Risk of Cognitive Decline in Women with Parkinson’s Disease Is Reduced by Early Age at Menarche
Bibliographic record
Abstract
Background: Parkinson’s disease (PD) is a neurodegenerative disorder affecting men more frequently than women, a difference that might be due to many factors, including sexual hormones. Estrogens seem to confer a protective effect on the nigrostriatal pathway in experimental studies but their effects on cognition in patients with PD are unknown. Aim: To investigate the impact of the exogenous and endogenous estrogens on cognitive impairment in women with PD. Methods and materials: We recruited and consecutively interviewed outpatient women affected by PD. Each patient underwent a cognitive assessment via the Montreal Cognitive Assessment scale (MoCA), an anamnestic collection of the reproductive lifespan variables and clinical features. We investigated if some of the reproductive lifespan variables investigated could predict cognition outcomes in post-menopausal women with PD. Results: A total of 90 women with PD were recruited. Women with MoCA ≥ 26 (n = 27) had a lower median age at menarche (11 [11,12] vs. 13 [12–14], p < 0.0001), lower disease duration in years (8.3 [6.1–12.7] vs. 9.4 [6–12.7], p = 0.6), and less advanced disease (1 [1,2] vs. 2 [1–3], p = 0.02). Among all the reproductive life-span variables, only earlier age at menarche significantly predicted higher scores on MoCA (aOR = 0.5 [0.3–0.8], p = 0.005). No other clinical and reproductive factors have been shown to have an influence on cognitive scores. Conclusions: Age at menarche correlated with cognitive outcomes. Our study suggests that earlier exposure to endogenous estrogens during a phase of development and plasticity of the brain might preserve women with PD from cognitive decline.
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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 | 0.003 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".