P4‐434: SLEEP AND COGNITIVE FUNCTION IN CHRONIC STROKE: A COMPARATIVE CROSS‐SECTIONAL STUDY
Bibliographic record
Abstract
Poor sleep is common following stroke, limits stroke recovery, and can contribute to further cognitive decline post-stroke. However, it is unclear what aspects of sleep are different in older adults with stroke compared to those without, and whether the relationship between sleep and cognitive function differs by stroke history. We therefore investigated whether older adults with stroke experience poorer sleep quality than older adults without stroke, and whether poor sleep quality attenuates cognitive performance among older adults with a history of stroke. This was an age- and sex-matched comparative cross-sectional study (Figure 1). Thirty five age- and sex-matched older adults with stroke (Age: 69.86 ± 1.13 years; 51.43% female) and without stroke (Age: 69.83 ± 1.12; 51.43% female) were compared with respect to sleep quality using the MotionWatch8© (MW8) and Pittsburgh Sleep Quality Index (PSQI). Cognitive performance was indexed using the Alzheimer's Disease Assessment Scale Plus (ADAS-Cog Plus). We examined differences in sleep quality and cognitive performance between groups using analysis of covariance (ANCOVA) controlling for age, sex, smoking history, body mass index, sleep medication use, and obstructive sleep apnea (OSA) diagnosis. Additionally, we performed multiple linear regressions to examine to examine the relationship between sleep quality and cognitive function based on history of stroke, while controlling for age, sex, education and OSA diagnosis. Our ANCOVA models are described in Table 1. Older adults with stroke had longer MW8 measured sleep duration (27.82 ± 12.17 minutes; p= 0.03) and greater fragmentation (6.44 ± 2.24; p< 0.01), but did not differ in PSQI from their non-stroke peers. There was a significant group x sleep quality interaction for fragmentation (β= 0.02; p< 0.01) (Figure 2) and efficiency (β= −0.03; p= 0.02) (Figure 3) on ADAS-Cog Plus performance, whereby differences in cognitive performance between older adults with and without stroke were accentuated in the presence of poor sleep quality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".