Seizure Burden and Neurologic Outcomes After Neonatal Encephalopathy
Bibliographic record
Abstract
Background and Objectives Seizures are common during neonatal encephalopathy (NE), but the contribution of seizure burden (SB) to outcomes remains controversial. This study aims to examine the relationship between electrographic SB and neurologic outcomes after NE. Methods This prospective cohort study recruited newborns ≥36 weeks postmenstrual age around 6 hours of life between August 2014 and November 2019 from a neonatal intensive care unit (NICU). Participants underwent continuous electroencephalography for at least 48 hours, brain MRI within 3–5 days of life, and structured follow-up at 18 months. Electrographic seizures were identified by board-certified neurophysiologists and quantified as total SB and maximum hourly SB. A medication exposure score was calculated based on all antiseizure medications given during NICU admission. Brain MRI injury severity was classified based on basal ganglia and watershed scores. Developmental outcomes were measured using the Bayley Scales of Infant Development, Third Edition. Multivariable regression analyses were performed, adjusting for significant potential confounders. Results Of 108 enrolled infants, 98 had continuous EEG (cEEG) and MRI data collected, of which 5 were lost to follow-up, and 6 died before age 18 months. All infants with moderate-severe encephalopathy completed therapeutic hypothermia. cEEG-confirmed neonatal seizures occurred in 21 (24%) newborns, with a total SB mean of 12.5 ± 36.4 minutes and a maximum hourly SB mean of 4 ± 10 min/h. After adjusting for MRI brain injury severity and medication exposure, total SB was significantly associated with lower cognitive (−0.21, 95% CI −0.33 to −0.08, p = 0.002) and language (−0.25, 95% CI −0.39 to −0.11, p = 0.001) scores at 18 months. Total SB of 60 minutes was associated with 15-point decline in language scores and 70 minutes for cognitive scores. However, SB was not significantly associated with epilepsy, neuromotor score, or cerebral palsy (p > 0.1). Discussion Higher SB during NE was independently associated with worse cognitive and language scores at 18 months, even after adjusting for exposure to antiseizure medications and severity of brain injury. These observations support the hypothesis that neonatal seizures occurring during NE independently contribute to long-term outcomes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".