Adding an endovascular aortic surgery program to a rural regional medical centre
Bibliographic record
Abstract
BACKGROUND: Abdominal aortic aneurysms requiring surgical intervention are generally treated by endovascular means. Such procedures are not always offered in rural hospitals, possibly leaving patients underserved. We reviewed our experience initiating an endoaortic surgery program. METHODS: A surgeon in a rural centre was credentialed to perform endovascular aortic aneurysm repair through collaboration with a university centre and was proctored locally for the first 5 abdominal aneurysm repairs. Web-based image storage was used to review complex cases as part of an ongoing partnership. Referred patients were screened for multiple aneurysms and underwent long-term monitoring. RESULTS: In all, 160 patients were evaluated for 176 aortic pathologies. Twenty-five patients (17 men) aged 55-89 years underwent 26 endovascular abdominal (n = 23) or thoracic (n = 3) aortic procedures. Emergent endovascular procedures were not performed. There were no operative deaths, requirements for dialysis or conversions to open repair. Two endoleaks required early reintervention. The median length of stay in hospital for endovascular procedures was 2.5 days. Chronic endoleaks were observed in 7 patients. An additional 8 patients underwent open abdominal aneurysm repair locally and 15 patients were referred to the university program. CONCLUSION: Creation of an endovascular aortic surgery program in a rural hospital is feasible through collaboration with a high-volume centre. Patient safety is enhanced by obtaining second opinions using web-based image review. Most interventions are for abdominal aortic aneurysms, but planning for a comprehensive aortic clinic is preferable.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".