Vitamin K Supplementation for the Prevention of Cardiovascular Disease: Where Is the Evidence? A Systematic Review of Controlled Trials
Bibliographic record
Abstract
Matrix gla protein (MGP) is an important vitamin K-dependent inhibitor of vascular calcification. High levels of uncarboxylated, dephosphorylated MGP have been associated with vascular calcification and are responsive to vitamin K treatment. In this systematic review, we summarize the available evidence examining whether vitamin K supplementation improves surrogate measures of cardiovascular disease including artery and valve calcification, atherosclerosis and artery stiffening. Data from controlled trials of adults were obtained by searching Ovid MEDLINE, Embase, the Cochrane Central Register of Controlled Trials and the Web of Science Core Collection. We identified nine randomized controlled trials for review, including trials of vitamin K1 or vitamin K2 supplementation, that assessed a surrogate measure of cardiovascular disease including arterial calcification, atherosclerosis or arterial stiffening. For each trial, the risk of bias was assessed applying Cochrane Collaboration methodology. The findings indicate that vitamin K does not consistently prevent progression of calcification, atherosclerosis or arterial stiffness. There may be some benefit in people with calcification at study entry. Studies were heterogenous, with relatively short follow-up and outcome measures were varied. While vitamin K supplementation clearly improves the carboxylation of dephosphoylated MGP, its role in mitigating vascular calcification is uncertain, based on current evidence.
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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 | 0.011 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.009 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".