Health-Oriented Sleep States: Making Sleep States Reflect Health Conditions.

Study Objectives: The rich information in sleep offers insights into brain function and overall health. The current guidelines for sleep staging by the American Academy of Sleep Medicine (AASM) rely on relatively broad categorizations. These traditional sleep stages are not optimized to reflect health status. Here, we propose health-oriented sleep states (HOSS) to better associate with pre-existing health conditions.

Methods: This observational retrospective cohort study involved 8673 participants from the Massachusetts General Hospital sleep laboratory. We examined seven pre-existing conditions: mild cognitive impairment (MCI), ischemic stroke, atrial fibrillation, myocardial infarction, type-2 diabetes, hypertension, and depression. We clustered a sleep staging model's hidden layer within each stage, where clusters represent sleep states. The number of sleep states was selected to maximize the average association with the health conditions, using the average area under the receiver operating characteristic curve (AUROC) across outcomes based on time spent in these states. We also assessed the area under the precision-recall curve (AUPRC).

Results: We identified 3 states within N3, 14 in N2, 6 in N1, 3 in R, and 9 in W. AUROC ranged from 0.608 to 0.723 across the seven outcomes, and AUPRC from 0.064 to 0.524. Among these outcomes, MCI/dementia, atrial fibrillation, myocardial infarction, and hypertension demonstrated significantly stronger associations with the health conditions compared to conventional AASM sleep stages.

Conclusions: Novel sleep states are linked to health conditions. A better understanding of the physiology behind these sleep states may further enhance the concept of using sleep as a window into overall health.