Cognitive deficits after general anaesthesia in animal models: a scoping review
Bibliographic record
Abstract
BACKGROUND: It remains controversial whether general anaesthetic drugs contribute to perioperative neurocognitive disorders in adult patients. Preclinical studies have generated conflicting results, likely because of differing animal models, study protocols, and measured outcomes. This scoping review of preclinical studies addressed the question: 'Do general anaesthetic drugs cause cognitive deficits in adult animals that persist after the drugs have been eliminated from the brain?' METHODS: Reports of preclinical studies in the MEDLINE database published from 1953 to 2021 were examined. A structured review process was used to assess original studies of cognitive behaviours, which were measured after treatment (≥24 h) with commonly used general anaesthetic drugs in adult animals. RESULTS: The initial search yielded 380 articles, of which 106 were fully analysed. The most frequently studied animal model was male (81%; n=86/106) rodents (n=106/106) between 2-3 months or 18-20 months of age. Volatile anaesthetic drugs were more frequently studied than injected drugs, and common outcomes were memory behaviours assessed using the Morris water maze and fear conditioning assays. Cognitive deficits were detected in 77% of studies (n=82/106) and were more frequent in studies of older animals (89%), after inhaled anaesthetics, and longer drug treatments. Limitations of the studies included a lack of physiological monitoring, mortality data, and risk of bias attributable to the absence of randomisation and blinding. CONCLUSIONS: Most studies reported cognitive deficits after general anaesthesia, with age, use of volatile anaesthetic drugs, and duration of anaesthesia as risk factors. Recommendations to improve study design and guide future research are presented.
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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 | 0.012 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".