Tricuspid Regurgitant Jet Velocity Point-of-Care Ultrasound Curriculum Development and Validation
Bibliographic record
Abstract
Introduction: The American College of Emergency Physicians (ACEP) recommends that Emergency Medicine physicians with advanced training can evaluate right ventricular (RV) pressures via point-of-care ultrasound (POCUS) by measuring a tricuspid regurgitant jet (TRJ). We were unable to find a published curriculum to deliver education for this at any skill level. Therefore, we developed, delivered, and evaluated a curriculum for the assessment of TRJ for novice physician sonographers. Methods: We designed an educational intervention for novice physician sonographers. The curriculum was created using a modified Delphi methodology. All novice sonographers participated in the educational intervention which consisted of a didactic lecture followed by hands-on-deliberate practice on healthy medical student volunteers with expert feedback in a simulated setting. Sonographer's knowledge was assessed at 3 time points: pre-intervention, immediately post-intervention, and 3 months post-intervention (retention assessment) by multiple choice exam. Results: Nine novice physician sonographers participated in the intervention. Mean exam performance increased from 55.6% [standard deviation (SD) 11.3%] on the pre-intervention exam to 94.4% (SD 7.3%) on the post-intervention exam and 92.9% (SD 12.5%) on the retention exam. The mean improvement between the pre- and post- exam was +38.9% (95% CI 31.8 - 46.0), and between the pre-exam and retention exam +37.1% (95% CI 22.3 - 52.0). Conclusion: Sonographer knowledge of TRJ assessment improved following a brief educational intervention as measured by exam performance. Given the expanding role of POCUS it is increasingly important to provide effective resources for teaching these skills. This work establishes the basis for further study and implementation of our TRJ curriculum.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".