Prolonged or recurrent acute seizures after pediatric arterial ischemic stroke are associated with increasing epilepsy risk
Bibliographic record
Abstract
AIM: To determine epilepsy risk factors after pediatric stroke. METHOD: A cohort of children with arterial ischemic stroke (birth-18y) was enrolled at 21 centers and followed for 1 year. Acute seizures (≤7d after stroke) and active epilepsy (at least one unprovoked remote seizure plus maintenance anticonvulsant at 1y) were identified. Predictors were determined using logistic regression. RESULTS: Among 114 patients (28 neonates and 86 children) enrolled, 26 neonates (93%) and 32 children (37%) had an acute seizure. Acute seizures lasted longer than 5 minutes in 23 patients (40%) and were frequently recurrent: 33 (57%) had 2 to 10 seizures and 11 (19%) had more than 10. Among 109 patients with 1-year follow-up, 11 (10%) had active epilepsy. For each year younger, active epilepsy was 20% more likely (odds ratio [OR] 0.8, 95% confidence interval [CI] 0.6-0.99, p=0.041). Prolonged or recurrent acute seizures also increased epilepsy risk. Each additional 10 minutes of the longest acute seizure increased epilepsy risk fivefold (OR 4.7, 95% CI 1.7-13). Patients with more than 10 acute seizures had a 30-fold increased epilepsy risk (OR 30, 95% CI 2.9-305). INTERPRETATION: Pediatric stroke survivors, especially younger children, have a high risk of epilepsy 1 year after stroke. Prolonged or recurrent acute seizures increase epilepsy risk in a dose-dependent manner.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".