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基于血氧饱和度和心肺耦合的光谱分析的自动睡眠呼吸暂停低通气指数。

Automated Apnea-Hypopnea Index from Oximetry and Spectral Analysis of Cardiopulmonary Coupling.

机构信息

Division of Pulmonary and Sleep Medicine, Elliot Health System, Manchester, New Hampshire.

Research and Development, SleepImage, Denver, Colorado; and.

出版信息

Ann Am Thorac Soc. 2021 May;18(5):876-883. doi: 10.1513/AnnalsATS.202005-510OC.

Abstract

The increased prevalence of obstructive sleep apnea (OSA) coincides with a severe shortage of sleep physicians. There is a need for widescale home-sleep-testing devices with accurate automated scoring to accelerate access to treatment. To examine the accuracy of an automated apnea-index (AHI) derived from spectral analysis of cardiopulmonary coupling (CPC) extracted from electrocardiograms, combined with oximetry signals, in relation to polysomnograms (PSGs). Electrocardiograms and pulse-oximeter tracings on PSGs from APPLES (Apnea Positive Pressure Long-term Efficacy Study) were analyzed. Distinct CPC spectral bands were combined with the oxygen desaturation index to create a derived AHI (DAHI). Correlation statistics between the DAHI and the conventionally scored AHI, in which hypopneas required ≥50% airflow reduction alone or a lesser airflow reduction associated with ≥3% desaturation or arousal, using PSGs from APPLES were calculated. A total of 833 adult subjects were included. The DAHI has excellent and strong correlation with the conventionally scored AHI on PSGs, with Pearson coefficients of 0.972 and receiver operating characteristic curves demonstrating strong agreement in all OSA categories: 98.5% in mild OSA (95% confidence interval [CI], 97.6-99.3%), 96.4% in moderate OSA (95% CI, 95.3-97.5%), and 98.5% in severe OSA (95% CI, 97.8-99.2%). An accurate automated AHI can be derived from oximetry and CPC.

摘要

阻塞性睡眠呼吸暂停(OSA)的患病率不断上升,与此同时,睡眠医学专家却严重短缺。因此,我们需要广泛使用具有准确自动评分功能的家用睡眠测试设备,以加快治疗的普及。本研究旨在探究从心电图中提取的心肺偶联(CPC)的频谱分析得出的自动呼吸暂停指数(AHI)与多导睡眠图(PSG)的相关性。对 APPLES(Apnea Positive Pressure Long-term Efficacy Study)中 PSG 的心电图和脉搏血氧仪轨迹进行分析。将明显的 CPC 频谱波段与氧减指数相结合,以创建衍生 AHI(DAHI)。使用 APPLES 中的 PSG 计算 DAHI 与传统评分 AHI 之间的相关统计数据,其中,呼吸暂停需要气流减少≥50%或气流减少较少但伴有≥3%的氧饱和度下降或觉醒。共有 833 名成年受试者纳入研究。在 PSG 上,DAHI 与传统评分 AHI 具有极好的强相关性,Pearson 系数为 0.972,受试者工作特征曲线显示在所有 OSA 类别中均具有很强的一致性:轻度 OSA(95%置信区间 [CI],97.6-99.3%)中为 98.5%,中度 OSA(95%CI,95.3-97.5%)中为 96.4%,重度 OSA(95%CI,97.8-99.2%)中为 98.5%。通过血氧仪和 CPC 可以得出准确的自动 AHI。

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