Use of slow-release melatonin in treatment-resistant depression.
Bibliographic record
Abstract
OBJECTIVE: To examine antidepressant augmentation with and hypnotic effects of slow-release melatonin (SR-melatonin) in patients with treatment-resistant depression. DESIGN: Open-label trial. SETTING: Tertiary care outpatient depression clinic. PATIENTS: Nine outpatients who had failed to respond to 2 or more 8-week trials of antidepressant medication. INTERVENTIONS: Patients received SR-melatonin 5 mg per day for the first 2 weeks and 10 mg per day for the final 2 weeks, in addition to their antidepressant medication. OUTCOME MEASURES: Structured Clinical Interview for DSM-IV, Axis 1 Disorders, Hamilton Rating Scale for Depression (HRSD), Beck Depression Inventory, Response Style Questionnaire, sleep and fatigue measures. RESULTS: One patient was excluded after 1 week because of the development of a mixed affective state. In the remaining 8 patients there was a 20% mean decrease in HRSD scores after 4 weeks of treatment, with no individual achieving an improvement of 50% or more. There was a 36% decrease on the 3-item HRSD related to insomnia, with 4 of 8 patients showing at least a 50% improvement on this measure. The greatest decrease in insomnia occurred during the last 2 weeks of the study, following the increase in dosage to 10 mg per day of SR-melatonin. Patients also reported significantly lower levels of fatigue post-treatment. CONCLUSIONS: SR-melatonin may be a useful adjunct for sleep, but does not substantially augment existing antidepressant therapies in some patients with treatment-resistant 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".