A Survey of Ultrasound Training in U.S. and Canadian Chronic Pain Fellowship Programs
Bibliographic record
Abstract
OBJECTIVE: To assess the current state of ultrasound training in U.S. and Canadian Chronic Pain Fellowship programs. DESIGN: U.S. as well as Canadian chronic pain fellowship programs were contacted via email and program directors were asked to complete a survey. The surveys were completed online using a questionnaire. SETTING: Questionnaire via email. PATIENTS: None. INTERVENTIONS: None. OUTCOME: To assess the current state of ultrasound training in U.S. and Canadian Chronic Pain Fellowship programs. MEASURES: Current teaching structure, types, and numbers of ultrasound-guided interventional pain procedures. RESULTS: Thirty-one responses (30.7%) from the 97 U.S. and four Canadian programs surveyed. Of the 31 programs that responded, 26 offered ultrasound training; five did not. These 31 programs averaged 4.1 fellows per year, majority 96.2% of the 26 programs taught ultrasound throughout the fellowship year. The type of ultrasound training varied, with the large majority 96.2% being patient based. Among 26 programs, 96.2% used ultrasound for peripheral nerve blocks, 76.9% used ultrasound for non-axial musculoskeletal injections, and 53.8% used ultrasound for axial nerve blocks. CONCLUSIONS: Chronic pain fellowships were teaching ultrasound-guided procedures to their fellows. The majority of the fellowships offered ultrasound training throughout the fellowship year. A majority of training was accomplished via hands-on experience with patients. Chronic pain fellows were receiving a majority of ultrasound training for peripheral nerve blocks, followed by nonaxial musculoskeletal blocks, with few axial nerve blocks being taught.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".