Current status of Canadian vascular surgery training: a survey of program directors.
Bibliographic record
Abstract
BACKGROUND: With the aging of the North American population and therefore the need for more modern vascular surgeons familiar with open operations and less invasive diagnostic and therapeutic regimens, we wished to obtain suggestions and recommendations that would allow our training programs to more adequately fulfil these needs. Our objectives were to assess recent trends in Canadian vascular surgery training with respect to the trainee's operative and nonoperative experience. METHODS: We mailed a survey to the directors of the 8 Canadian vascular surgery training programs, to ascertain the yearly operative volumes of their 3 most recent trainees with respect to 6 index operations: carotid endarterectomy (CEA), types I-IV thoracoabdominal aortic aneurysm (TAA) repair, elective open infrarenal aortic aneurysm (eAAA) repair, ruptured abdominal aortic aneurysm (rAAA) repair, endovascular abdominal aortic aneurysm repair (EVAR) and lower extremity arterial bypass (LEB). Additionally, information pertaining to nonvascular surgery rotations and the final practice location and type of practice for each trainee was requested. RESULTS: Seven (88%) of 8 program directors completed the survey. Between 1999 and 2002, vascular surgery trainees in Canadian training programs were exposed to the following yearly clinical volumes (expressed as mean [and standard deviation]): CEA 55.4 (33.9), TAA 6.2 (3.8), eAAA 63.8 (30.0), rAAA 13.5 (9.4), EVAR 14.9 (9.6) and LEB 74.5 (34.5). The range of yearly clinical volumes were: CEA 21-124, TAA 1-18, eAAA 30-133, rAAA 3-45, EVAR 0-34 and LEB 20-143. Nonvascular surgery rotations included: endovascular therapy, interventional radiology, noninvasive diagnostics and research. Forty-five (80.4%) of 56 recent graduates practise only vascular surgery. Most (73.2%) of our recent trainees have remained in Canada, with 41.1% settling in the province in which they trained. CONCLUSIONS: Canadian vascular surgery training programs provide more than sufficient operative experience for their trainees. Although some programs have been successful at providing training in endovascular therapies, the integration of such experience in our training programs continues to be a challenge.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".