Cognitive status and anxiety levels in female patients during the preoperative period
Bibliographic record
Abstract
BACKGROUND: Postoperative complications remain the primary cause of prolonged treatment duration, decompensation of existing comorbidities, and unfavorable clinical outcomes. One of the key concerns in surgery and anesthesiology is postoperative cognitive dysfunction, induced by the combined effects of surgical trauma and anesthetic agents. AIM: To assess the prevalence of cognitive impairment and anxiety among female patients admitted for elective surgical treatment. METHODS: A single-center, cross-sectional study was performed, enrolling female patients scheduled for surgical intervention on reproductive organs. During enrollment, a standard preoperative examination was conducted, along with testing using the Montreal Cognitive Assessment (MoCA) and the State-Trait Anxiety Inventory (STAI) by C.D. Spielberger (adapted by Yu.L. Khanin). RESULTS: Assessment of the main domains of cognitive status using the MoCA questionnaire revealed that female patients initially presented with varying cognitive statuses. Based on this test, two study groups were identified: Group A included 22 female patients without cognitive impairment (mean MoCA score: 28.4 ± 1.4 points; mean age: 37.2 ± 11.9 years), while Group B comprised 10 female patients with cognitive impairment (mean MoCA score: 22.9 ± 2.1 points; mean age: 49.1 ± 19.9 years). No statistically significant differences in age were found between the groups (p = 0.06), but significant differences were observed on the MoCA test (p 0.001). Anxiety assessment with the Spielberger–Khanin scale revealed a high level of trait anxiety in both groups: mean scores were 45.9 ± 8.3 in Group A and 45.6 ± 4.2 in Group B (p = 0.722). For state anxiety, mean scores were 44.5 ± 8.4 and 43.6 ± 6.7, respectively (p = 0.436), indicating a moderate level. CONCLUSION: Among female patients admitted for surgical treatment of reproductive system diseases, 31.3% exhibited newly diagnosed cognitive dysfunction, as well as state and trait anxiety associated with the upcoming surgery and anesthesia. Therefore, preoperative assessment of cognitive status and anxiety levels is essential to prevent worsening of existing cognitive impairment, postoperative cognitive dysfunction, or delirium.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".