Vitamin K Antagonists and Cognitive Function in Older Adults: The Three-City Cohort Study
Bibliographic record
Abstract
BACKGROUND: A growing body of evidence supports a beneficial role for vitamin K in brain and cognition, notably in studies where animals are rendered vitamin K deficient by warfarin, a potent vitamin K antagonist (VKA). Given VKAs are commonly used oral anticoagulants in older persons, we investigated the relationship between VKA therapy and cognitive performances over 10 years in participants of the Three-City study. METHODS: The Three-City cohort included 7,133 nondemented community dwellers, aged 65 years or older at baseline. Exposures to VKAs and platelet aggregation inhibitors, another antithrombotic agent, were determined at baseline. Participants underwent cognitive assessment at baseline and every 2 years over 10 years. Associations were analyzed with mixed linear models adjusting for many covariates including VKA and platelet aggregation inhibitor indications. RESULTS: About 239 (3.4%) and 1,192 (16.7%) of the participants were treated with VKAs and platelet aggregation inhibitors at baseline, respectively. VKA treatment was significantly associated with worse performances on Benton Visual Retention Test assessing visual memory (adjusted mean difference -0.29; p = .02 in multivariate models) and Isaacs Set Test assessing verbal fluency (adjusted mean difference -1.37; p = .0009) at baseline. Treatment with VKAs was not associated with global cognitive functioning on the Mini Mental State Examination, neither with rate of subsequent decline in scores on all three cognitive tests. No associations were found between platelet aggregation inhibitors and cognitive performances or rate of decline. CONCLUSION: These findings do not indicate a long-term detrimental effect of VKAs on cognition, but the risk-benefit balance of VKA treatment still deserves further 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".