P.050 Epilepsy phenotypes in patients with Sotos syndrome
Bibliographic record
Abstract
Background: Sotos syndrome is a genetic condition caused by NSD1 alterations, characterized by overgrowth, macrocephaly, dysmorphic features, and learning disability. Approximately half of children with Sotos syndrome develop seizures. We investigated the spectrum of seizure phenotypes in these patients. Methods: Patients were recruited from clinics and referral from support groups. Those withclinical or genetic diagnosis of Sotos syndrome and seizures were included. Phenotyping data was collected via structured clinical interview and medical chart review. Results: 25 patients with typical Sotos syndrome features were included. Of 14 tested patients, 64% (n=9) had NSD1 alterations. Most had developmental impairment (80%, n=20) and neuropsychiatric comorbidities (68%, n=17). Seizure onset was variable (2 months to 12 years). Febrile and absence seizures were the most frequent types (64%, n=16). Afebrile generalized tonicclonic (40%, n=10) and atonic (24%, n=6) seizures followed. Most patients (60%, n=15) had multiple seizure types. The majority (72%, n=18) was controlled on a single antiepileptic, or none; 4% (n=1) remained refractory to antiepileptics. Conclusions: The seizure phenotype in Sotos syndrome most commonly involves febrile convulsions or absence seizures. Afebrile tonic-clonic or atonic seizures may also occur. Seizures are typically well-controlled with antiepileptics. The rate of developmental impairment and neuropsychiatric comorbidities is high.
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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) | 0.007 | 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".