Pearls & Oy-sters: Genetic Epilepsy
Bibliographic record
Abstract
Genetic epilepsies, such as KCNQ2 gene variants, although uncommon, are potential causes of neonatal seizures in infants with complex congenital heart disease (CHD). KCNQ2-related seizures commonly present as tonic posturing with autonomic changes and a distinctive amplitude-integrated EEG (aEEG) pattern with increase in amplitude, immediately followed by background suppression. Seizures are typically refractory to commonly used antiepileptics in this age group and respond best to sodium channel blockers such as carbamazepine and fosphenytoin. We report the cases of 2 neonates with complex CHD who presented with seizures secondary to KCNQ2 gene variation and discuss how early recognition of clinical and EEG features led to early treatment and improved seizure burden. When investigating the etiology of neonatal seizures in the perioperative complex cardiac infant, genetic etiologies such as KCNQ2 variants should be considered, particularly in the absence of clinical examination and neuroimaging features consistent with brain injury. These 2 cases highlight the importance of a precision medicine approach using clinical examination and seizure semiology, bedside aEEG monitoring, genetic testing, and targeted treatments to improve patient care and outcomes.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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".