Superiority of a High Loading Dose of Cholecalciferol to Correct Hypovitaminosis D in Patients with Inflammatory/Autoimmune Rheumatic Diseases
Bibliographic record
Abstract
OBJECTIVE: To compare 3 different cholecalciferol supplementation regimens in patients with rheumatic diseases. METHODS: One hundred fifty-four patients who completed a 6-month course of cholecalciferol supplementation, of whom 111 had an autoimmune/inflammatory rheumatic disease (ARD) and 43 osteoarthritis (NARD), were retrospectively identified from a database of 872 consecutive adult patients who attended a tertiary level immuno-rheumatology clinic from 2007 to 2010. Patients with renal failure or primary hyperparathyroidism were excluded. Plasma 25-hydroxy vitamin D [25(OH)D] and parathyroid hormone (PTH) concentrations were evaluated at baseline and after completion of treatment with (i) a single oral dose of cholecalciferol 300,000 IU, followed by oral cholecalciferol 800-1000 IU daily for 6 months [high-dose loading treatment (HLT) group; n = 40]; (ii) a single oral dose of cholecalciferol 100,000 IU, followed by daily oral cholecalciferol as above [low-dose loading treatment (LLT) group; n = 30]; or (iii) daily oral cholecalciferol as above but without the loading dose [standard therapy (ST); n = 84]. RESULTS: The rates of serum 25(OH)D and PTH normalization (defined as values > 75 nmol/l and < 72.9 pg/ml, respectively) were as follows: HLT, 52.5% (95% CI 37.5-68.5) and 69.2% (95% CI 54.7-83.3); LLT, 36.7% (95% CI 19.7-54.3) and 53.8% (95% CI 36.2-71.8); ST, 31.0% (95% CI 21.1-40.9) and 35.0% (95% CI 14.1-55.9). All regimes increased 25(OH)D (p < 0.001) but only HLT reduced PTH (p < 0.01) in comparison to baseline. The ARD group had a similar 25(OH)D increase but a smaller PTH reduction than the NARD (p < 0.05). CONCLUSION: An HLT cholecalciferol regimen is needed to correct hypovitaminosis D of patients with rheumatic diseases, with superior 25(OH)D normalization and PTH suppression rates at 6 months.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".