TMVR after TA-TAVR: a re-redo surgery—case report
Bibliographic record
Abstract
Introduction: Transcatheter mitral valve replacement (TMVR) is a valuable treatment option in patients with severe mitral regurgitation. Prior transapical transcatheter aortic valve replacement (TA-TAVR) may complicate the procedure and is therefore considered a relative contraindication. In this case report, the authors describe the successful TMVR as a tertiary cardiac surgery and transapical redo procedure. Case Summary: An 83-year-old male patient, suffering from dyspnoea and angina, was diagnosed with severe mitral valve regurgitation (MR). He had already undergone cardiac surgery in the form of coronary artery bypass grafting at the age of 64 and TA-TAVR at 79 years. After a failed attempt at mitral valve transcatheter edge-to-edge repair, he opted for TMVR. Pre-TMVR computed tomography simulation was used to analyse possible interactions between the prostheses and to predict the neo-left ventricular outflow tract (neo-LVOT). The operation was carried out without complications. There was no bleeding and the LV function remained unchanged. On MRI, the valves were perfectly aligned without any signs of paravalvular leakage or LVOT obstruction. The patient was discharged seven days postoperatively. At the one-year follow up, there was no need for rehospitalisation and the patient had clinically improved (from NYHA IV to II). Echocardiography demonstrated a mean transvalvular gradient of under 5 mmHg and no residual MR. Conclusion: A redo transapical access for TMVR as a tertiary cardiac operation can be easily performed. Pre-operative CT suggested good alignment of the aortic and mitral valved stent which was confirmed postoperatively.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".