Patients with Very Early-onset Systemic Juvenile Idiopathic Arthritis Exhibit More Inflammatory Features and a Worse Outcome
Bibliographic record
Abstract
OBJECTIVE: Systemic juvenile idiopathic arthritis (SJIA) frequently leads to disability and damage. Predictive factors for a poor outcome include persistent systemic features and younger age at onset. We describe and analyze disease features in patients with early-onset (EO) SJIA (disease onset before age 18 mo) and compare them to patients with later-onset (LO) disease. METHODS: Clinical features at onset, activity measures (occurrence of macrophage activation syndrome, remission), and outcome measures for disability [Childhood Health Assessment Questionnaire (CHAQ) ≥ 0.5] and damage [radiographic joint destruction, Juvenile Arthritis Damage Index (JADI) score, growth retardation] observed during followup were analyzed retrospectively in patients with SJIA followed for ≥ 3 years since disease onset. RESULTS: In total 132 patients were included. SJIA started at age ≤ 18 months in 19 (14%) patients and at a later age in 113 (86%) children. At onset, serositis (p < 0.01) and hepatomegaly (p < 0.05) were more frequent in EO patients, who also exhibited lower hemoglobin levels (p < 0.03) and higher platelet counts (p < 0.03) than patients with LO. Macrophage activation syndrome occurred in 20 patients (11 EO and 9 LO; p < 0.0001). Remission was achieved by 49 patients (37%; 4 EO and 45 LO). At last visit, destructive hip disease (p < 0.04), growth retardation (p < 0.01), radiographic damage (p < 0.02), and disability (p < 0.04) were more frequent in patients with EO disease, who had higher JADI scores (p < 0.003). CONCLUSION: Patients with EO exhibited a more aggressive and destructive disease course than patients with LO SJIA.
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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 | 0.000 | 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) | 0.002 | 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".