Assessment of Cognitive Dysfunction and Quality of Recovery after General Anesthesia in Perimenopausal Women
Bibliographic record
Abstract
Background: Perimenopausal women often experience neurocognitive fluctuations due to hormonal changes, which may predispose them to cognitive dysfunction following general anesthesia. The perioperative period presents a unique vulnerability to such patients, yet limited data exist on their cognitive outcomes and overall recovery quality. Methods: This prospective observational study included 120 perimenopausal women (age 45–55 years) scheduled for elective surgery under general anesthesia. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) preoperatively, on postoperative day 1 and day 7. Quality of recovery was evaluated using the QoR-15 scale. Descriptive and inferential statistics were applied, including paired t -tests and ANOVA. Results: On postoperative day 1, the mean MMSE score decreased significantly from 28.7 ± 1.1 to 26.3 ± 1.6 ( P < 0.001), while the MoCA score dropped from 25.2 ± 1.5 to 22.0 ± 2.0 ( P < 0.001). Both scores showed improvement by day 7 (MMSE: 27.9 ± 1.3, MoCA: 24.1 ± 1.7) but remained below baseline ( P < 0.05). The mean QoR-15 score was 112.4 ± 9.8 on day 1, significantly lower than the preoperative value of 131.6 ± 6.5 ( P < 0.001), with partial recovery noted on day 7 (124.9 ± 8.2). Conclusion: Perimenopausal women exhibit significant early postoperative cognitive dysfunction and impaired quality of recovery after general anesthesia. Though partial cognitive and functional recovery occurs within a week, baseline levels are not fully restored.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".