Severe Myoclonic Epilepsy of Infancy: Extended Spectrum of GEFS<sup>+</sup>?
Bibliographic record
Abstract
PURPOSE: Severe myoclonic epilepsy of infancy (SMEI) is an intractable epilepsy of early childhood of unknown etiology. It is often associated with a family history of seizure disorders, but epilepsy phenotypes have not been well described. We sought to characterize the seizure phenotypes of relatives to better understand to the genetic basis of SMEI. METHODS: Probands with SMEI were identified, and systematic family studies were performed. Epilepsy syndromes were characterized in affected family members. RESULTS: Twelve probands with SMEI were identified. Eleven of the 12 probands with SMEI had a family history of seizures, and the twelfth was the result of a consanguineous marriage. We found that 16.7% of full siblings and 8.3% of parents had definite seizures. A total of 39 affected family members was identified. The most common phenotype was febrile seizures in 14, febrile seizures plus in seven, partial epilepsy in two, and there were single individuals with SMEI, myoclonic-astatic epilepsy, Lennox-Gastaut syndrome, and 13 cases with unclassified or unconfirmed seizures. CONCLUSIONS: The family history of seizures in SMEI is in keeping with the spectrum of seizure phenotypes seen in generalized epilepsy with febrile seizures plus (GEFS+). Our findings suggest that SMEI is the most severe phenotype in the GEFS+ spectrum.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".