Incidence, prevalence and aetiology of seizures and epilepsy in children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: To (1) summarize published, peer-reviewed literature about the incidence and prevalence of epilepsy in children from developed and developing countries around the world, and (2) discuss problems in defining aetiologies of epilepsy in children, and distinguish between seizures and epilepsy. METHODS: Review of selected literature with particular attention to systematic reviews. RESULTS: The incidence of epilepsy in children ranges from 41-187/100,000. Higher incidence is reported from underdeveloped countries, particularly from rural areas. The incidence is consistently reported to be highest in the first year of life and declines to adult levels by the end of the first decade. The prevalence of epilepsy in children is consistently higher than the incidence and ranges from 3.2-5.5/1,000 in developed countries and 3.6-44/1,000 in underdeveloped countries. Prevalence also seems highest in rural areas. The incidence and prevalence of specific seizure types and epilepsy syndromes is less well documented. In population-based studies, there is a slight, but consistent, predominance of focal seizures compared with generalized seizures. Only about one third of children with epilepsy can be assigned to a specific epilepsy syndrome, as defined by the most recently proposed system for organization of epilepsy syndromes. CONCLUSIONS: The incidence and prevalence of epilepsy in children appears to be lower in developed countries and highest in rural areas of underdeveloped countries. The reasons for these trends are not well established. Although focal seizures predominate, the incidence and prevalence of specific epilepsy syndromes is not well documented.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it