Valproate, bipolar disorder and polycystic ovarian syndrome
Bibliographic record
Abstract
INTRODUCTION: Polycystic ovarian syndrome is a syndrome of ovarian dysfunction with the principal features of hyperandrogenism and polycystic ovary morphology. A large number of studies conducted on this topic have suggested a possible role of anticonvulsants, particularly valproate, in the pathogenesis or risk factors associated with polycystic ovarian syndrome. Bipolar treatment guidelines from Canada and the United States of America recommend valproate as the first line strategy in the acute treatment of bipolar disorder. DISCUSSION: Most persons with bipolar disorder require maintenance treatment. Long-term administration of valproate in women with bipolar disorder or epilepsy is believed to result in the increased risk of hyperandrogenism, menstrual abnormalities and polycystic ovaries. Valproate may also increase the risk of infertility and other associated symptoms of polycystic ovarian syndrome. Therefore, particular caution is indicated in the use of valproate in women of reproductive age. CONCLUSION: The treatment of the female patients with bipolar disorder presents various challenges for the clinician. Every woman of reproductive age needs to know the risk and benefits of her pharmacologic treatment options. Bipolar disorder should be considered chronic disorder, whose development is largely affected by hormonal changes and reproductive cycle in women. These issues should be researched more thoroughly in order to opt for the most appropriate treatment in women with bipolar disorder.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| 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".