Critical care ultrasound training: a survey exploring the “education gap” between potential and reality in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Critical care ultrasound (CCUS) is now a core competency for Canadian critical care medicine (CCM) physicians, but little is known about what education is delivered, how competence is assessed, and what challenges exist. We evaluated the Canadian CCUS education landscape and compared it against published recommendations. METHODS: A 23-item survey was developed and incorporated a literature review, national recommendations, and expert input. It was sent in the spring of 2019 to all 13 Canadian Adult CCM training programs via their respective program directors. Three months were allowed for data collection and descriptive statistics were compiled. RESULTS: Eleven of 13 (85%) programs responded, of which only 7/11 (64%) followed national recommendations. Curricula differed, as did how education was delivered: 8/11 (72%) used hands-on training; 7/11 (64%) used educational rounds; 5/11 (45%) used image interpretation sessions, and 5/11 (45%) used scan-based feedback. All 11 employed academic half-days, but only 7/11 (64%) used experience gained during clinical service. Only 2/11 (18%) delivered multiday courses, and 2/11 (18%) had mandatory ultrasound rotations. Most programs had only 1 or 2 local CCUS expert-champions, and only 4/11 (36%) assessed learner competency. Common barriers included educators receiving insufficient time and/or support. CONCLUSIONS: Our national survey is the first in Canada to explore CCUS education in critical care. It suggests that while CCUS education is rapidly developing, gaps persist. These include variation in curriculum and delivery, insufficient access to experts, and support for educators.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it