Sex-specific differences in right heart remodelling and patient outcomes in secondary tricuspid regurgitation
Bibliographic record
Abstract
AIMS: Current guidelines lack sex-specific thresholds for assessing secondary tricuspid regurgitation (STR) severity and right ventricular (RV) and tricuspid annulus (TA) remodelling. We aimed to determine whether risk-based cut-offs for these parameters differ between men and women with STR. METHODS AND RESULTS: We included 554 patients (74 ± 13 years, 51% women) with moderate or severe STR. The primary endpoint was all-cause mortality or heart failure hospitalization. Women were older (P < 0.001) and had a higher prevalence of atrial fibrillation (P = 0.008) and atrial STR (P < 0.001), whereas men more frequently had coronary artery disease (P < 0.001), chronic kidney disease (P = 0.005), and mitral regurgitation (P < 0.001). Women exhibited smaller RV and TA dimensions and higher RV ejection fraction (RVEF) (P < 0.001). Over a median follow-up of 19 (8-27) months, 230 patients reached the composite endpoint. Event-free survival at 2 years was comparable between sexes (P = 0.183), even after inverse propensity weighting (P = 0.342). Sex-specific thresholds for STR severity were lower in women for effective regurgitant orifice area (EROA) (0.36 cm² vs. 0.43 cm²) and regurgitant volume (RegVol) (31 mL vs. 35 mL) but higher for regurgitant fraction (46% vs. 39%). Women also exhibited comparable risk at lower RV end-diastolic (81 mL/m² vs. 96 mL/m²) and end-systolic volumes (37 mL/m² vs. 49 mL/m²), higher RVEF (49% vs. 41%), and smaller TA diameter (19 mm/m² vs. 22 mm/m²). CONCLUSION: In STR, women face a similar risk at lower EROAs and RegVols, along with smaller RV volumes, higher RVEF, and reduced TA dimensions. These findings highlight the importance of incorporating sex-specific thresholds into clinical decision-making when assessing STR severity and right heart remodelling.
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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 | 0.000 |
| 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".