Photoplethysmography Analysis to Assess Cardio-Cerebrovascular Impact of Sleep

通过光电体积描记法分析评估睡眠对心脑血管的影响

• 批准号: 10266835
• 负责人: Younghoon Kwon
• 金额: $ 27.32万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10266835
• 关键词: Acute; Apnea; Biomedical Engineering; Biomedical Research; Blood Pressure; Brain; Cardiovascular Diseases; Cardiovascular Physiology; Cardiovascular system; Caring; Classification; Clinical; Clinical Research; Continuous Positive Airway Pressure; Coupled; Data; Data Set; Data Sources; Decision Making; Development; Effectiveness; Elderly; Electrocardiogram; Evaluation; Event; Exposure to; Frequencies; Health; Heart; High Prevalence; Hour; Impaired cognition; Individual; Information Systems; Information Theory; Injury; Investigation; Left Ventricular Mass; Lesion; Link; Magnetic Resonance Imaging; Measurement; Measures; Mediating; Medical; Methods; Modeling; Monitor; Morphology; Multi-Ethnic Study of Atherosclerosis; Neurocognitive; Obstructive Sleep Apnea; Older Population; Optics; Outcome; Oxygen; Patients; Personal Satisfaction; Photoplethysmography; Physiologic Monitoring; Physiologic pulse; Physiological; Polysomnography; Public Health; Pulse Oximetry; Randomized Controlled Trials; Risk; Shapes; Signal Transduction; Sleep; Sleep Apnea Syndromes; Structural defect; Techniques; Testing; Therapeutic; Time; Uncertainty; Work; aging population; arm; base; biomarker evaluation; cardiovascular disorder risk; cardiovascular effects; cardiovascular risk factor; cerebrovascular; clinical practice; cognitive ability; cognitive function; cognitive testing; cohort; epidemiology study; improved; indexing; instrument; interest; machine learning method; novel; older men; older women; phenotypic biomarker; predicting response; prospective; respiratory; response; risk stratification; screening; sensor; tool; treatment response; white matter

Project Summary Obstructive sleep apnea (OSA) is common in the aging population and is associated with increased risk of cardiovascular (CV) disease, including cerebrovascular injury. Repetitive exposure to acute CV response, such as sympathetic surge and blood pressure (BP) rise following obstructive respiratory events, is an important mediating mechanism linking OSA to CV disease and cerebrovascular injury. However, such acute CV responses are not effectively captured by conventional polysomnography metrics, such as the apnea hypopnea index (AHI) commonly used in OSA evaluation. This results in imprecise classification of patients in terms of their CV risk and may be responsible for inconsistent results in epidemiologic and clinical studies. More importantly, the uncertainty of the effectiveness of continuous positive airway pressure (CPAP) therapy in reducing the CV risk poses a significant challenge in therapeutic decision-making in older individuals. Therefore, the identification of additional phenotypic markers that better quantify the unfavorable CV effects of OSA and provide improved prediction of CV outcomes is crucial to improving risk stratification and clinical therapeutic decision-making. Herein, we propose to study novel physiologic measurements that can readily be retrieved from a single photoplethysmography (PPG) sensor and investigate whether PPG features are associated with markers of subclinical, clinical CV disease, and cerebrovascular injury. We will extract PPG features from polysomnography obtained in the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study and examine whether PPG features are associated with CV outcomes, including left ventricular mass, aortic stiffness, and incident cardiovascular events, as well as markers of cerebrovascular injury, including brain structural abnormalities by MRI and cognitive impairment by Cognitive Abilities Screening Instrument in the older men and women. We will compare the association of PPG features with these outcomes with that of conventional OSA assessment metrics (such as apnea hypopnea index). The main PPG feature of interest is slope transit time. To assess the utility of the various PPG features for use in estimating and classifying outcomes, we will use novel machine learning methods, such as are based on the GNOSIS (Generalized Networks for the Optimal Synthesis of Information Systems) information-theory-based modeling tool. Subsequently, we will determine how PPG features predict BP treatment response to CPAP and O2 therapy using data from the HeartBEAT randomized controlled trial. This study attempts to identify novel PSG metrics that are cardiovascular-centric and to assess their clinical utility in the older adults. The findings of the study will provide a basis for further development of a simpler method by which to assess and monitor OSA. Considering the high prevalence of OSA in older populations, coupled with its impact on adverse health outcomes, the proposal has significant public health implications.

项目摘要 阻塞性睡眠呼吸暂停（OSA）在老年人群中很常见，并且与以下风险增加有关： 心血管（CV）疾病，包括脑血管损伤。反复暴露于急性CV反应，例如 由于阻塞性呼吸事件后交感神经冲动和血压（BP）升高， OSA与心血管疾病和脑血管损伤的介导机制。然而，这种急性CV 常规的多导睡眠描记术度量（例如呼吸暂停）不能有效地捕获响应 低通气指数（AHI）常用于OSA评估。这导致患者的不精确分类， 这可能与其CV风险有关，并可能导致流行病学和临床研究结果不一致。 更重要的是，持续气道正压通气（CPAP）治疗在 降低CV风险对老年人的治疗决策提出了重大挑战。 因此，鉴定更好地量化不利的CV效应的额外表型标记物是必要的。 OSA并提供更好的CV结局预测对于改善风险分层和临床 治疗决策 在这里，我们建议研究新的生理测量，可以很容易地从一个单一的检索， 光电体积描记（PPG）传感器，并调查PPG特征是否与 亚临床、临床CV疾病和脑血管损伤。我们将提取PPG特征， 多民族动脉粥样硬化研究（梅萨）睡眠研究和检查中获得的多导睡眠图 PPG特征是否与CV结局相关，包括左心室质量、主动脉僵硬度和 突发心血管事件以及脑血管损伤的标志物，包括脑结构 老年男性的MRI异常和认知能力筛查工具的认知功能障碍 和妇女我们将比较PPG特征与这些结果的相关性与传统的 OSA评估指标（如呼吸暂停低通气指数）。感兴趣的主要PPG特征是斜率转换 时间为了评估各种PPG特征用于估计和分类结果的效用，我们将 使用新的机器学习方法，例如基于GNOSIS（Generalized Networks for the 信息系统的最优综合）信息理论为基础的建模工具。 随后，我们将确定PPG特征如何预测对CPAP和O2治疗的BP治疗反应 使用来自HeartBEAT随机对照试验的数据。 本研究试图确定以心血管为中心的新型PSG指标，并评估其临床意义。 在老年人中的效用。研究结果将为进一步发展一个更简单的 评估和监测OSA的方法。考虑到OSA在老年人群中的高患病率， 加上对健康的不良影响，这项建议对公共健康有重大影响。