Ischemic Mitral Regurgitation: A Complex Multifaceted Disease
Bibliographic record
Abstract
Ischemic mitral regurgitation (MR) is a complex multifactorial disease that involves global and regional left ventricular remodeling as well as dysfunction and distortion of the components of the mitral valve including the chordae, annulus and leaflets. This is a frequent (13-59%) complication of myocardial infarction, which is associated with a poor prognosis. The suboptimal results obtained with the most commonly used surgical strategy, that is, restrictive annuloplasty combined with coronary artery bypass graft, emphasize the need to develop alternative or concomitant surgical techniques that directly target the causal mechanisms of the disease. A comprehensive assessment of mitral valve configuration and left ventricular geometry and function prior to surgery as well as an accurate quantification of MR severity at rest and during exercise may help improve patient risk stratification and better individualize the surgical strategy based on the patient's specific characteristics. The purpose of this review is to summarize the current state of knowledge with regard to the definition, prevalence, mechanisms, outcome and treatment of ischemic MR.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".