Paroxetine Versus Placebo and Other Agents for Depressive Disorders
Bibliographic record
Abstract
OBJECTIVE: To compare paroxetine with placebo and other antidepressants across multiple efficacy and tolerability outcomes. DATA SOURCES: Searches were conducted in MEDLINE (1966-2004), EMBASE (1980-2004), CINAHL (1982-2004), all Evidence-Based Medicine Reviews (1991-2004), HealthSTAR (1975-2004), BIOSIS (1980-2004), and PsycINFO (1840-2004). Medical Subject Headings (MeSH) included "paroxetine" OR "Paxil" exploded. The searches were not restricted by language, publication type, or study design. STUDY SELECTION: A study report was included if it described a randomized trial of paroxetine versus placebo or other antidepressants for patients with depressive disorders. Records were screened independently by 2 reviewers under the supervision of another reviewer. DATA EXTRACTION: Three investigators abstracted data, including study design, trial characteristics, and psychiatric assessment tools, using a prespecified form. Two investigators assessed quality of reporting using Jadad's scale. DATA SYNTHESIS: We included 62 unique randomized controlled trials. Paroxetine yielded consistently and significantly better remission (rate difference [RD]: 10% [95% CI = 6 to 14]), clinical response (RD: 17% [95% CI = 7 to 27]), and symptom reduction (effect size: 0.2 [95% CI = 0.1 to 0.3]) than placebo. Such consistency in the evidence base was not observed between paroxetine and other antidepressants. Pairwise comparisons of paroxetine and venlafaxine, mirtazapine, mianserin, or fluoxetine yielded inconsistent results across efficacy outcomes. Controlled-release paroxetine was the only antidepressant with significantly fewer dropouts due to adverse events than immediate-release paroxetine (RD: 5% [95% CI = 0.1 to 11]). CONCLUSIONS: There were no significant and valid differences between paroxetine and other antidepressants to suggest that multiple modes of action improve clinical outcomes.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".