Phenotypic Features and Longterm Outcomes of Pediatric Inflammatory Bowel Disease Patients with Arthritis and Arthralgia
Bibliographic record
Abstract
OBJECTIVE: The natural history of pediatric inflammatory bowel disease (IBD) patients with joint involvement has not been clearly described. Thus, we aimed to investigate phenotypic features and clinical outcomes of this distinct association. METHODS: The medical records of patients with pediatric IBD diagnosed from 2000 to 2016 were reviewed retrospectively. Main outcome measures included time to first flare, hospitalization, surgery, and biologic therapy. RESULTS: Of 301 patients with Crohn disease (median age 14.2 yrs), 37 (12.3%) had arthritis while 44 (14.6%) had arthralgia at diagnosis. Arthritis and arthralgia were more common in women (p = 0.028). Patients with arthritis and arthralgia demonstrated lower rates of perianal disease (2.7% and 4.5% vs 16.9%, p = 0.013), whereas patients with arthritis were more likely to be treated with biologic therapy (HR 2.05, 95% CI 1.27-3.33, p = 0.009). Of 129 patients with ulcerative colitis (UC; median age 13.7 yrs), 3 (2.3%) had arthritis and 16 (12.4%) had arthralgia at diagnosis. Patients with arthralgia were treated more often with corticosteroids (p = 0.03) or immunomodulator therapies (p = 0.003) compared with those without joint involvement. The likelihood to undergo colectomy was significantly higher in patients with arthralgia (HR 2.9, 95% CI 1.1-7.4, p = 0.04). During followup (median 9.0 yrs), 13 patients developed arthritis (3.3%). Arthralgia at diagnosis was a significant predictor for the development of arthritis during followup (HR 9.0, 95% CI 2.86-28.5, p < 0.001). CONCLUSION: Pediatric IBD patients with arthritis have distinct phenotypic features. Arthralgia at diagnosis is a predictor for colectomy in UC and a risk factor for the development of arthritis during followup.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".