Xenon Attenuates Cerebral Damage after Ischemia in Pigs
Bibliographic record
Abstract
BACKGROUND: Cerebral blood flow may be compromised in a variety of anesthetic procedures, and ischemic cerebral complications represent the leading cause of morbidity after cardiac operations. With the growing importance of neuroprotective strategies, the current study was designed to determine whether xenon would attenuate cardiac arrest-induced brain injury in pigs. METHODS: Twenty-four pigs (aged 12-16 weeks) were investigated in a randomized design. General hemodynamics, intracranial pressure, brain tissue oxygenation, and cerebral microdialysis parameters were investigated. The animals were assigned to two groups to receive anesthesia with either xenon (75%) in oxygen (25%) or total intravenous anesthesia combined with air in oxygen (25%) ventilation 15 min before cardiac arrest. After induction (t0) of cardiac arrest of 4 min, cardiopulmonary resuscitation was performed for 1 min, and the induced ventricular fibrillation was terminated by electrical defibrillation. The investigation time was 240 min. RESULTS: Approximately 60 s after cardiac arrest, brain tissue oxygenation decreased to a critical level of less than 5 mmHg, paralleled by a decrease in electroencephalographic activity. Glycerol as a damage marker increased significantly (> 200 m; P < 0.05), with a peak 90 min after cardiac arrest in both groups. Glycerol concentrations during reperfusion were significantly lower and normalized faster in the xenon group as compared with the total intravenous anesthesia group. CONCLUSION: Although the primary ischemic lesion in this model was similar in both groups, the cerebral microdialysis data show that xenon induces a differential neurochemical benefit in cerebral cell damage and metabolism as compared with total intravenous anesthesia in vivo during cerebral reperfusion after cardiac arrest in a pig model.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".