Development and Testing of Reduced Joint Counts in Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To develop and test reduced joint counts in children with juvenile idiopathic arthritis (JIA). METHODS: Four reduced joint counts including 45, 35, 27, and 10 joints were devised by a panel of experienced pediatric rheumatologists, who selected the joints to be included based on the ease of technical assessment, functional relevance, and frequency of involvement. Three large samples of patients with JIA (total n=4353) who had a detailed joint assessment available were used to develop and test reduced joint counts. Performance of reduced counts was examined by comparing their Spearman correlation with the standard (i.e., complete) joint count. Construct validity was evaluated by calculating Spearman correlation with other JIA outcome measures. Responsiveness to clinical change was determined through the standardized response mean (SRM). RESULTS: Spearman correlations of reduced joint counts with the whole joint count and with the other JIA outcome measures were comparable, revealing that they had similar ability to serve as surrogate for the whole joint count and construct validity. Responsiveness to clinical change was also comparable across reduced counts (SRM 0.83-1.09 for active joint counts and 0.63-0.81 for restricted joint counts). Based on these results and considering the relative feasibility of the different counts, the 27-joint reduced count is proposed for use in JIA. This joint count includes the cervical spine and the elbow, wrist, metacarpophalangeal (from first to third), proximal interphalangeal, hip, knee, and ankle joints. CONCLUSION: Reduced joint counts appear to be as reliable as standard joint counts in assessment of the severity of joint disease and its change over time in children with JIA.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".