A model of cardiopulmonary bypass staged training integrating technical and non-technical skills dedicated to cardiac trainees
Bibliographic record
Abstract
OBJECTIVES: To develop a standardized simulation-based curriculum to teach medical knowledge and technical, communication and critical thinking skills necessary to initiate and wean from cardiopulmonary bypass (CPB) to junior cardiac trainees (CTs) in France. Performance on post-curricular tests was compared between CTs who participated in the new curriculum to those who did not. METHODS: The simulation-based curriculum was developed by content and education experts. Simulations sequentially taught the skills necessary for initiating and weaning from CPB as well as managing crises by adding fidelity and complexity to scenarios. Nine CTs were randomly assigned to the new curriculum (n=5) or the traditional curriculum (n=4). Skills were assessed using tests of medical knowledge and technical, communication (GRS) and critical thinking (SCT) skills. A two-sample Wilcoxon rank-sum test compared average scores between the two groups. Alpha of 0.05 was set to indicate statistically significant differences. RESULTS: The resutls revealed that CTs in the new curriculum significantly outperformed CTs in the traditional curriculum on technical (18.2 vs 14.8, p=0.05) and communication (3.5 vs 2.2, p=0.013) skills. There was no significant difference between CTs in the new curriculum in the Script Concordance Test (16.5 vs 14.8, p=0.141) and knowledge tests (26.9 vs 24.6, p=0.14) compared to CTs in the traditional curriculum. CONCLUSION: Our new curriculum teaches communication and technical skills necessary for CPB. The results of this pilot study are encouraging and relevant. They give grounds for future research with a larger panel of trainees. Based on the current distribution of scores, a sample size of 12 CTs per group should yield significant results for all tests.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".