Changes in Body Mass Index in Children with Juvenile Idiopathic Arthritis Treated with Tumor Necrosis Factor Inhibitors
Bibliographic record
Abstract
OBJECTIVE: To evaluate changes in body mass index (BMI) among cohorts of children with juvenile idiopathic arthritis (JIA) with and without tumor necrosis factor (TNF) inhibitor therapy. METHODS: We performed a retrospective chart review of children with JIA who newly initiated TNF inhibitor therapy and had at least 1 year of subsequent followup (TNF cohort). We also included children with JIA and at least 1 year of followup without any TNF inhibitor therapy (comparator cohort). Children with systemic arthritis were excluded. Age and sex specific BMI z-scores and their corresponding categories (normal, overweight, obese) were determined. We compared changes from a baseline visit to the last followup visit using t-test for BMI z-scores and chi square and Kruskal-Wallis tests for BMI categories. RESULTS: The TNF cohort had 167 patients; the comparator cohort had 37. The median study followup was 2.8 and 2.2 years, respectively. The cohorts had similar age, sex, race, weight, and height distributions. The TNF cohort had a statistically significant increase in BMI z-score from baseline (+0.15; p = 0.02) that was not significantly different from the increase (+0.09) observed in the comparator cohort (p = 0.5). There was no significant change in the proportions of overweight and obese children in the TNF cohort compared to baseline (p = 0.6) or compared to the change in the comparator cohort (p = 0.2). CONCLUSION: Over more than 2 years of followup, we did not observe a significant increase in BMI among children with JIA receiving TNF inhibitor compared to those not receiving it.
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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) | 0.000 | 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".