Prediction of Physiological Events in People with Sleep Disordered Breathing

睡眠呼吸障碍患者生理事件的预测

• 批准号: 8133670
• 负责人: Jonathan A Waxman
• 金额: $ 4.29万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8133670
• 关键词: Accidents; Address; Adverse event; Algorithms; Apnea; Arousal; Attention; Automobile Driving; Behavior; Behavioral; Biological Neural Networks; Breathing; Characteristics; Chicago; Cognitive deficits; Collaborations; Complex; Computers; Continuous Positive Airway Pressure; Cranial Nerves; Detection; Development; Devices; Disease; Effectiveness; Electric Stimulation; Electroencephalography; Electronics; Environmental air flow; Event; Excessive Daytime Sleepiness; Exhibits; Functional disorder; Future; Glean; Goals; Graph; Illinois; Imagery; Impaired cognition; Impairment; Individual; Injury; Laboratories; Lead; Machine Learning; Maintenance; Measurable; Medical; Memory; Methodology; Methods; Network-based; Obstructive Sleep Apnea; Outcome; Patients; Pattern; Performance; Physiological; Physiological Processes; Polysomnography; Population; Predictive Value; Predisposition; Process; Property; Public Health; Quality of life; Research; Retrieval; Risk; Scientist; Sex Characteristics; Signal Transduction; Sleep; Sleep Apnea Syndromes; Sleep Deprivation; Smoking; Social Interaction; Social Network; Societies; Source; System; Systems Theory; Techniques; Testing; Tidal Volume; Time; Time Series Analysis; Titrations; Universities; Wakefulness; Woman; Work; Workplace; Zebra; adverse outcome; automobile accident; cost; design; executive function; experience; heart rate variability; improved; innovation; insight; men; neurophysiology; novel; novel strategies; pharynx muscle; respiratory; simulation; sleep onset; theories; tool

DESCRIPTION (provided by applicant): Sleep-disordered breathing (SDB) refers to a spectrum of disorders characterized by abnormal respiratory patterns or levels of ventilation during sleep. The most common is obstructive sleep apnea (OSA). People with OSA experience repetitive apnea (cessation of breathing) and hypopnea (marked decrease in tidal volume) during sleep in association with airway compromise and excessive daytime sleepiness (EDS). An arousal, or brief, often unnoticed, disruption of sleep is commonly associated with apnea. People with OSA also exhibit cognitive dysfunction, including impairment to memory, attention, and executive function. OSA- associated EDS and cognitive dysfunction are thought to significantly contribute to automobile accidents and workplace injuries. The first aim of this research is to predict the onset of nocturnal apnea, hypopnea, and arousal. Our proposal to accomplish this aim represents an entirely new approach to improving the effectiveness and tolerability of SBD therapy. The most common therapy is continuous positive airway pressure (CPAP), which is difficult for many patients to tolerate. Existing auto-adjusting PAP may be more tolerable but relies on detection of disordered breathing events and does not appear to improve quality of life compared with conventional CPAP. Predicting these events could lead to more effective titration of PAP levels and improved outcomes. Other therapies, such as the electrical stimulation of various cranial nerves or pharyngeal muscles, could also be improved by predicting disordered breathing. The second aim is to predict the onset of unintended daytime sleep while subjects undergo maintenance of wakefulness tests, which assess one's ability to resist sleep in a soporific condition. The third aim is to predict performance lapses during driving simulations. Accomplishing aims two and three could lead to the development of warning devices for at-risk individuals. Our novel prediction algorithms track the interactions between several physiological systems and reveal the most important predictors. The fourth aim is to contrast the key predictors between OSA, acutely sleep-deprived, and control subjects, and between men and women. By doing so, we expect to gain insight into the underlying pathophysiology of SDB and EDS, and will investigate sex differences in OSA and sleep deprivation. OSA is a major public health problem whose effects on society are comparable to those of smoking. The capability to predict its adverse consequences will be an invaluable tool to improve the quality of life of people with SDB, reduce the associated costs, and improve public health

描述（由申请人提供）：睡眠呼吸呼吸（SDB）是指以异常呼吸模式或睡眠期间通风水平为特征的疾病。最常见的是阻塞性睡眠呼吸暂停（OSA）。 OSA经历重复呼吸暂停（呼吸的停止）和呼吸呼吸症（潮汐体积减少）的人与气道折衷和过度的白天嗜睡（EDS）有关。唤醒或简短的，通常没有注意到的睡眠破坏通常与呼吸暂停有关。 OSA患者还表现出认知功能障碍，包括对记忆，注意力和执行功能的损害。据认为，与OSA相关的ED和认知功能障碍可显着造成汽车事故和工作场所伤害。这项研究的第一个目的是预测夜间呼吸暂停，呼吸症和唤醒的发作。我们实现此目标的建议是提高SBD疗法的有效性和耐受性的全新方法。最常见的疗法是连续的阳性气道压力（CPAP），这对于许多患者来说很难容忍。现有的自动调整后的PAP可能更容易容忍，但依赖于检测无序的呼吸事件，与常规CPAP相比，似乎没有改善生活质量。预测这些事件可能会导致PAP水平更有效的滴定和改善的结果。其他疗法，例如各种颅神经或咽肌的电刺激，也可以通过预测呼吸无序来改善。第二个目的是预测意想不到的白天睡眠的发作，而受试者进行清醒测试的维护，该测试评估了一个人在可厌食状态下抵抗睡眠的能力。第三个目的是预测驾驶模拟期间的性能失误。完成目标两个和三个可能会导致为高危个人开发警告设备。我们的新型预测算法跟踪了几种生理系统之间的相互作用，并揭示了最重要的预测因子。第四个目的是对比OSA，急性睡眠不足和控制对象以及男女之间的关键预测因素。通过这样做，我们希望能够深入了解SDB和EDS的基本病理生理学，并将研究OSA和睡眠剥夺的性别差异。 OSA是一个重大的公共卫生问题，其对社会的影响与吸烟的影响相当。预测其不利后果的能力将是提高SDB人生活质量，降低相关成本并改善公共卫生的宝贵工具