The internal mammary artery – use as a free graft in coronary artery bypass grafting – evidence, technical considerations and controversies
Bibliographic record
Abstract
BackgroundIn-situ internal mammary artery (IMA) grafting remains the gold standard in coronary artery bypass grafting (CABG), particularly for left anterior descending artery revascularisation. However, the role of free-IMA grafts-especially free right IMA (RIMA) and select cases of free left IMA (LIMA)-has expanded in response to anatomical and technical constraints. This narrative review synthesises current evidence on free-IMA use during CABG.MethodsA structured literature search was conducted using PubMed (1946-2025) and Embase (1974-2025), supplemented by Web of Science, Google Scholar, and thesis repositories. Studies were included if they reported outcomes related to free-IMA grafting, regardless of pump status or harvesting technique. Of 74 eligible studies, 9 chosen studies specifically reported free-RIMA outcomes and were analysed in detail.ResultsFree-RIMA grafting demonstrated excellent long-term patency (up to 96%) and favourable survival outcomes when used as composite or direct aorto-coronary grafts. Multi-arterial grafting (MAG) and total arterial grafting (TAG) strategies incorporating free-IMA conduits were associated with reduced major adverse cardiac events (MACE) and improved freedom from repeat revascularisation. Despite these benefits, uptake of free-IMA techniques remains low in Europe and North America, often limited by institutional preferences and operator experience.ConclusionCurrent evidence supports the selective use of free-IMA grafts in CABG, particularly when in-situ deployment is not feasible. Prospective studies are needed to validate long-term outcomes beyond 10 years, compare free-IMA with radial artery grafts, and define optimal arterial configurations for durable revascularisation.
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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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".