Switching from Antipsychotic to Quetiapine XR Treatment in Patients with Schizophrenia and High from Low Depression Symptoms
Bibliographic record
Abstract
Purpose: Assess the efficacy of once-daily extended release quetiapine fumarate (quetiapine XR) in patients with schizophrenia and depressive symptoms. Methods: 12-week, multi-centre, open-label study in adult patients with schizophrenia (D1444C00147). Patients were cross titrated to quetiapine XR over three days (Day 1: 300 mg; Day 2: 600 mg; Days 3-84: 400-800 mg/day [flexible dosing]). Two patient subsets: high depression symptoms (PANSS depression cluster score ≥ 12) and low depression symptoms (PANSS depression cluster score < 12) at baseline. Change from baseline of PANSS total score and PANSS depression cluster score were analysed by subgroup. Results: Mean (SD) change at Day 84 (LOCF) in PANSS depression cluster score was -4.8 (3.3) for patients with high depression (n=109) and -1.1 (2.7) for patients with low depression (n=362). Mean (SD) change from baseline at Day 84 (LOCF) in PANSS total score was -24.3 (18.5) for patients with high depression and -10.5 (18.0) for patients with low depression. at Day 84: in patients switched to quetiapine XR owing to “lack of efficacy”, mean change (SD) from baseline in PANSS depression cluster score was -5.2 (3.2) and -1.3 (2.8) for patients with high and low depression, respectively; in patients switched due to “insufficient tolerability”, mean change (SD) in PANSS depression cluster score was -4.1 (3.5) and -0.6 (2.5) for patients with high and low, respectively. Conclusions: Quetiapine XR showed promising results in patients with schizophrenia and depressive symptoms switched from other antipsychotics due to suboptimal efficacy or tolerability. Further randomised, clinical trials are warranted.
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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 | 0.002 |
| 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) | 0.001 | 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".