Pan-American League of Associations for Rheumatology (PANLAR) Recommendations and Guidelines for Musculoskeletal Ultrasound Training in the Americas for Rheumatologists
Bibliographic record
Abstract
OBJECTIVE: To develop guidelines for Musculoskeletal Ultrasound (MSKUS) training for rheumatologists in the Americas. METHODS: A total of 25 Rheumatologists from 19 countries of the American Continent participated in a consensus-based interactive process (Delphi method) using 2 consecutive electronic questionnaires. The first questionnaire included the following: the relevance of organizing courses to teach MSKUS to Rheumatologists, the determination of the most effective educational course models, the trainee levels, the educational objectives, the requirements for passing the course(s), the course venues, the number of course participants per instructor, and the percentage of time spent in hands-on sessions. The second questionnaire consisted of questions that did not achieve consensus (>65%) in the first questionnaire, topics, and pathologies to be covered at each course MSKUS level. RESULTS: General consensus was obtained for MSKUS courses to be divided into 3 educational levels: basic, intermediate, and advanced. These courses should be taught using a theoretical-didactic and hands-on model. In addition, the group established the minimum requirements for attending and passing each MSKUS course level, the ideal number of course participants per instructor (4 participants/instructor), and the specific topics and musculoskeletal pathologies to be covered. In the same manner, the group concluded that 60% to 70% of course time should be focused on hands-on sessions. CONCLUSION: A multinational group of MSKUS sonographers using a consensus-based questionnaire (Delphi method) established the first recommendations and guidelines for MSKUS course training in the Americas. Pan-American League of Associations for Rheumatology urges that these guidelines and recommendations be adopted in the future by both national and regional institutions in the American continent involved in the training of Rheumatologists for the performance of MSKUS.
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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 | 0.046 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".