Quantitative assessment of brain microvascular and tissue oxygenation during cardiac arrest and resuscitation in pigs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cardiac arrest is associated with a very high rate of mortality, in part due to inadequate tissue perfusion during attempts at resuscitation. Parameters such as mean arterial pressure and end-tidal carbon dioxide may not accurately reflect adequacy of tissue perfusion during cardiac resuscitation. We hypothesised that quantitative measurements of tissue oxygen tension would more accurately reflect adequacy of tissue perfusion during experimental cardiac arrest. Using oxygen-dependent quenching of phosphorescence, we made measurements of oxygen in the microcirculation and in the interstitial space of the brain and muscle in a porcine model of ventricular fibrillation and cardiopulmonary resuscitation. Measurements were performed at baseline, during untreated ventricular fibrillation, during resuscitation and after return of spontaneous circulation. After achieving stable baseline brain tissue oxygen tension, as measured using an Oxyphor G4-based phosphorescent microsensor, ventricular fibrillation resulted in an immediate reduction in all measured parameters. During cardiopulmonary resuscitation, brain oxygen tension remained unchanged. After the return of spontaneous circulation, all measured parameters including brain oxygen tension recovered to baseline levels. Muscle tissue oxygen tension followed a similar trend as the brain, but with slower response times. We conclude that measurements of brain tissue oxygen tension, which more accurately reflect adequacy of tissue perfusion during cardiac arrest and resuscitation, may contribute to the development of new strategies to optimise perfusion during cardiac resuscitation and improve patient outcomes after cardiac arrest.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 it