The influence of depression and anxiety on cognition in people with multiple sclerosis: a cross-sectional analysis.

There are conflicting findings about the relationships between depression, anxiety, and cognitive dysfunction in people with multiple sclerosis (MS), and a paucity of research has examined the cumulative influence on cognition of depression plus anxiety. This study aimed to determine whether elevated symptoms of depression and anxiety alone or in combination are associated with worse cognition in people with MS. In this cross-sectional analysis, people with MS consecutively seen at a tertiary neuropsychiatry clinic completed the Hospital Anxiety and Depression Scale for symptoms of depression (HADS-D) and anxiety (HADS-A), and the Minimal Assessment of Cognitive Function in MS for cognitive indices. Accounting for covariates, regression models predicted cognitive indices from scores for HADS-D, HADS-A, and the interaction. Of 831 people with MS, 72% were female, mean age was 43.2 years, and median Expanded Disability Status Scale score was 2.0. Depressive symptoms were independently predictive of lower verbal fluency (Controlled Oral Word Association Test, p < 0.01), verbal learning (California Verbal Learning Test-II (CVLT-II) total learning, p = 0.02), verbal delayed recall (CVLT-II delayed recall, p < 0.01), and processing speed (Symbol Digit Modalities Test, p < 0.01; three-second Paced Auditory Serial Addition Test (PASAT), p = 0.05; two-second PASAT, p = 0.01). Anxiety in people with depression predicted decreased visuospatial function (Judgment of Line Orientation, p = 0.05), verbal learning (p < 0.01), verbal delayed recall (p < 0.01), visuospatial recall (Brief Visuospatial Memory Test-Revised, p = 0.02), and executive function (Delis-Kaplan Executive Function System, p < 0.01). Anxiety alone was not independently predictive of cognition. In conclusion, depression, especially with comorbid anxiety, is associated with cognitive dysfunction in people with MS.

A French Version of a Voice Recognition Symbol Digit Modalities Test Analog.

We previously showed that a fully automated voice recognition analog of the Symbol Digit Modalities Test (VR-SDMT) is sensitive in detecting processing speed deficits in people with multiple sclerosis (pwMS). We subsequently developed a French language version and administered it to 49 French-Canadian pwMS and 29 matched healthy control (HC) subjects. Significant correlations between the VR-SDMT and traditional oral SDMT were found in the MS (r = -0.716, p < 0.001) and HC (r = -0.623, p < 0.001) groups. These findings in French replicate our previous findings and confirm the utility of voice recognition software in assessing cognition in pwMS.