<scp>Parent‐Reported</scp> Medication Side Effects and Their Impact on <scp>Health‐Related</scp> Quality of Life in Children With Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To describe the frequency and severity of parent-reported medication side effects (SEs) in children with juvenile idiopathic arthritis (JIA) relative to physician-reported actionable adverse events (AEs), and to assess their impact on health-related quality of life (HRQoL). METHODS: Newly diagnosed JIA patients recruited between 2017 and 2019 to the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry were included. Parents reported presence and severity (0 = no problem, 10 = very severe) of medication SEs at every clinic visit. Physicians were asked to report any actionable AE. HRQoL was assessed using the Quality of My Life (QoML) questionnaire (0 = the worst, 10 = the best) and parent's global assessment (0 = very well, 10 = very poor). Analyses included proportion of visits with SEs or actionable AEs, cumulative incidence by Kaplan-Meier methods, and HRQoL impact measured with longitudinal mixed-effects models. RESULTS: SEs were reported at 371 of 884 (42%) visits (95% confidence interval [95% CI] 39, 45%) in 249 patients, with a median of 2 SEs per visit (interquartile range [IQR] 1-3), and median severity of 3 (IQR 1.5-5). Most SEs were gastrointestinal (32.5% of visits) or behavioral/psychiatric (22.4%). SE frequency was lowest with nonsteroidal antiinflammatory drugs alone (34.7%) and highest with prednisone and methotrexate combinations (66%). SE cumulative incidence was 67% (95% CI 59, 75) within 1 year of diagnosis, and 36% (95% CI 28, 44) for actionable AEs. Parent global and QoML scores were worse with SEs present; the impact persisted after adjusting for pain and number of active joints. CONCLUSION: Parents report that two-thirds of children with JIA experience SEs impacting their HRQoL within 1 year of diagnosis. SE mitigation strategies are needed in managing JIA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".