开发和验证一个Nomogram模型来预测阻塞性睡眠呼吸暂停
Jingjing Huang1,2,3, Zhujian Wang4, Fang Shi1,2,3
1Department of Otolaryngology-Head and Neck Surgery, Eye & ENT Hospital of Fudan University, Shanghai, China.
Ear, nose, & throat journal
|April 11, 2024
概括
一个新的诺莫格拉姆模型使用血液氧气和常规血液指标预测阻塞性睡眠呼吸暂停 (OSA). 这种方法为OSA诊断提供了一种更快,更具成本效益的替代方案.
科学领域:
- 医学诊断 医学诊断 医学诊断
- 呼吸系统医学 呼吸系统医学
- 生物统计学 生物统计学
背景情况:
- 多睡眠学 (PSG) 是一种确定的,但耗时且昂贵的诊断工具,用于怀疑阻塞性睡眠呼吸暂停 (OSA).
- 需要更容易获得和更有效的方法来预测OSA风险.
- 常规血液指标和氧和水平是随时可用的临床数据.
研究的目的:
- 开发和验证一个用于预测OSA的名ogram模型.
- 该模型主要利用氧和和例行血液检测结果.
- 为OSA查提供一个具有成本效益和节省时间的替代方案.
主要方法:
- 对685名怀疑患有OSA的患者进行了回顾性分析.
- 多变量分析以确定名ogram构造的显著预测因素.
- 内部验证使用引导和歧视和校准 (C指数) 的评估.
主要成果:
- 确定了关键预测因素:年龄,性别,BMI,平均脉氧和率,夜间% SpO2 < 90%,红细胞,高血压和RDW-SD.
- 诺米图表显示出强大的预测性能,C指数为0.935 (内部验证) 和0.957 (外部验证).
- 该模型在两个验证队列中都表现出良好的校准和歧视.
结论:
- 开发的诺米图有效地使用可访问的临床参数预测OSA风险.
- 这种工具可以帮助医生做出临床决策,潜在地减少诊断时间和成本.
- 诺米图为怀疑OSA的患者提供了一个有希望的,高效的查方法.
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