Right Ventricular Longitudinal Strain Predicts Survival in Patients With Functional Tricuspid Regurgitation
Bibliographic record
Abstract
BACKGROUND: Functional tricuspid regurgitation (TR) is a frequent finding in echocardiography. Despite general consent that right ventricular (RV) dysfunction impacts outcome of patients with TR, it is still unknown which echocardiographic parameters most accurately reflect prognosis. In this study we aimed to evaluate the prevalence of RV dysfunction and its prognostic value in patients with TR. METHODS: Data from 1089 consecutive patients were analysed. Tricuspid annular plane systolic excursion (TAPSE), fractional area change, and right ventricular free wall longitudinal strain (RV strain) were used to define RV dysfunction. Patients were followed for 2-year all-cause mortality. For prediction of survival, reclassification and C statistics of RV functional parameters using TR grade as reference model were performed. RESULTS: Among the patients studied, 13.9% showed no TR, 61.2% had mild TR, 19.6% had moderate TR, and 5.3% had severe TR. The TR grade was associated with increased mortality (log rank, P < 0.001). Impaired RV strain and TAPSE were independent predictors for mortality (RV: hazard ratio [HR], 1.130; 95% confidence interval [CI], 1.099-1.160; P < 0.001; TAPSE: HR, 1.131; 95% CI, 1.085-1.175; P < 0.001). Both RV strain and TAPSE improved the reference model for survival prediction (RV: integrated discrimination improvement [IDI], 0.184; 95% CI, 0.146-0.221; P < 0.001; TAPSE: IDI, 0.057; 95% CI, 0.037-0.077; P < 0.001). CONCLUSIONS: Echocardiographic evaluation of RV function appears to useful for patients with TR. Assessment of RV strain provides additional value for prediction of 2-year mortality.
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 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 | 0.004 |
| 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 | 0.001 |
| 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".