Cerebral Fractional Oxygen Extraction is Inversely Correlated with Oxygen Delivery in the Sick, Newborn, Preterm Infant
Bibliographic record
Abstract
Cerebral blood flow (CBF) is known to be low in newborn infants, but this has not been shown to be damaging. The purpose of this study was to investigate the relationships between cerebral haemoglobin flow, blood flow, oxygen delivery, oxygen consumption, venous saturation, and fractional oxygen extraction (OEF) in newborn, preterm infants. Measurements were made by near-infrared spectroscopy in 13 very preterm, extremely low birth weight infants (median gestation 25 weeks) during the first 3 days after birth. There was a negative correlation between cerebral oxygen delivery and OEF (n=13, r=-0.5, P=0.03), which implies that when there is a reduction in cerebral oxygen delivery in sick preterm infants, increased cerebral oxygen extraction may be responsible for maintaining oxygen availability to the brain. During the first 3 days after birth CBF (n=13, r=0.7, P=0.01), oxygen delivery (n=13, r=0.5, P=0.03), and oxygen consumption (n=13, r=0.7, P=0.004) all increased. This increase in oxygen consumption indicates increased cerebral metabolic activity after birth, which is likely to be a normal adaptation to extrauterine life. The increases in blood flow and oxygen delivery may also be normal adaptations that facilitate this increase in metabolic activity. There was a decrease (P=0.04) in mean (+/-s.d.) cerebral OEF between day 1 (0.37+/-0.10) and day 2 (0.29+/-0.09), with no change between day 2 and day 3. Taking into account the negative correlation between OEF and oxygen delivery, this decrease in OEF may be because of increased oxygen delivery during this time.
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 | 0.000 | 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) | 0.000 | 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".