Transcatheter tricuspid valve intervention: to repair or to replace?
Bibliographic record
Abstract
PURPOSE OF REVIEW: The burden of tricuspid regurgitation (TR) is high in the aging population, almost 4% in the age group over 75 have moderate or more TR. This carries a poor prognosis and an increased incidence of mortality, prolonged hospitalization, and rehospitalization in symptomatic patients with severe TR is observed. Percutaneous tricuspid valve intervention has emerged as a viable therapeutic option, with an increasingly large toolbox of both tricuspid repair and replacement devices. The optimal strategy, timing and patient selection for transcatheter intervention are yet to be determined. This review focuses on the current strengths and limitations of transcatheter tricuspid repair vs. replacement, drawing on lessons learned from surgery. RECENT FINDINGS: Early outcome studies have been published in the last 2 years for many of the new percutaneous tricuspid valve devices. We have summarized these results and compared them to surgical tricuspid valve repair and replacement. We found that surgical data shows a tendency to better outcome with tricuspid valve repair compared to replacement. For transcatheter interventions studies comparing repair and replacement are lacking but both interventions show good procedural success rates and are efficient in reducing the grade of tricuspid regurgitation. SUMMARY: Transcatheter tricuspid valve interventions offer a safe and effective alternative to tricuspid surgery or medical therapy. The decision between valve replacement and repair should be based on patient anatomy, operator experience and device availability until head-to-head comparison of different devices are available.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.005 | 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".