Health‐Related Quality of Life in an Inception Cohort of Children With Juvenile Idiopathic Arthritis: A Longitudinal Analysis
Bibliographic record
Abstract
OBJECTIVE: To describe changes in health-related quality of life (HRQoL) over time in children with juvenile idiopathic arthritis (JIA), relative to other outcomes, and to identify predictors of unfavorable HRQoL trajectories. METHODS: Children with JIA in the Research in Arthritis in Canadian Children emphasizing Outcomes (ReACCh-Out) cohort were included. The Juvenile Arthritis Quality of Life Questionnaire (JAQQ, a standardized instrument), health-related Quality of My Life (HRQoML, an instrument based on personal valuations), and JIA core variables were completed serially. Analyses included median values, Kaplan-Meier survival curves, and latent trajectory analysis. RESULTS: A total of 1,249 patients enrolled at a median of 0.5 months after diagnosis were followed for a median of 34.2 months. The degree of initial HRQoL impairment and probabilities of reaching the best possible HRQoL scores varied across JIA categories (best for oligoarthritis, worst for rheumatoid factor-positive polyarthritis). Median times to attain best possible HRQoL scores (JAQQ 59.3 months, HRQoML 34.5 months), lagged behind those for disease activity, pain, and disability measures. Most patients followed trajectories with minimal or mild impairment; however, 7.6% and 13.8% of patients, respectively, followed JAQQ and HRQoML trajectories with persistent major impairment in HRQoL. JIA category, aboriginal ethnicity, and baseline disease activity measures distinguished between membership in trajectories with major and minimal impairments. CONCLUSION: Improvement in HRQoL is slower than for disease activity, pain, and disability. Improvement of a measure based on respondents' preferences (HRQoML) is more rapid than that of a standardized measure (JAQQ). Higher disease activity at diagnosis heralds an unfavorable HRQoL trajectory.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".