SSRI’s en depressieve klachten bij schizofrenie : een systematische review
Bibliographic record
Abstract
BACKGROUND: Patients with schizophrenia frequently have depressive symptoms. Current guidelines do not provide specific recommendations regarding the treatment of these symptoms, nor do they mention the role that selective serotonin reuptake inhibitors (ssris) can play in the treatment. AIM: To investigate whether ssris are more effective than placebo in treating depressive symptoms in patients with schizophrenia. METHOD: We searched the literature systematically using PubMed, embase, Cochrane Library and Psycinfo. We selected articles on the basis of inclusion and exclusion criteria and the methodologies used and compared the severity of patients symptoms before and after treatment. RESULTS: We found only four published studies of randomised, double blind, placebo-controlled trials. These showed that an ssri was significantly more effective than a placebo (the difference being 0.4 - 6.7 points on the Hamilton Depression Rating Scale and 0.2 - 2.6 on the Calgary Depression Scale for Schizophrenia). CONCLUSION: There are indications that ssris are effective for the treatment of depressive symptoms in patients with schizophrenia. However, the total sample size was limited and individual studies had several methodological limitations.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".