Non-Fellowship regional anesthesia training and assessment: an international Delphi study on a consensus curriculum
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: While there are several published recommendations and guidelines for trainees undertaking subspecialty Fellowships in regional anesthesia, a similar document describing a core regional anesthesia curriculum for non-fellowship trainees is less well defined. We aimed to produce an international consensus for the training and teaching of regional anesthesia that is applicable for the majority of worldwide anesthesiologists. METHODS: This anonymous, electronic Delphi study was conducted over two rounds and distributed to current and immediate past (within 5 years) directors of regional anesthesia training worldwide. The steering committee formulated an initial list of items covering nerve block techniques, learning objectives and skills assessment and volume of practice, relevant to a non-fellowship regional anesthesia curriculum. Participants scored these items in order of importance using a 10-point Likert scale, with free-text feedback. Strong consensus items were defined as highest importance (score ≥8) by ≥70% of all participants. RESULTS: 469 participants/586 invitations (80.0% response) scored in round 1, and 402/469 participants (85.7% response) scored in round 2. Participants represented 66 countries. Strong consensus was reached for 8 core peripheral and neuraxial blocks and 17 items describing learning objectives and skills assessment. Volume of practice for peripheral blocks was uniformly 16-20 blocks per anatomical region, while ≥50 neuraxial blocks were considered minimum. CONCLUSIONS: This international consensus study provides specific information for designing a non-fellowship regional anesthesia curriculum. Implementation of a standardized curriculum has benefits for patient care through improving quality of training and quality of nerve blocks.
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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 | 0.116 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| 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".