A new Canadian inception cohort for juvenile idiopathic arthritis: The Canadian Alliance of Pediatric Rheumatology Investigators Registry
Bibliographic record
Abstract
OBJECTIVES: The aim was to describe the design, methods and initial findings of a new Canadian inception cohort of children with JIA, The Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) JIA Registry. METHODS: The CAPRI JIA Registry was started in 2017 to collect information prospectively on children enrolled within 3 months of JIA diagnosis across Canada. The registry has a non-traditional modular design, with no artificially set times for registry visits to occur, streamlined multi-method data collection that requires 2-4 min per visit, and reports cumulative incidence of treatments, outcomes and adverse events calculated by Kaplan-Meier survival methods. RESULTS: A total of 166 patients, enrolled a median of 6 weeks after JIA diagnosis at 10 centres, were included. The median age at diagnosis was 9 years [interquartile range (IQR) 3, 13], 61% were female and 51% had oligoarticular JIA. The median three-variable clinical Juvenile Arthritis Disease Activity Score was 6.5 (IQR 4, 10) at enrolment, and the median time to first attainment of clinically inactive disease (CID) was 24 weeks (by 1 year, 81%). Within 1 year of diagnosis, 70% of patients had started a DMARD and 35% a biologic agent. The rates of adverse events and serious adverse events were 60 and 5.8 per 100 patient-years, respectively. CONCLUSION: This streamlined and flexible registry minimizes the burden of data collection and interference with clinic operations. Initial findings suggest that treatments for newly diagnosed patients with JIA in Canada have intensified, and now 81% of patients attain CID within 1 year of diagnosis.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 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".