Assessment of the tricuspid valve using cardiovascular magnetic resonance
Bibliographic record
Abstract
PURPOSE OF REVIEW: The rapid search for suitable tricuspid transcatheter devices has ignited renewed enthusiasm in accurate characterization of tricuspid valve disease. Cardiovascular magnetic resonance (CMR), traditionally used as the gold standard in assessment for right ventricular size and function, has recently seen its use expanded to assess both the structure and function of the tricuspid apparatus. This review will highlight the role of CMR in tricuspid valve disease and compare it with other commonly used imaging modalities. RECENT FINDINGS: Dynamic anatomical assessment of the tricuspid apparatus, in combination with accurate leaflet identification, is possible with CMR. Tricuspid regurgitation volume and fraction are derived through an indirect volumetric method, and therefore, able to overcome many traditional hurdles involved with valve regurgitation quantitation. Adverse right heart prognostic factors in tricuspid valve disease, such as right heart volumes, function, and tissue characterization, are optimally assessed using CMR. SUMMARY: Cardiovascular magnetic resonance is a powerful modality that should be harnessed in order to obtain a multifaceted assessment of tricuspid valve structure, function, and the effects of valve disease on right heart remodeling.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| 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 | 0.001 |
| 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".