Techniques, Complications, and Pitfalls of Endoscopic Saphenectomy for Coronary Artery Bypass Grafting Surgery
Bibliographic record
Abstract
OBJECTIVES: The purpose of the present paper is to discuss technical features of endoscopic saphenectomy with CO2 insufflation for CABG surgery and to highlight special situations in which to avoid potential pitfalls that may be encountered. METHODS: The initial section describes the approaches used with endoscopic saphenectomy with insufflation of CO2 at the Montreal Heart Institute and the Wausau Heart Institute, which can be used by operators with different levels of experience. The following sections expose numerous intraoperative tricks and maneuvers to facilitate the procedure. Specific situations associated with increased difficulty are reviewed such as the obese patient, venous insufficiency, vein tethered to the dermis, and double venous systems. Complications specific to the technique such as gas embolism, tunnelitis, and hematomas are discussed and preventive measures are proposed to avoid the rare morbidity associated with endoscopic harvesting. Preparation of the patient as well as monitoring during the intervention are also reviewed. RESULTS: Adherence to the comprehensive approach presented in this text should to ensure retrieval of high-quality grafts with a low complication rate providing patients with the full benefits, both cardiac and functional, of this minimally invasive technique of saphenous vein harvesting for 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".