No-touch saphenous vein: current understanding of the conduit ‘less handled’
Bibliographic record
Abstract
PURPOSE OF REVIEW: The no-touch technique is an established method to harvest the saphenous vein (NT-SV), which is the most commonly used conduit in coronary artery bypass grafting. Herein, we summarize the foundational evidence, as well as highlight recent innovations and ongoing clinical trials involving NT-SV. RECENT FINDINGS: Through preservation of perivascular tissue for atraumatic handling and omission of manual distension, the NT-SV maintains endothelial nitrous oxide synthase levels and experiences less vascular smooth muscle cell activation, which translates to slower progression of atherosclerosis and less size mismatch of the graft and target vessel. These biomolecular advantages allow NT-SV to provide superior graft patency compared to conventional skeletonized saphenous vein and approximating that of the radial artery. Nonetheless, the clinical benefits of NT-SV for mortality and reduction in major adverse cardiac and cerebrovascular events are insufficiently studied in the long-term. The drawback of NT-SV is the short-term harvest site complications, which may potentially be addressed by the advent of endoscopic no-touch technique. SUMMARY: NT-SV is a promising conduit, and its role will be further clarified in upcoming clinical trials and as follow-up lengthens. However, conduit selection and harvest technique should ultimately be personalized to the individual patient.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".