Umbilical artery carbon dioxide decreases the risk for hypoxic‐ischaemic encephalopathy
Bibliographic record
Abstract
Abstract Aim An accurate biomarker for metabolic acidosis at birth is needed. Our aims were to investigate the link between umbilical artery pCO2 and the risk for hypoxic‐ischaemic encephalopathy (HIE) and to compare false‐negative screen results in newborn infants with HIE using three umbilical artery blood gas biomarkers. Methods From a cohort of newborn infants ≥35 weeks born in Ottawa, Canada, between January 2007 and December 2016, we highlighted those with HIE or who died. We compared the umbilical artery pCO2 for matched pH >mean versus matched pH ≤mean. We compared false‐negative rates for three umbilical artery biomarkers—pH <7.0, base deficit ≥16 mmol/L and neonatal eucapnic pH ≤7.14. Results This study included 51 286 newborn infants, 51% male and a mean gestational age of 38.9 ± 1.5 weeks. The rate for HIE or death with umbilical artery pCO2 for matched pH >mean was 22%, compared to 78% for matched pH ≤mean. In 60 HIE or deaths, the false‐negative rate for umbilical artery neonatal eucapnic pH ≤7.14 was 8%; compared to 31% for pH <7.00 and 36% for base deficit ≥16 mmol/L. Conclusion The rate of HIE or death is lower in newborn infants with higher pCO2. Using neonatal eucapnic pH decreases the risk of missing newborn infants with HIE.
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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 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".