Males and females differ in reported sexual functioning with escitalopram treatment for major depressive disorder: A CAN-BIND-1 study report
Bibliographic record
Abstract
Background: Antidepressant use for major depressive disorder (MDD) is frequently associated with sexual dysfunction. Aims: Cross-sectional and longitudinal relationships between antidepressant treatment outcomes and sexual functioning (SF) were evaluated separately for males and females receiving escitalopram. We further assessed the association between pre- and posttreatment SF. Methods: In all, 208 of the 211 CAN-BIND-1 trial participants (77 males and 131 females) with MDD and detectable drug blood levels were eligible for the analyses. All received escitalopram (10–20 mg) for 8 weeks. At baseline and Week 8, participants completed the Montgomery–Åsberg Depression Rating Scale (MADRS) and the SexFx scale, which measures sexual satisfaction and SF frequency. Mixed-model repeated measures assessed baseline to Week 8 SF changes among participants with different response/remission statuses. Multiple linear regression analyses examined SF differences between treatment outcomes at Week 8 as well as associations between pretreatment and eventual SF. Results: For both sexes, overall sexual satisfaction improved among responders but not among nonresponders ( p < 0.05). For females, overall SF frequency did not change significantly over time regardless of response status. For males, overall SF decreased significantly among nonresponders; orgasm decreased significantly among nonresponders and, to a lesser extent, among responders ( p < 0.05). For both sexes, pretreatment SF was significantly associated with SF at Week 8 across all domains ( p < 0.05). Conclusion: For both sexes, sexual satisfaction improves with response to escitalopram. For females, the response does not correspond to improvements in SF frequency. For males, SF frequency, particularly that of orgasm, declines regardless of response/nonresponse. ClinicalTrials.gov identifier: NCT01655706
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".