Fever, Seizures and Encephalopathy
Bibliographic record
Abstract
Fever-associated seizures and febrile encephalopathy are common neurological problems in children. Infections of the nervous system are responsible for the majority of cases. However, there is a spectrum of infection-associated and inflammatory conditions associated with the triad of fever, seizures, and encephalopathy. Apart from complex febrile seizures and febrile status epilepticus, fever infection-related epilepsy syndrome of childhood (FIRES), infantile hemiconvulsion hemiplegia epilepsy syndrome (IHHE), acute encephalopathy with delayed diffusion restriction (AESD), acute necrotizing encephalopathy of childhood (ANE), and reversible splenial lesion syndrome (RESLES) are age-related clinical phenotypes of fever-related epilepsy and encephalopathy. Awareness of these entities is important for appropriate diagnosis and the prompt use of immunomodulatory/immunosuppressive therapies. In this review, we discuss the pathophysiology, clinical phenotypes, and management approaches of these fever-related seizure and encephalopathy states.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".