Neonatal seizures in hypoxic–ischaemic encephalopathy – risks and benefits of anticonvulsant therapy
Bibliographic record
Abstract
The risk of seizures is at its highest during the neonatal period, and the most common cause of neonatal seizures is hypoxic-ischaemic encephalopathy (HIE). This enhanced vulnerability is caused by an imbalance in the expression of receptors for excitatory and inhibitory neurotransmission, which is age dependent. There has been progress in detecting the electrophysiological abnormalities associated with seizures using amplitude-integrated electroencephalography (aEEG). Data from animal studies indicate a variety of risk factors for seizures, but there are limited clinical data looking at the long-term neurodevelopmental consequences of seizures alone. Neonatal seizures are also associated with increased risk of further epileptic seizures; however, it is less clear whether or not this results from an underlying pathology, and whether or not seizures confer additional risk. Phenobarbital and phenytoin are still the first-line antiepileptic drugs (AEDs) used to treat neonatal seizures, although they are effective in only one-third of affected infants. Furthermore, based on findings from animal studies, there are concerns regarding the risks associated with using these AEDs. Clinicians face a difficult challenge because, although seizures can be easily identified using aEEG, treatment options are limited, and there are uncertainties regarding treatment outcomes. There is a need to obtain long-term follow-up data, comparing groups of infants treated with or without current therapies. If these analyses indicate a definite benefit of treating neonatal seizures, then novel therapeutic approaches should be developed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".