Current Evidence: Seizures in Extremely Low Gestational Age Newborns (ELGANs)
Bibliographic record
Abstract
Extremely low gestational age newborns (ELGANs) are born at or below 28 weeks of gestational age. Despite improved obstetric care, the incidence of preterm birth continues to rise in advanced countries. Preterm birth remains a major cause of infant mortality, and for infants who survive, neonatal seizures are a significant predictor of later neurologic morbidity. However, little is known about risk factors for neonatal seizures in ELGANs. Understanding the association between neonatal seizures and the development of other neurologic disorders is important given the increasing prevalence of ELGANs. Identifying risk factors that contribute to the development of neonatal seizures in ELGANs may offer insights into novel mechanisms of epileptogenesis in the developing brain and improvements in the prevention or treatment of seizures in preterm infants, including ELGANs. In this literature review, we outline the limitations of epidemiologic studies of neonatal seizures in ELGANs and discuss risk factors for neonatal seizures.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".