Robotic hybrid coronary revascularization versus conventional off‐pump coronary bypass surgery in women with two‐vessel disease
Bibliographic record
Abstract
BACKGROUND: Hybrid coronary revascularization (HCR) treats coronary artery disease (CAD) by combining a minimally invasive surgical approach with the left internal mammary artery (LIMA) to the left anterior descending (LAD) artery and percutaneous coronary intervention (PCI) for non-LAD vessels. This study aimed to compare immediate and long-term outcomes between robotic HCR and off-pump coronary artery bypass (OPCAB) via sternotomy in women with two-vessel CAD. METHODS AND RESULTS: We compared all robotic HCR (LIMA-to-LAD plus stent; n = 55) and OPCAB (LIMA-to-LAD plus saphenous vein graft; n = 54) performed at a single institution between May 2005 and January 2021. To adjust for the selection bias of receiving either HCR or OPCAB, we performed a propensity score analysis of 31 matched pairs. In the immediate postoperative period, no statistically significant difference was observed for operative mortality and HCR was associated with lower rates of blood transfusion (25.8% vs. 54.8%; p = .038), and shorter hospital length of stay (4.0 vs. 6.0 days; p = .009). After a mean follow-up of 7.0 ± 4.9 years, we observed no statistically significant differences between the groups for overall survival (hazard ratio [HR]: 0.48, 95% confidence interval [CI]: 0.09-2.64, p = .401), myocardial infarction (HR: 1.60, 95% CI: 0.14-17.64, p = .703), stroke (HR not assessable; almost zero events), target vessel revascularization (HR: 0.45, 95% CI: 0.08-2.47, p = .359), angina (HR: 0.64, 95% CI: 0.20-2.01, p = .444) and major adverse cardiac and cerebrovascular events (HR: 0.46, 95% CI: 0.14-1.52, p = .202). CONCLUSIONS: Robotic HCR provides for women with two-vessel CAD a shorter postoperative recovery with fewer blood transfusions, with similar long-term outcomes when compared with conventional OPCAB via sternotomy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".