Predictors of early inactive disease in a juvenile idiopathic arthritis cohort: Results of a Canadian multicenter, prospective inception cohort study
Bibliographic record
Abstract
OBJECTIVE: To determine early predictors of 6-month outcomes in a prospective cohort of patients with juvenile idiopathic arthritis (JIA). METHODS: Patients selected were those enrolled in an inception cohort study of JIA, the Research in Arthritis in Canadian Children Emphasizing Outcomes Study, within 6 months after diagnosis. The juvenile rheumatoid arthritis core criteria set and quality of life measures were collected at enrollment and 6 months later. Outcomes evaluated included inactive disease, Juvenile Arthritis Quality of Life Questionnaire (JAQQ) scores, and Childhood Health Assessment Questionnaire (C-HAQ) scores at 6 months. RESULTS: Thirty-three percent of patients had inactive disease at 6 months. Onset subtype and most baseline core criteria set measures correlated with all 3 outcomes. Relative to oligoarticular JIA, the risks of inactive disease were lower for enthesitis-related arthritis, polyarthritis rheumatoid factor (RF)-negative JIA, and polyarthritis RF-positive JIA, and were similar for psoriatic arthritis. In multiple regression analyses, the baseline JAQQ score was an independent predictor of all 3 outcomes. Other independent baseline predictors included polyarthritis RF-negative and systemic JIA for inactive disease; C-HAQ score and polyarthritis RF-positive JIA for the 6-month C-HAQ score; and active joint count, pain, and time to diagnosis for the 6-month JAQQ score. CONCLUSION: Clinical measures soon after diagnosis predict short-term outcomes for patients with JIA. The JAQQ is a predictor of multiple outcomes. Time to diagnosis affects quality of life in the short term.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".