Hormonal Treatments for Bipolar Disorder: A Review of the Literature
Bibliographic record
Abstract
Hormonal therapies may play a role in the treatment of bipolar disorder. Preliminary evidence suggests that: 1) tamoxifen has anti-manic properties; 2) hormone replacement therapy represents a good augmentation strategy in treatment-resistant peri-menopausal depression; and 3) certain oral contraceptives could prevent menstrual exacerbations of affective symptoms. Potential neurobiological mechanisms of the anti-manic effects of tamoxifen include the inhibition of protein kinase C in addition its anti-estrogenic effects. Estrogen is a serotonergic and adrenergic agonist as well as an agent promoting neurogenesis in the hippocampus through glutamatergic synaptic formation, which may be the basis of its antidepressant activity. Progesterone appears to decrease serotonergic and adrenergic tone and activity, while increasing GABAA receptor activation through its active metabolite allopregnanolone, which may be the basis of its anxiolytic, sedative, and potentially anti-manic properties. Although there is consistency between the evidence for clinical efficacy and neurobiological mechanisms of hormonal treatments, the current state of knowledge relies on studies with several methodological limitations. On the other hand, benefits of hormonal treatment include protection from osteoporosis and several gynecological cancers, as well as safe contraception in a population at-risk for unplanned pregnancy. Nonetheless, hormonal treatments should be reserved for treatment-resistant bipolar depression or mania, or when contra-indications to other psychotropic medications are present. Institution of regular monitoring for medical complications and drug-drug interactions are essential to minimize risks and maximize benefits.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".