The Intersection of Menopause and Epilepsy: A Review of Current Knowledge and Gaps
Bibliographic record
Abstract
While hormonal changes have been recognised to influence seizure control and have been studied in association with menstrual cycles and pregnancy, there is a paucity of data on the menopause transition in epilepsy. Given the known effects of sex steroid hormones on neuronal excitability, their endogenous fluctuations during perimenopause, as well as menopause hormone treatments, may alter seizure control. Epilepsy may also be associated with premature ovarian insufficiency and early menopause. This is especially important for epilepsy-related comorbidities, for which menopause can constitute a second hit, such as osteoporosis. Additional considerations for females with epilepsy across the menopause continuum include changes in antiseizure medication clearance and potential interactions with menopausal hormone therapy or other concomitant medications. This comprehensive review summarises the currently available literature on epilepsy and menopause, highlights gaps in knowledge, and underscores the need for research efforts, particularly longitudinal studies investigating the menopause transition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".