Clinimetric Evaluation of the Simpson-Angus Scale in Older Adults With Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: Parkinsonism (or Parkinson's syndrome [PS]) remains common in patients exposed to antipsychotic drugs. One clinical tool used in its detection and follow-up, the Simpson-Angus Scale (SAS), has been under revision lately. We further examined the discriminative power of the SAS to detect PS and its efficacy as a measure of PS intensity in chronic schizophrenia. METHODS: Fifty-six outpatients between 50 and 75 years of age, under stable antipsychotic drug therapy, provided consent to undergo an evaluation along the SAS and Unified Parkinson's Disease Rating Scale III motor subsection, split according to the presence or absence of PS defined in the UK Parkinson's Disease Society Brain Bank (UKPDSBB) criteria or Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria. RESULTS: The identification rate for PS was 39.3% based on UKPDSBB criteria applied to the Unified Parkinson's Disease Rating Scale III, compared with 62.5% and 87.5% according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria and SAS cutoff value greater than 0.3, respectively. Median SAS scores for PS and PS-free participants were comparable. The SAS yielded high sensitivity (90.9%) but low specificity (17.7%). κ Values generally revealed only slight agreement between the group allocation provided by the SAS and the UKPDSBB criteria. Receiver operating characteristic curve for screening performance of the SAS provided poor prediction of subject status. CONCLUSIONS: The SAS lacks specificity and constitutes an imperfect detection and measurement tool for PS in older adults. Raising the cutoff score would avoid inflation in PS identification. The scale is probably best used as a measure of change relative to baseline score following an intervention, but results should be interpreted with caution.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".