Bibliographic record
Abstract
Objective: The Scottish Genetic and Autoimmune Childhood Epilepsy (GACE) study takes a prospective population-based approach to the investigation of new onset epilepsy and complex febrile seizures, allowing us to estimate the degree to which genetic and autoimmune aetiologies contribute.We expect to recruit >300 cases over 3 years (2014)(2015)(2016)(2017).Method: Patients are recruited from all 21 centres seeing children with febrile or afebrile seizures in the Scottish National Health Service.We use multiple sources to identify cases.Inclusion criteria: child under the age of 3 years (<3y) with newly diagnosed epilepsy; child <3 years presenting with febrile or afebrile status epilepticus (seizure >10 minutes); child <3 years presenting with 2 or more febrile or afebrile seizures within 24-hours; neonatal seizures continuing beyond day 28.Exclusion criterion: structural/metabolic aetiology already established.Consent was taken for genetic testing (104 gene epilepsy panel), autoimmune testing (10 autoantibodies), and clinical follow-up.Data is stored on a national web-based clinical system.Results: We present preliminary results.As of September 2016 we have recruited 216 patients, of whom 154 (71%) had been given a diagnosis of epilepsy by the time of recruitment.The incidence of epilepsy <3 years (without an established structural/metabolic cause) in Scotland is 1 in 788 live births.So far 20% of those cases tested have a positive genetic aetiology, and 7% have antibody positivity for pathologically relevant epitopes.The most frequently occurring genetic aetiology is SCN1A mutation (7 cases).All SCN1A-positive cases had suspected Dravet syndrome at recruitment.The incidence of SCN1A-positive Dravet syndrome in this population is 1 in 17,300 live births.Conclusion: Positive genetic and autoantibody test results occur in a significant proportion of children <3 years presenting with new onset epilepsy and complex febrile seizures.Prospective follow-up of this cohort will reveal the extent to which aetiology correlates with prognosis and guides management.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.790 | 0.581 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".