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利用氧饱和度的自动频域分析作为睡眠呼吸暂停低通气综合征的筛查工具。

Automated frequency domain analysis of oxygen saturation as a screening tool for SAHS.

机构信息

Universidad de Cádiz-Escuela Superior de Ingeniería, Dpto. de Ingeniería de Sistemas y Automática, C/Chile s/n, CP 11002 Cádiz, Spain.

出版信息

Med Eng Phys. 2012 Sep;34(7):946-53. doi: 10.1016/j.medengphy.2011.10.015. Epub 2011 Dec 3.

DOI:10.1016/j.medengphy.2011.10.015
PMID:22137675
Abstract

Sleep apnea-hypopnea syndrome (SAHS) is significantly underdiagnosed and new screening systems are needed. The analysis of oxygen desaturation has been proposed as a screening method. However, when oxygen saturation (SpO(2)) is used as a standalone single channel device, algorithms working in time domain achieve either a high sensitivity or a high specificity, but not usually both. This limitation arises from the dependence of time-domain analysis on absolute SpO(2) values and the lack of standardized thresholds defined as pathological. The aim of this study is to assess the degree of concordance between SAHS screening using offline frequency domain processing of SpO(2) signals and the apnea-hypopnea index (AHI), and the diagnostic performance of such a new method. SpO(2) signals from 115 subjects were analyzed. Data were divided in a training data set (37) and a test set (78). Power spectral density was calculated and related to the desaturation index scored by physicians. A frequency desaturation index (FDI) was then estimated and its accuracy compared to the classical desaturation index and to the apnea-hypopnea index. The findings point to a high diagnostic agreement: the best sensitivity and specificity values obtained were 83.33% and 80.44%, respectively. Moreover, the proposed method does not rely on absolute SpO(2) values and is highly robust to artifacts.

摘要

睡眠呼吸暂停低通气综合征(SAHS)的诊断率明显较低,需要新的筛查系统。对血氧饱和度(SpO2)的分析已被提出作为一种筛查方法。然而,当 SpO2 被用作独立的单通道设备时,时域分析算法要么具有高灵敏度,要么具有高特异性,但通常两者都不具备。这种局限性源于时域分析对绝对 SpO2 值的依赖性,以及缺乏定义为病理性的标准化阈值。本研究旨在评估离线频域处理 SpO2 信号对睡眠呼吸暂停低通气指数(AHI)进行 SAHS 筛查的程度,并评估这种新方法的诊断性能。分析了 115 名受试者的 SpO2 信号。数据分为训练数据集(37 个)和测试数据集(78 个)。计算了功率谱密度,并将其与医生评分的饱和度指数相关联。然后估算了频域饱和度指数(FDI),并将其与经典饱和度指数和呼吸暂停低通气指数进行比较。研究结果表明,该方法具有较高的诊断一致性:获得的最佳灵敏度和特异性值分别为 83.33%和 80.44%。此外,该方法不依赖于绝对 SpO2 值,对伪影具有高度鲁棒性。

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