Incident vertebral fractures among children with rheumatic disorders 12 months after glucocorticoid initiation: A national observational study
Bibliographic record
Abstract
OBJECTIVE: To determine the frequency of incident vertebral fractures (IVF) 12 months after glucocorticoid (GC) initiation in children with rheumatic diseases and to identify children at higher risk. METHODS: Children with rheumatic diseases initiating GC were enrolled in a prospective observational study. Annual spine radiographs were evaluated using the Genant semiquantitative method. Spine areal bone mineral density (aBMD) was measured every 6 months. Clinical features, including cumulative GC dose, back pain, disease and physical activity, calcium and vitamin D intake, and spine aBMD Z scores, were analyzed for association with IVF. RESULTS: Seven (6%) of 118 children (95% confidence interval 2.9-11.7%) had IVF. Their diagnoses were: juvenile dermatomyositis (n = 2), systemic lupus erythematosus (n = 3), systemic vasculitis (n = 1), and mixed connective tissue disease (n = 1). One child was omitted from the analyses after 4 months because of osteoporosis treatment for symptomatic IVF. Children with IVF received on average 50% more GC than those without (P = 0.030), had a greater increase in body mass index (BMI) at 6 months (P = 0.010), and had greater decrements in spine aBMD Z scores in the first 6 months (P = 0.048). Four (67%) of 6 children with IVF and data to 12 months had spine aBMD Z scores less than -2.0 at 12 months compared to 16% of children without IVF (P = 0.011). CONCLUSION: The incidence of VF 12 months following GC initiation was 6%; most children were asymptomatic. Children with IVF received more GC, had greater increases in BMI, and had greater declines in spine aBMD Z scores in the first 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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".