Survival Benefit of Multiple Arterial Revascularization With and Without Supplementary Saphenous Vein Graft
Bibliographic record
Abstract
Background It is unknown if the presence of saphenous vein grafting (SVG) adversely affects late survival following coronary surgery with multiple arterial grafting (MAG) versus single arterial grafting. Methods and Results A retrospective, observational, multicenter cohort study from 2001 to 2020 was conducted using the Australian and New Zealand Society of Cardiac and Thoracic Surgeons Database linked to the National Death Index. Patients undergoing primary isolated coronary artery bypass grafting with ≥2 grafts were included, and exclusions were patients aged <18 years, reoperations, concomitant or previous cardiac surgery, and the absence of arterial grafting. Demographics, comorbidities, medication, and operative configurations were propensity score matched between cohorts. The primary outcome was all‐cause late death. Of 59 689 eligible patients, 35 113 were MAG (58.8%), and 24 576 were single arterial grafting (41.2%). Of the MAG cohort, 17 055 (48.6%) patients did not receive supplementary SVG (total arterial revascularization). Matching separately generated 22 764 patient pairs for MAG versus single arterial grafting, and 11 137 patient pairs for MAG with total arterial revascularization versus MAG with ≥1 supplementary vein grafts. At a median follow‐up duration of 5.0 years postoperatively, the mortality rate was significantly lower for MAG than single arterial grafting (hazard ratio [HR], 0.79 [95% CI, 0.76–0.83]; P <0.001). The stratified MAG analysis found that MAG with total arterial revascularization had a lower risk of late death (HR, 0.85 [95% CI, 0.80–0.91]; P <0.001) compared with MAG with ≥1 supplementary vein grafts. Sensitivity analyses produced consistent outcomes as the primary analysis. Following adjustment for the presence of SVG in the Cox model, the survival advantage of incremental number of arteries was lost. Conclusions Multiple arterial grafting has significantly improved long‐term survival compared with single arterial grafting. A further incremental survival benefit exists when no SVG is used.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".