Vitamin K status and inflammation are associated with cognition in older Irish adults
Bibliographic record
Abstract
Studies have shown associations between reduced vitamin K status and poor cognitive function. However, despite this apparent link, direct studies measuring cognitive function, vitamin K status and inflammation are lacking. In the current study, The ELDERMET cohort was investigated to identify associations between cognition, vitamin K status and inflammation. The primary aim of the ELDERMET study was to investigate the relationship between gut bacteria, diet, lifestyle and health in 500 older Irish adults. Significant differences in serum phylloquinone, dietary phylloquinone and inflammatory markers were found across varying levels of cognitive function, after controlling for sex, age, body mass index (BMI), triglycerides and blood pressure. In addition, significantly higher levels of dietary phylloquinone were found in those with better cognition compared to those with the poorest function. Higher levels of inflammatory were also associated with poor cognition. Furthermore, both dietary and serum phylloquinone were significant independent predictors of good cognitive function, after controlling for confounders. This study highlights the importance of dietary vitamin K as a potentially protective cognitive factor; it also provides evidence for the correlation between cognition and inflammation. Strategies should be devised by which elderly populations can access rich dietary sources of phylloquinone to maintain cognition.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".