Prevalent hypertension and stroke in the Sleep Heart Health Study: association with an ECG-derived spectrographic marker of cardiopulmonary coupling.

CONVENTIONAL POLYSOMNOGRAPHY CATEGORIZES SLEEP IN STAGES N1, N2, N3, AND REM. THIS SCORING IS BASED ON PREDOMINANT ELECTROENCEPHALOGRAPHIC (EEG) frequency, amplitude, and the occurrence of characteristic wave complexes, along with eye movements and chin muscle tone, that predominate within consecutive 30-sec epochs. Scoring of respiratory abnormality during sleep identifies and counts discrete episodes of reductions in flow, which are further characterized as central or obstructive, based on measures of respiratory effort or related flow signal characteristics. While these scoring approaches yield useful information, they provide summary measures that may fail to capture other key aspects of sleep quality and respiratory disturbance during sleep. For example, conventional scoring does not take into account the sequential dynamics of respiratory fluctuations or of cardiopulmonary coupling. Polysomnographic methods that complement standard approaches have been described. One such approach to characterize sleep uses the stability domain.1,2 A proposed EEG marker of unstable NREM sleep is termed cyclic alternating pattern (CAP),1 in which repetitive phasic events (slow wave bursts, α and β frequency intrusions into ongoing NREM sleep) alternate with a background with lower EEG amplitude. When phasic events are absent or do not reach amplitude criteria, sleep is designated as stable, or non-CAP. This approach is purely EEG-based and is limited by dependence on EEG amplitude changes. We developed a method to characterize sleep stability, using a continuous single-channel ECG, by mathematically combining QRS (R) wave amplitude fluctuations that are related to the mechanical effects of respiration (ECG-derived respiration signal) with heart rate variability changes that are associated with neuroautonomic tone modulation.3 The output of this method, called the sleep spectrogram, provides both graphical and numerical data that are measures of cardiopulmonary coupling interactions. Low frequency coupling predominates in unstable NREM sleep and correlates with periods of CAP, while high frequency coupling predominates in stable NREM sleep and correlates with non-CAP. A subset of low frequency coupling, designated as elevated-low frequency coupling (e-LFC), was found to correlate with visually scored apneas and hypopneas.4 Further, analysis of the spectral dispersion of e-LFC showed 2 distinctive patterns, a narrow spectral band e-LFC (e-LFCNB) and a broad spectral band elevated-low frequency coupling.4 We have shown that e-LFCNB is associated with central apneas and periodic breathing and is a biomarker that predicts the induction of central apneas during positive airway pressure titration.4 To further explore the pathophysiological implications and potential utility of this ECG-derived measure, we examined the clinical and polysomnographic correlates of e-LFCNB in the large, community-based cohort of middle-aged and older adults participating in the Sleep Heart Health Study. Specifically, we explored the relation of e-LFCNB to sleep quality after adjusting for sleep apnea severity, age, body mass index, and associations with hypertension or vascular disease. Our hypothesis was that e-LFCNB would be associated with greater severity of sleep apnea and an increased adjusted risk of hypertension, secondary to excessive activation of the respiratory chemoreflex.