Comparison of two vitamin D supplementation strategies in children with sickle cell disease: a randomized controlled trial
Bibliographic record
Abstract
Summary Previously, we showed that nearly 70% of children followed in our sickle cell disease (SCD) clinic were vitamin D‐ deficient and had low vitamin intake with poor use of supplements. We compared the change in serum 25‐hydroxyvitamin D [25(OH)D], safety and clinical impact of two vitamin D supplementation regimens in children with SCD. Children (5–17 years, all genotypes) were randomized to a single bolus of vitamin D3 (300 000 IU; n = 18) or placebo (n = 20). All children received a prescription for daily 1 000 IU vitamin D3. Serum 25(OH)D and calcium, urinary calcium/creatinine ratio, musculoskeletal pain, quality of life, haematology and bone markers were assessed at baseline and three months post intervention. Bolus administration led to a greater rise in 25(OH)D levels from baseline compared to placebo (20 ± 16 nmol/l vs. 2 ± 19 nmol/l; P = 0·003) and correction of vitamin D deficiency. No hypercalcaemia nor hypercalciuria occurred during the study, but more children in the bolus group experienced gastrointestinal symptoms within the first month (P = 0·04). There were no differences between groups for other outcomes. The use of a high‐dose vitamin D bolus combined with daily 1 000 IU vitamin D3 was more efficient in raising 25(OH)D levels than daily supplementation alone in children with SCD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".