Treating schizophrenia during menopause
Bibliographic record
Abstract
OBJECTIVE: The aim of this review is to examine three questions: What are the risks and benefits of treating women with schizophrenia with hormone therapy (HT) at menopause? Should the antipsychotic regimen be changed at menopause? Do early- and late-onset women with schizophrenia respond differently to HT at menopause? METHODS: MEDLINE databases for the years 1990 to 2016 were searched using the following interactive terms: schizophrenia, gender, menopause, estrogen, and hormones. The selected articles (62 out of 800 abstracts) were chosen on the basis of their applicability to the objectives of this targeted narrative review. RESULTS: HT during the perimenopause in women with schizophrenia ameliorates psychotic and cognitive symptoms, and may also help affective symptoms. Vasomotor, genitourinary, and sleep symptoms are also reduced. Depending on the woman's age and personal risk factors and antipsychotic side effects, the risk of breast cancer and cardiovascular disease may be increased. Antipsychotic types and doses may need to be adjusted at menopause, as may be the mode of administration. CONCLUSIONS: Both HT and changes in antipsychotic management should be considered for women with schizophrenia at menopause. The question about differences in response between early- and late-onset women cannot yet be answered.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".