可穿戴设备测量活动与患者报告的心力衰竭结果之间的关联
Jessica R Golbus1, Kensey Gosch2, Mary C Birmingham3
1Division of Cardiovascular Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA; Michigan Integrated Center for Health Analytics and Medical Prediction (MiCHAMP), University of Michigan, Ann Arbor, Michigan, USA. Electronic address: https://twitter.com/JRGolbus.
智能手表每天的步数与心力衰竭患者的健康状况和随着时间的推移的症状有非线性联系. 这一发现有助于在心力衰竭研究和护理中解释可穿戴设备数据.
科学领域:
- 心脏病学 心脏病学
- 数字健康数字健康
- 患者报告的结果
背景情况:
- 可穿戴设备越来越多地用于研究和临床环境.
- 可穿戴设备数据的临床相关性,特别是与验证结果相关的临床相关性,尚未完全理解.
研究的目的:
- 研究智能手表测量身体活动与心力衰竭患者以患者为中心的结果之间的关系.
主要方法:
- CHIEF-HF (Canagliflozin:对心力衰竭的健康状况,生活质量和功能状况的影响) 试验招募了拥有智能手机的心力衰竭患者.
- 参与者使用了Fitbit Versa 2,并连续完成了堪萨斯城心肌病问卷 (KCCQ).
- 线性回归模型评估了每天的步数/爬的地板和KCCQ分数 (总症状和身体限制) 在基线和超过12周之间的关联.
主要成果:
- 总共有425名患者被纳入;44.5%是女性,40.9%的射出分数减少.
- 较高的每日步数与更好的基线KCCQ-总症状和KCCQ-物理限制得分相关 (P < 0.001).
- 每日步数的变化与KCCQ-总症状 (P = 0.004) 和KCCQ-物理限制 (P = 0.003) 评分的非线性变化有显著的关联.
结论:
- 每日步数显示心力衰竭患者的健康状况与非线性关联,无论是基线还是纵向.
- 这些发现支持可穿戴设备数据对评估心力衰竭患者状态的有用性.
- 结果可以帮助在临床和研究背景下对心力衰竭管理的可穿戴传感器数据进行解释.
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