Achievement of a State of Inactive Disease at Least Once in the First 5 Years Predicts Better Outcome of Patients with Polyarticular Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate whether the achievement of inactive disease in the first 5 years predicts a more favorable outcome of children with juvenile idiopathic arthritis (JIA). METHODS: We reviewed clinical charts of 123 patients who started taking methotrexate, were followed for at least 5 years, and received a yearly assessment in the first 5 years. At each yearly visit, the presence of inactive disease was assessed. Patients were divided into 3 groups: (1) patients who never reached inactive disease; (2) patients who reached inactive disease in only 1 visit; and (3) patients who reached inactive disease in > or = 2 visits. Outcome was evaluated after 6 to 18 years (median 7.1 yrs) by assessing the following clinical measures: restricted joint count, Childhood Health Assessment Questionnaire (CHAQ), Juvenile Arthritis Damage Index (JADI), and Poznanski score of radiographic damage. RESULTS: In the first 5 years, 62 patients (50.4%) were noted to have active disease at their yearly visit, 40 patients (32.5%) were noted to have inactive disease only once, and 21 patients (17.1%) were noted to have inactive disease in > or = 2 visits. Patients who achieved inactive disease 1 or more times had lower restricted joint count (p = 0.007) and JADI-Articular score (p = 0.004) at last followup visit than those who never reached such a state. A similar trend, although not significant, was observed for CHAQ and Poznanski score of radiographic damage. CONCLUSION: Attainment of the state of inactive disease at least once in the first 5 years was found to be associated with less longterm joint damage and with a trend toward less functional impairment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".