年龄和目击呼吸暂停是中风后阻塞性睡眠暂停的独立预测因素:一项前性队列研究
Michela Figorilli1,2, Marta Melis1,2, Chiara Cualbu3
1Sleep Disorder Research Center, Department of Medical Sciences and Public Health, University of Cagliari, 09124 Cagliari, Italy.
Journal of clinical medicine
|December 11, 2025
概括
使用年龄和目击呼吸暂停的新模型有效地识别了中风患者的阻塞性睡眠暂停 (OSA). 这种简单的工具可以改善风险分层,帮助早期检测和中风后的二次预防.
科学领域:
- 神经学 神经学
- 睡眠医学 睡眠医学
- 心血管研究研究心血管研究
背景情况:
- 阻塞性睡眠呼吸暂停 (OSA) 是常见的,并且通常在中风幸存者中未被检测到,这会对结果产生负面影响.
- 在急性中风情况下,目前的OSA查方法缺乏足够的准确性.
- 需要简单的临床预测因子来更好地分层中风后患者的OSA风险.
研究的目的:
- 在急性中风患者中确定阻塞性睡眠呼吸暂停 (OSA) 的简单临床预测因素.
- 在这个人群中开发OSA风险分层模型.
- 评估模型的性能与现有的选工具相比.
主要方法:
- 对116名急性中风患者的前性研究.
- 进行了临床评估,柏林问卷,爱普沃思睡眠度量表 (ESS) 和家庭睡眠呼吸暂停测试 (HSAT).
- 后勤回归分析了预测因素;使用准确度,灵敏度,特异性和ROC曲线评估模型性能.
主要成果:
- 阻塞性睡眠呼吸暂停 (OSA) 在36%的患者中被诊断出.
- 确定的独立OSA预测因素是年龄和目击呼吸暂停.
- 该模型 (年龄+出现的呼吸暂停) 显示准确率为72.9%,特异性为90.3%,并且表现优于柏林问卷和ESS.
结论:
- 一个简单的临床模型整合年龄和目击的呼吸暂停可靠地识别高风险的OSA患者中风后.
- 与标准的OSA查问卷相比,该模型显示出更高的歧视性表现.
- 高特异性支持在资源有限的环境中针对性地分配HSAT,可能改善中风治疗途径.
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