Effects of once-daily adjunct quetiapine XR on sleep disturbance in patients with mdd: a pooled analysis from two acute studies
Bibliographic record
Abstract
Introduction Disrupted sleep is common in depression. Objectives Investigate effects of adjunct extended release quetiapine fumarate (QTP-XR) on sleep disturbance and quality in patients with MDD and inadequate response to antidepressant (AD) therapy. Methods Data were pooled from two (D1448C00006/D1448C00007) 6-week, double-blind, randomised, placebo (placebo+AD)-controlled studies of adjunct QTP-XR (15 0 mg/day and 300 mg/day). Primary endpoint: MADRS total score change versus placebo+AD. Secondary endpoints (post hoc): change from randomisation in MADRS item 4 (reduced sleep), HAM-D items 4, 5 and 6 (early-, middle- and late-insomnia), sleep disturbance factor (HAM-D items 4+5+6) and sleep quality (PSQI global score). MADRS total score change in patients with baseline HAM-D sleep disturbance factor score > = 4 or < 4 (high and low sleep disturbance, respectively) was evaluated. Results 919 patients received adjunct QTP-XR: 150 mg/day (n = 309), 300 mg/day (n = 307), placebo+AD (n = 303). At Week 6, adjunct QTP-XR (both doses) reduced MADRS item 4, HAM-D sleep disturbance factor, HAM-D items 4, 5 and 6 and PSQI global scores from baseline versus placebo+AD (p < 0.001). In patients with baseline HAM-D>=4 (n = 226, 215 and 210, respectively) adjunct QTP-XR (both doses) improved (p< 0.01) MADRS total score versus placebo+AD from Week 1 onward. In patients with baseline HAM-D< 4 (n = 83, 92, 93, respectively) adjunct QTP-XR (both doses) improved (not statistically significantly) MADRS total score versus placebo+AD at Week 6. Conclusions Adjunct QTP-XR significantly restored sleep and improved sleep quality in patients with MDD and inadequate response to AD. Significant improvement in depressive symptoms was demonstrated with adjunct QTP-XR in patients with MDD and high baseline sleep disturbance. AstraZeneca funded.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".