Do hyperoxaemia and hypocapnia add to the risk of brain injury after intrapartum asphyxia?
Bibliographic record
Abstract
BACKGROUND: Episodes of hyperoxaemia and hypocapnia, which may contribute to brain injury, occur unintentionally in severely asphyxiated neonates in the first postnatal hours. OBJECTIVE: To determine whether hyperoxaemia and/or hypocapnia during the first 2 hours of life add to the risk of brain injury after intrapartum asphyxia. METHODS: Retrospective cohort study in term infants with post-asphyxial hypoxic ischaemic encephalopathy (HIE) born between 1985 and 1995. Severe and moderate hyperoxaemia were defined as Pao(2) >26.6 and Pao(2) >13.3 kPa (200 and 100 mm Hg). Severe and moderate hypocapnia were defined as Paco(2) <2.6 and Paco(2) <3.3 kPa (20 and 25 mm Hg). Adverse outcome ascertained by age 24 months was defined as death, severe cerebral palsy, or any cerebral palsy with blindness, deafness, or developmental delay. With outcome as the dependent variable, multivariate analyses were performed including hyperoxaemic and hypocapnic variables, and factors adjusted for initial disease severity. RESULTS: Of 244 infants, 218 had known outcomes, 127 of which were adverse (64 deaths, 63 neurodevelopmental deficits). Multivariate analyses showed an association between adverse outcome and episodes of severe hyperoxaemia (odds ratio (OR) 3.85, 95% confidence interval (CI) 1.67 to 8.88, p = 0.002), and severe hypocapnia (OR 2.34, 95% CI 1.02 to 5.37, p = 0.044). The risk of adverse outcome was highest in infants who had both severe hyperoxaemia and severe hypocapnia (OR 4.56, 95% CI 1.4 to 14.9, p = 0.012). CONCLUSIONS: Severe hyperoxaemia and severe hypocapnia were associated with adverse outcome in infants with post-asphyxial HIE. During the first hours of life, oxygen supplementation and ventilation should be rigorously controlled.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".