Vitamin K and cognitive function in healthy older adults. The NuAge Study
Bibliographic record
Abstract
Evidence is accumulating from in vitro and rodent studies that vitamin K plays a role in brain and could have a positive effect on cognitive function, especially during aging. The present study examined cross‐sectional associations between vitamin K status and cognitive performance in 320 cognitively‐healthy men and women aged 70–85 y from the Québec Longitudinal Study on Nutrition and Successful Aging. Vitamin K status was measured as serum phylloquinone concentrations. Verbal and non‐verbal episodic memory, executive functions, and speed of processing were assessed using 13 cognitive scores from 6 tests. The median serum phylloquinone concentration was 1.06 nmol/L (range, 0.08–23.57 nmol/L). After adjustment for covariates including diet quality and serum lipid profile, higher serum phylloquinone concentration (log‐transformed) was associated with better cognitive scores ( Z ‐transformed) on the second (β = 0.47; 95% CI = 0.13 to 0.82), the third (β = 0.41; 95% CI = 0.06 to 0.75), and the 20‐min delayed (β = 0.47; 95% CI = 0.12 to 0.82) trials of the RL/RI‐16 Free and Cued Recall Task, a test of verbal episodic memory. No associations were found with non‐verbal episodic memory, executive functions, and speed of processing. Overall, our study provides evidence for a role of vitamin K in episodic verbal memory among healthy older adults. This research was supported by the Canadian Institutes of Health Research.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".