| Autor: |
Kalyan Palepu, Kolia Sadeghi, Dave Kleinschmidt, Jacob Donoghue, Seth Chapman, Alex Arslan, M. Brandon Westover, Sydney S. Cash, Jay Pathmanathan |
| Rok vydání: |
2022 |
| DOI: |
10.21203/rs.3.rs-1558817/v1 |
| Popis: |
Study Objectives. Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design. Methods. We estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by ability to distinguish NREM2 from other NREM sleep stages and by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial. Results. Mean sigma power in NREM2 was indistinguishable from other NREM states in 25% of recordings, vs only 7% for direct spindle measurement (P |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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