Reference:
Al Ashry H, Ni Y, Thomas R. Characteristics Cardiopulmonary Sleep Spectrograms Open a Novel Window Into Sleep Biology – Implications for Health and Disease. Front. Neurosci., 2021. DOI:10.3389/fnins.2021.755464
Objectives:
To review physiological basis, techniques and applications of CardioPulmonary Coupling (CPC) output and spectrograms in sleep, in health and disease and to show that: (1) CPC shows a fundamental characteristic of NREM sleep – bimodality, across number of physiologies, (2) CPC has several uses in sleep apnea care – diagnosis, phenotype, tracking outcomes, (3) CPC can diagnose and track non-apneic sleep fragmentation and medication effects, and should be used in the appropriate clinical context.
Conclusion:
The CPC method provides a window into sleep physiology and key information about sleep during health and disease. There are several forms of CPC, which may provide information about normal sleep physiology and pathological sleep states ranging from insomnia to sleep apnea and hypertension. Sleep profiling using CPC demonstrates the impact of stable and unstable sleep on insomnia (exaggerated variability), hypertension (unstable sleep as risk factor), improved glucose handling (associated with stable sleep), drug effects (benzodiazepines increase sleep stability), sleep apnea phenotypes (obstructive vs. central sleep apnea), sleep fragmentations due to psychiatric disorders (increased unstable sleep in depression).
Practical Significance:
As CPC may be computed from reduced or limited signals such as the electrocardiogram (ECG) or photoplethysmogram (PPG) vs. full polysomnography (PSG), a wide application, including wearable and non-contact devices is possible, allowing for studying sleep in greater numbers, and with greater ease, in a wider range of conditions, with nearly limitless repeatability, than typically possible with traditional PSG or current home sleep apnea testing devices (HSAT). When computed from PPG, which may be acquired from oximetry alone, an automated apnea hypopnea index (sAHI) derived from CPC-oximetry can be calculated.