Glucocorticoid‐related changes in body mass index among children and adolescents with rheumatic diseases
Bibliographic record
Abstract
OBJECTIVE: To examine the temporal and dose-related effects of glucocorticoids (GCs) on body mass index (BMI) in children with rheumatic diseases. METHODS: Children initiating GCs for a rheumatic disease (n = 130) were assessed every 3 months for 18 months. BMI, weight, and height Z score trajectories were described according to GC starting dosage in prednisone equivalents: high (≥1.0 mg/kg/day), low (<0.2 mg/kg/day to a maximum of 7.5 mg/day), and moderate (between high and low) dosage. The impact of GC dosing, underlying diagnosis, pubertal status, physical activity, and disease activity on BMI Z scores and on percent body fat was assessed with longitudinal mixed-effects growth curve models. RESULTS: The GC starting dose was high in 59% and moderate in 39% of patients. The peak BMI Z score was +1.29 at 4 months with high-dose GCs and +0.69 at 4.2 months with moderate-dose GCs (P < 0.001). Overall, 50% (95% confidence interval 41-59%) of the children returned to within +0.25 SD of their baseline BMI Z score. Oral GC dose over the preceding 3 months was the most significant determinant of BMI Z score and percent body fat. The proportion of days in receipt of GCs, disease activity, and a diagnosis of systemic-onset juvenile idiopathic arthritis were also associated with BMI Z scores. The correlation between changes in BMI and changes in percent body fat was 0.09. CONCLUSION: In children with rheumatic diseases starting moderate and high doses of GCs, BMI Z scores peaked at 4 months, and only half returned to within +0.25 SD of their baseline BMI Z score after 18 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".