Evolving Concepts and Technologies in Mitral Valve Repair
Bibliographic record
Abstract
O ver the past few decades, it has become apparent that mitral valve repair is preferable to mitral valve replacement for the majority of patients undergoing surgery for mitral regurgitation (MR).The advantages of mitral valve repair include low rates of thromboembolism, resistance to endocarditis, excellent late durability reported for as long as 25 years, and no need for anticoagulation in the majority of patients.[1][2][3][4][5] Because of these advantages of repair over replacement, the threshold for performing mitral valve repair has been lowered to include patients with MR who have early symptoms or even those who are asymptomatic, assuming that the chance of successful repair is Ն90% according to the latest American College of Cardiology/American Heart Association guidelines.6,7 Recently, surgeons have evaluated new techniques to further improve mitral valve repair, and cardiologists and surgeons are increasingly interested in the potential for percutaneous approaches to mitral valve repair.8 Myxomatous MR affects 1% to 2% of the population and therefore is a common pathology for mitral valve surgery, but the complexity of the operation may be difficult, which leads to generally low rates of repair.In a recent review, only 44.3% of patients in the United States who required mitral valve surgery for MR received a mitral valve repair, 9 and in the Euro Heart Survey, repair rates were similarly low (46.5%).10 The goals of mitral repair are to maintain leaflet mobility, remodel the annulus, and allow normal coaptation of the anterior and posterior leaflets.Recent advances in techniques and new concepts for mitral repair are important to cardiologists and other clinicians interested in the management of patients with mitral valve disease.Accordingly, an improved understanding of these concepts will aid in the development of innovative techniques to create safe, durable, reliable, and reproducible mitral valve repair techniques, both by open and by less invasive surgical methods.Many of these concepts may be applicable with novel percutaneous approaches.[11][12][13][14] We aim to clarify these concepts and techniques in this review.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".