The Value of Neuroimaging Studies in Pediatric Febrile Status Epilepticus
Bibliographic record
Abstract
Febrile seizures are common in children, with incidence rates up to 14% in developing countries; febrile status epilepticus accounts for roughly 5% of all febrile seizure cases. Both status epilepticus and febrile status epilepticus are life-threatening conditions that put children at risk of future epilepsy and that require timely diagnosis and care. However, there are difficulties in applying these diagnostic concepts to daily practice due to a lack of precise definitions of the disorders. In addition, there are no unified standardized neuroimaging diagnostic guidelines, and the significance of imaging findings, when observed, remains uncertain. Even though some brain MRI features occurring in the acute phase and over long-term follow-up have been studied in both children and animals, the causal relationships between these findings and risk of adverse seizure outcomes still need clarifying. Guidelines on eligibility criteria, optimal imaging modalities and protocols, timing of imaging, and the specific brain areas and structures to be evaluated and reported, along with their specific characteristics, are urgently required. This review summarizes clinical issues related to the varied definitions of febrile status epilepticus and the data regarding the acute and chronic neuroimaging changes observed in febrile status epilepticus.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".