Effect of increasing doses of vitamin D on bone mineral density and serum N‐terminal telopeptide in elderly women: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: There are few controlled studies of the effect of different doses of vitamin D3 on bone mineral density (BMD). OBJECTIVES: We conducted a randomized placebo-controlled trial of increasing doses of vitamin D3 in 163 Caucasian and 31 African American women with serum 25-hydroxyvitamin D (25OHD) ≤50 nmol/L. This is an analysis of secondary outcome BMD to see if there is an association between percent change in BMD and dose of vitamin D3. METHODS: Participants were randomly assigned to placebo, vitamin D3 400, 800, 1600, 2400, 3200, 4000, or 4800 IU/day; calcium supplements, average 600mg, were given to provide a total calcium intake of 1200 mg/d. The primary outcome was 12-month serum 25OHD level. Analysis methods include ANOVA and Pearson correlations. RESULTS: The mean percent increase (±SD) in BMD at 12 months for all women was small; total body, 0.62% (± 2.72), femoral neck 0.59% (±3.58) and spine 0.43% (±2.80). There was no difference in BMD or serum N-telopeptide in response to vitamin D by dose or race. The increase in total body, spine and hip BMD in elderly women given vitamin D doses between 400 and 4800 IU daily and calcium supplementation is small, unrelated to dose or 12-month serum 25OHD, free 25OHD or 1,25(OH)2D. There was no evidence of a threshold change in BMD with increasing serum 25OHD or free 25OHD in this population. CONCLUSIONS: We found no significant effect of daily vitamin D dose ranging from 400 to 4800 IU/day on BMD or serum N-terminal telopeptides in elderly women with initially low serum 25OHD.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".