HEART RATE VARIABILITY IN SLEEP-DISORDERED BREATHING

睡眠呼吸紊乱时的心率变异性

• 批准号: 6870260
• 负责人: MICHAEL C K KHOO
• 金额: $ 15.47万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2007-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6870260
• 关键词: REM sleep; autonomic nervous system; clinical research; heart rate; human data; neuroregulation; polysomnography; pulmonary respiration; respiratory airflow disorder; sleep disorders

DESCRIPTION (provided by applicant): The long-term objective of this project is to determine whether mild-to-moderate sleep-disordered breathing (SDB) leads to alterations in cardiac autonomic control that are detectable from nocturnal measurements of heart rate variability (HRV) and respiration. Since conventional spectral analysis of HRV can be seriously confounded by inter-subject differences or intra-individual changes in ventilation and ventilatory pattern during SDB, a recently developed algorithm will be used to compute "respiration-adjusted" spectral indices of HRV. This algorithm will be applied to a large sample of cardiorespiratory data derived from unattended home-based polysomnograms collected by the Sleep Heart Health Study. The specific goals of this study are to determine whether: (1) the conventional and "respiration-adjusted" spectral indices of HRV in quiet wakefulness are correlated with apnea-hypopnea index in individuals with severity of SDB; (2) chronic exposure to SDB alters the dependencies of the "respiration-adjusted" spectral indices of HRV on sleep state; (3) increasing severity of SDB leads to alterations in the amplitude and time-course of ultradian oscillations in the derived "respiration-adjusted" spectral measures of HRV. The application of this form of HRV analysis to a large database of polysomnographic data is likely to lead to a better understanding of the causal links that relate SDB to cardiovascular or cerebrovascular disease. As well, improved knowledge of the nocturnal rhythmicity of fluctuations in intrinsic autonomic activity and how this changes with chronic exposure to SDB could also provide important insights into the timing of acute cardiovascular events, such as myocardial infarction and stroke.

描述（由申请人提供）：该项目的长期目标是确定轻度到中度的睡眠呼吸（SDB）是否会导致心脏自主控制的改变，这些呼吸可从心率变异性（HRV）和呼吸的夜间测量中检测到。由于SDB期间的通气间差异或个性化通气和通气模式的个体内变化可能会严重混淆HRV的常规光谱分析，因此最近开发的算法将用于计算“呼吸调整后的” HRV光谱独立性。该算法将应用于大量的心肺数据样本，这些数据是根据Sleep Heart Health研究收集的无人看管的基于家用的多聚词的。这项研究的具体目标是确定：（1）在安静清醒中，HRV的常规和“呼吸调整”光谱指数与SDB严重程度的个体中的呼吸暂停指数相关； （2）长期暴露于SDB会改变HRV对睡眠状态的“呼吸调整”光谱指数的依赖性； （3）SDB的严重程度的增加会导致在衍生的“呼吸调整后的”频谱测量中的超级振荡幅度和时间顺序的改变。这种形式的HRV分析应用于大量的多摄影数据数据库，可能会使人们更好地了解将SDB与心血管或脑血管疾病相关的因果关系。同样，对内在自主活动的波动的夜间节奏性的提高知识以及长期暴露于SDB的变化也可以为急性心血管事件的时机（例如心肌梗塞和中风）提供重要的见解。