Implementation and Assessment of a Curriculum for Renal Point of Care Ultrasound (POCUS) Training
Bibliographic record
Abstract
Purpose: Renal ultrasound is a non-invasive method to assess for obstructive acute kidney injury (AKI). Point of care ultrasound (POCUS) has been shown to be a good screening tool for obstructive AKI, and with formal training, has high sensitivity and specificity. We aimed to evaluate the effectiveness and feasibility of integrating a novel renal POCUS curriculum into an existing two-week nephrology rotation for internal medicine residents. Methods: We enrolled internal medicine residents rotating on a two-week nephrology rotation between September 2022 and June 2023. Pre-recorded online lectures and a hands-on session on image acquisition were provided. Pre-and post-rotation confidence questionnaires and knowledge tests were collected. At the end of the rotation, participants were evaluated using a skills checklist. Evaluation for knowledge retention was assessed 6–12-months post-rotation with a post-survey and knowledge test. Results: Of the 16 residents that were enrolled, 12 residents completed pre- and post-rotation questionnaires and tests, and 15 residents completed the 6–12-month follow-up. The confidence level showed significant improvement post-test and at 6–12-month follow-up. Knowledge test scores showed a trend towards improvement that did not achieve statistical significance (pre- 6.0 [5.0-7.25], post- 6.5 [5.75-8.0], 6–12-months 7.0 [6.0-8.0] p=0.40). On the skills checklist, an average of 16.8 out of 18 steps were done correctly. Conclusion: Our study showed confidence improvement and a trend towards knowledge improvement after integrating a novel Renal POCUS curriculum into a nephrology rotation. Further iterative changes, such as deliberate practice, or practice with immediate feedback, should be considered.
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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 | 0.001 | 0.000 |
| 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".