Extrapyramidal symptoms in substance abusers with and without schizophrenia and in nonabusing patients with schizophrenia
Bibliographic record
Abstract
Extrapyramidal symptoms (EPS) such as parkinsonism, dystonia, dyskinesia, and akathisia are conditions of impaired motor function, which are associated with chronic antipsychotic treatment in schizophrenia. In addition, EPS is often exacerbated by psychoactive substance (PAS) abuse, which is frequently observed in this population. Few studies, however, have investigated the contribution of PAS abuse on EPS in PAS-abusers without comorbid psychosis. This study compared the occurrence of EPS in outpatient schizophrenia patients with (DD group; n= 36) and without PAS abuse (SCZ group; n = 41) as well as in nonschizophrenia PAS abusers undergoing detoxification [substance use disorder (SUD) group; n = 38]. Psychiatric symptoms were measured using the Positive and Negative Syndrome Scale and the Calgary Depression Scale for schizophrenia. Extrapyramidal symptoms were evaluated with the Extrapyramidal Symptoms Rating Scale and the Barnes Akathisia Scale. SUD diagnoses were complemented with urine drug screenings. We found that DD patients exhibited significantly more parkinsonism than SCZ patients. Our subanalyses revealed that cocaine and alcohol abuse/dependence was responsible for the increase in parkinsonism in DD patients. Additionally, we found that SUD individuals exhibited significantly more akathisia than SCZ patients. In these latter individuals, subanalyses revealed that alcohol and cannabis abuse/dependence was responsible for the increase in akathisia. Our results suggest that PAS abuse is a contributor to EPS in individuals with and without schizophrenia.
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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 | 0.001 |
| 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 | 0.001 |
| 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".