Use of psychotropic medication in women with psychotic disorders at menopause and beyond
Bibliographic record
Abstract
PURPOSE OF REVIEW: Drugs have been extensively prescribed for the treatment of psychotic symptoms in schizophrenia and related disorders, as well as for the management of psychotic features in delirium, dementia and affective disorders. The aim of this narrative review is to focus on the recent literature on drug treatment in women with psychosis at the transition to menopause and subsequently. RECENT FINDINGS: The recent literature emphasizes the following points: the efficacy of antipsychotic medication in psychosis is largely confined to the alleviation of delusions and hallucinations; menopause and ageing alter the kinetics and dynamics of drug action; drugs other than antipsychotics are currently being tested to address the cognitive, affective and negative symptoms of psychotic illnesses; menopausal symptoms add to comorbidities and require simultaneous treatment, raising the probability of deleterious drug interactions; antipsychotic drugs have many side effects and contribute to high mortality rates in the older psychosis population. SUMMARY: A major implication for research is that antipsychotic drugs with a wider range of action and with fewer side effects are urgently needed. The clinical implications of the pharmacotherapy of psychotic illness are: older women's needs must be assessed through a comprehensive history and review of systems and physical and mental examination. To avoid adverse effects, drug dosages are best kept low and polypharmacy avoided wherever possible. It is important to frequently reassess older patients, as their pharmacotherapy requirements change with age and with comorbidity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".