Cardiac magnetic resonance markers of progressive RV dilation and dysfunction after tetralogy of Fallot repair
Bibliographic record
Abstract
OBJECTIVE: Patients with repaired tetralogy of Fallot (TOF) are followed serially by cardiac magnetic resonance (CMR) for surveillance of RV dilation and dysfunction. We sought to define the prevalence of progressive RV disease and the optimal time interval between CMR evaluations. METHODS: Candidates were selected from a multicentre TOF registry and were included if ≥2 CMR studies performed ≥6 months apart were available without interval cardiovascular interventions. Patients with 'disease progression' (defined as increase in RV end-diastolic volume index (RVEDVi) ≥30 mL/m(2), decrease in RVEF ≥10% or decrease in LVEF ≥10%) were compared with those with 'disease non-progression' (defined as RVEDVi increase ≤5 mL/m(2), RVEF decrease ≤3% and LVEF decrease ≤3%). RESULTS: A total of 849 CMR studies in 339 patients (median age at first CMR 23.6 years) were analysed. Over a median interval of 2.2 years between CMR pairs, RVEDVi increased 4±18 mL/m(2) (p<0.001), RV end-systolic volume index increased 3±13 mL/m(2) (p<0.001), RVEF decreased 1%±6% (p=0.02) and LVEF decreased 1%±6% (p=0.001). Disease progression was observed in 15% (n=76) and non-progression in 26% (n=133). There were no significant differences between those with and without progression in baseline demographic, anatomic, ECG, exercise or baseline CMR characteristics. The optimal time interval between CMR studies for detection of progression was a 3-year interval (63% sensitivity, 65% specificity, area under the receiver operating characteristic curve 0.65). CONCLUSIONS: Although progressive RV dilation and decline in biventricular systolic function occur at a slow pace in the majority of adults with repaired TOF, 15% of patients experience rapid disease progression. The results of this study support the practice of serial CMR examinations to identify progressive disease at a time interval of up to 3 years.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".