0056 Rest-Activity Rhythms (RARs) and Cognitive Functions in Early Post-menopausal Women
Bibliographic record
Abstract
Abstract Introduction RAR disruptions are more common among individuals with dementia than healthy individuals. In healthy older women, RAR disruption predicted future diagnosis of Mild Cognitive Impairment (MCI). With no cure for Alzheimer’s Disease, it is crucial to identify modifiable risk-factors for early prevention of cognitive decline. Here we aim to determine whether RAR disruption was associated with cognitive status and cognitive performance in early post-menopausal women, thereby representing a modifiable risk factor for dementia. Methods The sample drawn from MsBrain study, included 229 cognitively unimpaired women and 42 women with MCI/dementia, based on score on Montreal Cognitive Assessment (MOCA) adjusted for age and race. Participants completed a 72-hour wrist actigraphy monitoring and neuropsychological assessment including: California Verbal Learning Test (CVLT), Letter Number Sequencing (LNS), Card Rotation Test, Symbol Digit Modalities Test (SDMT). Latent profile analysis (LPA) was performed using five nonparametric RAR variables (intra-daily variability (IV), inter-daily stability (IS), relative amplitude (RA), alpha and F-statistic). The association between RAR clusters and cognitive performance and the relationship between RAR clusters, cognitive status and race/ethnicity were assessed using linear regression models, controlling for age, race/ethnicity, education and body mass index (BMI); and using chi-square test respectively. Results LPA revealed three clusters: Robust with high F-Stat, RA and IS and low IV; Normal;Weak with low RA and high alpha. The proportion of subjects with MCI/dementia did not differ between clusters however there was a significant association between race and RAR clusters, X2 (2, N = 271)=14.18, p<0[P1] .001, with non-white women more likely than white women to belong in the Weak group (p < .01). In an adjusted analysis of healthy women, the Weak group performed worse than the Robust group in LNS control (p<.050 ). In the unadjusted model, the Weak group performed worse than Robust group in CVLT Total Learning and Long Delay Recall and SDMT (p=.0074, p=.011and p= .0041, respectively). Conclusion Non-white women had weaker RAR than their white counterparts. Weaker RARs related to poorer working memory as measured by LNS; and poorer verbal memory and processing speed, measured by CVLT and SDMT however these effects were largely influenced by covariates, particularly race/ethnicity and education. Support (If Any)
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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 | 0.000 | 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) | 0.002 | 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 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".