低兴奋值内型和CPAP坚持:来自大型,多样化的临床队列的见解
medRxiv : the preprint server for health sciences
|November 24, 2025
概括
一个先前的模型将低兴奋值与阻断性睡眠呼吸暂停中CPAP坚持不佳联系起来,并没有对多样化的队列进行概括. 潜在的个人资料分析发现了一个"低ARTH驱动"的内型,其坚持性持续低.
科学领域:
- 睡眠医学 睡眠医学
- 呼吸系统医学 呼吸系统医学
- 临床研究 临床研究
背景情况:
- 低兴奋值 (ArTH) 与阻塞性睡眠呼吸暂停 (OSA) 中持续正气道压力 (CPAP) 坚持性降低有关.
- 来自RICCADSA试验的多特征模型以前将低ARTH与CPAP坚持不佳联系在一起.
- 这个模型对多样化,现实世界人口的通用性需要验证.
研究的目的:
- 为了验证先前衍生出的多特征模型,预测CPAP在一个大规模的现实世界OSA队列中的坚持.
- 探索替代的线性和非线性方法,以更好地预测CPAP的坚持.
- 根据病理生理特征和它们与CPAP坚持的关联来识别不同的患者概况.
主要方法:
- 来自SNOOzzzE队列的成年OSA患者被分析,CPAP启动是在多眠术后1年内.
- 关键的病理生理特征,包括兴奋值 (ArTH) 和循环增益,都来自于多睡眠学数据.
- 隐形形状分析 (LPA) 用于识别基于特征的集群,与传统的线性回归模型一起.
主要成果:
- 之前的多特征模型在验证队列中显示了较差的预测性能 (AUC=0.51).
- 一个新的线性模型在训练期间过度适应,在测试中失败 (AUC=0.55).
- LPA确定了一个"低ARTH驱动"集群具有显著较低的附着性和一个"低ARTH和高循环增益"集群具有稳定的使用.
结论:
- 以前建立的预测CPAP坚持的多特征模型不能对不同的临床群体进行概括.
- 潜在的个人资料分析揭示了一个独特的"低ArTH驱动"内型,其特点是持续的低CPAP坚持.
- 这种内型可能是未来针对OSA管理的个性化干预措施的目标,等待进一步验证.
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