Hybrid approach for coronary artery revascularization
Bibliographic record
Abstract
PURPOSE OF REVIEW: Recently, hybrid coronary artery revascularization (HCAR), combining the benefits of both percutaneous coronary intervention and coronary artery bypass graft surgery (CABG) while minimizing their respective shortcomings, has been developed. This review is aimed to explore and discuss recent clinical outcomes and patient selection, and comment on surgical approaches for HCAR. RECENT FINDINGS: Current forms of HCAR include off-pump mini-sternotomy or on-pump full sternotomy CABG [left internal mammary artery (LIMA)-to-left anterior descending artery(LAD) CABG followed by drug-eluting stents (DES) to non-LAD territories], robotic-assisted off-pump HCAR (robotic LIMA-to-LAD CABG and DES to non-LAD territories), and off-pump mini-thoracotomy single-vessel small thoracotomy (LIMA-to-LAD CABG), all of which have reported acceptable early to mid-term patency rates and freedom from major cardiac and cerebrovascular adverse events. As long-term effectiveness compared with conventional CABG remains to be demonstrated, especially in patients with diabetes and patients with higher SYNTAX scores, appropriate discussion between the 'Heart Team' and patient is needed prior to HCAR. SUMMARY: HCAR presents an attractive alternative option for treating patients with multivessel coronary artery disease because it maximizes the clear survival benefits of LIMA-LAD grafting, improves quality assurance with completion angiography, and allows quicker patient recovery; furthermore, patients avoid the negative systemic inflammatory effects of cardiopulmonary bypass and delayed healing after 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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) | 0.000 | 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".