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

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.