Abstract 10353: Independent Validation of the Ecg Risk Score for Sudden Death Risk Stratification in Pediatric Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Background: Hypertrophic cardiomyopathy (HCM) is the leading cause of sudden cardiac death (SCD) in children and young adults. An ECG risk score tested in a Swedish cohort of 155 children with HCM had 97% sensitivity, 80% specificity, 45% positive predictive value (PPV), and 99% negative predictive value (NPV) for SCD risk prediction. Our goal was to validate the ECG risk score in an independent HCM cohort. Methods: Phenotype-positive pediatric HCM patients seen at a single center between 1987-2019 with at least 5 years follow-up from diagnosis, or a SCD event within 5 years of diagnosis, were retrospectively identified. First-evaluation ECGs were analyzed by a single operator blinded to patient outcomes. ECG risk score was calculated using QRS electrical axis, amplitude, duration, ST/T-wave abnormalities and QTc duration. The primary outcome was a composite of SCD, aborted sudden cardiac arrest, and appropriate shock from a prophylactic ICD. Results: Of 144 eligible patients with a median follow-up 14.6 yrs, 22 experienced SCD events within five years from diagnosis at a median age 12.1 yrs. The ECG risk score in patients experiencing a SCD event was 2-fold higher i.e. 8 (IQR 7-10) compared to the remaining cohort i.e. 4 (IQR 2-8) (p<0.001). An ECG risk score >5 had a sensitivity of 95% (CI 77%-100%), specificity 56% (46%-65%), PPV 28% (24%-33%), NPV 99% (91%-100%), and a receiver operating characteristic area under the curve of 0.76 for its ability to discriminate between patients with and without SCD events ( Figure 1 ). Compared to the discovery cohort, the score had strong sensitivity and NPV, but lower specificity and PPV. Conclusions: The ECG risk score for SCD risk stratification performed well in an independent Canadian validation cohort but overestimated SCD risk. Futher analysis will determine if inclusion of the ECG risk score can enhance the performance of currently available SCD risk prediction models for pediatric HCM.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".