Angiographic Patency of Coronary Artery Bypass Conduits: A Network Meta‐Analysis of Randomized Trials
Bibliographic record
Abstract
Background Several randomized trials have compared the patency of coronary artery bypass conduits. All of the published studies, however, have performed pairwise comparisons and a comprehensive evaluation of the patency rates of all conduits has yet to be published. We set out to investigate the angiographic patency rates of all conduits used in coronary bypass surgery by performing a network meta-analysis of the current available randomized evidence. Methods and Results A systematic literature search was conducted for randomized controlled trials comparing the angiographic patency rate of the conventionally harvested saphenous vein, the no-touch saphenous vein, the radial artery (RA), the right internal thoracic artery, or the gastroepiploic artery. The primary outcome was graft occlusion. A total of 4160 studies were retrieved of which 14 were included with 3651 grafts analyzed. The weighted mean angiographic follow-up was 5.1 years. Compared with the conventionally harvested saphenous vein, both the RA (incidence rate ratio [IRR] 0.54; 95% CI, 0.35-0.82) and the no-touch saphenous vein (IRR 0.55; 95% CI, 0.39-0.78) were associated with lower graft occlusion. The RA ranked as the best conduit (rank score for RA 0.87 versus 0.85 for no-touch saphenous vein, 0.23 for right internal thoracic artery, 0.29 for gastroepiploic artery, and 0.25 for the conventionally harvested saphenous vein). Conclusions Compared with the conventionally harvested saphenous vein, only the RA and no-touch saphenous vein grafts are associated with significantly lower graft occlusion rates. The RA ranks as the best conduit. Registration URL: https://www.crd.york.ac.uk/prospero; Unique identifier: CRD42020164492.
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 | 0.031 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".