Procedural Tools and Technics for Transcatheter Paravalvular Leak Closure: Lessons from a Decade of Experience
Bibliographic record
Abstract
Prosthetic paravalvular leaks (PVLs) are associated with congestive heart failure and hemolysis. Surgical PVL closure carries high risks. Transcatheter implantation of occluding devices in PVL is a lower risk but challenging procedure. Of the available devices, only two have been specifically approved in Europe for transcatheter PVL closure (tPVLc): the Occlutech® Paravalvular Leak Device (PLD) and Amplatzer™ ParaValvular Plug 3 (AVP 3). Here, we review the various tools and devices used for tPVLc, based on three observational registries including 748 tPVLc procedures performed in 2005–2021 at 33 centres in 11 countries. In this case, 12 registry investigators with over 20 tPVLc procedures each described their practical tips and tricks regarding imaging, approaches, delivery systems, and devices. They considered three-dimensional echocardiography to be the cornerstone of PVL assessment and procedure guidance. Anterograde trans-septal mitral valve and retrograde aortic approaches were used in most centres, although some investigators preferred the transapical approach. Hydrophilic-coated low-profile sheaths were used most often for device deployment. The AVP 3 and PLD devices were chosen for 89.0% of procedures. Further advances in design and materials are awaited. These complex procedures require considerable expertise, and experience accumulated over a decade has no doubt contributed to improve practices.
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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 | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".