A meta-analysis of the efficacy of venlafaxine extended release 75–225 mg/day for the treatment of major depressive disorder
Bibliographic record
Abstract
OBJECTIVE: To evaluate the short-term efficacy of venlafaxine extended release (ER) 75-225 mg/day compared with placebo for treating major depressive disorder (MDD) and to examine associations between baseline characteristics and efficacy outcomes in MDD patients treated with venlafaxine ER 75-225 mg/day. RESEARCH DESIGN AND METHODS: This meta-analysis included published and unpublished short-term, double-blind, placebo-controlled, Wyeth/Pfizer sponsored studies of venlafaxine ER at doses up to 225 mg/day in adults with MDD. CLINICAL TRIAL REGISTRATION: All trials were conducted before trial registration became mandatory. MAIN OUTCOME MEASURES: response and remission at week 8 were evaluated using logistic regression models, with terms for study, treatment group, and baseline characteristics in the models. Safety and tolerability was assessed based on adverse events (AEs) and discontinuations due to AEs. RESULTS: total score did not predict response. Discontinuations due to AEs were reported for 9.4% of venlafaxine-ER-treated patients compared with 3.6% of placebo-treated patients. Key limitations: Five studies met the criteria for inclusion. Several differences in design between included studies limited the analysis: one study did not include a week 3 assessment (the week 3 time point was therefore dropped from the analysis), one study had two venlafaxine ER dose arms, which were combined into one group for the meta-analysis, and mixed- and flexible-dose studies were pooled. CONCLUSIONS: total score at baseline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.043 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".