Coronary Artery Bypass Surgery Without Saphenous Vein Grafting
Bibliographic record
Abstract
Approximately 95% of patients of any age undergoing contemporary, coronary bypass surgery will receive at least 1 saphenous vein graft (SVG). It is recognized that SVG will develop progressive and accelerated atherosclerosis, resulting in a stenosis, and in occlusion that occurs in 50% by 10 years postoperatively. For arterial conduits, there is little evidence of progressive failure as for SVG. Could avoidance of SVG (total arterial revascularization [TAR]) lead to a different late (>5 year) survival? A literature review of 23 studies (N = 100,314 matched patients) at a mean 8.8 years postoperative found reduced all-cause mortality for TAR (HR: 0.77; 95% CI: 0.71-0.84; P < 0.001). An expanded analysis with a new unpublished data set (N = 63,288 matched patients) was combined with the literature review (N = 127,565). It found reduced all-cause mortality for TAR (HR: 0.78; 95% CI: 0.72-0.85; P < 0.001). Additional Bayesian analysis found a very high probability of a TAR-associated reduction all-cause mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".