Cognitive impairment in essential tremor assessed by the cerebellar cognitive affective syndrome scale
Bibliographic record
Abstract
Background: Essential tremor (ET) is a movement disorder characterized by cerebellar neurodegenerative changes. ET is also associated with non-motor symptoms including cognitive impairment. The neuropsychologic profile of a patient with ET could relate to cerebellar cognitive affective syndrome (CCAS). Objective: This study aimed to assess the prevalence of cognitive impairment in patients with ET and identify whether the cognitive impairment in ET corresponds to a CCAS. Methods: Cognitive functions were evaluated with the CCAS-Scale (CCAS-S) in 20 patients with ET and 20 controls matched for age, sex, and level of education. The results of the CCAS-S were compared between patients and controls. The underlying determinant of CCAS inpatients with ET was identified through the correlation between the results of the CCAS-S and age at onset of symptoms, disease duration, and the Essential Tremor Rating Assessment Scale (TETRAS). Results: On a group level, ET patients performed significantly worse than matched controls. In total, 13 individuals with ET had a definite CCAS (CCAS-S failed items ≥ 3). ASO and TETRAS scores significantly correlated with CCAS-S performances in ET patients. Conclusion: CCAS is highly prevalent in patients with ET which supports the cerebellar pathophysiology of associated cognitive impairment and supports a more systematic use of the CCAS-S to cognitively assessed patients with ET.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".