Bilateral internal thoracic artery graft configuration and coronary artery bypass grafting conduits
Bibliographic record
Abstract
PURPOSE OF REVIEW: Bilateral internal thoracic arteries (BITAs) have demonstrated their superiority over all other types of graft in terms of patency and survival benefit. BITA implementation requires the surgeon's evaluation of the patient's coronary anatomy and demographics. There is no single ideal approach to BITA utilization, but instead a variety of configurations that can be implemented based on the patient characteristics. RECENT FINDINGS: This article details the advantages and disadvantages of several BITA configurations in the setting of left-sided myocardial revascularization and right-sided myocardial revascularization. Different BITA configurations will be described and will ultimately serve as a guide to avoiding technical difficulties and helping surgeons construct decision-making trees to direct the implementation of BITA grafts. SUMMARY: BITA grafting provides long-term clinical benefit over conventional grafting. Efforts should be directed toward a more efficient use of internal thoracic arteries, reducing the need for a third complementary graft, and toward identification of the best alternative to the saphenous vein graft as the third graft material for complete revascularization. Surgeons should ask their cardiologists to be as accurate as possible regarding the severity of the coronary lesion. If the severity of the lesion is not obvious upon an informal qualitative assessment, a functional flow reserve of the lesion should be performed, in order to identify the optimal graft.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".