CDR®+FTLD-NACC) 有负相关性.
- PC1也显示出显著的诊断组差异,与健康和MCI组相比,FTLD患者的PC1得分下降.
- 与休息活动开始时间相关的PC3与全球认知得分有负相关性.
结论:
- 来自FitbitTM数据的活动变异性和幅度突出显示了FTLD综合征中的独特行为特征.
- 这些不同的活动概况使FTLD患者与患有MCI或功能完整的患者有区别.
- 通过可穿戴设备的被动动动图提供了对神经退行性疾病进展的宝贵见解.
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