Abstract
BackgroundIt is essential to investigate cognitive deficits in multiple sclerosis (MS) to develop evidence-based cognitive rehabilitation strategies. Here we refined cognitive decline assessment using the automated tests of the Cambridge Neuropsychological Test Automated Battery (CANTAB) and hierarchical cluster analysis.MethodsWe searched for groups of distinct cognitive profiles in 35 relapsing-remitting MS outpatients and 32 healthy controls. All individuals participated in an automated assessment (CANTAB) and in a pencil and paper general neuropsychological evaluation.ResultsHierarchical cluster analysis of the CANTAB results revealed two distinct groups of patients based mainly on the Simple Reaction Time (RTI) and on the Mean Latency of Rapid Visual Processing (RVP). The general neuropsychological assessment did not show any statistically significant differences between the cluster groups. Compared to the healthy control group, all MS outpatients had lower scores for RTI, RVP, paired associate learning, and delayed matching to sample. We also analyzed the associations between CANTAB results and age, education, sex, pharmacological treatment, physical activity, employment status, and the Expanded Disability Status Scale (EDSS). Although limited by the small number of observations, our findings suggest a weak correlation between performance on the CANTAB and age, education, and EDSS scores.ConclusionsWe suggest that the use of selected large-scale automated visuospatial tests from the CANTAB in combination with multivariate statistical analyses may reveal subtle and earlier changes in information processing speed and cognition. This may expand our ability to define the limits between normal and impaired cognition in patients with Multiple Sclerosis.
Highlights
It is essential to investigate cognitive deficits in multiple sclerosis (MS) to develop evidence-based cognitive rehabilitation strategies
We expect that an improved understanding of cognitive deficits in MS could help guide evidence-based cognitive rehabilitation programs, and the selection of therapy, based on the cognitive profiles of MS patients [19, 20]. This observational exploratory study investigated whether the Cambridge Neuropsychological Test Automated Battery (CANTAB) in combination with hierarchical cluster analysis could detect subtle cognitive declines in MS to classify MS patients according to their performance on selected CANTAB tests
Our results suggest that the use of large-scale automated visuospatial tests, such as the CANTAB could improve the signal-to-noise ratio and reveal subtle and earlier changes in information processing speed (RTI and Rapid Visual Processing (RVP)) and learning and memory (PAL and Delayed Matching to Sample (DMS)) in MS patients
Summary
It is essential to investigate cognitive deficits in multiple sclerosis (MS) to develop evidence-based cognitive rehabilitation strategies. Despite the high prevalence rates of cognitive dysfunction in MS, for many decades physicians and patients focused on the overt motor dysfunctions that affect the activities of daily life. It was not until 1991 that cognitive dysfunction began to be assessed in terms of its frequency, patterns, and prediction [2]. Until this time, cognitive function was not routinely assessed in patients [3,4,5], and the implications of cognitive deficits on the quality of life of MS patients remained unknown [6]. Neuroimaging continues to confirm this, and is helping define the extent and localization of areas in the central nervous system that are impaired in MS. [8, 9]
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