Assessing the Long-term Patency and Clinical Outcomes of Venous and Arterial Grafts Used in Coronary Artery Bypass Grafting: A Meta-analysis
Bibliographic record
Abstract
Introduction The long-term patency of the grafts used during the coronary artery bypass grafting (CABG) is one of the most significant predictors of the clinical outcomes. The gold standard graft used during CABG with the best long-term patency rate and the better clinical outcomes is left internal thoracic artery (LITA) grafted to the left coronary artery (LCA). The controversy lies in choosing the second-best conduit for the non-left coronary artery (NLCA) with similar patency rate as LITA. This meta-analysis examines the long-term patency and clinical outcomes of all arterial grafts versus all venous grafts used during the CABG. Methods A comprehensive literature search of all published randomized control trials (RCTs) assessing long-term patency and clinical outcomes of grafts used in CABG was conducted using PubMed, Cochrane Central Registry of Controlled Trials, and Google Scholar (1966-2018). Keywords searched included combinations of "CABG", "venous grafts in CABG", "arterial grafts in CABG", "radial artery grafts in CABG", "gastroepiploic artery grafts in CABG", "patency and clinical outcomes". Inclusion criteria included: RCTs comparing the long-term patency, and clinical outcomes of radial artery, right internal thoracic artery, gastroduodenal artery, and saphenous vein grafts used in CABG. Long-term patency of the grafts and clinical outcomes were analyzed. Results Eight RCTs involving 2,091 patients with 1,164 patients receiving arterial grafts and 927 patients receiving venous grafts were included. There was no difference between the long-term patency rate (relative risk (RR) = 1.050, 95% confidence interval (CI) = 0.949 to 1.162, and p = 0.344), overall mortality rate (RR = 1.095, 95% CI = 0.561 to 2.136, and p = 0.790), rate of myocardial infarction (MI) (RR = 0.860, 95% CI = 0.409 to 1.812, and P = 0.692), and re-intervention rate (RR = 0.0768, 95% CI = 0.419 to 1.406, and P = 0.392) between arterial and venous grafts. Conclusion The use of arterial conduits over the venous conduits has no significant superiority regarding the long-term graft patency, the rate of MI, overall mortality, and the rate of revascularization following CABG. Additional adequately powered studies are needed to further evaluate the long-term outcomes of arterial and venous grafts following the CABG.
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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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.048 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".