Epidemiology of focal onset seizures in children aged >1 month to 4 years in Europe, United States, and Canada: A literature review
Bibliographic record
Abstract
The present study aims to report the currently available epidemiology of focal onset seizures in children aged >1 month to 4 years with the help of a literature review. The terms 'seizure*' OR 'epilepsy' combined with pediatric and epidemiology terms were used to search Embase, PubMed, and Web of Science up to November 16, 2021. Due to the scarcity of epidemiology data on focal onset seizures, the incidence and prevalence were estimated using the proportion of focal onset seizures in epilepsy patients from the most recently published articles. The estimated annual incidence per 100,000 children of focal onset seizures in children of 0-4 years of age ranged from 25.1 (95 % confidence interval [CI] 18.9-32.7) in the United Kingdom to 111.8 in the United States. The estimated period prevalence of focal onset seizures in children 0-4 years of age ranged from 0.15 % (99 % CI 0.13-0.18) in Canada to 0.61 % in the United States. Neurodevelopmental outcomes and psychiatric disorders were the most commonly reported comorbidities in children with epilepsy of age 0-4 years. Presence of focal onset seizures in children with different epilepsy syndromes needs to be thoroughly considered in the treatment planning of this population of interest.
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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) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".