Characteristics of Cerebellar Cognitive Affective Syndrome in patients with acute cerebellar stroke and its impact on outcome
Bibliographic record
Abstract
Abstract Objectives To evaluate the cerebellar cognitive affective syndrome scale (CCAS-S) in patients with acute cerebellar stroke (ACS) and examine its relationship with the outcomes. Methods We included patients who experienced ACS for the first time and were hospitalized in Steel Memorial Yawata Hospital within 7 days of stroke onset between April 2021 and April 2023. The CCAS-S, Mini-Mental State Examination (MMSE), and Scale for the Assessment and Rating of Ataxia (SARA) scores were evaluated 1 week after stroke onset, and Functional Independence Measure (FIM)/Barthel Index (BI) at discharge, physical function, activities of daily life, duration of hospitalization, and outcome (discharge destination) were evaluated. The Mann–Whitney U test was used to compare CCAS-S scores and variables. Results Thirteen consecutive patients with ACS (nine women) and age-and sex-matched healthy controls (seven women) were included. The MMSE score was within the normal range in all patients; however, patients with stroke had a lower total CCAS-S score (median 72, interquartile range [IQR] 66–80) and a higher number of failed tests (median 4, IQR 3–5) than healthy controls. Significant deficits were observed in semantic fluency (p = 0.008), category switching (p = 0001), and similarity (p = 009). Possible, probable, and definite CCAS were diagnosed in two, one, and 10 patients, respectively. Patients discharged home showed better SARA and FIM/BI scores but similar CCAS-S scores compared to those discharged to rehabilitation hospitals. Conclusion CCAS, along with impaired executive and language functions, is frequently observed in ACS patients; however, impaired motor function, and not CCAS, influences the outcome.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".