Canadian Rheumatology Association Recommendations for the Screening, Monitoring, and Treatment of Juvenile Idiopathic Arthritis-associated Uveitis
Bibliographic record
Abstract
OBJECTIVE: To develop Canadian recommendations for the screening, monitoring, and treatment of uveitis associated with juvenile idiopathic arthritis (JIA). METHODS: Recommendations were developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE)-ADOLOPMENT approach. A working group of 14 pediatric rheumatologists, 6 ophthalmologists, 2 methodologists, and 3 caregiver/patient representatives reviewed recent American College of Rheumatology (ACR)/Arthritis Foundation (AF) recommendations and worked in pairs to develop evidence-to-decision (EtD) tables. A survey to assess agreement and recommendations requiring group discussion was completed. EtD tables were presented, discussed, and voted upon at a virtual meeting, to produce the final recommendations. A health equity framework was applied to all aspects of the adolopment process including the EtD tables, survey responses, and virtual meeting discussion. RESULTS: The survey identified that 7 of the 19 recommendations required rigorous discussion. Seventy-five percent of working group members attended the virtual meeting to discuss controversial topics as they pertained to the Canadian environment, including timing to first eye exam, frequency of screening, escalation criteria for systemic and biologic therapy, and the role of nonbiologic therapies. Equity issues related to access to care and advanced therapeutics across Canadian provinces and territories were highlighted. Following the virtual meeting, 5 recommendations were adapted, 2 recommendations were removed, and 1 was developed de novo. CONCLUSION: Recommendations for JIA-associated uveitis were adapted to the Canadian context by a working group of pediatric rheumatologists, ophthalmologists with expertise in the management of uveitis, and parent/patient input, taking into consideration cost, equity, and access.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".