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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".