Febrile seizures and genetic epilepsy with febrile seizures <i>plus</i> (GEFS+)
Bibliographic record
Abstract
To review the literature about febrile seizures and GEFS plus with special emphasis on management and outcome. Selected literature review. Febrile seizures are the most common convulsive event in humans, occurring in 2-6% of the population. The aetiology is complex with strong evidence for a heterogeneous genetic predisposition interacting with fever of any cause, with certain viral infections having a greater effect. A large amount of literature has established that febrile seizures have no long-term consequences on cognition or behaviour. Unfortunately, about 40% of children with a first febrile seizure will have a recurrence. The strongest predictor of recurrence is age <14-16 months at the time of the first febrile seizure. Epilepsy follows febrile seizures in ∼3% cases, with the concepts of simple and complex febrile seizures providing relatively weak prediction. Very prolonged febrile seizures may lead to mesial temporal sclerosis and temporal lobe epilepsy although the degree of risk remains uncertain. Investigations beyond establishing the cause of the provoking fever are nearly always unnecessary. Treatment is mainly reassurance and there is some evidence that parents eventually "come to grips" with the fear that their children are dying during a febrile seizure. Antipyretic medications are remarkably ineffective to prevent recurrences. Daily and intermittent prophylactic medications are ineffective or have unacceptable side effects or risks. "Rescue" benzodiazepines may prevent prolonged recurrences for selected patients with a first prolonged febrile seizure although this has not been proven. Genetic epilepsy with febrile seizures plus (GEFS+) is a complex autosomal dominant disorder usually caused by mutations in SCN1A (a voltage-gated sodium channel). One third of patients have febrile seizures only; two thirds have a variety of epilepsy syndromes, both focal and generalized. Febrile seizures may distress parents but rarely have any long-term consequences. Reassurance is the only treatment for the vast majority. Identifying patients with GEFS plus may lead to further investigations and counselling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".