Cognitive impairment and associated metabolic and hormonal factors in women with polycystic ovarian syndrome: a Montreal Cognitive Assessment-based case-control study
Bibliographic record
Abstract
Polycystic ovarian syndrome (PCOS) is a complex endocrine disorder affecting reproductive-aged women, frequently accompanied by metabolic dysfunction, hyperandrogenism, and psychological disturbances. Recent studies suggest possible links between PCOS and cognitive dysfunction, but evidence remains limited. We used the Montreal Cognitive Assessment (MoCA) to assess cognitive function in women with PCOS, and we investigated the interrelationships between hormonal dysregulation, metabolic dysfunction, and inflammatory status. A total of 120 women with PCOS (Rotterdam criteria) and 60 age-matched healthy controls underwent cognitive evaluation using MoCA. Demographic, anthropometric, hormonal, metabolic, and inflammatory markers and lipid profiles were assessed. PCOS patients demonstrated significantly lower total MoCA scores vs. controls (24.29 vs. 27.82, p<0.001). Cognitive impairment (MoCA<26) occurred in 34.16% of PCOS patients. Executive function, attention, language, and orientation domains were significantly impaired, while memory-related domains remained relatively preserved. Women with PCOS showed distinct cognitive vulnerability, particularly in executive, attention, language, and orientation domains. Cognitive dysfunction may represent an underrecognized PCOS aspect, warranting regular screening and future longitudinal studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".