Cerebellar Cognitive Affective Syndrome: A Two‐Case Report
Bibliographic record
Abstract
BACKGROUND: Cerebellar cognitive affective syndrome (CCAS) is clinically characterized by impaired functioning across all cognitive domains, particularly executive function and mood regulation. CCAS is attributed to lesions compromising cerebellar structures that modulate cognition and affection. Diagnosis is based on identifying neuropsychiatric symptoms in patients with cerebellar lesions, supported by neuropsychological assessments, especially the CCAS scale (CCAS-S). We report two patients diagnosed with CCAS evaluated in our clinic in 2024. METHOD: The first case, a 72-year-old man, presented with progressive cognitive complaints and personality changes 3 years after a cerebellar stroke. He had become less communicative and reported difficulties planning, organizing, and performing tasks he previously did effortlessly. His family also noted forgetfulness and working memory problems. He scored 15/30 on the Montreal Cognitive Assessment (MoCA). Brain MRI did not feature brain atrophy; however, it showed multiple chronic infarcts in the cerebellum, mesencephalon, and pons. He underwent neurocognitive evaluation where he underscored in all cognitive domains, particularly in attention, executive, and visuospatial functions. In the CCAS-S he failed 8/10 items with a raw score of 50/120. The second case is a 65-year-old man with a history of infarcts affecting multiple cerebellar territories, who clinically presented with diminished verbal fluency and deterioration of executive functioning, with no significant personality changes or memory loss. He had no evidence of brain atrophy in structural neuroimaging and scored 28/30 in MoCA. He failed 5/10 items and had a raw score of 65/120 in the CCAS-S. They were both diagnosed with CCAS. RESULT: Both patients lacked evidence of a neurodegenerative process or supratentorial lesion, and both had sequelae of lesions involving the cerebellum. The clinical suspicion of CCAS was reaffirmed with the CCA-S. CONCLUSION: CCAS is a cause of cognitive and behavioral impairment different from classic neurodegenerative pathologies. High clinical suspicion, exclusion of alternative causes, and neurocognitive assessment are needed to achieve accurate diagnosis. The CCAS-S appears to be a useful tool to assess suspected CCAS cases. Further research is needed to clarify the physiopathology of CCAS and improve its diagnosis and treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".