Repeat Revascularization after Minimally Invasive Coronary Artery Bypass Grafting
Bibliographic record
Abstract
OBJECTIVE: Minimally invasive coronary artery bypass grafting (MICS CABG) via a small left thoracotomy is a novel technique for coronary revascularization that is increasingly used around the world. However, multivessel MICS CABG is difficult, and concerns about repeat revascularization (RR) have been raised. This longitudinal study describes the rates of RR among patients who have undergone MICS CABG and identifies targets for improvement. METHODS: A prospective observational study was performed on the 306 MICS CABG patients operated on by a single surgeon from 2005 to 2015. Minimally invasive coronary artery bypass grafting was performed through a small left thoracotomy, using the in situ left internal mammary artery, ± a radial artery, and 1 to 3 saphenous veins anastomosed proximally to the aorta. Patients were followed annually. We examined the difference between the first half and second half of the series to ascertain the effects of a learning curve. RESULTS: Eighty percent of the procedures were performed off-pump. The median number of grafts performed were 2, and the left anterior descending, diagonals, obtuse marginals, and posterior interventricular artery were the distal targets in 94%, 12%, 44%, and 26%, respectively. The graftability index (#grafts/#diseased vessels) was 0.93. Revascularization of targets smaller than 1.5 mm decreased from 69% to 50% (P = 0.002) between the series' first and second halves. Overall, RR was needed in 21 patients (6.9%) and was performed at a mean ± SD of 1.7 ± 1.6 years postoperatively. The culprit lesion was attributed to the index surgical procedure ("graft-associated") in 52%, to a stent stenosis or progression of native disease in 43%, and was unidentified in 5%. Patients with graft-associated RR had a lower graftability index at operation (0.73 vs 0.94) and more frequent involvement of the circumflex system (0.8 vs 0.3). The overall rate of RR at 3 years decreased from 11% in the first half to 2.6% in the second half (P = 0.001). CONCLUSIONS: The need for RR is part of the learning curve with MICS CABG, involves a graft in half of the cases, is more common in patients who had a lower graftability index at operation, and markedly improves with experience.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".