Abstract 14760: Myocardial Scarring by Magnetic Resonance Predicts Sudden Cardiac Death in Pediatric Patients With Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Introduction: Cardiovascular magnetic resonance (CMR) with late gadolinium enhancement (LGE) has been shown to be an independent predictor of sudden cardiac death (SCD) in adults with hypertrophic cardiomyopathy (HCM). The clinical significance of LGE in pediatric HCM patients is unknown. Hypothesis: LGE improves the SCD risk prediction in children with HCM. Methods: We retrospectively analyzed the CMR images and reviewed the outcomes pediatric HCM patients. Results: Amongst the 720 patients from 30 centers, 73% were male, with a mean age of 14.2±4.8 years. During a mean follow up of 2.6±2.7 years (range 0-14.8 years), 34 experienced an episode of SCD or equivalent. LGE (Figure 1A) was present in 34%, with a mean burden of 14±21g, or 2.5±8.2g/m2 (6.2±7.7% of LV myocardium). The presence of ≥1 adult traditional risk factor (family history of SCD, syncope, LV thickness >30mm, non-sustained ventricular tachycardia on Holter) was associated with an increased risk of SCD (HR=4.6, p<0.0001). The HCM Risk-Kids score predicted SCD (p=0.002). The presence of LGE was strongly associated with an increased risk (HR=3.8, p=0.0003), even after adjusting for traditional risk factors (HR adj =3.2, p=0.003) or the HCM Risk-Kids score (HR adj =3.5, p=0.003). Furthermore, the burden of LGE was associated with increased risk (HR=2.1/10% LGE, p<0.0001). LGE burden remained independently associated with an increased risk for SCD after adjusting for traditional risk factors (HRadj=1.5/10% LGE, p=0.04) or HCM Risk-Kids (HRadj=1.9/10% LGE, p=0.0018, Figure 1B). The addition of LGE burden improved the predictive model using traditional risk markers (C statistic 0.67 vs 0.77, p=0.003) and HCM Risk-Kids (C statistic 0.68 vs 0.74, p=0.045). Conclusions: Quantitative LGE is an independent risk factor for SCD in pediatric patients with HCM and improves the performance of traditional risk markers and the HCM Risk-Kids Score for SCD risk stratification in this population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".