An Empirical Comparison of Commonly Used Universal Rating Scales for Dystonia
Bibliographic record
Abstract
ABSTRACT Background There are several widely used clinical rating scales for documenting the severity and distribution of various types of dystonia. Objectives The goal of this study was to evaluate the performance of the most commonly used scales in a large group of adults with the most common types of isolated dystonia. Methods Global Dystonia Rating Scale (GDRS) and the Burke‐Fahn‐Marsden Dystonia Rating Scale (BFM) scores were obtained for 3067 participants. Most had focal or segmental dystonia, with smaller numbers of multifocal or generalized dystonia. These scales were also compared for 209 adults with cervical dystonia that had Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) scores and 210 adults with blepharospasm that had Blepharospasm Severity Scale (BSRS) scores. Results There were strong correlations between the GDRS and BFM total scores (r = 0.79) and moderate correlations for their sub scores (r > 0.5). Scores for both scales showed positive skew, with an overabundance of low scores. BFM sub‐scores were not normally distributed, due to artifacts caused by the provoking factor. Relevant sub‐scores of the GDRS and BFM also showed moderate correlations with the TWSTRS (r > 0.5) for cervical dystonia and the BSRS (r > 0.5) for blepharospasm. Conclusions The BFM is more widely used than the GDRS, but these results suggest the GDRS may be preferable for focal and segmental dystonias. The overabundance of very low scores for both scales highlights challenges associated with discriminating very mild dystonia from other abnormal movements or variants of normal behavior.
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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 | 0.048 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".