Characteristics and Outcomes of Patients with Atrial Versus Ventricular Secondary Tricuspid Regurgitation Undergoing Tricuspid Transcatheter Edge-to-Edge Repair – Results from the TriValve Registry
Bibliographic record
Abstract
AIM: Functional or secondary tricuspid regurgitation (STR) is the most common phenotype of tricuspid regurgitation (TR) with atrial STR (ASTR) and ventricular STR (VSTR) being recently identified as two distinct entities. Data on tricuspid transcatheter edge-to-edge repair (T-TEER) in patients with STR according to phenotype (i.e. ASTR vs. VSTR) are lacking. The aim of this study was to assess characteristics and outcomes of patients with ASTR versus VSTR undergoing T-TEER. METHODS AND RESULTS: Patients with STR undergoing T-TEER were selected from the Transcatheter Tricuspid Valve Therapies (TriValve) registry. ASTR was defined by (i) left ventricular ejection fraction ≥50%, (ii) atrial fibrillation, and (iii) systolic pulmonary artery pressure <50 mmHg. Patients not matching these criteria were classified as VSTR. Patients with primary TR and cardiac implantable electronic device were excluded. Key endpoints included procedural success and survival at follow-up. A total of 298 patients were enrolled in the study: 65 (22%) with ASTR and 233 (78%) with VSTR. Procedural success was similar in the two groups (80% vs. 83% for ASTR vs. VSTR, p = 0.56) and TEER was effective in reducing TR in both groups (from 97% of patients with baseline TR ≥3+ to 23% in ASTR and to 15% in VSTR, all p = 0.001). At 12-month follow-up, survival was significantly higher in the ASTR versus VSTR cohort (91% vs. 72%, log-rank p = 0.02), with VSTR being an independent predictor of mortality at multivariable analysis (hazard ratio 4.75). CONCLUSIONS: In a real-world, multicentre registry, T-TEER was effective in reducing TR grade in both ASTR and VSTR. At 12-month follow-up, ASTR showed better survival than VSTR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".