Musculoskeletal ultrasound (MSK-US) in pediatric rheumatology: European preliminary results of the survey of the Pediatric Ultrasound Group of the Omeract Ultrasound Task Force
Bibliographic record
Abstract
Despite the growing interest and use of MSK-US in children, its current use in paediatric rheumatology is not known. To identify the current use of MSK-US and the areas most suitable for its development and standardisation in paediatric rheumatology. A questionnaire of 10 single or composite questions, including professional data, current use in daily practice, current clinical relevance of the main features of MSK-US, and areas for prospective development, has been sent to the members of PRINTO/PRES. 92/389 (24%) answers have been collected from 37 countries. The responders are mainly pediatric rheumatologists (80%), have a long-lasting clinical experience in paediatric rheumatology (74% >10 years), and are more clinicians (>70%) than researchers (24%). MSK-US is used in clinical practice by>90%: personally by 40%, 49% by the radiologist, 16% by the adult rheumatologist. The most relevant features of MSK-US are the high patient’s acceptability (76%), the immediate improving of diagnosis of joint and soft tissue disease (73%), the assessment of synovitis and tendons/tendons’sheaths (73% and 70%), and the support to imaging guided joint injections (67%). The anatomical sites best suited for MSK-US are hips (87%), ankles (78%), wrists (65%), knees (64%), and mid-foot (63%). MSK-US is considered important for diagnosis, therapy monitoring, and research (70%). We identified the current use of MSK-US in paediatric rheumatology among the European network of PRINTO/PRES. The results outline the major reasons and areas of interest, useful for future steps towards a wider international standardized development of MSK-US in paediatric rheumatology.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".