Proposed Core Set of Items for Measuring Disease Activity in Systemic Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To date, there are no standardized disease activity tools for systemic juvenile idiopathic arthritis (sJIA). We developed a core set of disease activity measures for sJIA. METHODS: We conducted a validation study in patients with sJIA recruited from 3 Canadian institutions. Disease activity scores were based on questionnaires, clinical factors, and laboratory measures. The physician's global assessment was our criterion standard. We determined the strength of association of each item with the criterion standard. We then surveyed international experts to determine the top 10 items. Finally, we used the experts' responses to generate a proposed core set of disease activity measures. RESULTS: We enrolled 57 subjects - 26 with moderately or severely active disease, and 31 with mildly active or inactive disease. Items that most strongly correlated with the criterion standard were number of active joints (r = 0.79), parent's global assessment of disease activity (r = 0.53), erythrocyte sedimentation rate (ESR; r = 0.62), and C-reactive protein (CRP; r = 0.61). The response rate from international experts was 82% (154/187). Items with the most votes, in descending order, were number of active joints, number of days with fever in the preceding 2 weeks, patient's and parent's global assessments of disease activity, sJIA rash, ESR, CRP, and hemoglobin level. CONCLUSION: We propose a core set of items for measuring disease activity in sJIA. Future research should be aimed at further validation of this core set in the international context.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".