Long-Term Results of Heart Operations Performed by Surgeons-in-Training
Bibliographic record
Abstract
BACKGROUND: We investigated the association between trainees performing supervised operations and late outcomes of patients undergoing cardiac surgery. METHODS AND RESULTS: Data were prospectively collected on patients who underwent coronary artery bypass graft surgery, aortic valve replacement, or a combination of these between 1998 and 2005 at the Maritime Heart Center, Halifax, Canada. In-hospital mortality and a composite outcome of in-hospital mortality, stroke, bleeding, intra-aortic balloon pump insertion, renal failure, and sternal infection was compared between teaching (n=1054) and nonteaching cases (n=5877). Late survival and cardiovascular hospital readmissions were also examined. To adjust for baseline risk disparities, we used logistic regression for dichotomous in-hospital outcomes and Cox proportional hazards regression for survival data. Resident cases were significantly more likely to have high-risk features such as depressed ventricular function, redo operation, and urgent or emergent procedure. Resident as primary operator was not independently associated with in-hospital mortality (OR, 1.09; 95% CI, 0.75 to 1.58; P=0.66) or with the composite outcome (OR, 1.01; 95%, CI 0.82 to 1.26; P=0.90). The Kaplan-Meier event-free survival of the 2 groups was equivalent at 1, 3, and 5 years (log-rank P=0.06). By Cox regression, resident cases were not associated with late death or cardiovascular rehospitalization (hazard ratio, 1.05; 95% CI, 0.94 to 1.17; P=0.42). CONCLUSIONS: Cases performed by senior-level cardiac surgery residents were more likely to have greater acuity and complexity than staff surgeon-performed cases. However, clinical outcomes were similar in the short- and long-term. Allowing residents to perform cardiac surgery is not associated with adverse patient outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".