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How to detect cognitive dysfunction at early stages of multiple sclerosis?

EA 2966, Neurobiology of Myelin Disorders Laboratory, University Victor Segalen; and Department of Neurology, CHU, Bordeaux, France

M C Bonnet

EA 2966, Neurobiology of Myelin Disorders Laboratory, University Victor Segalen; and Department of Neurology, CHU, Bordeaux, France

E Salort

EA 2966, Neurobiology of Myelin Disorders Laboratory, University Victor Segalen; and Department of Neurology, CHU, Bordeaux, France

Y Arimone

INSERM, U657, Department of Pharmacology, University Victor Segalen, 33076 Bordeaux, Cedex, France

M Boudineau

EA 2966, Neurobiology of Myelin Disorders Laboratory, University Victor Segalen; and Department of Neurology, CHU, Bordeaux, France

K G Petry

EA 2966, Neurobiology of Myelin Disorders Laboratory, University Victor Segalen; and Department of Neurology, CHU, Bordeaux, France

B Brochet

EA 2966, Neurobiology of Myelin Disorders Laboratory, University Victor Segalen; and Department of Neurology, CHU, Bordeaux, France, bruno.brochet{at}chu-bordeaux.fr

Detecting cognitive dysfunction may be clinically important during the early stages of multiple sclerosis (MS). We assessed a self-report questionnaire on cognitive complaints and individual neuropsychological tests to select patients with early relapsing-remitting MS (RRMS) who needed comprehensive cognitive testing.

Fifty-seven patients underwent neurological and neuropsychological assessment, including Rao’s Brief Repeatable Battery (BRB) and the complete SEP-59 Questionnaire, a French adaptation of the MSQOL-54, which contains four specific questions about self-perception of cognitive functions. Predictive values, specificity, sensitivity and accuracy of five individual neuropsychological tests-Selective Reminding Test, Symbol Digit Modalities Test (SDMT), Similarities Subtest, PASAT and Stroop Test-were calculated to predict cognitive impairment.

Only 10.5% of patients did not report any cognitive complaint, while most reported complaints. On the basis of cognitive performances, 59.7% of patients were classified as cognitively impaired, although only one cognitive score was correlated with cognitive complaints. Depressive symptoms and fatigue were associated with more cognitive complaints. Sensitivity of the SDMT to predict cognitive impairment was 74.2%, specificity was 76.9% and accuracy was 75.4%. Since, at this stage, patients’ cognitive complaints are already influenced by depression and fatigue and do not accurately reflect cognitive performances, the SDMT may help to select patients for testing with a more complete cognitive battery.

Key Words: cognition • multiple sclerosis • relapsing-remitting diagnosis

Multiple Sclerosis, Vol. 12, No. 4, 445-452 (2006)
DOI: 10.1191/1352458506ms1289oa


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