The impact of surgery with general anesthesia on cognitive function and putamen volume: a cross-sectional study among older adults
Bibliographic record
Abstract
Background Previous studies have shown that surgery under general anesthesia may diminish cognitive function; however, the proposed mechanisms need further elucidation. The purpose of the current study was twofold: (1) to compare overall and domain-specific differences in cognitive function between the surgery under general anesthesia group and the control group, and (2) to investigate the possible mechanisms of surgery under general anesthesia affecting cognitive function, using T1-structural magnetic resonance imaging. Methods A total of 194 older adults were included in this study. Patients were divided into a surgery under general anesthesia group (n = 92) and a control group (n = 104). The two groups were matched for age, sex, and educational level. All participants underwent clinical evaluation, neuropsychological testing, blood biochemistry analysis, and T1 phase structural magnetic resonance imaging. Results We found that older adults with a history of surgery under general anesthesia had lower Montreal Cognitive Assessment (MoCA) scores and smaller right putamen volumes (p < 0.05). Linear regression analysis (mediation model) indicated that surgery under general anesthesia affected MoCA scores by diminishing the volume of the right putamen (B = 1.360, p = 0.030). Conclusion We found evidence that older adults who underwent surgery under general anesthesia had poorer cognitive function, which may have been caused by an apoptotic or otherwise toxic effect of anesthetic drugs on the volume of the right putamen.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".