0109 Exploring the Link Between Total Sleep Duration on Cognitive Performance in Older Veterans: A Preliminary Report
Bibliographic record
Abstract
Abstract Introduction Sleep is an influential factor in cognitive performance, with short sleep duration (6 hours or less) negatively impacting cognition. Prolonged, untreated sleep disturbances have been linked to dementia diagnosis and Alzheimer’s disease. Methods Here, we conducted a secondary cross-sectional data analysis from a clinical trial (NCT05500170, PI: Weiss) investigating the effects of dietary supplementation with nicotinamide riboside on sleep and cognition in older Veterans (n=24, aged 65-85 years old). We focused on baseline findings related to sleep duration and cognitive function, employing descriptive analysis and Pearson correlation coefficients. Sleep duration was collected using the Fitbit Charge 5, a wrist-worn device capable of monitoring multiple sleep parameters, including total sleep time, time in bed, sleep efficiency, sleep latency, and wake after sleep onset. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA), a screening tool for mild cognitive dysfunction. The MoCA analyzes various cognitive domains, including attention and concentration, orientation, language, and memory, with an additional point awarded for higher education attainment. MoCA total score ranges from 0 to 30, with scores above 26 indicating normal cognition, 18-25 reflecting mild cognitive impairment, 10-15 indicating moderate impairment, and severe impairment with a score below 10. Results Participants reported TST ranged from 1.84-6.70 hours, and MoCA scores ranged from 25-29 (SD value = 1.25). Preliminary findings showed a modest positive correlation between average baseline total sleep duration and cognitive function (r=0.362). Conclusion Future investigations will assess the longitudinal relationship between total sleep duration and cognition progression. Support (if any) NIA: 4R00AG079117-03 (Weiss)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".