Treatment-emergent sexual dysfunction with SSRIs and duloxetine: Effectiveness and functional outcomes over a 6-month observational period
Bibliographic record
Abstract
OBJECTIVE: To evaluate frequencies of treatment-emergent sexual dysfunction (TESD) in patients with major depressive disorder (MDD) treated with duloxetine or selective serotonin reuptake inhibitor (SSRI) monotherapy for up to 6 months in a prospective, observational study. METHODS: Sexually active MDD patients without sexual dysfunction at entry were enrolled from twelve countries (N = 1,647). TESD was assessed over the study period using the Arizona sexual experience (ASEX) scale. A priori-specified secondary 6-month clinical endpoints were also examined. RESULTS: The frequency of TESD at 6 months with duloxetine was comparable to that with SSRI monotherapy (23.4 and 28.7%, respectively; P = 0.087). Improvements in Clinical Global Impressions of Severity (CGI-S), 16-item Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR(16)), Integral Inventory for Depression (IID) total scores, remission and sustained remission rates were statistically significantly greater with duloxetine than SSRI monotherapy at 6 months (P < 0.001 for each), but TESD attenuated improvements in quality of life measures. Four factors were consistently significantly (P ≤ 0.05) associated with TESD at week 8 and 6 months. CONCLUSIONS: Six-month TESD rates were comparable between duloxetine and SSRIs, with greater MDD effectiveness in favour of duloxetine. Improved recognition and management of TESD may improve quality of life for MDD patients in usual clinical practice.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".