Patient-reported Outcomes across Categories of Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Although there is increasing reliance on patient-reported outcomes (PRO) for disease management, there is little known about the differences in PRO across juvenile idiopathic arthritis (JIA) categories. The purpose of our study was to assess PRO across JIA categories, including pain, quality of life, and physical function, and to determine clinical factors associated with differences in these measures across categories. METHODS: This was a longitudinal cohort study of patients with JIA at a tertiary care pediatric rheumatology clinic. Subjects, PRO, and clinical variables were identified by querying the electronic medical record. Mixed-effects regression assessed pain, quality of life, and function. RESULTS: Subjects with enthesitis-related arthritis (ERA) and undifferentiated JIA had significantly more pain, poorer quality of life, and poorer physical function. The ERA and undifferentiated JIA categories, physician's global disease activity assessment, female sex, and nonsteroidal antiinflammatory drug use were significantly associated with more pain, poorer quality of life, and poorer function. In models limited to ERA, female sex and tender enthesis count were significant predictors of decreased function. CONCLUSION: ERA and undifferentiated JIA categories had poorer PRO than other JIA categories. Further work is needed to address ways to improve PRO in children with JIA, with a special focus on children with ERA and undifferentiated JIA.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".