改善帕金森病中跌倒和认知障碍的预测:分散观察研究的协议
Audrey Hoyt1, Casey Dorney1, Peggy Auinger1
1University of Rochester Medical Center, Rochester, United States.
JMIR research protocols
|August 27, 2025
概括
本研究使用数字工具和参与者报告的症状来预测帕金森病 (PD) 的跌倒和认知衰退. 这些发现旨在改善PD患者的早期诊断和干预.
科学领域:
- 神经学
- 数字健康
- 临床试验
背景情况:
- 帕金森病 (PD) 显著导致通过跌倒和认知障碍的残疾.
- 早期识别高危人群对于及时干预至关重要.
- 之前的研究 (AT-HOME PD) 已经确定了早期PD的远程表征.
研究的目的:
- 评估数字工具和远程报告是否有助于预测病人的跌倒和认知障碍.
- 量化PD患者随时间变化的体力活动.
- 探索身体活动与PD临床进展之间的关系.
主要方法:
- 一个分散的观察性研究,涉及多达200名PD患者.
- 使用临床和数字表型,包括视频访问,可穿戴传感器,智能手机任务和在线调查.
- 通过每周的自动呼叫进行评估;由共识委员会进行认知诊断.
主要成果:
- 该研究于2023年9月启动;到2025年1月,已有142名参与者注册.
- 参与者的平均年龄为69.2岁,59.9%是男性,96.5%是白人.
- 疾病的平均持续时间为8.9年.
结论:
- AT-HOME PD2 远程收集中期PD患者的临床和数字数据.
- 这项研究旨在预测跌倒和认知障碍, 以获得更好的长期结果.
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