Carbon dioxide levels in neonates: what are safe parameters?
Bibliographic record
Abstract
Abstract There is no consensus on the optimal pCO2 levels in the newborn. We reviewed the effects of hypercapnia and hypocapnia and existing carbon dioxide thresholds in neonates. A systematic review was conducted in accordance with the PRISMA statement and MOOSE guidelines. Two hundred and ninety-nine studies were screened and 37 studies included. Covidence online software was employed to streamline relevant articles. Hypocapnia was associated with predominantly neurological side effects while hypercapnia was linked with neurological, respiratory and gastrointestinal outcomes and Retinpathy of prematurity (ROP). Permissive hypercapnia did not decrease periventricular leukomalacia (PVL), ROP, hydrocephalus or air leaks. As safe pCO2 ranges were not explicitly concluded in the studies chosen, it was indirectly extrapolated with reference to pCO2 levels that were found to increase the risk of neonatal disease. Although PaCO2 ranges were reported from 2.6 to 8.7 kPa (19.5–64.3 mmHg) in both term and preterm infants, there are little data on the safety of these ranges. For permissive hypercapnia, parameters described for bronchopulmonary dysplasia (BPD; PaCO2 6.0–7.3 kPa: 45.0–54.8 mmHg) and congenital diaphragmatic hernia (CDH; PaCO2 ≤ 8.7 kPa: ≤65.3 mmHg) were identified. Contradictory findings on the effectiveness of permissive hypercapnia highlight the need for further data on appropriate CO2 parameters and correlation with outcomes. Impact There is no consensus on the optimal pCO2 levels in the newborn. There is no consensus on the effectiveness of permissive hypercapnia in neonates. A safe range of pCO2 of 5–7 kPa was inferred following systematic review.
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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 | 0.022 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".