在COVID-19肺炎患者的成年人中,人工智能引导的全度得分和阻塞性睡眠呼吸暂停
Zeynep Atçeken1, Yeliz Çelik2, Çetin Atasoy1
1Department of Radiology, Koç University Faculty of Medicine, İstanbul, Türkiye
Thoracic research and practice
|February 11, 2025
概括
在CT扫描上,人工智能分析的肺不透明度 (TOS) 与COVID-19幸存者的阻塞性睡眠呼吸暂停 (OSA) 严重程度有关. 这种人工智能驱动的成像指标可能有助于评估感染后的睡眠呼吸暂停风险.
科学领域:
- 肺部医学 肺部医学
- 睡眠医学 睡眠医学
- 放射学 放射学是一门学科.
背景情况:
- 之前的研究通过柏林问卷将胸部CT上的AI导向的全度得分 (TOS) 与高风险阻塞性睡眠呼吸暂停 (OSA) 联系起来.
- 在有冠状病毒疾病-2019 (COVID-19) 感染史的患者中,TOS严重程度和多睡眠学 (PSG) 确认的OSA严重程度之间的关联需要进一步调查.
研究的目的:
- 检查前COVID-19感染患者中CT扫描中AI量化的TOS严重程度与PSG确定的OSA严重程度之间的关联.
主要方法:
- 后期分析包括56名被诊断患有COVID-19肺炎的患者,他们接受了CT和一夜间PSG.
- 人工智能软件计算了TOS (不透明区域的体积/肺部总体积). 严重的TOS被定义为TOS≥15.
- OSA被定义为一个呼吸暂停-呼吸暂停指数 (AHI) ≥15事件/h.
主要成果:
- 21名参与者患有OSA,35人没有.
- 与非OSA组 (2.8) (P=0.047) 相比,OSA组 (10.5) 的中位数TOS显著更高.
- 多变量逻辑回归显示,OSA,AHI和氧气脱度指数与严重的TOS相关 (P <0.05),调整为共变量.
结论:
- 基于人工智能CT的TOS严重程度与COVID-19肺炎病史患者的OSA严重程度有关.
- 这些发现支持OSA风险与COVID-19患者不良结果之间的先前关联.
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