Can medical learners achieve point-of-care ultrasound competency using a high-fidelity ultrasound simulator?: a pilot study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Point-of-care ultrasound (PoCUS) is currently not a universal component of curricula for medical undergraduate and postgraduate training. We designed and assessed a simulation-based PoCUS training program for medical learners, incorporating image acquisition and image interpretation for simulated emergency medical pathologies. We wished to see if learners could achieve competency in simulated ultrasound following focused training in a PoCUS protocol. METHODS: Twelve learners (clerks and residents) received standardized training consisting of online preparation materials, didactic teaching, and an interactive hands-on workshop using a high-fidelity ultrasound simulator (CAE Vimedix). We used the Abdominal and Cardiothoracic Evaluation by Sonography (ACES) protocol as the curriculum for PoCUS training. Participants were assessed during 72 simulated emergency cardiorespiratory scenarios. Their ability to complete an ACES scan independently was assessed. Data was analyzed using R software. RESULTS: Participants independently generated 574 (99.7%) of the 576 expected ultrasound windows during the 72 simulated scenarios and correctly interpreted 67 (93%) of the 72 goal-directed PoCUS scans. CONCLUSIONS: Following a focused training process using medical simulation, medical learners demonstrated an ability to achieve a degree of competency to both acquire and correctly interpret cardiorespiratory PoCUS findings using a high-fidelity ultrasound simulator.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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