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智能手机衍生的行为数据与类风湿关节炎爆发之间的关联

Elizabeth Mollard1, Sofia Pedro2, Kaleb Michaud1,2

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此摘要是机器生成的。

患者报告的结果和智能手机数据可以帮助预测类风湿性关节炎 (RA) 爆发. 这项研究发现了流动性,沟通模式和RA爆发发生之间的关联,这表明早期检测的潜力.

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科学领域:

  • 类风湿病学 类风湿病学
  • 数字健康数字健康
  • 数据科学数据科学数据科学

背景情况:

  • 类风湿性关节炎 (RA) 爆发显著影响患者的生活质量.
  • 早期发现RA爆发对于有效的疾病管理至关重要.

研究的目的:

  • 描述类风湿性关节炎 (RA) 的发作频率和严重程度.
  • 评估患者报告结果 (PRO) 的短期变化是否可以信号RA爆发.
  • 为了检查被动智能手机数据和自我报告的RA火焰之间的关系.

主要方法:

  • 在条件和固定阶段收集PRO,以及被动智能手机数据 (移动性,通信).
  • 用物流通用估计方程模型和多变量分析来评估关联.
  • 在分析中,调整了人口和季节性混因素.

主要成果:

  • 爆发与更糟糕的PRO有关,包括患者的整体评估和疼痛.
  • 增加的移动性和更长的短信与更少的火焰有关.
  • 反应时间较慢和短短的短信与爆发发生率增加相关.

结论:

  • 将PRO与被动智能手机数据集成,揭示了与RA爆发发生的新相关性.
  • 这些发现表明,有可能开发用于早期RA爆发识别的预测模型.
  • 个性化算法可以改善未来的类风湿性关节炎疾病管理.