Beyond the left ventricle: modern echocardiographic assessment of right ventricular function in tricuspid regurgitation
Bibliographic record
Abstract
BACKGROUND: The right ventricle (RV) and tricuspid valve (TV) have historically been neglected in cardiovascular research and clinical practice. However, growing evidence has established RV dysfunction and tricuspid regurgitation (TR) as independent predictors of mortality and morbidity across a range of cardiac pathologies. The emergence of transcatheter tricuspid valve interventions (TTVI) has further emphasized the need for accurate and reproducible assessment of RV function in the presence of TR. OBJECTIVE: To provide a comprehensive review of current echocardiographic approaches of RV assessment in the context of TR. This review highlights their strengths, limitations, and clinical relevance. We focus particularly on advanced imaging modalities and their role in patient selection and outcome prediction following TTVI. METHODS: We review contemporary literature on RV anatomy and pathophysiology and critically evaluate echocardiographic modalities, including two-dimensional (2D) indices, three-dimensional (3D) volumetry, strain imaging, and noninvasive RV-pulmonary artery (PA) coupling surrogates, for their role in diagnosing RV dysfunction, guiding risk stratification, and predicting clinical outcomes in patients considered for TTVI. RESULTS: Conventional echocardiographic measures of RV function such as tricuspid annular plane systolic excursion (TAPSE) and fractional area change (FAC) are limited by geometric assumptions, regional motion bias, and load dependence. Emerging echocardiographic techniques, including 3D imaging, free wall longitudinal strain (FWLS), effective RV ejection fraction (eRVEF), and RV-PA coupling indices, demonstrate improved accuracy and prognostic utility. In patients with TR, progressive RV remodeling, altered contraction patterns, and altered ventricular interdependence contribute to clinical decompensation. While TTVI provides hemodynamic and symptomatic benefit, it can also reveal latent RV dysfunction, underscoring the importance of thorough pre- and postprocedural evaluation. CONCLUSION: Accurate assessment of RV structure and function is critical for optimal management of TR, particularly in candidates for TTVI. A multiparametric echocardiographic strategy that integrates advanced imaging techniques with functional indices provides a more complete characterization of RV performance, supports procedural planning, and improves risk stratification. Future research should aim to establish TR-specific thresholds, validate emerging functional markers, and develop standardized, evidence-based algorithms to guide clinical decision-making.
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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 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| 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".