Bibliographic record
Abstract
PURPOSE OF REVIEW: In the past year, there has been progress on several fronts in the field of mitral valve surgery and intervention. Here, we review key publications regarding the surgical and transcatheter management of mitral valve disease. RECENT FINDINGS: This past year heralded the publication of the 2014 American Heart Association (AHA)/American College of Cardiology (ACC) Guidelines for the Management of Patients With Valvular Heart Disease. Regarding degenerative mitral regurgitation, low risk of operative mortality and data demonstrating clinical benefit for early surgery are prompting renewed calls for early intervention before guideline-based triggers. For functional mitral regurgitation, the precise roles of chordal-sparing replacement versus repair and the optimal management of moderate disease at the time of surgical revascularization are unclear. Sternal-sparing minimally invasive mitral valve surgery has become a mature procedure in experienced centers and offers comparable surgical morbidity and mortality with superior cosmesis and faster return to baseline function. Transcatheter interventions for mitral regurgitation continue to undergo development and testing. Mounting experience and ongoing clinical trials with the MitraClip endovascular edge-to-edge repair device will provide important data on the optimal target population for this device. SUMMARY: This past year has seen important advances in the surgical treatment of degenerative and functional mitral regurgitation as well as continued refinement of transcatheter interventions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.027 |
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".