Abstract 18376: Angiographic Graft Patency After Multivessel Minimally Invasive Coronary Artery Bypass Grafting: MICS CABG Patency Study
Bibliographic record
Abstract
Objective: Previous publications from our institutions have shown that minimally invasive coronary artery bypass grafting (MICS CABG) is safe, widely applicable, and associated with fewer infections, less transfusions, and better recovery than standard CABG. However, graft patency rates are unknown. The MICS CABG Patency Study prospectively evaluated angiographic bypass graft patency at 6 months after MICS CABG. Methods: In this dual-center study, 61 patients were prospectively enrolled and underwent MICS CABG through a 4-7cm left thoracotomy approach, where the left internal thoracic artery (LITA), the ascending aorta for proximal anastomoses, and all distal coronary targets were accessed without endoscopic or robotic assistance. The primary outcome was graft patency at 6 months, using 64-slice CT angiography. Secondary outcomes included conversions to sternotomy and major adverse cardiovascular events (MACE). ( Clinical Trial Registration Unique identifier: NCT01334866 ) Results: Mean age was 64.1±8.1 years, the mean ejection fraction was 48.8±10.4%, and there were 8 females in the study (13.1%). Surgeries were performed off-pump in 52 patients (85.2%). Complete revascularization was achieved in all patients, and the median number of grafts was 3. There was no perioperative mortality, no conversion to sternotomy, and 1 reopening for bleeding. Transfusion occurred in 15 patients (24.6%).The median length of hospital stay was 4 days, and patients were followed-up to 6 months, with no mortality or MACE. At 6 months, overall CT angiographic graft patency was 91.2% for all grafts, and 100% for LITA grafts. Conclusions: MICS CABG is safe, feasible, and associated with excellent rates of graft patency at 6 months post-surgery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".