Prevalent vertebral fractures among children initiating glucocorticoid therapy for the treatment of rheumatic disorders
Bibliographic record
Abstract
OBJECTIVE: Vertebral fractures are an under-recognized problem in children with inflammatory disorders. We studied spine health among 134 children (87 girls) with rheumatic conditions (median age 10 years) within 30 days of initiating glucocorticoid therapy. METHODS: Children were categorized as follows: juvenile dermatomyositis (n = 30), juvenile idiopathic arthritis (n = 28), systemic lupus erythematosus and related conditions (n = 26), systemic arthritis (n = 22), systemic vasculitis (n = 16), and other conditions (n = 12). Thoracolumbar spine radiograph and dual x-ray absorptiometry for lumbar spine (L-spine) areal bone mineral density (BMD) were performed within 30 days of glucocorticoid initiation. Genant semiquantitative grading was used for vertebral morphometry. Second metacarpal morphometry was carried out on a hand radiograph. Clinical factors including disease and physical activity, calcium and vitamin D intake, cumulative glucocorticoid dose, underlying diagnosis, L-spine BMD Z score, and back pain were analyzed for association with vertebral fracture. RESULTS: Thirteen vertebral fractures were noted in 9 children (7%). Of these, 6 patients had a single vertebral fracture and 3 had 2-3 fractures. Fractures were clustered in the mid-thoracic region (69%). Three vertebral fractures (23%) were moderate (grade 2); the others were mild (grade 1). For the entire cohort, mean +/- SD L-spine BMD Z score was significantly different from zero (-0.55 +/- 1.2, P < 0.001) despite a mean height Z score that was similar to the healthy average (0.02 +/- 1.0, P = 0.825). Back pain was highly associated with increased odds for fracture (odds ratio 10.6 [95% confidence interval 2.1-53.8], P = 0.004). CONCLUSION: In pediatric rheumatic conditions, vertebral fractures can be present prior to prolonged glucocorticoid exposure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".