Predictors and Correlates of Vitamin D Status in Children and Adolescents with Osteogenesis Imperfecta
Bibliographic record
Abstract
BACKGROUND: The prevalence of vitamin D deficiency and its consequences on bone in pediatric bone fragility disorders is not well characterized. In the present study, we evaluated determinants of vitamin D status in children and adolescents with osteogenesis imperfecta (OI) and assessed the relationship between 25-hydroxyvitamin D (25OH D) serum concentrations and lumbar spine areal bone mineral density (LS-aBMD). MATERIALS AND METHODS: This retrospective cross-sectional study comprised 315 patients with a diagnosis of OI type I, III, or IV (aged 1.1-17.9 yr; 161 girls) who had not received bisphosphonate treatment at the time of 25OH D analysis. In 282 patients (90%), LS-aBMD measurements were available at the same time. RESULTS: Serum concentrations of 25OH D ranged from 14 to 133 nmol/liter and were less than 50 nmol/liter in 86 patients (27%). Regression analysis revealed that age (P < 0.001), season (P < 0.001), and OI severity (P = 0.048), but not gender, were significant independent predictive factors of 25OH D levels. Serum 25OH D concentrations were negatively correlated with serum PTH levels (P = 0.003) and urinary cross-linked N-telopeptides of type I collagen to creatinine ratios (P = 0.005). Serum 25OH D levels were positively associated (P = 0.02) with LS-aBMD z-scores after accounting for OI severity, age, and gender. CONCLUSION: Serum 25OH D levels are positively associated with LS-aBMD z-scores in children and adolescents with OI types I, III, and IV.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".