ECG-derived estimators of sleep physiology

描述(申请人提供)：多导睡眠图是一种劳动密集型的、昂贵的、不切实际的重复检查来评估疗效。睡眠呼吸紊乱(SDB)严重程度的典型衡量标准包括事件计数，如呼吸暂停-低呼吸指数，使用生理学上任意的评分标准。这些测量只与成人和儿童的神经行为和心血管结果有适度的相关性。标准睡眠阶段评分区分REM和NREM睡眠类型和NREM深度，但提供的生理稳定性信息很少。因此，需要一种简单、廉价且容易重复的方法来测量SDB的存在及其对睡眠状态生理学和稳定性的影响。研究人员开发了一种基于单导联心电信号的心肺耦合定量分析的全自动体表心电图睡眠生理学估计器。这种方法结合了生理性呼吸与周期性呼吸对与心率变异性和QRS电轴相关的心电参数的机械和自主效应的使用。与SDB相关的生理不稳定睡眠表现为循环交替模式(CAP)的脑电形态，与常规分期评分无关。相比之下，非CAP时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，因此提供了一个有希望的新的睡眠生理和病理生物标记物，基于睡眠行为不稳定时期的睡眠百分比。这项拟议研究的目标是：1)使用睡眠实验室数据库改进这项技术。2)使用已建立的数据库，在社区居住的成年人(睡眠心脏健康研究，SHHS)和儿童(神经行为评估和儿童睡眠，NAP)中测试它作为SDE检测器。3)将生物标志物与日间过度嗜睡、主观睡眠质量和心血管发病率(SHHS)以及神经认知功能降低(NAPS)相关联。

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).