Efficacy of the novel antidepressant agomelatine for anxiety symptoms in major depression
Bibliographic record
Abstract
OBJECTIVES: Anxiety in major depression is associated with increased morbidity. The antidepressant, agomelatine, which acts as an agonist at melatonin MT(1) and MT(2) receptors and as an antagonist at serotonin 5-HT(2C) receptors, has demonstrated efficacy and safety in both major depression and generalized anxiety disorder. Here, we investigated the efficacy of agomelatine in anxious depression. METHODS: Data from three placebo-controlled short-term trials of agomelatine and three comparative studies of agomelatine versus fluoxetine, sertraline, and venlafaxine were pooled. Effects of agomelatine on anxiety symptoms were assessed with the Hamilton Anxiety Rating Scale in four studies (one vs placebo and three vs active comparator) and with the Hamilton Depression Rating Scale (HAMD) anxiety subscore in all six studies. Anxiolytic and antidepressant efficacies of agomelatine were assessed in patients with more severe anxiety symptoms at baseline (score ≥5 on HAMD anxiety subscore). RESULTS: Agomelatine had a significantly greater effect on anxiety symptoms than both placebo and a number of comparator antidepressants. In more anxious depressed patients, agomelatine had a significantly greater effect on anxiety and depressive symptoms than both placebo and comparator antidepressants. CONCLUSION: Once-a-day oral agomelatine is a new, efficacious alternative option for the treatment of anxiety in patients with major depression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".