Is general anesthesia neuroinjury-free and safe for gynecological patients’ cognition? A comparison of two typical anesthesia schemes based on propofol and sevoflurane
Bibliographic record
Abstract
INTRODUCTION: The aim of the study was to evaluate the neurocognitive safety of two schemes of general anesthesia based on propofol or sevoflurane applied to patients undergoing laparoscopic gynecological operations, with a special focus on the patients' age, American Society of Anesthesiologists (ASA) physical status/risk category I, II, or III, and levels of neuromarkers. MATERIAL AND METHODS: The Montreal Cognitive Assessment (MoCA) was chosen for cognitive assessment. The potential neuroinjury after anesthesia and operation was assessed with a set of neuromarkers: glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), tau protein (tau), and ubiquitin C-terminal hydrolase L1 (UCH-L1). The study was conducted on a group of women with no prior neurological or psychiatric diseases. RESULTS: A total of 61 patients (mean age 40.57 years) were included in the study (29 patients under propofol-based anesthesia [PBA], 32 patients under sevoflurane-based anesthesia [SBA]). The groups were demographically comparable. The patients in both groups exhibited a postoperative increase in the MoCA regardless of the type of anesthesia. The NFL and UCH-L1 levels increased significantly in both groups. The GFAP levels were significantly higher in the SBA group. Neither the age nor the increase in the neuromarkers influenced the patients' cognition. CONCLUSIONS: The types of anesthesia applied in the laparoscopic gynecological operations resulted in a cognitively safe outcome despite detectable alterations in the neuromarkers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".