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Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study

Cecilie Jacobsen, Robert Zivadinov, Kjell‐Morten Myhr, Turi O. Dalaker, Ingvild Dalen, Ralph H. B. Benedict, Niels Bergsland, Elisabeth Farbu

2021Multiple Sclerosis Journal - Experimental Translational and Clinical22 citationsDOIOpen Access PDF

Abstract

OBJECTIVES: To identify Magnetic Resonance Imaging (MRI), clinical and demographic biomarkers predictive of worsening information processing speed (IPS) as measured by Symbol Digit Modalities Test (SDMT). METHODS: Demographic, clinical data and 1.5 T MRI scans were collected in 76 patients at time of inclusion, and after 5 and 10 years. Global and tissue-specific volumes were calculated at each time point. For the primary outcome of analysis, SDMT was used. RESULTS: Worsening SDMT at 5-year follow-up was predicted by baseline age, Expanded Disability Status Scale (EDSS), SDMT, whole brain volume (WBV) and T2 lesion volume (LV), explaining 30.2% of the variance of SDMT. At 10-year follow-up, age, EDSS, grey matter volume (GMV) and T1 LV explained 39.4% of the variance of SDMT change. CONCLUSION: This longitudinal study shows that baseline MRI-markers, demographic and clinical data can help predict worsening IPS. Identification of patients at risk of IPS decline is of importance as follow-up, treatment and rehabilitation can be optimized.

Topics & Concepts

Multiple sclerosisAtrophyGrey matterExpanded Disability Status ScalePsychologyMagnetic resonance imagingLongitudinal studyWhite matterMedicinePhysical medicine and rehabilitationAudiologyInternal medicineRadiologyPathologyPsychiatryMultiple Sclerosis Research StudiesCerebral Palsy and Movement DisordersEpilepsy research and treatment
Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study | Litcius