Movement disorders in neuroleptic-naïve patients with schizophrenia spectrum disorders
Bibliographic record
Abstract
BACKGROUND: Spontaneous Movements Disorders (SMDs) or dyskinetic movements are often seen in patients with schizophrenia and other psychotic disorders, and are widely considered to be adverse consequences of the use of antipsychotic medications. Nevertheless, SMDs are also observed in the pre-neuroleptic ear and among patients who were never exposed to antipsychotic medications. The aim of this study was to determine the extent of SMDs among antipsychotic-naïve patients in a low income setting, and to evaluate contextually relevant risk factors. METHODS: The study was a cross-sectional facility-based survey conducted at a specialist psychiatric hospital in Addis Ababa, Ethiopia. Consecutive consenting treatment-naïve patients with a diagnosis of schizophrenia, schizoaffective disorder and schizophreniform disorder contacting services for the first time were assessed using the Simpson-Angus Rating Scale (SAS) and the Abnormal Involuntary Movement Scale (AIMS) to evaluate the presence of SMDS. Scale for the Assessment of Negative Symptoms (SANS) and Scale for the Assessment of Positive Symptoms (SAPS) were administered to evaluate negative and positive symptom profiles respectively. Body mass index (BMI) was used as a proxy measure for nutritional status. RESULT: Sixty-four patients, 67.2% male (n = 43), with first contact psychosis who met the DSM-IV-TR criteria for schizophrenia (n = 47), schizophreniform disorder (n= 5), and schizoaffective disorder (n = 12) were assessed over a two month study period. Seven patients (10.9%) had SMDs. BMI (OR = 0.6, 95% CI = 0.40, 0.89; p = 0.011) and increasing age (OR = 1.10; 95% CI = 1.02, 1.20; p = 0.017) were associated with SMD. CONCLUSIONS: This finding supports previous suggestions that abnormal involuntary movements in schizophrenia and other psychotic disorders may be related to the pathophysiology of psychotic disorders and therefore cannot be attributed entirely to the adverse effects of neuroleptic medication.
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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 | 0.001 | 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) | 0.002 | 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".