Maintenance Study for Adolescent Depression
Bibliographic record
Abstract
OBJECTIVE: Although recent studies and meta-analyses confirm the efficacy of antidepressants in the acute phase of treatment for adolescent depression, there are few data available to allow assessment of the value of continued use of antidepressants in depressed adolescents after acute response. This study examines the benefit of maintenance treatment with sertraline in adolescents aged 13-19 years with major depression using a multi-site randomized placebo controlled discontinuation design. METHODS: Subjects with a diagnosis of depression who responded to open-label treatment with sertraline in a 12-week acute phase and did not relapse with open-label continuation treatment for 24 weeks were randomized to placebo or continued treatment with sertraline for 52 weeks. RESULTS: Twenty-two subjects were randomized to maintenance treatment with sertraline (n = 13) versus placebo (n = 9). A higher proportion of subjects treated with sertraline (38%) remained well as compared to those on placebo (0%). Survival analyses found no significant differences between the groups (p = 0.17). CONCLUSIONS: This is the first study to examine the outcome to maintenance treatment for adolescents with major depression. Although the sample size was small, the findings suggest a possible benefit of maintenance treatment with sertraline over placebo. A larger clinical trial with adequate power is required to confirm or disconfirm these findings.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".