Warfarin and aortic valve calcification in hemodialysis patients
Bibliographic record
Abstract
Abstract Background: This retrospective cohort study was designed to determine the association between long-term exposure to warfarin and severity of aortic valve (AV) calcification in hemodialysis (HD) patients. Methods: One hundred and eight HD patients underwent a study-specific echocardiogram. A grading scheme was used to classify AV calcification as none, mild, moderate and severe. Demographic, biochemical and medication data were abstracted by chart review. Results: One hundred and eight subjects were enrolled. A minority had no calcification (n=17, 15.7%), the majority had mild calcification (n=62, 57.4%), and fewer had calcification rated as moderate (n=16, 14.8%) or severe (n=13, 12%). Dialysis vintage was associated with severity of AV calcification (p=0.04). The 18 subjects with long-term warfarin exposure (36.7 ± 19.7 months) were more likely to have severe AV calcification (p=0.04). The odds ratio of falling into a higher category of AV calcification following 18 months of warfarin was 3.77 (95% confidence ratio, 0.97-14.70; p=0.055). There was an association between lifetime months of warfarin exposure and severity of AV calcification (p=0.004) that was independent of dialysis vintage, calcium and calcitriol intake. Conclusions: The data suggest that warfarin may be associated with severity of AV calcification in HD patients and support the need for prospective studies.
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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 | 0.002 |
| 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 | 0.001 |
| 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".