Malnutrition and Outcomes in Patients with Tricuspid Regurgitation Undergoing Transcatheter Tricuspid Valve Repair
Bibliographic record
Abstract
AIMS: The impact of malnutrition in patients with tricuspid regurgitation (TR) undergoing tricuspid transcatheter edge-to-edge repair (T-TEER) is not well established. We evaluated the impact of malnutrition among patients with symptomatic TR undergoing T-TEER. METHODS AND RESULTS: Baseline nutritional status was evaluated using the geriatric nutritional risk index (GNRI), based on serum albumin concentrations and body weight to ideal body weight ratio, among patients with symptomatic TR undergoing T-TEER, enrolled in the multicentre EuroTR registry between March 2016 and February 2024. Malnutrition was defined as GNRI ≤98. The primary outcome of interest was all-cause mortality. A total of 1034 patients were included (mean age 78.4 ± 7.3 years, 47.7% male). Among them, GNRI ≤98 (i.e. malnutrition) was observed in 211 patients (20.4%). Estimated rates of all-cause death at 2 years were 45.9% and 28.2% in patients with and without malnutrition, respectively (log-rank p < 0.001). After multivariable adjustment, malnutrition was independently associated with an increased risk of mortality (adjusted hazard ratio 1.53, 95% confidence interval 1.11-2.10, p = 0.009), also confirmed at inverse probability of treatment weighting-adjusted analysis. As compared to post-procedural residual TR ≥3+, residual TR ≤2+ was associated with a similar lower risk of mortality in patients with and without malnutrition (interaction p = 0.947). CONCLUSION: In the large, real-world, multicentre EuroTR registry, malnutrition was present in one out of five patients with symptomatic TR undergoing T-TEER and was independently associated with increased mortality. The prognostic benefit of successful T-TEER in reducing mortality was consistently observed in patients with and without malnutrition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".