High Adiposity and Serum Leptin Accompanied by Altered Bone Turnover Markers in Severe Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate interactions between skeleton and adipose tissue, and association of adipokines and bone turnover markers with disease-related factors in patients with severe juvenile idiopathic arthritis (JIA). METHODS: Forty-nine patients (median age 14.8 yrs, median disease duration 10.2 yrs) with refractory polyarticular JIA and 89 sex-matched and age-matched healthy controls participated in the study. Study subjects underwent clinical examination, body composition assessment with dual-energy X-ray absorptiometry, and analyses for leptin, adiponectin, and bone turnover markers. RESULTS: Patients with JIA were shorter and more often overweight (p = 0.001) or obese (p < 0.001) than controls. They had significantly higher serum leptin, even when adjusted for fat mass (p < 0.001), than did controls. Adiponectin did not differ between the groups. Concentration of carboxyterminal telopeptide of type I collagen was higher (p = 0.006) in patients. The inverse association between leptin and bone turnover markers disappeared in controls but was strengthened in patients when adjusted for fat mass. Leptin, adiponectin, or bone markers did not associate with variables of disease activity. CONCLUSION: Patients with severe JIA had high adiposity accompanied by increased bone resorption. Their serum leptin was higher, even independently of fat mass. Leptin tended to associate inversely with bone turnover markers but did not associate with variables of disease activity.
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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 | 0.001 |
| 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 | 0.000 |
| 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".