Association of acne, hirsutism, androgen, anxiety, and depression on cognitive performance in polycystic ovary syndrome: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: While polycystic ovary syndrome (PCOS) is often associated with psychological distress, its most frequent clinical characteristics include acne, hirsutism and increased level of androgen hormones. OBJECTIVE: To evaluate the level of depression and anxiety, hirsutism, acne, and level of androgen hormones in PCOS and control group and its association with cognitive function. MATERIALS AND METHODS: This cross-sectional study was conducted on 53 women with PCOS and 50 healthy women as a control group. Data were collected using a questionnaire including the samples' demographic information, clinical features, clinical findings of hyperandrogenism, and the Beck Depression and Anxiety questionnaire. In addition, the acne and hirsutism levels of the subjects were evaluated using the global acne grading system and the Ferriman-Gallwey scoring system, respectively. The Montreal Cognitive Assessment (MoCA) is a screening test for cognitive impairment that covers major cognitive domains. RESULTS: A significant difference was found between the two groups in the mean levels of acne, hirsutism, total testosterone, free androgen index, depression, and anxiety. However, some mean values of the MoCA were lower in the women of case group compared to the control group. Additionally, a significant difference was observed between the two groups in the domains of visual-spatial ability (p = 0.009), executive function (p = 0.05), attention (p = 0.03), and total MoCA scores (p = 0.002). CONCLUSION: The PCOS women demonstrated significantly lower performance on the tests of executive function, attention, and visual-spatial function than the healthy control women.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".