Impact of sex on outcomes after percutaneous repair of functional mitral valve regurgitation
Bibliographic record
Abstract
Background The role of percutaneous repair of functional mitral regurgitation (MR) is evolving. Left ventricle remodeling is known to be different between men and women; however, outcomes following percutaneous repair of functional MR have not considered the impact of sex. Methods Between 2012 and 2018, 175 patients underwent percutaneous repair of functional MR with the Mitra Clip NT/NTR (Abbott, Irvine CA) at our institution. Patients were assessed in a dedicated clinic with a follow-up that averaged 0.7±1.2 years and extended to 5.7 years. Results Men had a larger body surface area than women (p<0.001), whereas women were more likely than men to have diabetes preoperatively (p=0.02). There were no deaths or instances of single leaflet detachment. Immediate post-procedure MR was <2+ in 158 (90%) with a mean trans-mitral valve repair gradient of 3.4±1.0 and 3.5±2.1 mm Hg, respectively for women and men (p=0.8). One- and 2-year freedom from MR >3+ was 86.0±3.5% and 77.6±5.1%, respectively. After adjusting for differences between male and female patients, women were more likely to have recurrent MR >3+ (hazard ratio 4.7, 95% confidence interval 1.2-18.4, p=0.03). Upon adjusted analysis, there was also no association between gender and survival (p=0.2). One- and 2- year survival was 69.8±4.3% and 54.3±5.5%, respectively. Conclusion Women are more likely to have recurrent severe MR after percutaneous repair of functional MR. The mechanism for this remains undetermined.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".