The effect of melatonergic and non-melatonergic antidepressants on sleep: weighing the alternatives
Bibliographic record
Abstract
In DSM-IV the occurrence of disturbed sleep is one of the principal diagnostic criteria for major depressive disorder (MDD). Further, there is evidence of reciprocity between the two conditions such that, even in the absence of current depressive symptoms, disturbed sleep often predicts their development. The present review discusses the effects of antidepressants on sleep and evaluates the use of the recently developed melatonin agonist-selective serotonin antagonists on sleep and depression. Although many antidepressants such as the tricyclics, monoamine oxidase inhibitors, serotonin-norepinephrine reuptake inhibitors, several serotonin receptor antagonists and selective serotonin reuptake inhibitors (SSRIs) have all been found successful in treating depression, their use is often associated with a disruptive effect on sleep. SSRIs, currently the most widely prescribed of the antidepressants, are well known for their instigation or exacerbation of insomnia. The recently introduced novel melatonin agonist and selective serotonin antagonist antidepressant, agomelatine, which has melatonin MT(1) and MT(2) receptor agonist and 5-HT(2c) antagonist properties, has been useful in treating patients with MDD. Its rapid onset of action and effectiveness in improving the mood of depressed patients has been attributed to its ability to improve sleep quality. These properties underline the use of melatonin analogues as a promising alternative for the treatment of 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".