Musculoskeletal Ultrasound in Childhood Arthritis Limited Examination: A Comprehensive, Reliable, <scp>Time‐Efficient</scp> Assessment of Synovitis
Bibliographic record
Abstract
Objective To develop and initially validate a comprehensive pediatric musculoskeletal ultrasound (MSUS) joint‐specific scoring system, and to determine the minimum number of joints needed to identify active disease. Methods A semiquantitative scoring system was developed by consensus and initially validated by interrater reliability using intraclass correlation coefficients (ICCs). Subsequently, newly diagnosed juvenile idiopathic arthritis patients with an active joint count of >4 had a 42‐joint MSUS performed at baseline and 3 months using this protocol. A minimum set of joints needed to identify all patients with synovitis on MSUS was obtained through a data reduction process. Spearman's correlation (r s ) was calculated to determine the association between MSUS findings and clinical Juvenile Arthritis Disease Activity Score in 10 joints (cJADAS10). Standardized response means (SMRs) were used to assess change over time. Results The final joint‐specific scoring system revealed an excellent interrater reliability (ICC 0.81–0.96) for all joints. Thirty patients were enrolled. Scanning 5 joints bilaterally (wrists, second and third metacarpophalangeal joints, knees and ankles) captured 100% of children with B‐mode synovitis and had moderate correlation with the cJADAS10 at baseline (r s = 0.45). Mean ultrasound scores at baseline and follow‐up were 28.3 and 22.3, with an SRM of 0.69 ( P = 0.002) for 42 joints, and 36 and 27.7, with an SRM of 0.76 ( P = 0.003) for the reduced joints, respectively. Conclusion A limited MSUS examination called musculoskeletal ultrasound in childhood arthritis limited examination (MUSICAL) captures all patients with active synovitis, and our new joint‐specific scoring system is highly reliable and sensitive to change.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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 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".