Paroxetine Increased the Serum Estrogen in Postmenopausal Women with Depressive and Anxiety Symptoms
Bibliographic record
Abstract
Objective: Both of selective serotonin reuptake inhibitors (SSRIs) and estrogen can modulate emotion and cognition function in post-menopause women, moreover SSRIs can influence estrogen system in rats and aquatic wildlife but most of them for reproductive ability. The aim of this study was to investigate the possible relationship between SSRI, estrogen, and emotion and cognition in post-menopause women with anxiety and depressive symptoms .Methods: A double-blind, randomized controlled trials of Paroxetine, an SSRI (n = 44), versus placebo (n = 38) for 6 months in post-menopausal women with anxiety and depressive symptoms. For screening anxiety, depression and mild cognitive impairment (MCI), we use the Hamilton Anxiety Rating Scale (HAM-A), the Hamilton Depression Rating Scale (HAM-D) and the Chinese Version of the Montreal cognitive assessment (MoCA-CV). And sex hormones were measured by ELASE method which is serum estradiol (E2), follicle stimulating hormone (FSH) and luteinizing hormone (LH). Results: Paroxetine increased serum E2 and decreased LH, FSH significantly (P < 0.05). Meanwhile, HAM-A and HAM-D scores declined and MoCA-CV score raised by Paroxetine (P < 0.05). We also found that a negative association between E2 and scores of HAM-A and HAM-D at pre-treatment and post-treatment of Paroxetine (HAM-A: R = ?0.27, R = ?0.24; HAM-D: R = ?0.65, R = ?0.37), while a positive correlation between E2 and MoCA-CV scores (R = 0.52, R = 0.47). Conclusions: This founding suggests that SSRI can increase serum estrogen levels and the change of estrogen may be one of mechanism in SSRI’s improve emotion and cognitive function in post-menopausal women.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".