Interdisciplinary Periprocedural Management of Patients Undergoing Transapical TMVI with the Tendyne System: A Narrative Review and Institutional Experience
Bibliographic record
Abstract
OBJECTIVES: Mitral regurgitation (MR) represents the most common valvular heart disease (VHD) in the Western world. While transcatheter mitral valve repair (M-TEER) is the leading interventional treatment for surgically high-risk patients, transcatheter mitral valve implantation (TMVI) is reserved for selected patients with unsuitable anatomy for M-TEER. This review aims to summarize our institutional experience with transapical TMVI using the Tendyne valve (Abbott Vascular, CA, USA), focusing on interdisciplinary preoperative, intraoperative, and postoperative management strategies. METHODS: We conducted a narrative review of current literature on TMVI with the Tendyne system and integrated it with a comprehensive analysis of our interdisciplinary clinical experience. Data were collected regarding patient selection, imaging protocols, procedural techniques, and postoperative care. RESULTS: Utilizing the Tendyne valve, TMVI addresses symptomatic moderate-to-severe or severe MR in patients unsuitable for conventional surgery or M-TEER. Successful outcomes require thorough patient selection, including assessment of mitral annular calcification, absence of intracardiac thrombus, low left ventricular outflow tract (LVOT) obstruction risk, and optimal annular sizing. Multimodal imaging, particularly transoesophageal echocardiography and cardiac computed tomography, is essential for procedural planning and execution. TMVI is performed under general anaesthesia with intraoperative transoesophageal guidance and haemodynamic monitoring to minimize complications such as LVOT obstruction, bleeding, and valve malposition. Postoperative management emphasizes haemodynamic stabilization, bleeding control, and surveillance for paravalvular leaks or device dysfunction. CONCLUSIONS: TMVI with the Tendyne valve provides a viable and effective treatment for selected patients with symptomatic relevant MR. Optimal outcomes are dependent on meticulous interdisciplinary collaboration, advanced imaging protocols, and comprehensive perioperative management.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".