A tale of two ventricles: ventricular-ventricular interactions and LV dysfunction after surgical repair of Tetralogy of Fallot
Bibliographic record
Abstract
Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect with good long-term survival after surgical correction.1 Nonetheless, patients suffer from significant morbidity and mortality including exercise intolerance, arrhythmias, and sudden death, presenting an important healthcare burden.2 To date, most clinical and research emphasis in TOF has been placed on right ventricular (RV) pathology. Indeed, progressive RV dilatation and dysfunction are common and are well-established risk factors for adverse clinical outcomes.3,4 In contrast, relatively little attention has been paid to left ventricular (LV) dysfunction and to adverse ventricular–ventricular interactions in this population. However, recent studies show that LV dysfunction is not only common in adults after TOF repair, but is linked to adverse clinical outcomes.5–7 The mechanisms driving LV dysfunction in this population appear to be related, at least in part, to RV dysfunction.8 RV and LV ejection fraction (EF) are closely related after TOF repair, and myocardial deformation studies demonstrate impairment in multiple components of both RV and LV myocardial mechanics.9–13 Importantly, reduced LV deformation, which is related in part to RV enlargement,8 is an independent predictor of arrhythmia and death in adults after TOF repair.2 However, the precise nature of LV dysfunction after surgical repair of TOF and the underlying mechanisms driving adverse ventricular–ventricular interactions in this condition remain incompletely understood.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".