Transjugular Transcatheter Tricuspid Valve Replacement in Patients With Cardiac Implantable Electronic Devices
Bibliographic record
Abstract
BACKGROUND: Cardiac implantable electronic device (CIED)-related tricuspid regurgitation (TR) is common. Transcatheter tricuspid valve replacement (TTVR) is feasible with CIEDs in the right ventricle; however, data in this population are limited. OBJECTIVES: This study retrospectively analyzed patients undergoing compassionate-use transjugular TTVR with the LuX-Valve Plus for symptomatic TR with CIEDs from January 2022 to August 2024 at 17 international centers. METHODS: The primary endpoint was procedural TR reduction. Secondary endpoints included TR reduction, survival at 30 days, NYHA functional class changes, and CIED function at follow-up. Non-CIED group was used for comparison. RESULTS: Of 99 patients, 36 (36.4%) had CIEDs. Baseline characteristics were similar, though the CIED group had a higher EuroSCORE (European System for Cardiac Operative Risk Evaluation) II score and more comorbidities. Procedural success (CIED vs non-CIED: 91.7% vs 95.2%; P = 0.781), 30-day mortality (5.6% vs 4.8%; P > 0.999), TR reduction (≤1+: 83.8% vs 84.9%; P > 0.999), and NYHA functional class I/II (80.8% vs 83.7%; P = 0.89) were comparable. The CIED cohort exhibited a higher numerical incidence of conversion to surgery (8.3% vs 1.6%) and tricuspid reintervention (11.5% vs 3.3%) within 6 months; however, these differences did not reach statistical significance (P = 0.267 and P = 0.160, respectively). Of the 22 patients with postoperative interrogation (median of 3.3 months), 9.1% of CIED patients exhibited worsening device parameters, with no need for lead replacement or extraction. CONCLUSIONS: Transjugular TTVR is safe and effective for managing TR and heart failure in patients with CIEDs. Due to the small sample size, these findings highlight the need for larger, prospective studies to validate these outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".