Understanding cognitive features of cervical dystonia: application of the cerebellar cognitive affective syndrome scale (CCAS-S)
Bibliographic record
Abstract
Cervical Dystonia (CD) is now recognized to encompass a constellation of non-motor symptoms, including sensory, cognitive, and psychiatric manifestations, which significantly affect patients' quality of life. Cerebellar dysfunction may affect cognitive and affective processing in CD, mirroring cognitive and affective patterns observed in Cerebellar Cognitive and Affective Syndrome (CCAS). To investigate impairments in cerebellar-dependent cognitive and affective domains in CD patients using the Cerebellar Cognitive and Affective Syndrome scale (CCAS-S), and to analyze the potential relationship between cognitive deficits and clinical features of CD. The CCAS-S was administered to twenty CD patients and twenty controls (HC) matched for age, gender, level of education, and MMSE score. For CD patients, disease severity and disability were evaluated using the Toronto Western Spasmodic Torticollis Rating Scales (TWSTRS), while tremor was assessed through the Fahn-Tolosa-Marin Clinical Rating Scale for Tremor (FTM). CD exhibited a significantly lower total CCAS-S score, and a higher number of failed items compared to HC, with marked deficits in specific sub-items such as fluency, delayed verbal recall, similarities, and affective domain. The total number of failed tests revealed high predictive ability (AUC = 0.90), with no significant correlations between disease duration, clinical outcomes, and CCAS-S performance. The CCAS-S is a sensitive screening tool in differentiating cognitive performance in CD and HC, showing a critical cerebellar involvement in the cognitive and affective symptoms of dystonia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".