Interventional Treatment of Severe Tricuspid Regurgitation
Bibliographic record
Abstract
BACKGROUND: Transcatheter caval valve implantation is under evaluation as a treatment option for inoperable patients with severe tricuspid regurgitation (TR). The procedure involves the catheter-based implantation of bioprosthetic valves in the inferior vena cava and superior vena cava to treat symptoms associated with TR. This study is the first to evaluate the feasibility, safety, and efficacy of this interventional concept. METHODS AND RESULTS: Twenty-five patients (mean age, 73.9±7.6 years; women, 52.0%) with severe symptomatic TR despite optimal medical treatment deemed unsuitable for surgery were treated with caval valve implantation under a compassionate clinical use program. Technical feasibility defined as procedural success, hemodynamic effect defined as venous pressure reduction, and safety defined as periprocedural adverse events were evaluated, with clinical follow-up at discharge and up to 12 months. The functional impact was evaluated by assessment of New York Heart Association class at the time of hospital discharge. The total number of valves implanted in the caval position was 31. Patients were treated with single (inferior vena cava-only; n=19; 76.0%) or bicaval valve implantation (inferior vena cava+superior vena cava; n=6; 24.0%). Either balloon-expandable valves (Sapien XT/3: n=18; 72.0%) or self-expandable valves (TricValve: n=6; 24.0%; Directflow: n=1; 4.0%) were used. Procedural success was achieved in 96% (n=24). Early and late valve migration requiring surgical intervention occurred in 1 patient each. Thirty-day and in-hospital mortality were 8% (2 of 25) and 16% (4 of 25). Causes of in-hospital mortality included respiratory (n=1) or multiple organ failure (n=3) and were not linked to the procedure. Mean overall survival in the study cohort was 316±453 days (14-1540 days). CONCLUSIONS: Caval valve implantation for the treatment of severe TR and advanced right ventricular failure is associated with a high procedural success rate and seems safe and feasible in an excessive-risk cohort. The study demonstrates hemodynamic efficacy with consistent elimination of TR-associated venous backflow and initial clinical improvement. These results encourage further trials to determine which patients benefit most from this interventional approach.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".