The impact of menopause and hormonal therapy on Alzheimer’s disease: a systematic review
Bibliographic record
Abstract
Introduction: Women are at a greater risk of developing Alzheimer’s disease (AD) compared to men. This difference has one of its causal explanations in the association with sex hormone levels and their abrupt decline during menopause. Objective: The aim of this study was to review how postmenopausal sex hormone changes influence AD and how hormonal therapy (HT) may impact this trajectory, providing an overview of the literature. Methods: A systematic review was conducted by searching bibliographic databases, including PubMed, Scopus, Embase, Web of Science, and VHL, using the keywords “women,” “Alzheimer’s,” “sex hormones,” and “menopause.” The inclusion criteria followed the PICO (population, intervention, control, and outcomes) strategy, and the quality of nonrandomized studies was assessed using the Newcastle-Ottawa Scale. Out of the 263 articles identified, 19 met all inclusion criteria. Results: The reviewed studies consistently show that the decline in sex hormones, particularly estradiol, plays a significant role in the potential development of AD in postmenopausal women. An earlier onset of menopause is associated with reduced gray matter volume in key brain regions such as the hippocampus, parahippocampal gyri, perirhinal cortex, and amygdala, all crucial for memory. These structural changes suggest that a younger age at menopause may contribute to a higher risk of AD. Although HT does not significantly alter the overall relationship between menopause and AD incidence, two studies indicate that HT may provide cognitive protection, including lower β-amyloid deposition, in women at higher genetic risk, such as those with the APOE ε-4 allele or a family history of AD. Conclusion: An earlier age at menopause is linked to a higher risk of AD. However, HT may provide a preventive option for women with the APOE ε-4 allele or a family history of the disease.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".