HEART RATE VARIABILITY IN SLEEP-DISORDERED BREATHING

睡眠呼吸紊乱时的心率变异性

• 批准号: 6760818
• 负责人: MICHAEL C K KHOO
• 金额: $ 15.48万
• 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 2006-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6760818
• 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）：本项目的长期目标是确定轻度至中度睡眠呼吸障碍（SDB）是否会导致心脏自主控制的改变，这些改变可通过夜间心率变异性（HRV）和呼吸测量来检测。由于常规的HRV频谱分析可能会受到SDB期间通气和呼吸模式的受试者间差异或个体内变化的严重混淆，因此最近开发的算法将用于计算HRV的“呼吸调整”频谱指数。该算法将被应用到一个大样本的心肺数据来自无人值守的家庭为基础的多导睡眠图收集的睡眠心脏健康研究。本研究的具体目的是确定：（1）安静清醒状态下HRV的常规和“呼吸调整”频谱指数与严重SDB个体的呼吸暂停低通气指数是否相关;（2）长期暴露于SDB改变了“呼吸调整”HRV频谱指数对睡眠状态的依赖性;（3）SDB的严重程度增加导致HRV的“呼吸调整”频谱测量中的超日振荡的幅度和时间过程的改变。将这种形式的HRV分析应用于大型多导睡眠图数据库可能会更好地了解SDB与心血管或脑血管疾病之间的因果关系。此外，对内在自主活动波动的夜间节律性以及这种波动如何随着长期暴露于SDB而变化的更好了解也可以为急性心血管事件（如心肌梗死和中风）的时间提供重要见解。