Increased extrapyramidal symptoms in patients with schizophrenia and a comorbid substance use disorder
Bibliographic record
Abstract
Few data have been gathered about the impact of psychoactive substances on extrapyramidal symptoms (EPS) in schizophrenia, and so far, inconsistent results have been reported. We studied 41 outpatients with schizophrenia (based on DSM-IV criteria), who were divided into two groups: with (n = 17) and without (n = 24) a substance use disorder (alcohol, cannabis, and/or cocaine). Both groups were matched for sociodemographic data and psychiatric symptoms (Positive and Negative Syndrome Scale). EPS were evaluated with the Extrapyramidal Symptoms Rating Scale and the Barnes Akathisia Scale, and all patients were stable on either quetiapine or clozapine. Patients receiving anticholinergic drugs were excluded. Analyses of variance were conducted on both groups and showed that schizophrenia patients with a comorbid substance use disorder (especially cocaine) displayed more EPS compared with non-abusing patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".