Active Vitamin D and Accelerated Progression of Aortic Stiffness in Hemodialysis Patients: A Longitudinal Observational Study
Bibliographic record
Abstract
BACKGROUND: We hypothesized that high-dose active vitamin D therapy in the form of alphacalcidol (α-calcidol), used to treat secondary hyperparathyroidism in chronic kidney disease, could lead to vascular calcification and accelerated progression of aortic stiffness. METHODS: We conducted an observational study in 85 patients on chronic hemodialysis, among which 70 were taking a weekly dose of α-calcidol of <2 µg and 15 were taking a weekly dose of ≥2 µg (pharmacological dose). Parathyroid hormone, 25-hydroxyvitamin D, fibroblast growth factor 23, and α-klotho were determined. Aortic stiffness was assessed by determination of carotid-femoral pulse wave velocity (cf-PWV) at baseline and after a mean follow-up of 1.2 years. A multivariable regression model was used to evaluate the impact of pharmacological dose of α-calcidol on the progression of aortic stiffness. RESULTS: At baseline, clinical, biological, and hemodynamic parameters were similar. At follow-up, cf-PWV increased more in patients with pharmacological dose of α-calcidol (0.583±2.291 m/s vs. 1.948±1.475 m/s; P = 0.04). After adjustment for changes in mean blood pressure and duration of follow-up, pharmacological dose of α-calcidol was associated with a higher rate of progression of cf-PWV (0.969 m/s; 95% confidence interval = 0.111-1.827; P = 0.03), and this association persisted after further adjustments for parameters of mineral metabolism. CONCLUSIONS: In this study, pharmacological dose of α-calcidol was associated with accelerated progression of aortic stiffness. This study suggest that the vascular safety of active vitamin D posology may need to be specifically addressed in the treatment of chronic kidney disease-related bone mineral disorder.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".