How do surgeons decide? Conduit choice in coronary artery bypass graft surgery in the UK
Bibliographic record
Abstract
OBJECTIVES: Conduits used in coronary artery bypass grafting may have significant impact on outcomes, but evidence is mixed and there is large variation in practice. This study provides insights into the opinions of the UK surgeons on conduit use and their decision-making processes. METHODS: A questionnaire was created using the Ottawa Decision Support Framework to elicit the importance that surgeons placed on bilateral internal mammary artery grafting, skeletonization, total arterial revascularization and sequential anastomoses on a scale of 1-10. Scores ≥8 were deemed 'important' and ≤3 'not important'. Surgeons were asked to specify changes to practice in frail patients or emergencies. Additional questions included conduit type used, factors affecting decision-making and vein harvesting methods. Questionnaires were administered in person with data analysed centrally. RESULTS: Ninety-seven consultant cardiac surgeons from 25 centres responded. Thirty-two percent surgeons routinely used radial arteries and 36% used right internal mammary artery. High-quality evidence contributed most to decision-making receiving a total of 328/960 points, with consultant experience being the second (255/960 points). There was a bimodal distribution of perceived importance of bilateral internal mammary artery use, with 29 (30%) 'important' and 'not important' scores each. 23% of surgeons found total arterial revascularization important. Most surgeons (64%) preferred pedicled mammary arteries. Twenty-six percent of surgeons considered sequential grafting to be important. CONCLUSIONS: Low uptake of total arterial revascularization and bilateral internal mammary artery among the UK consultants may be due to the lack of high-quality evidence demonstrating a significant benefit. It is also possible that reluctance to use certain conduits may stem from low levels of exposure to conduits or inadequate training, particularly given the importance of consultant experience on decision-making.
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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 | 0.004 | 0.032 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".