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@ARTICLE{Liu:274046,
author = {Liu, Qi and Rubarth, Kerstin and Faber, Jennifer and
Sulzer, Patricia and Dogan, Imis and Barkhoff, Miriam and
Minnerop, Martina and Berlijn, Adam M and Elben, Saskia and
Jacobi, Heike and Aktories, Julia-Elisabeth and Huvermann,
Dana M and Erdlenbruch, Friedrich and Van der Veen, Raquel
and Müller, Johanna and Nio, Enzo and Frank, Benedikt and
Köhrmann, Martin and Wondzinski, Elke and Siebler, Mario
and Reetz, Kathrin and Konczak, Jürgen and Konietschke,
Frank and Klockgether, Thomas and Synofzik, Matthis and
Röske, Sandra and Timmann, Dagmar and Thieme, Andreas},
title = {{S}ubtypes of cognitive impairment in cerebellar disease
identified by cross-diagnostic cluster-analysis: results
from a {G}erman multicenter study.},
journal = {Journal of neurology},
volume = {272},
number = {1},
issn = {0367-004X},
address = {Heidelberg},
publisher = {Springer},
reportid = {DZNE-2025-00027},
pages = {83},
year = {2025},
abstract = {Cognitive and neuropsychiatric impairment, known as
cerebellar cognitive affective syndrome (CCAS), may be
present in cerebellar disorders. This study identified
distinct CCAS subtypes in cerebellar patients using cluster
analysis.The German CCAS-Scale (G-CCAS-S), a brief screening
test for CCAS, was assessed in 205 cerebellar patients and
200 healthy controls. K-means cluster analysis was applied
to G-CCAS-S data to identify cognitive clusters in patients.
Demographic and clinical variables were used to characterize
the clusters. Multiple linear regression quantified their
relative contribution to cognitive performance. The ability
of the G-CCAS-S to correctly distinguish between patients
and controls was compared across the clusters.Two clusters
explained the variance of cognitive performance in patients'
best. Cluster 1 $(30\%)$ exhibited severe impairment.
Cluster 2 $(70\%)$ displayed milder dysfunction and
overlapped substantially with that of healthy controls.
Cluster 1 patients were on average older, less educated,
showed more severe ataxia and more extracerebellar
involvement than cluster 2 patients. The cluster assignment
predicted cognitive performance even after adjusting for all
other covariates. The G-CCAS-S demonstrated good
discriminative ability for cluster 1, but not for cluster
2.The variance of cognitive impairment in cerebellar
disorders is best explained by one severely affected and one
mildly affected cluster. Cognitive performance is not only
predicted by demographic/clinical characteristics, but also
by cluster assignment itself. This indicates that factors
that have not been captured in this study likely have
effects on cognitive cerebellar functions. Moreover, the
CCAS-S appears to have a relative weakness in identifying
patients with only mild cognitive deficits.The study has
prospectively been registered at the German Clinical Study
Register ( https://www.drks.de ; DRKS-ID: DRKS00016854).},
keywords = {Humans / Male / Female / Cognitive Dysfunction: diagnosis /
Cognitive Dysfunction: etiology / Cognitive Dysfunction:
physiopathology / Middle Aged / Germany: epidemiology /
Cluster Analysis / Cerebellar Diseases: complications /
Cerebellar Diseases: diagnosis / Cerebellar Diseases:
physiopathology / Aged / Adult / Neuropsychological Tests /
Cerebellar cognitive affective syndrome (CCAS) (Other) /
Cerebellar disorders (Other) / Cluster analysis (Other) /
German CCAS-Scale (Other) / Subgroups of CCAS (Other)},
cin = {Clinical Research (Bonn) / AG Gasser / AG Wagner / Patient
Studies (Bonn)},
ddc = {610},
cid = {I:(DE-2719)1011001 / I:(DE-2719)1210000 /
I:(DE-2719)1011201 / I:(DE-2719)1011101},
pnm = {353 - Clinical and Health Care Research (POF4-353)},
pid = {G:(DE-HGF)POF4-353},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:39708269},
pmc = {pmc:PMC11663179},
doi = {10.1007/s00415-024-12831-1},
url = {https://pub.dzne.de/record/274046},
}