Residual Tricuspid Regurgitation After Tricuspid Transcatheter Edge-to-Edge Repair: Insights Into the EuroTR Registry
Bibliographic record
Abstract
Abstract Aims Data on the prognostic impact of residual tricuspid regurgitation (TR) after tricuspid transcatheter edge-to-edge repair (T-TEER) are scarce. The aim of this analysis was to evaluate 2-year survival and symptomatic outcomes of patients in relation to residual TR after T-TEER. Methods and results Using the large European Registry of Transcatheter Repair for Tricuspid Regurgitation (EuroTR registry) we investigated the impact of residual TR on 2-year all-cause mortality and New York Heart Association (NYHA) functional class at follow-up. The study further identified predictors for residual TR ≥3+ using a logistic regression model. The study included a total of 1286 T-TEER patients (mean age 78.0 ± 8.9 years, 53.6% female). TR was successfully reduced to ≤1+ in 42.4%, 2+ in 40.0% and 3+ in 14.9% of patients at discharge, while 2.8% remained with TR ≥4+ after the procedure. Residual TR ≥3+ was an independent multivariable predictor of 2-year all-cause mortality (hazard ratio 2.06, 95% confidence interval 1.30–3.26, p = 0.002). The prevalence of residual TR ≥3+ was four times higher in patients with higher baseline TR (vena contracta >11.1 mm) and more severe tricuspid valve tenting (tenting area >1.92 cm2). Of note, no survival difference was observed in patients with residual TR ≤1+ versus 2+ (76.2% vs. 73.1%, p = 0.461). The rate of NYHA functional class ≥III at follow-up was significantly higher in patients with residual TR ≥3+ (52.4% vs. 40.5%, p < 0.001). Of note, the degree of TR reduction significantly correlated with the extent of symptomatic improvement (p = 0.012). Conclusions T-TEER effectively reduced TR severity in the majority of patients. While residual TR ≥3+ was associated with worse outcomes, no differences were observed for residual TR 1+ versus 2+. Symptomatic improvement correlated with the degree of TR reduction.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".