Relationship between vitamin D status and bone mineralization, mass, and metabolism in children with osteogenesis imperfecta: Histomorphometric study
Bibliographic record
Abstract
The effect of low vitamin D levels in children with bone fragility disorders has not been examined in detail. In this study, we evaluated the relationship between vitamin D status and parameters of skeletal mineralization, mass, and metabolism in a group of pediatric osteogenesis imperfecta (OI) patients. This retrospective study consisted of 71 patients with a diagnosis of OI type I, III, or IV (ages 1.4 to 17.5 years; 36 girls) who had not received bisphosphonate treatment before iliac bone biopsy. Serum 25-hydroxyvitamin D [25(OH)D] levels ranged from 13 to 103 nmol/L and were less than 50 nmol/L in 37 patients (52%). None of the OI patients had radiologic signs of rickets or fulfilled the histomorphometric criteria for the diagnosis of osteomalacia (ie, elevated results for both osteoid thickness and mineralization lag time). Serum 25(OH)D levels were negatively correlated with age and serum parathyroid hormone levels but were not correlated with any parameter of bone mineralization (ie, osteoid thickness, mineralization lag time, or bone-formation rate per bone surface) or bone mass (ie, lumbar spine areal bone mineral density, iliac bone volume per tissue volume, or iliac cortical width). We found no evidence that serum 25(OH)D levels in the range from 13 to 103 nmol/L were associated with measures of bone mineralization, metabolism, or mass in children with OI.
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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 | 0.002 | 0.001 |
| 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".