Quantitative measurement of sleep quality using cardiopulmonary coupling analysis: a retrospective comparison of individuals with and without primary insomnia

• Published in: Sleep & breathing Vol. 17; no. 2; pp. 713 - 721
• Main Authors: Schramm, Preetam J., Thomas, Robert, Feige, Bernd, Spiegelhalder, Kai, Riemann, Dieter
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.05.2013; Springer; Springer Nature B.V
• Subjects: Adult; Autonomic Nervous System - physiopathology; Biological and medical sciences; Cardiopulmonary resuscitation; Comparative studies; CPR; Dentistry; Disorders of higher nervous function. Focal brain diseases. Central vestibular syndrome and deafness. Brain stem syndromes; Electrocardiography; Female; Fourier Analysis; Fundamental and applied biological sciences. Psychology; Heart Rate - physiology; Humans; Insomnia; Internal Medicine; Male; Medical sciences; Medicine; Medicine & Public Health; Middle Aged; Multiple sclerosis and variants. Guillain barré syndrome and other inflammatory polyneuropathies. Leukoencephalitis; Multivariate Analysis; Nervous system (semeiology, syndromes); Neurology; Original Article; Otorhinolaryngology; Pediatrics; Pneumology/Respiratory System; Polysomnography; Reference Values; Respiration; Signal Processing, Computer-Assisted; Sleep apnea; Sleep Initiation and Maintenance Disorders - etiology; Sleep Initiation and Maintenance Disorders - physiopathology; Sleep Stages - physiology; Sleep. Vigilance; Vertebrates: nervous system and sense organs; Cardiopulmonary coupling; Sleep spectrogram; Insomnia; Electrocardiogram; Nervous system diseases; Sleep disorder; Retrospective; Sleep; Electrocardiography; Sleep wake cycle; Coupling; Neurological disorder; Comparative study
• ISSN: 1520-9512; 1522-1709; 1522-1709
• DOI: 10.1007/s11325-012-0747-6

Objective The purpose of this study was to determine the utility of a new operator-independent, automated measure of sleep physiology based on cardiopulmonary coupling (CPC) analysis in subjects with primary insomnia vs. good sleepers. Patients/methods The polysomnograms of 50 subjects with primary insomnia and 36 good sleepers were summarized and analyzed from a consecutive two-night protocol. The electrocardiograms (ECG) from adaptation and baseline night polysomnograms were analyzed using CPC analysis. This Fourier-based technique uses heart rate variability and ECG R wave amplitude fluctuations associated with respiration to generate frequency maps of coupled autonomic–respiratory oscillations. The resulting sleep spectrogram is able to categorize sleep as “stable” (high-frequency coupling [HFC], 0.1–0.4 Hz) and “unstable” (low-frequency coupling [LFC], 0.1–0.01 Hz), independent of standard sleep stages. Wake and rapid eye movement sleep exhibit very low-frequency coupling (VLFC, 0.0039–0.01 Hz). Elevated LFC (e-LFC) is a subset of LFC that is associated with fragmented sleep of various etiologies. Results CPC variables showed a significant multivariate analysis of variance group, night, and group × night main effect, except for HFC by night. Relative to good sleepers, primary insomnia patients on adaptation night had lower HFC, a putative biomarker of stable sleep, and HFC/LFC ratio, an indicator of sleep quality. The primary insomnia group also had higher LFC, an index of unstable sleep, and an increase in VLFC and e-LFC compared to good sleepers on adaptation night. On baseline night, the primary insomnia group had increased LFC, VLFC, and e-LFC and a lower HFC/LFC ratio. Except for HFC, good sleepers had larger CPC variable differences between adaptation and baseline nights compared to the primary insomnia group. Conclusion Primary insomnia subjects have a marked worsening of sleep quality on the adaptation night, which is well captured by both conventional and ECG-derived sleep spectrogram techniques. The larger improvement of sleep quality was found among good sleepers and captured only by CPC analysis. The operator-independent, automated measure of sleep physiology demonstrated functionality to differentiate and objectively quantify sleep quality.