IS THE PROGNOSTIC VALUE OF EARLY AMPLITUDE INTEGRATED EEG ALTERED IN ASPHYXIATED INFANTS UNDERGOING SYSTEMIC HYPOTHERMIA
Bibliographic record
Abstract
Objective This study aims to investigate the correlation between amplitude integrated EEG (aEEG) at 6 and 24 h post partum, magnetic resonance imaging (MRI) findings and short-term outcome in full-term infants treated with systemic hypothermia after perinatal asphyxia and moderate/severe hypoxic–ischaemic encephalopathy (HIE). Methods Between December 2006 and December 2007, 24 infants with HIE were treated with systemic hypothermia (body temperature 33–34°C for 72 h) according to national guidelines, using a Thecoterm device. aEEG was continuously monitored and the level of encephalopathy assessed. Brain MRI was conducted within the first 2 weeks. Follow-up of motor functions according to the Alberta infant motor scale (defined as normal/mild–severe dysfunction) and behavioural function was carried out at 1, 4, 6 and 12 months. Results aEEG data were available from 17 neonates. At 6 h 12 infants exhibited a severely abnormal burst-suppression pattern. Only four infants had persisting burst-suppression at 24 h. A continuous/discontinuous normal voltage pattern was observed in five and 13 infants at 6 and 24 h, respectively (see table). Conclusions Severe aEEG abnormalities were found to normalise within the first 24 h in two-thirds of the infants. The prognostic value of early aEEG might be altered in infants undergoing systemic hypothermia.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".