Surgeon case conferencing in elective aortic surgery
Bibliographic record
Abstract
Background: Surgeon case conferences (SCCs) involve same-phenotype surgeons (i.e., surgeons who perform similar procedures such as orthopedic or vascular surgeons) meeting to discuss upcoming consecutive cases; other specialties are excluded to ensure a focus on surgical considerations. Given that some studies found that SCCs sometimes led to treatment plan changes among patients with gastrointestinal malignancies, we sought to test SCCs in vascular surgery. Methods: A pre-study workshop with researchers and vascular surgeons at a single institution produced relevant SCC elements, including the decision to focus on aortic procedures; definitions of major (e.g., convert from open to endovascular approach) and minor (e.g., additional preoperative testing) treatment changes; and an aortic SCC form. The form facilitated collection of data related to the initial treatment plan, the consensus treatment plan, and a description of treatment plan changes. During subsequent SCCs, for each patient, the primary surgeon presented their initial treatment plan, a confidence score for this plan (on a Likert scale of 1 to 5, from no to high confidence), and patient details. Subsequent group discussion produced a consensus treatment plan and a description of any plan changes. Study outcomes included rates of major and minor change from the primary surgeon’s initial plan to the consensus plan, and confidence scores for patients with and without a plan change. Results: Six vascular surgeons from a single academic hospital with a high procedure volume reviewed 100 consecutive patients during 33 aortic SCCs over a 10-month period. The rate of change from initial to consensus treatment plans was 39%. Rates of major and minor changes were 10% and 29%, respectively. Patient and treatment measures were similar for patients with and without a treatment change. Confidence scores for initial treatment plans were similar for patients with and without a change (median score 4 and 5, respectively; p = 0.09). Conclusion: A structured SCC changed 39% of primary vascular surgeons’ initial treatment plans related to aortic procedures, even though confidence scores in initial treatment plans were similar for patients with and without changes. Our results suggest that vascular surgeons should seek structured input from colleagues for all patient cases not just those they perceive as challenging.
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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 | 0.015 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".