ECG-derived estimators of sleep physiology

描述（由申请人提供）：多导睡眠图是劳动密集型的，昂贵的，并且不适合重复执行以评估治疗效果。典型的睡眠呼吸障碍（SDB）严重程度的测量包括事件计数，如呼吸暂停低通气指数，它利用生理学上任意的评分标准。这些测量结果与成人和儿童的神经行为和心血管结果只有轻微的相关性。标准睡眠阶段评分区分快速眼动和非快速眼动睡眠类型和深度，但提供的生理稳定性信息很少。因此，需要一种简单、廉价且易于重复的方法来测量SDB对睡眠状态生理学和稳定性的影响。研究人员基于单导联心电图对心肺耦合的定量分析，开发了一种全自动表面心电图（ECG）衍生的睡眠生理学估计器。这种方法结合了生理呼吸和周期性呼吸对与心率变异性和QRS电轴相关的心电图参数的机械和自主作用。与SDB相关的生理性不稳定睡眠表现为循环交替模式（CAP）的脑电图形态，与常规分期评分无关。相反，非cap期代表着生理上稳定的睡眠行为。我们发现耦合估计器与CAP和非CAP状态有很强的相关性，从而提供了一个有希望的基于睡眠行为不稳定时期的睡眠百分比的睡眠生理学和病理学的新生物标志物。这项研究的目标是：1)使用睡眠实验室数据库来完善这项技术。2)利用已建立的数据库，在社区居住的成人（睡眠心脏健康研究，SHHS）和儿童（神经行为评估和儿科睡眠，nap）中测试其作为SDE检测器。3)将生物标志物与白天过度嗜睡、主观睡眠质量和心血管发病率（SHHS）以及神经认知功能（NAPS）降低联系起来。

DESCRIPTION (PROVIDED BY APPLICANT): Polysomnograms are labor-intensive, expensive and impractical to perform repeatedly to assess therapeutic efficacy. Typical measures of sleep disordered breathing (SDB) severity include event counts, such as the apnea-hypopnea index, that utilize physiologically arbitrary scoring criteria. These measures correlate only modestly with neurobehavioral and cardiovascular outcomes in adults and children. Standard sleep stage scoring differentiates REM and NREM sleep types and NREM depth, but provides little information about physiological stability. Thus, there is a need for a simple, inexpensive and easily repeatable measure of the presence and impact of SDB on sleep state physiology and stability. The investigators have developed a fully automated surface electrocardiogram (ECG)-derived sleep physiology estimator, based on the quantitative analysis of cardiopulmonary coupling from a single-lead ECG. This approach combines the use of mechanical and autonomic effects of physiologic vs. periodic breathing on ECG parameters related to heart rate variability and QRS electrical axis. Physiologically unstable sleep associated with SDB manifests the EEG morphology of cyclic alternating pattern (CAP), regardless of conventional stage scoring. In contrast, periods of non-CAP represent physiologically stable sleep behavior. We have found that the coupling estimator shows a strong correlation with CAP and non- CAP states, thus providing a promising new biomarker of sleep physiology and pathology based on the percentage of sleep spent in periods of unstable sleep behavior. The goals of the proposed research are to: 1) Refine the technique using a sleep laboratory database. 2) Test it, using established databases, as a SDE detector in community-dwelling adults (Sleep Heart Health Study, SHHS) and children (Neurobehavioral Assessment and Pediatric Sleep, NAPS). 3) To correlate the biomarker with excessive daytime sleepiness, subjective sleep quality and cardiovascular morbidity (SHHS), and reduced neurocognitive function (NAPS).