P1591Novel transcatheter repair system for the treatment of severe tricuspid regurgitation
Bibliographic record
Abstract
Background: Transcatheter edge-to-edge repair of severe tricuspid regurgitation (TR) has been shown to be a feasible and safe treatment option for selected patients at prohibitive operative risk. Large tricuspid leaflet coaptation gaps and severe leaflet tethering represent challenging anatomic conditions that may limit the efficacy of transcatheter repair techniques. The purpose of this first-in-man experience was to investigate the procedural feasibility of the novel PASCAL transcatheter repair system (Edwards Lifesciences, Irvine, CA, USA) which incorporates a spacer and enables independent leaflet grasping to overcome some of the mentioned anatomic challenges. Methods and results: Nine patients with severe symptomatic TR were treated with the PASCAL system in a compassionate use program at 3 sites. All patients suffered from severe right sided heart failure (NYHA III-IV) due to severe TR and were deemed inoperable by the institutional heart teams. The procedures were performed via the right femoral vein under general anesthesia using transesophageal echocardiographic guidance. Procedural success was defined as reduction of at least one TR grade. If simultaneous grasping of two tricuspid leaflets was not achievable due to a large coaptation gap and/or severe leaflet tethering, the system allowed for independent leaflet grasping – usually the anterior or posterior tricuspid leaflet first, followed by grasping of the septal leaflet.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".