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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".