Abstract 10566: Echocardiographic Predictors of Successful Transcatheter Mitral Valve Repair with the Mitraclip System
Bibliographic record
Abstract
Introduction: Residual mitral regurgitation (rMR) and elevated transmitral gradients (TMG) are associated with worse outcomes after percutaneous mitral repair. This study aims to assess if pre-intervention MR jet width and its relation to the mitral commissural length (MCL) are able to predict post-procedure rMR and TMG. Methods: Preprocedural echocardiographic images were retrospectively reviewed in 74 patients who underwent an edge-to-edge repair (2014-2018). Maximal MR jet width and MCL were measured from a bi-commissural view. Complete follow-up echocardiographic examination was performed at 1-3 months. Left ventricle (LV) and left atrial (LA) severe dilation were defined as LV end-diastolic diameter ≥6.5 cm and LA indexed volume ≥48 ml/m 2 . Presence of rMR ≥moderate, combination of rMR and TMG >5 mmHg (rMR+TMG), and all-cause mortality within 1-year follow-up were examined. Results: Of 74 patients, 25 (34%) had rMR [17/25 moderate and 8/25 severe)] and 39 (53%) had either rMR or elevated TMG. Both MR jet width and its ratio with MCL were good predictors for the implantation of >2 clips (p<0.01 for both). Patients with rMR had a significantly larger pre-procedural jet width versus those without MR (1.63±0.54 cm vs 1.29±0.53 cm; p=0.01); without significant difference for the ratio of jet width/MCL (p=0.07). However, this ratio was higher in patients having rMR+TMG (41.05±13.15 % vs 34.26±12.64 %; p=0.03). In univariate analysis, MR jet width was a good predictor of rMR (OR: 3.35, 95%CI: 1.09-10.48; p=0.03) and severe post-intervention LV (OR: 6.43, 95%CI: 1.35-45.01; p=0.03) and LA dilation (OR: 3.02, 95%CI: 1.16-8.69; p=0.03); whereas the ratio was a good predictor of rMR+TMG (OR: 1.69, 95%CI: 1.12-2.70; p=0.02). Patients with rMR and rMR+TMG tended to be at higher risk of mortality at one year, without reaching statistical significance in this small population (24% vs 14%, p=0.17 and 23% vs 11%, p=0.14 respectively). Conclusion: MR jet width and its ratio with MCL are respectively associated to rMR or combined rMR+TMG after percutaneous mitral repair. MR jet width was also useful to identify patients who remained with severe LV and LA dilatation post-intervention.
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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 | 0.001 |
| 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) | 0.004 | 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".