Less invasive multivessel coronary artery bypass grafting: now is the time
Bibliographic record
Abstract
PURPOSE OF REVIEW: Less invasive multivessel coronary artery bypass grafting techniques have seen a progressive evolution over the last two decades. In their current state, they are easily reproduced and applicable to most patients requiring multivessel revascularization. The purpose of this review is to highlight their importance among a spectrum of evolving therapies and the accruing evidence in their favour. RECENT FINDINGS: The first large dual center experience with minimally invasive coronary artery bypass grafting (MICS CABG) demonstrated the feasibility of performing multivessel surgical revascularization without the need for sternotomy or cardiopulmonary bypass. Subsequent angiographic studies to assess graft patency showed excellent early results. Studies comparing MICS CABG to conventional CABG demonstrate faster recovery while reducing hospitalization and cost. SUMMARY: Multivessel less invasive coronary artery bypass grafting is basically limited to two procedures, MICS CABG and robotically assisted totally endoscopic CABG (TECAB). MICS CABG has evolved as a procedure that preserves the safety and efficacy of conventional CABG while avoiding the associated morbidity. It is reproducible, versatile and holds promise as the procedure of choice for multivessel coronary revascularization in the future. TECAB is likely the pinnacle of minimally invasive coronary surgery, the growth of which is hindered by widespread acceptance and industry involvement.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".