Considerations & challenges of mitral valve repair in females: diagnosis, pathology, and intervention
Bibliographic record
Abstract
PURPOSE OF REVIEW: Disparities in mitral valve (MV) repair outcomes exist between men and women. This review highlights sex-specific differences in MV disease aetiology, diagnosis, as well as timing and type of intervention. RECENT FINDINGS: Females present with more complicated disease: anterior or bileaflet prolapse, leaflet dysplasia/thickening, mitral annular calcification, and mixed mitral lesions. The absence of indexed echocardiographic mitral regurgitation (MR) severity parameters contributes to delayed intervention in women, resulting in more severe symptom burden at time of surgery. The sequelae of chronic MR also necessitate concomitant procedures (e.g. tricuspid repair, arrhythmia surgery) at the time of mitral surgery. Complex MV pathology, greater patient acuity, and more complicated procedures collectively pose challenges to successful MV repair and postoperative recovery. As a consequence, women receive disproportionately more MV replacement than men. In-hospital mortality after MV repair is also greater in women than men. Long-term outcomes of MV repair are comparable after risk-adjustment for preoperative status; however, women experience a greater incidence of postoperative heart failure. SUMMARY: To address the inequity in MV repair outcomes between sexes, indexed diagnostic measurements, diligent surveillance of asymptomatic MR, increased recruitment of women in large clinical trials, and mandatory reporting of sex-based subgroup analyses are recommended.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".