Safety and efficiency assessment of training Canadian cardiac surgery residents to perform aortic valve surgery
Bibliographic record
Abstract
BACKGROUND: Research has demonstrated equivalent patient safety outcomes for various cardiac procedures when the primary surgeon was a supervised trainee. However, cardiac surgery cases have become more complex, and the Canadian cardiac surgery education model has undergone some changes. We sought to compare patient safety and efficiency of aortic valve replacement (AVR) between Canadian patients treated by senior cardiac trainees and those treated by certified cardiac surgeons. METHODS: We completed a single-centre, case-matched, prospectively collected and retrospectively analyzed study of AVR. Patients were matched between trainees and consultants for age, sex, New York Heart Association and Canadian Cardiovascular Society status, urgency of operation and diabetes status. RESULTS: We analyzed 1102 procedures: 624 isolated AVRs and 478 AVRs with coronary artery bypass graft (CABG). For isolated AVR, there was no significant difference in 30-d mortality (p = 0.13) or in major adverse events (p = 0.38) between the groups. In the AVR+CABG group, there was no significant difference in 30-day mortality (p = 0.10) or in the rates of major adverse events (p = 0.37) between the groups. Secondary outcomes (hospital and intensive care unit lengths of stay, valve size and type) did not differ significantly between the groups for isolated AVR or AVR+CABG. CONCLUSION: Despite a higher-risk patient population and changes in the cardiac surgery training model, it appears that outcomes are not negatively affected when a senior trainee acts as the primary surgeon in cases of AVR.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".