Preliminary Definitions for the Sonographic Features of Synovitis in Children
Bibliographic record
Abstract
OBJECTIVE: Musculoskeletal ultrasonography (US) has the potential to be an important tool in the assessment of disease activity in childhood arthritides. To assess pathology, clear definitions for synovitis need to be developed first. The aim of this study was to develop and validate these definitions through an international consensus process. METHODS: The decision on which US techniques to use and the components to be included in the definitions, as well as the final wording, were developed by 31 US experts in a consensus process. A Likert scale of 1-5 (where 1 = complete disagreement and 5 = complete agreement) was used. A minimum of 80% of the experts scoring 4 or 5 was required for final approval. The definitions were then validated on 120 standardized US images of the wrist, metacarpophalangeal joints, and tibiotalar joints, displaying various degrees of synovitis at various ages. RESULTS: B-mode and Doppler should be used for assessing synovitis in children. A US definition of the various components (i.e., synovial hypertrophy, effusion, and Doppler signal within the synovium) was developed. The definition was validated on still images with a median of 89% of participants (range 80-100) scoring it as 4 or 5 on a Likert scale. CONCLUSION: US definitions of synovitis and its elementary components covering the entire pediatric age range were successfully developed through a Delphi process and validated in a web-based still-images exercise. These results provide the basis for the standardized US assessment of synovitis in clinical practice and 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 | 0.062 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".