一个新的数据驱动模型来定义体育活动指标,并预测慢性阻塞性肺病患者的死亡率
Qichen Deng1,2, Alex van 't Hul3, Hieronymus van Hees3
1Department of Research and Development, Ciro, Horn, The Netherlands. qichendeng@ciro-horn.nl.
Scientific reports
|July 22, 2025
概括
一个新的体力活动 (PA) 评分,整合运动频率和振幅,比步数或能量消耗更好地预测慢性阻塞性肺病 (COPD) 患者的死亡率.
科学领域:
- 肺部医学 肺部医学
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
背景情况:
- 身体活动 (PA) 是慢性阻塞性肺病 (COPD) 的关键预后指标.
- 传统的PA指标,如步数,缺乏强度信息,能源支出 (EE) 依赖于间接假设.
- 为了准确的COPD患者评估,需要更全面的PA指标.
研究的目的:
- 使用加速度计数据开发和验证一种新的数据驱动的PA分数.
- 为了比较这种新的PA得分与COPD患者死亡率的步数和EE的预测值.
主要方法:
- 荷兰COPD数据库的回顾性分析 (404名患者).
- 使用富里埃分析分析的原始加速度计数据来推导PA得分的运动频率和振幅.
- 后勤回归用于比较PA得分,步数和EE的死亡率预测准确度.
主要成果:
- 新的PA分数和步数显示了类似的每日模式,但分布不同.
- 与步数相比,PA评分在预测死亡率方面显示了2.8%的更高准确度和5.6%的更高平衡准确度.
- 能源支出 (EE) 显示出死亡率预测表现最低.
结论:
- 拟议的PA分数为评估COPD体育活动提供了更精细和更强大的指标.
- 除了步数之外,整合运动特征对于改善COPD患者死亡率预测至关重要.
- 这种数据驱动的方法提高了COPD临床和研究环境中的PA评估.
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