Abstract 20149: Effect of Mitral Valve Area Following Surgical Repair for Degenerative Mitral Regurgitation on Exercise Hemodynamics and Functional Consequences
Bibliographic record
Abstract
Introduction: Mitral valve (MV) area is the key measure of mitral stenosis (MS) in rheumatic MV disease, but its role in the follow-up of patients who had MV repair for degenerative mitral regurgitation (MR) remains uncertain. Our objective is to evaluate the relationships of MV area with hemodynamic effects at rest and during exercise, and with functional measures in patients following MV repair for degenerative MR. Methods: We prospectively assessed 110 patients who had MV repair for degenerative MR and no more than mild residual MR. Patients with aortic valve disease and ventricular dysfunction were excluded. The patients underwent comprehensive echo assessment at rest and during supine bicycle exercise. Brain natriuretic peptide (BNP) levels and SF36 questionnaires were also performed. MV area was calculated using the continuity equation. The patients were divided into 2 groups for comparison (MV area < 1.5 cm 2 vs > 1.5 cm 2 ). Results: 22 patients (20%) had MV area < 1.5 cm 2 . The 2 groups were similar in age. Patients with MVR < 1.5 cm 2 had worse resting and exercise hemodynamics, more limited exercise capacity and higher BNP levels compared to those with larger MV area (Table). These patients also had lower scores in physical functioning, vitality (p=0.01) and social function (p=0.04), based on the SF36 questionnaires. Multivariate analysis showed that MV area is an independent predictor of exercise capacity (p=0.003). Conclusion: In patients following MV repair for degenerative MR, MV area is a useful measure of MS severity because it is associated with resting and exercise hemodynamics and functional consequences. MV area should be routinely measured in this clinical setting, and refinement in MV repair techniques is needed to optimize MV area in addition to eliminate MR.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 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".