Bibliographic record
Abstract
It has been customary for interventional cardiologists involved in carotid artery stenting, to underline non-inferiority of the percutaneous technique versus surgical carotid endarterectomy. To that end, all cause morbidity and mortality figures of both methods are compared. Surgery has, in most large randomized studies, had an edge over stenting in terms of cerebrovascular adverse events. This may have partly been due to occasional indiscriminate indication for stenting in lesions and/or vessels with unfavourable characteristics (severe target vessel tortuosity and calcification, Type III aortic arch, and so on). On one hand, the author pleads for improvement of the excellent results of endarterectomy, by subjecting all patients planned for surgery to a thorough preoperative cardiological work up, including generous invasive investigation, thus reducing the incidence of perioperative myocardial infarction, heart failure and cardiac death. On the other hand, we are convinced that the results of carotid stenting should then be compared to best practice surgery. The rate of neurological adverse event rate after carotid endarterectomy at our institution lies under 0.7% at 30 days postoperatively. Specifically, the goal should be that carotid stenting underbids surgical endarterectomy, also and mainly, in terms of cerebral and cerebrovascular adverse events. Cardiac morbidity and mortality as well as laryngeal nerve palsy should no more be the main arguments for the percutaneous approach. This should easily be possible if patient selection for carotid revascularisation would be approached according to morphological criteria, in analogy with the "Syntax"-score used to optimise revascularisation strategies in coronary artery disease.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.015 |
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".