Extended-release quetiapine fumarate in the treatment of patients with major depressive disorder: adjunct therapy
Bibliographic record
Abstract
Approximately half of the patients with major depressive disorder (MDD) respond insufficiently to current antidepressants, resulting in increased risk of relapse and residual symptoms. Strategies available include dose increase, combination with a second agent, switching antidepressants, adjunct treatment, psychotherapy or exercise. Efficacy and tolerability of once-daily extended-release quetiapine fumarate (quetiapine XR) adjunct to index antidepressant therapy in patients with MDD and an inadequate response to treatment were assessed in two acute studies as part of a global clinical trial program. Quetiapine XR significantly improved depressive symptoms versus placebo. Significant improvement in quality of life versus placebo was confined to elderly patients with MDD. Tolerability was consistent with the known pharmacological profile of quetiapine: the most common adverse events were dry mouth, somnolence, sedation, dizziness and fatigue. Quetiapine XR is approved in the EU, USA and several other countries worldwide as adjunctive treatment for patients with MDD and an inadequate response to previous antidepressants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".