1156 Polysomnographic Total Sleep Time: A Novel Biomarker For Dementia

Abstract

Abstract Introduction Neuroprotection, early diagnosis, and behavioral intervention are national priorities for dementia research. Sleep duration is emerging as an important potential remediable risk factor. In this study, we examined whether total sleep time (TST) derived from attended overnight polysomnography (PSG) studies is associated with an increased prevalence of dementia diagnosis and determined the optimal cut-point. Methods We identified 69,847 PSG sleep studies using CPT code 95810 from 2000-19 in the US Department of Veteran Affairs (VA) national database of patient care. We used natural language processing to verify PSG reports and extract TST values from the patient free-text notes. We examined a TST of 240-420 minutes in 10-minute increments using a run chart (time series) approach to determine the optimal cut-point for determining greater odds of dementia. Results Patients had a mean age of 55.4±13.8, 91.5% were male, and 64% were Caucasian. PSG studies revealed a mean TST of 310.6±79.5 minutes. The run chart time series analysis revealing < 360 minutes being the optimal cut-point for increased odds of dementia (OR: 1.64, 95% CI: 1.36-1.99, p<.05). Conclusion Lower TST predicted higher prevalence of dementia diagnosis. TST of 360 minutes may serve as the optimal cut-point to determine greater odds of dementia. This is an important study examining PSG sleep duration and the prevalence of dementia across 19 years in the largest integrated healthcare system in the US. TST may function as a potential biomarker for developing dementia. Support This material is based upon work supported in part by the Department of Veteran Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). Dr. Nowakowski is also supported by a National Institutes of Health (NIH) Grant (R01NR018342).