Escitalopram versus ethinyl estradiol and norethindrone acetate for symptomatic peri- and postmenopausal women
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To examine the efficacy and tolerability of escitalopram (ESCIT) compared to estrogen and progestogen therapy (EPT) for the treatment of symptomatic peri- and postmenopausal women. DESIGN: Forty women (aged 40-60 years) with depressive disorders and menopause-related symptoms were randomly assigned to an 8-week open trial with ESCIT (flexible dose, 10-20 mg/day; fixed dose, 10 mg/day for the first 4 weeks) or estrogen plus progestogen therapy (ethinyl estradiol 5 microg/day plus norethindrone acetate 1 mg/day). Primary outcome measures included Montgomery-Asberg Depression Rating Scale and the Greene Climacteric Scale at week 8. Secondary outcome measures included the Clinical Global Impressions as well as sleep and quality of life assessments. RESULTS: Thirty-two women (16 on EPT, 16 on ESCIT) were included in the analyses. Full remission of depression (score of <10 on the Montgomery-Asberg Depression Rating Scale) was observed in 75% (12/16) of subjects treated with ESCIT, compared to 25% (4/16) treated with EPT (P = 0.01, Fisher's exact tests). Remission of menopause-related symptoms (>50% decrease in Greene Climacteric Scale scores) was noted in 56% (9/16) of women treated with ESCIT compared to 31.2% (5/16) on EPT (P = 0.03, Pearson's chi2 tests). Improvement in sleep, hot flashes, and quality of life was observed with both treatments. CONCLUSIONS: ESCIT is more efficacious than EPT for the treatment of depression and has a positive impact on other menopause-related symptoms. ESCIT may constitute a treatment option for symptomatic menopausal women who are unable or unwilling to use hormone therapy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it