A comparison of surgical, total percutaneous, and hybrid approaches to treatment of combined coronary artery and valvular heart disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this review is to compare outcomes of surgical valve replacement (SVR) and coronary artery bypass grafting (CABG), minimally invasive cardiac surgery (MICS) SVR and percutaneous coronary intervention (PCI), and transcatheter aortic valve replacement and PCI for the treatment of combined coronary artery disease (CAD) and valvular heart disease (VHD). RECENT FINDINGS: Several studies have attempted to identify key differences in outcomes with hybrid MICS SVR and PCI approaches to combined CAD and VHD. Recent studies have demonstrated that MICS SVR and PCI, when compared with conventional open SVR and CABG, demonstrate reduced or unchanged morbidity and mortality. However, the rate of bleeding in MICS SVR and PCI is consistently higher likely because of the effects of antiplatelet therapy. SUMMARY: A shift toward MICS has occurred in the preceding decades, with outcomes improving in recent years. With limited ability to perform CABG through MICS approaches, attempts have been made at hybrid procedures to address multiple presenting concerns while allowing for the benefits of MICS approaches. Hybrid MICS SVR and PCI approaches may provide suitable alternatives to traditional surgical approaches with reduced intra and postoperative morbidity and mortality, with the notable exception of bleeding complications.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".