0271 Actigraphy Based Measures of Sleep Disruption and Circadian Rhythms in the WashU Biomarkers of Alzheimer’s Disease in Sleep and EEG (BASE) Cohort
Bibliographic record
Abstract
Abstract Introduction Prospective studies of Alzheimer’s disease (AD) demonstrate sleep-wake disturbances may precede and accelerate with cognitive decline. Use of wrist-actigraphy in conjunction with overnight polysomnography (PSG) enables researchers to evaluate diverse characteristics of sleep and circadian rhythms. Though outcome measures from these devices have been implicated in the progression of AD, because of great individual differences, it is valuable to internally replicate within cohort. Here we demonstrate application of actigraphy in the context of healthy aging to identify patterns of activity that predict cognitive decline. Methods Participants were prospectively recruited at Washington University as part of the BASE study and wore an Actiwatch2 (Philips-Respironics) and cross-validated for sleep and wake using polysomnography. The watch was worn continuously for at least 5 consecutive nights to be included in the analysis (n = 68, age = 71.1 ± 4.5 years). Rest-activity rhythms were computed using compiled code from National Sleep Research Resource (actiCircadian) pipeline implemented in MATLAB R2021a (Mathworks). Clinical Dementia Rating (CDR) scales and cognitive tests were conducted on the first day of actigraphy recording. Results Individuals with cognitive impairment (CDR Global Score > 0) had increased wake after sleep onset (WASO) and reduced sleep efficiency compared with individuals with no impairment (CDR = 0). (unpaired ttest: p = 0.02 and p = 0.02). Participants with cognitive impairment had a trend toward reduced relative amplitude (RA) (p = 0.06). Reduced (worse) RA was correlated with worse performance on the Trail Making Task A (Pearson r: -0.37, p = 0.002). Higher (better) interdaily Stability (IS) was associated with better responses on subjective questionnaires including Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index (Pearson r: -0.24 p = 0.051; r: 0.242, p = 0.047, respectively). Conclusion Actigraphically-derived rest-activity metrics are correlated with cognitive status, cognitive test performance, and subjective sleep questionnaires. Support (If Any) NIH R01 AG059507, ARCS Foundation Scholar
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".