Clinical outcomes and predictors of transapical transcatheter mitral valve replacement: the Tendyne Expanded Clinical Study
Bibliographic record
Abstract
BACKGROUND: Transcatheter mitral valve replacement (TMVR) is a therapeutic option for patients with severe mitral regurgitation (MR) who are ineligible for conventional surgery. There are limited data on the outcomes of large patient cohorts treated with TMVR. AIMS: This study aimed to investigate the outcomes and predictors of mortality for patients treated with transapical TMVR. METHODS: This analysis represents the clinical experience of all patients enrolled in the Tendyne Expanded Clinical Study. Patients with symptomatic MR underwent transapical TMVR with the Tendyne system between November 2014 and June 2020. Outcomes and adverse events up to 2 years, as well as predictors of short-term mortality, were assessed. RESULTS: A total of 191 patients were treated (74.1±8.0 years, 62.8% male, Society of Thoracic Surgeons Predicted Risk of Mortality 7.7±6.6%). Technical success was achieved in 96.9% (185/191), and there were no intraprocedural deaths. At 30-day, 1- and 2-year follow-up, the rates of all-cause mortality were 7.9%, 30.8% and 40.5%, respectively. Complete MR elimination (MR <1+) was observed in 99.3%, 99.1% and 96.3% of patients, respectively. TMVR treatment resulted in consistent improvement of New York Heart Association Functional Class and quality of life up to 2 years (both p<0.001). Independent predictors of early mortality were age (odds ratio [OR] 1.11; p=0.003), pulmonary hypertension (OR 3.83; p=0.007), and institutional experience (OR 0.40; p=0.047). CONCLUSIONS: This study investigated clinical outcomes in the full cohort of patients included in the Tendyne Expanded Clinical Study. The Tendyne TMVR system successfully eliminated MR with no intraprocedural deaths, resulting in an improvement in symptoms and quality of life. Continued refinement of clinical and echocardiographic risks will be important to optimise longitudinal outcomes.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".