Sleep in Untreated Patients With Schizophrenia: A Meta-Analysis
Bibliographic record
Abstract
The present meta-analysis investigated the characteristics of sleep in patients with schizophrenia without neuroleptic treatment at the time of sleep recording. The 20 selected studies included 652 participants (321 patients with schizophrenia and 331 healthy subjects). Effect sizes were evaluated using d values for the following sleep variables: sleep latency (SL), total sleep time (TST), sleep efficiency index (SEI), total awake time (TAT), stage 2 percentage (S2%), stage 4 percentage, slow-wave-sleep percentage, rapid-eye-movement (REM) percentage, and REM latency. The initial meta-analysis revealed that patients with schizophrenia have the following sleep disorders: increased SL, decreased TST, and decreased SEI. A moderator analysis revealed that these sleep disorders were worse for the neuroleptic-withdrawal group relative to the never-treated group. However, only never-treated patients showed significantly increased TAT and diminished S2%. These results confirm that patients with schizophrenia have sleep disorders that are not necessarily a consequence of neuroleptic treatments, suggesting that sleep disorders are an intrinsic feature of schizophrenia. However, it must be noted that some sleep disorders may be amplified by residual effects of neuroleptic withdrawal, while others appear to be dampened by neuroleptic treatment.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.019 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".