Long-Term Treatment of Depression with Antidepressants: A Systematic Narrative Review
Bibliographic record
Abstract
OBJECTIVE: To examine the available scientific evidence for answers to clinically relevant questions on the effectiveness and tolerability of antidepressant drugs (ADs) for the long-term treatment of depression. METHOD: The Cochrane Library was searched up to July 2006. When no complete Cochrane review was available, we looked in PubMed for relevant systematic reviews or individual randomized controlled trials. RESULTS: There was no good evidence that increasing the dosage of the initial AD is an effective strategy for patients with no, or partial, response to acute-phase treatment. There was no good evidence that switching between chemical classes of antidepressant was more effective than switching within a class. There was limited support from randomized trials for several augmentation strategies. There was good evidence for the effectiveness of long-term therapy to prevent relapse in patients who remitted after acute-phase treatment. The application of principles of evidence-based medicine suggested that thoughtful, individualized application of evidence is more appropriate than general statements. CONCLUSIONS: Available evidence provides some support for the effectiveness of several augmentation strategies in the management of patients with no, or partial, response to acute-phase treatment and for the individualized application of groupwise robust evidence for maintenance treatment with ADs to prevent relapses. However, side effects of these long-term treatments with ADs are poorly studied and reported.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".