Bibliographic record
Abstract
CONTEXT: The health burden of antipsychotic medication is well known, but the disproportionate effect on women as compared with men is underappreciated. OBJECTIVE: The goal of this article is preventive--to better inform clinicians so that the risks to women and to their offspring can be diminished. METHOD: All PubMed sources in which the search term gender (or sex) was linked to a side effect of antipsychotic medication were reviewed. RESULT: There is general agreement in the literature on women's increased susceptibility to weight gain, diabetes, and specific cardiovascular risks of antipsychotics, with less consensus on malignancy risks and risks to the fetus. Cardiovascular death, to which men are more susceptible than women, is disproportionately increased in women by the use of antipsychotics. Sedating antipsychotics raise the risk of embolic phenomena during pregnancy, and postpartum. Prolactin-elevating drugs suppress gonadal hormone secretion and may enhance autoimmune proclivity. CONCLUSIONS: Clinicians need to be aware of the differential harm that women (and their offspring) can incur from the side effects of antipsychotics.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".