Weekly high‐dose ergocalciferol to correct vitamin <scp>D</scp> deficiency/insufficiency in hemodialysis patients: A pilot trial
Bibliographic record
Abstract
Controversy exists on which vitamin D (D2 or D3) and which dosage scheme is the best to obtain and maintain adequate 25 OH D levels in dialysis patients safely. We tried to determine whether high-dose vitamin D2 supplementation could obtain optimal vitamin D status without inducing hypercalcemia. We studied 82 patients on dialysis not taking active vitamin D therapy and supplemented them with oral vitamin D2 72,000 IU/week for 12 weeks followed by 24,000 IU/week as maintenance therapy during 36 weeks. By week 12, serum 25(OH)D increased from 15.2 ± 5.4 to 42.5 ± 13.2 ng/mL (P < 0.01) at week 12 and remained optimal (34.7 ± 12.0); 84.8% of the patients reached values ≥30 ng/mL. iPTH and alkaline phosphatase did not change at 48 weeks compared with baseline, but bone alkaline phosphatase decreased significantly (54.3 ± 46.0 to 44.3 ± 25.0; P = 0.02). Uncorrected serum Ca increased significantly at the end of follow-up (9.03 ± 0.42 to 9.14 ± 0.62; P = 0.04); hypercalcemia was presented in two patients in the first control visit (week 12), in one patient in the second control (week 30), and in one patient in the third control (week 48). In 222 serum calcium determinations during follow-up, hypercalcemia was observed in only 1.8% of cases. This vitamin D2 oral regimen with initial high doses was safe and sufficient to obtain and maintain optimal serum 25(OH)D concentrations and prevent vitamin D insufficiency in chronic kidney disease patients on dialysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".