Assessing Risk of Health Outcomes From Brain Activity in Sleep

**Background and objectives: **Patterns of electrical activity in the brain
(EEG) during sleep are sensitive to various health conditions even at
subclinical stages. The objective of this study was to estimate sleep EEG-
predicted incidence of future neurologic, cardiovascular, psychiatric, and
mortality outcomes.

**Methods: **This is a retrospective cohort study with 2 data sets. The
Massachusetts General Hospital (MGH) sleep data set is a clinic-based cohort,
used for model development. The Sleep Heart Health Study (SHHS) is a
community-based cohort, used as the external validation cohort. Exposure is
good, average, or poor sleep defined by quartiles of sleep EEG-predicted risk.
The outcomes include ischemic stroke, intracranial hemorrhage, mild cognitive
impairment, dementia, atrial fibrillation, myocardial infarction, type 2
diabetes, hypertension, bipolar disorder, depression, and mortality. Diagnoses
were based on diagnosis codes, brain imaging reports, medications, cognitive
scores, and hospital records. We used the Cox survival model with death as the
competing risk.

**Results: **There were 8673 participants from MGH and 5650 from SHHS. For
all outcomes, the model-predicted 10-year risk was within the 95% confidence
interval of the ground truth, indicating good prediction performance. When
comparing participants with poor, average, and good sleep, except for atrial
fibrillation, all other 10-year risk ratios were significant. The model-
predicted 10-year risk ratio closely matched the observed event rate in the
external validation cohort.

**Discussion: **The incidence of health outcomes can be predicted by brain
activity during sleep. The findings strengthen the concept of sleep as an
accessible biological window into unfavorable brain and general health
outcomes.