PS-115 1h-nmr Measurment Of Cord Glycerol Succinate Predicts Severe Encephalopathy And Death In Neonatal Hypoxic-ischaemic Encephalopathy
Bibliographic record
Abstract
Background and aims The outcome of infants with severe hypoxic-ischaemic encephalopathy (HIE) remains extremely poor. Early identification of these infants could improve patient management and direct care. Our aim was to correlate the metabolomic profile of umbilical cord blood (UCB) with outcome in neonatal HIE. Methods Full term infants with perinatal asphyxia and healthy matched controls were recruited from 2009 to 2011. All had UCB biobanked at -80°C within 3 h of birth and multichannel electroencephalogram (EEG) recorded in the first 24 h of life. The metabolite profile of UCB was analysed using nuclear magnetic resonance (NMR) spectroscopy. Infant outcome was assessed using the Bayley Scales of Infant and Toddler development at 3 years. Results The UCB metabolomic profile of 118 infants was described; 59 healthy controls, 34 perinatal asphyxia (no HIE) and 25 HIE defined by Sarnat score and EEG (13 mild, 6 moderate, 6 severe). Of the 6 cases of severe HIE, at 3 years; 4 have died, 1 survived with severe dyskinetic cerebral palsy and 1 had a normal outcome. A characteristic pattern of raised glycerol + succinate occurred in those infants with severe encephalopathy and very low voltage EEG (R2 = 0.49, p < 0.001). Conclusion Alterations in glycerol and succinate at birth reflect critical energy failure in infants with severe neuronal injury. This measurement at birth could help clinicians to identify infants who will not benefit from standard neuroprotection and may need experimental intervention, or limitation of care.
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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 | 0.001 |
| 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".