Effect of Phenobarbitone on Amplitude-Integrated Electroencephalography in Neonates with Hypoxic-Ischemic Encephalopathy during Hypothermia
Bibliographic record
Abstract
BACKGROUND: Phenobarbitone induces suppression of cerebral electrical activity on amplitude-integrated electroencephalography (aEEG) in neonates with hypoxic-ischemic encephalopathy (HIE); however, its effect during therapeutic hypothermia (TH) has not been well characterized. OBJECTIVE: To evaluate the effect of phenobarbitone on aEEG in neonates with HIE undergoing TH. METHODS: Thirty-five neonates born at ≥350 weeks gestational age (GA), who received phenobarbitone as first-line antiepileptic drug during TH for ≥ Sarnat stage II HIE with aEEG recordings were retrospectively studied. Background pattern, upper and lower margin voltages were characterized for a 30-min period before and 30-60 min after phenobarbitone administration. Primary outcome was presence of severely abnormal aEEG pattern after phenobarbitone administration. RESULTS: Mean (±SD) GA and median birth weight were 38.2 ± 1.9 weeks and 3.1 (2.5-3.9) kg, respectively. Phenobarbitone (10-20 mg/kg), administered at median age 16.8 h, was associated with background pattern worsening in 19/29 (65.5%) cases. Severe background patterns were more prevalent in post- versus pre-phenobarbitone tracings (21/29 [72%] vs. 11/29 [38%]; p = 0.01). Presence of severe pattern versus either continuous normal voltage or discontinuous normal voltage pattern post-phenobarbitone, (20/25 [80%] vs. 3/8 [38%]; p = 0.036) was associated with death or moderate-to-severe injury on MRI brain. Median time to trace recovery, when measurable, was 4 h (45 min-72 h). CONCLUSIONS: Phenobarbitone induces significant suppression on aEEG in infants with HIE undergoing TH. Development of severe aEEG background patterns after phenobarbitone may unmask a population at greater risk of abnormal outcome.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".