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，不切实际的重复执行，以评估治疗效果。睡眠呼吸障碍（SDB）严重程度的典型测量包括事件计数，如呼吸暂停-呼吸不足指数，其利用生理学上的任意评分标准。这些指标与成人和儿童的神经行为和心血管结局仅适度相关。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、廉价且易于重复的SDB对睡眠状态生理学和稳定性的存在和影响的测量。研究人员开发了一种全自动的体表心电图（ECG）衍生的睡眠生理估计器，基于单导联ECG的心肺耦合的定量分析。该方法结合了生理呼吸与周期性呼吸对与心率变异性和QRS电轴相关的ECG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周期性交替模式（CAP）的EEG形态，无论常规阶段评分如何。相反，非CAP期代表生理稳定的睡眠行为。我们已经发现，耦合估计量显示出与CAP和非CAP状态的强相关性，从而基于在不稳定睡眠行为的时段中花费的睡眠的百分比提供了睡眠生理学和病理学的有希望的新生物标志物。本研究的目标是：1）使用睡眠实验室数据库完善该技术。2)使用已建立的数据库进行测试，作为社区居民成年人（睡眠心脏健康研究，SHHS）和儿童（神经行为评估和儿科睡眠，NAPS）的睡眠检测器。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).