Screening for abdominal aortic aneurysms in Canada: 2020 review and position statement of the Canadian Society for Vascular Surgery
Bibliographic record
Abstract
Abdominal aortic aneurysms (AAAs) remain a major risk to patients, despite level 1 evidence for screening to prevent rupture events and decrease mortality. In 2007, the Canadian Society for Vascular Surgery (CSVS) published a review and position statement for AAA screening in Canada. Since that publication, there have been a number of updates in the published literature affecting screening recommendations. In this paper, we present a review of some of the controversies in the AAA screening literature to help elucidate differences in the various published screening guidelines. This article represents a review of the data and updated recommendations for AAA screening in the Canadian population on behalf of the CSVS. Les anévrismes de l’aorte abdominale (AAA) continuent de poser un risque majeur pour les patients, malgré des données probantes de niveau 1 à l’appui du dépistage pour prévenir les ruptures et réduire la mortalité. En 2007, la Société canadienne de chirurgie vasculaire (SCCV) a publié une revue et un énoncé de position sur le dépistage de l’AAA au Canada. Depuis lors, plusieurs mises à jour ont paru dans la littérature et elles ont un impact sur les recommandations relatives au dépistage. Dans le présent article, nous présentons une synthèse de quelques controverses soulevées dans la littérature sur le dépistage de l’AAA afin d’expliquer les différences entre les diverses lignes directrices publiées à ce sujet. Cet article propose au nom de la SCCV une revue des données probantes et des recommandations à jour sur le dépistage de l’AAA dans la population canadienne.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".