Long-Term Outcomes After Transcatheter Tricuspid Valve-in-Valve Replacement
Bibliographic record
Abstract
OBJECTIVES: Transcatheter tricuspid valve-in-valve (ViV) replacement has emerged as a less invasive alternative to redo surgery in patients with failing bioprosthetic tricuspid valves. While short- and mid-term outcomes have been reported, data on long-term follow-up remain limited. METHODS: The authors conducted a single-center observational study including 12 consecutive patients who underwent transcatheter tricuspid ViV replacement. Clinical, echocardiographic, and procedural data were prospectively collected. Patients were followed at 1 and 12 months, and yearly thereafter; follow-up included annual clinical visits and echocardiography. RESULTS: The mean age of the patients was 45 years (range, 23-69 years); 92% were women, and the indication for ViV was prosthetic valve regurgitation in most (58%) cases. A balloon-expandable SAPIEN valve (Edwards Lifesciences) was implanted in all cases, with 100% procedural success. After a mean follow-up of 6 years (range, 1-11 years), 3 (25%) patients died, and 1 was readmitted because of heart failure. Functional status improved significantly, with all surviving patients in New York Heart Association class I or II at last follow-up. Transvalvular gradients remained stable over time in 83% of the patients. Two (17%) patients developed bioprosthetic valve dysfunction during follow-up: one due to significant tricuspid stenosis and the other due to severe tricuspid regurgitation. CONCLUSIONS: Tricuspid ViV replacement offers durable symptomatic improvement and stable prosthesis function during long-term follow-up in most cases. This study is the first to report outcomes greater than or equal to 5 years in this population and supports the continued use of ViV as a viable option for these patients. Larger studies are warranted to validate these findings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".