Imaging in repaired tetralogy of Fallot with a focus on recent advances in echocardiography
Bibliographic record
Abstract
PURPOSE OF REVIEW: Imaging is essential for the management of adults with repaired tetralogy of Fallot (rToF). Echocardiography and cardiac magnetic resonance imaging are the central modalities to assess rToF. Here we review recent literature on imaging rToF, focusing on echocardiography and advances in assessment of cardiac mechanics. RECENT FINDINGS: Several two-dimensional, three-dimensional, and Doppler echo parameters have been proposed to assess pulmonary regurgitation, right ventricular volumes and ejection fraction, but most of them still have important limitations in their feasibility and reliability compared to cardiac magnetic resonance (CMR). Myocardial deformation imaging to study ventricular and atrial mechanics, regional function, ventricular-ventricular interactions, and electro-mechanical dyssynchrony has yielded insights into the pathophysiologic mechanisms of right ventricular and left ventricular dysfunction; thereby predicting clinical outcomes and exercise capacity, allowing among others, evaluation of the impact of pulmonary valve replacement (PVR). Emerging technologies are expected to further our understanding of the drivers of dysfunction and guide indications and timing of PVR. SUMMARY: Echocardiography and CMR have complementary and overlapping roles in rToF and contribute to our understanding of its pathophysiology and management.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".