Anesthetic Neuroprotection in Experimental Stroke in Rodents
Bibliographic record
Abstract
BACKGROUND: Patients undergoing endovascular therapy for acute ischemic stroke may require general anesthesia to undergo the procedure. At present, there is little clinical evidence to guide the choice of anesthetic in this acute setting. The clinical implications of experimental studies demonstrating anesthetic neuroprotection are poorly understood. Here, the authors evaluated the impact of anesthetic treatment on neurologic outcome in experimental stroke. METHODS: Controlled studies of anesthetics in stroke using the filament occlusion model were identified in electronic databases up to December 15, 2015. The primary outcome measures, infarct volume, and neurologic deficit score were used to calculate the normalized mean difference for each comparison. Meta-analysis of normalized mean difference values provided estimates of neuroprotection and contributions of predefined factors: study quality, the timing of treatment, and the duration of ischemia. RESULTS: In 80 retrieved publications anesthetic treatment reduced neurologic injury by 28% (95% CI, 24 to 32%; P < 0.0001). Internal validity was high: publication bias enhanced the effect size by 4% or less, effect size increased with study quality (P = 0.0004), and approximately 70% of studies were adequately powered. Apart from study quality, no predefined factor influenced neuroprotection. Neuroprotection failed in animals with comorbidities. Neuroprotection by anesthetics was associated with prosurvival mechanisms. CONCLUSIONS: Anesthetic neuroprotection is a robust finding in studies using the filament occlusion model of ischemic stroke and should be assumed to influence outcomes in studies using this model. Neuroprotection failed in female animals and animals with comorbidities, suggesting that the results in young male animals may not reflect human stroke.
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How this classification was reachedexpand
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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".