Paroxetine increases estrogen and cognition in postmenopausal anxiety-depression patients
Bibliographic record
Abstract
Objective To investigate the effect of paroxetine on sex hormone levels and cognitive function in post-menopausal anxiety/depression patients.Methods Eighty-two post-menopausal patients who were diagnosed as anxiety/depression disorder and were not receiving hormone replacement therapy participated in aprospective,6-month,open-label naturalistic study.Patients were divided into an antidepressant treatment group(44cases)and a non-antidepressant treatment(control)group(38cases).We collected demographic data,sex hormone levels,psychological cognitive rating scale scores.Results Paroxetine significantly increased serum E2from(48.45±10.25)pg/mL to(57.24±14.65)pg/mL,while FSH declined from(50.56±16.78)mIU/mL to(28.90±11.34)mIU/mL(P0.05),LH also decreased from(24.18±6.25)mIU/mL to(18.43±4.55)mIU/mL(P0.05).Moreover,there were significant differences in E2,FSH,LH when comparing antidepressant group and control group after treatment.Meanwhile,HAM-A and HAM-D scores were decreased and MoCA-CV score was raised by paroxetine(P0.05).We also found a negative association between E2 and scores of HAM-A and HAM-D at pre 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 at pretreatment of Paroxetine(r = 0.52,r = 0.47).Conclusions Paroxetine improves cognitive function in postmenopausal anxiety-depression patients,possibly by increasing endogenous estrogen discharge and delaying degeneration of the gonads.
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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) | 0.000 | 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) | 0.001 | 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 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".