Inhibiting the Progression of Arterial Calcification with Vitamin K in HemoDialysis Patients (iPACK-HD) Trial: Rationale and Study Design for a Randomized Trial of Vitamin K in Patients with End Stage Kidney Disease
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease, which is due in part to progressive vascular calcification, is the leading cause of death among patients with end stage kidney disease (ESKD) on dialysis. A role for vitamin K in the prevention of vascular calcification is plausible based on the presence of vitamin K dependent proteins in vascular tissue, including matrix gla protein (MGP). Evidence from animal models and observational studies support a role for vitamin K in the prevention of vascular calcification. A large-scale study is needed to investigate the effect of vitamin K supplementation on the progression of vascular calcification in patients with ESKD, a group at risk for sub-clinical vitamin K deficiency. METHODS/DESIGN: We plan a prospective, randomized, double-blind, multicenter controlled trial of incident ESKD patients on hemodialysis in centers within North America. Eligible subjects with a baseline coronary artery calcium score of greater than or equal to 30 Agatston Units, will be randomly assigned to either the treatment group (10 mg of phylloquinone three times per week) or to the control group (placebo administration three times per week). The primary endpoint is the progression of coronary artery calcification defined as a greater than 15% increase in CAC score over baseline after 12 months. DISCUSSION: Vitamin K supplementation is a simple, safe and cost-effective nutritional strategy that can easily be integrated into patient care. If vitamin K reduces the progression of coronary artery calcification it may lead to decreased morbidity and mortality in men and women with ESKD. TRIAL REGISTRATION: NCT 01528800.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".