Impact of Prosthesis‐Patient Mismatch on Left Ventricular Myocardial Mechanics After Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to compare left ventricular (LV) remodeling using myocardial strain between patients with severe aortic stenosis (AS) treated with transcatheter aortic valve replacement (TAVR) with and without prosthesis-patient mismatch (PPM). METHODS AND RESULTS: In a retrospective study, speckle-tracking echocardiography was used to measure global longitudinal strain (GLS) and strain rate (GLSR), circumferential strain, and rotation before and at mid-term follow-up post-TAVR. Moderate and severe PPM were defined as an effective orifice area ≤0.85 and <0.65 cm(2)/m(2), respectively. A total of 102 patients (median age, 83 years [77-88]) with severe AS were included. At 6±3 months post-TAVR, moderate and severe PPM were found in 32 (31%) and 9 (9%) patients. Patients without PPM had a significant regression in LV mass (from 134±41 to 119±38 g/m(2); P=0.001) at follow-up whereas those with PPM did not. There was a significant improvement in LV GLS (-12.8±4.0 to -14.3±4.3%; P=0.01), GLSR (-0.61±0.20 to -0.73±0.25 second(-1); P<0.001), and early diastolic strain rate (0.52±0.20 to 0.64±0.20 second(-1); P<0.001) in patients without PPM, but not in those with PPM. After adjustment for pre-TAVR ejection fraction and post-TAVR aortic regurgitation, patients without PPM had greater improvement in LV longitudinal strain parameters compared to those with PPM. After a median follow-up of 46.1 months (interquartile range, 35.4-60.8), there was no difference in survival between patients with and without PPM. CONCLUSIONS: TAVR was associated with an incidence of PPM of 40%. Greater reverse LV remodeling using myocardial strain was evident in patients without PPM compared to PPM. Presence of PPM was not associated with mortality.
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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) | 0.001 | 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".