Assessment of Potential Biomarkers of Subclinical Vitamin K Deficiency in Patients with End-Stage Kidney Disease
Bibliographic record
Abstract
BACKGROUND: A significant proportion of hemodialysis patients have functional, but modifiable, vitamin K deficiency. OBJECTIVE: To determine the correlates of poor vitamin K status in hemodialysis patients. DESIGN: Cross-sectional study. SETTING: Hemodialysis units at Kingston General Hospital and its satellite centres, Ontario, Canada. PATIENTS: Patients undergoing outpatient hemodialysis for end-stage kidney disease. MEASUREMENTS: Serum concentrations of phylloquinone, undercarboxylated prothrombin, also known as protein induced by vitamin K absence or antagonism - factor II (PIVKA-II), and the percentage of undercarboxylated osteocalcin (%ucOC). METHODS: Vitamin K status was determined in fasting blood samples of hemodialysis patients. Bivariate relationships were examined using parametric and non-parametric statistics as appropriate. Multivariable linear regression models were applied to identify predictors of vitamin K status. RESULTS: Among 44 HD patients, criteria for subclinical vitamin K deficiency were met in 13.6% (phylloquinone < 0.4 nmol/L), 51% (%ucOC > 20%) and 90.9% (PIVKA-II > 2.0 nmol/L) of subjects. Phylloquinone levels were positively associated with total cholesterol, triglyceride levels and non-smoking status. Higher %ucOC was associated with increased calcium-phosphate product. Increased PIVKA-II levels were observed with advancing age, reduced dialysis adequacy, lower HDL and a history of coronary artery disease. There were no associations found among the individual biomarkers of vitamin K status. In a multi-variable model, triglycerides were the only significant predictor of phylloquinone levels, while increasing phosphate and decreasing PTH were independent predictors of %ucOC. PIVKA-II levels increased by 0.54 nmol/L for every 10-year increase in age. LIMITATIONS: Observational study; small sample size. CONCLUSIONS: A significant proportion of HD patients met criteria for subclinical vitamin K deficiency. Of the biomarkers measured, PIVKA-II may be superior given its independence of renal function or dyslipidemia, both of which may confound the other vitamin K biomarkers. Studies in patients with ESKD linking biomarkers of vitamin K status to important patient outcomes, including cardiovascular disease, nutritional status and mortality, are required in order to determine the optimal biomarker for evaluating vitamin K status in this particular population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".