Undiagnosed Heart Disease Leading to Sudden Unexpected Death in Childhood: A Retrospective Study
Bibliographic record
Abstract
OBJECTIVES: Heart disease accounts for a significant proportion of sudden unexpected deaths among children. We describe here demographic features, pathological conditions, and the frequency of premonitory symptoms in a retrospective series of cases of sudden unexpected cardiac death (SUCD) attributable to undiagnosed structural heart disease. METHODS: A chart review of autopsies involving children 0 to 17 years of age that were performed at the Hospital for Sick Children (Toronto, Ontario, Canada) between 1984 and 2003 was conducted. Cases of sudden unexpected death within 24 hours after clinical presentation with previously undetected fatal heart disease were included. Cases with multiple or thoracic trauma and chronic or multisystem disease were excluded. RESULTS: During the 20-year study period, 4926 autopsies were performed. A total of 103 cases (2.1%), involving 51 male patients and 52 female patients 1 day to 15 years of age (mean: 2.9 ± 4.2 years), were diagnosed as having SUCD. The most common diagnoses were myocarditis (n = 37 [35.9%]), hypoplastic left heart syndrome (HLHS) (n = 19 [18.4%]), dilated cardiomyopathy (DCM) (n = 16 [16.5%]), coronary artery anomalies (n = 6 [5.8%]), and aortic stenosis (n = 5 [4.9%]). There was a significant difference in the mean age of presentation between leading causes of SUCD (6.5 days for HLHS, 1.7 years for DCM, and 5.4 years for myocarditis; P < .0001). Of 103 cases, 27 (26.2%) had premonitory symptoms documented. CONCLUSION: SUCD accounted for 2.1% of all autopsies, and HLHS, DCM, and myocarditis were the 3 most common diagnoses, which presented at increasing ages.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".