一个预测模型为患有高血压的成年人量身定制的体力活动建议:观察性研究
Yuhui Yang1, Manqing Chen1, Weiwei Hu1
1Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta Xilu Road, Xi'an, Shaanxi, 710061, China, 86 13772075793.
Journal of medical Internet research
|January 9, 2026
概括
个性化体力活动 (PA) 模式可以显著影响高血压 (BP) 的成年人死亡风险. 根据个体特征量身定制PA可改善预后,降低全因死亡风险.
科学领域:
- 心血管健康 心血管健康
- 运动生理学 运动生理学
- 生物统计学 生物统计学
背景情况:
- 对于患有高血压的成年人来说,身体活动 (PA) 的益处可能因个体特征而异,这一领域需要进一步研究.
- 了解这种异质性对于优化高血压人群的健康结果至关重要.
研究的目的:
- 研究个体特征如何改变身体活动 (PA) 模式与死亡率之间的关联.
- 开发和验证一个可预测的模型,以最佳的PA模式,根据个体患者的个人资料.
主要方法:
- 使用加速度计数据定义了四种不同的PA模式 (活跃的周末战士,活跃的常规,活跃的光PA,基线PA).
- 在英国生物银行 (UKB) 队列中训练了一种机器学习模型,并在国家健康和营养检查调查 (NHANES) 队列中验证,以预测最佳的PA模式.
- 多变量考克斯模型评估了与预测的最佳模式相比,当前PA模式和全因死亡率之间的关联.
主要成果:
- 预测模型表现出强的性能,用于10年死亡率预测,接收器操作特征曲线下的面积为86.4%.
- 影响最佳PA模式的关键因素包括中风史,年龄,性别,血压等级和抗高血压药物.
- 当前和预测的最佳PA模式之间的不一致性与UKB队列中全因死亡风险增加28%有关.
结论:
- 个体特征显著影响高血压 (BP) 的成年人最佳体力活动 (PA) 模式.
- 开发的预测模型和Web应用程序可以帮助临床医生提供个性化的PA建议.
- 根据个体资料定制的PA策略有可能改善高血压患者的预后并降低高血压患者的死亡率.
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