Clinical targeting of the cerebral oxygen cascade to improve brain oxygenation in patients with hypoxic–ischaemic brain injury after cardiac arrest
Bibliographic record
Abstract
The cerebral oxygen cascade includes three key stages: (a) convective oxygen delivery representing the bulk flow of oxygen to the cerebral vascular bed; (b) diffusion of oxygen from the blood into brain tissue; and (c) cellular utilisation of oxygen for aerobic metabolism. All three stages may become dysfunctional after resuscitation from cardiac arrest and contribute to hypoxic-ischaemic brain injury (HIBI). Improving convective cerebral oxygen delivery by optimising cerebral blood flow has been widely investigated as a strategy to mitigate HIBI. However, clinical trials aimed at optimising convective oxygen delivery have yielded neutral results. Advances in the understanding of HIBI pathophysiology suggest that impairments in the stages of the oxygen cascade pertaining to oxygen diffusion and cellular utilisation of oxygen should also be considered in identifying therapeutic strategies for the clinical management of HIBI patients. Culprit mechanisms for these impairments may include a widening of the diffusion barrier due to peri-vascular oedema and mitochondrial dysfunction. An integrated approach encompassing both intra-parenchymal and non-invasive neuromonitoring techniques may aid in detecting pathophysiologic changes in the oxygen cascade and enable patient-specific management aimed at reducing the severity of HIBI.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".