Bibliographic record
Abstract
PURPOSE OF REVIEW: This article reviews the physiological and pathophysiological effects of anaemia on the brain, focusing on the hypothesis that anaemia-induced cerebral hypoxia contributes to anaemic cerebral dysfunction and injury. It also reviews evidence that the regulated increase in cerebral blood flow observed during anaemia represents a compensatory neuroprotective mechanism invoked to optimize cerebral oxygen delivery, thereby protecting the brain from hypoxic injury. RECENT FINDINGS: Severe anaemia, or low haematocrit, has been associated with cognitive dysfunction, impaired cerebral vascular regulation, neurological injury, and increased mortality, which suggests that the brain is vulnerable to anaemia-induced injury. Reduced cerebral tissue oxygen tension has been measured directly at haemoglobin concentrations near 35 g/l, suggesting that hypoxia may contribute to anaemic cerebral injury. A demonstration of increased hypoxic cerebral gene expression, including neuronal nitric oxide synthase, may provide a more sensitive means of determining the minimum haemoglobin concentration at which anaemia-induced cerebral hypoxia can be detected. The measurement of increased cerebral cortical neuronal nitric oxide synthase messenger RNA and protein levels in rats, at haemoglobin concentrations between 50 and 60 g/l, suggests that cerebral hypoxia occurred at these higher haemoglobin concentrations. Mechanisms regulating anaemic cerebral vasodilation and increased cerebral oxygen delivery, including nitric oxide, require further elucidation to establish their role in protecting the brain during anaemia. SUMMARY: Characterization of mechanisms of anaemia-induced cerebral injury will contribute to the development of optimal therapeutic strategies for anaemic patients. Such strategies would include a clearer definition of transfusion triggers based on physiological endpoints. The overall goal of these efforts would be to minimize morbidity and mortality associated with anaemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".