Three Arterial Grafts Improve Late Survival
Bibliographic record
Abstract
Background: Little evidence shows whether a third arterial graft provides superior outcomes compared with the use of 2 arterial grafts in patients undergoing coronary artery bypass grafting. A meta-analysis of all the propensity score-matched observational studies comparing the long-term outcomes of coronary artery bypass grafting with the use of 2-arterial versus 3-arterial grafts was performed. Methods: A literature search was conducted using MEDLINE, EMBASE, and Web of Science to identify relevant articles. Long-term mortality in the propensity score-matched populations was the primary end point. Secondary end points were in-hospital/30-day mortality for the propensity score-matched populations and long-term mortality for the unmatched populations. In the matched population, time-to-event outcome for long-term mortality was extracted as hazard ratios, along with their variance. Statistical pooling of survival (time-to-event) was performed according to a random effect model, computing risk estimates with 95% confidence intervals. Results: Eight propensity score-matched studies reporting on 10 287 matched patients (2-arterial graft: 5346; 3-arterial graft: 4941) were selected for final comparison. The mean follow-up time ranged from 37.2 to 196.8 months. The use of 3 arterial grafts was not statistically associated with early mortality (hazard ratio, 0.93; 95% confidence interval, 0.71–1.22; P =0.62). The use of 3 arterial grafts was associated with statistically significantly lower hazard for late death (hazard ratio, 0.8; 95% confidence interval, 0.75–0.87; P <0.001), irrespective of sex and diabetic mellitus status. This result was qualitatively similar in the unmatched population (hazard ratio, 0.57; 95% confidence interval, 0.33–0.98; P =0.04). Conclusions: The use of a third arterial conduit in patients with coronary artery bypass grafting is not associated with higher operative risk and is associated with superior long-term survival, irrespective of sex and diabetic mellitus status.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".