Abstract 18515: Forward Flow Ejection Fraction as a Major Determinant of Outcome in Organic Mitral Regurgitation
Bibliographic record
Abstract
Introduction: The optimal timing of mitral valve (MV) surgery in patients with organic mitral regurgitation (OMR) is controversial. The objective of this study was to determine independent predictors of cardiac events in patients with OMR and no triggers for mitral valve surgery. Hypothesis: We hypothesized that forward LV ejection fraction (LVEF) calculated by the Dumesnil’s method (i.e. stroke volume measured in LV outflow tract divided by left ventricular end diastolic volume) is superior to the LVEF measured by the biplane Simpson’s method. Methods: Two hundred seventy eight patients with OMR (i.e. severity grade ≥1/4) and Doppler echocardiography exam at least 6 months before MV surgery or death were included. Clinical and echocardiographic data of 278 patients with OMR were analyzed retrospectively. The study end-point was the composite of death or need for mitral valve surgery. Results: During a mean follow-up of 5.4 ± 3.2 years, there were 147 (53%) events: 96 (35%) mitral surgeries and 66 (24%) deaths. There was no difference in the Simpson LVEF (65 ± 6% vs 65 ± 4%; p=0.86) and global longitudinal strain (-21.18 ± 3.26 % vs -21.26 ± 2.44 %; p=0.86) between patients who had an event versus those who were event-free during follow-up. However, LVEF calculated by Dumesnil’s method at baseline was lower in the event-group (47 ± 15%vs 59 ± 15%; p<0.0001) compared to the non-event group. After adjustment for age, sex, Charlson’s probability, coronary artery disease, ACE inhibitors, β-blockers, diuretics, AF and MR grade, forward LVEF by Dumesnil’s method remained an independent predictor of the occurrence of cardiac events (adjusted hazard ratio: 1.09, 95% interval confidence: 1.02-1.17; p=0.01). Conclusion: This study shows that the forward LVEF calculated by the Dumesnil’s method is superior to the standard LVEF or to longitudinal strain to predict outcomes in OMR. These results could help to improve risk stratification of patients with OMR and thereby individualized the treatment’s strategy. Further prospective studies are needed to confirm these findings.
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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 | 0.002 |
| 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) | 0.003 | 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".