Development and reliability of a novel ultrasonographic joint-specific scoring system for synovitis with reference atlas for patients with juvenile idiopathic arthritis
Bibliographic record
Abstract
OBJECTIVE: To develop an ultrasonographic image acquisition protocol and a joint-specific scoring system for synovitis with reference atlas in patients with juvenile idiopathic arthritis (JIA) and to assess the reliability of the system. METHODS: Seven rheumatologists with extensive ultrasound experience developed a scanning protocol and a semiquantitative joint-specific scoring system for B-mode (BM) synovitis for the elbow, wrist, metacarpophalangeal 2-3, proximal interphalangeal 2-3, hip, knee, ankle and metatarsophalangeal 2-3 joints. An ultrasonographic reference atlas for BM synovitis, divided in four age groups (2-4, 5-8, 9-12, 13-18 years), and power Doppler (PD) activity was then developed. Reliability was assessed for all joints on still images and in a live exercise including 10 patients with JIA, calculated by intraclass correlation coefficient (ICC) and weighted kappa. RESULTS: A scanning protocol and scoring system for multiple joints with reference atlas composed of images with four different score levels for BM and PD were developed. Still image scoring for BM synovitis on joint level showed good to excellent intra-reader reliability (ICC/kappa ranges: 0.75-0.95/0.63-0.91) and moderate to excellent inter-reader reliability (ICC/kappa ranges: 0.89-0.99/0.50-0.91). Still image scoring for PD activity showed excellent intra-reader and inter-reader reliability (ICC/kappa: 0.96/0.91 and ICC/kappa: 0.97/0.80, respectively). In the live scoring, inter-reader reliability (ICC/kappa) was moderate to excellent for BM synovitis (0.94/0.51) and PD activity (0.91/0.60). CONCLUSION: An ultrasonographic image acquisition protocol and joint-specific scoring system with reference atlas were developed and demonstrated moderate to excellent reliability for scoring of synovitis in patients with JIA. This can be a valuable tool in clinical practice and future research.
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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 | 0.010 | 0.020 |
| 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 | 0.000 |
| 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 | 0.001 |
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".