Natural History of Growth and Body Composition in Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
BACKGROUND: In patients with juvenile idiopathic arthritis (JIA), growth impairment and altered body composition, including disturbed skeletal development, are well-known long-term complications. Data on longitudinal growth in patients with systemic and polyarticular JIA reveal growth impairment in the active phases of the disease. With reduction in disease activity and lower glucocorticoid (GC) doses, some patients experience 'catch-up' growth; however, many have only a slight improvement in height standard deviation during puberty or after cessation of GC treatment. The consequence is a final height below the 3rd percentile and below the genetic height potential. Although few studies have specifically addressed body composition in children with JIA, studies on the development of bone mass have described notable deficits in both GC-treated and GC-naïve children. In recent years, the deficits in bone mass have been related, in part, to the deficits in muscle mass, which are prevalent in these patients. CONCLUSIONS: The major goal for physicians caring for patients with JIA is optimal disease control while maintaining normal growth. Early recognition of patients who develop prolonged growth disturbances and altered body composition is important as these abnormalities contribute to long-term morbidity and need to be addressed both diagnostically and therapeutically when treating children with JIA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".