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Reduction in Cognitive Processing Speed Surrounding Multiple Sclerosis Relapse

Authors :
Kyla A. McKay
Sahl K. Bedri
Ali Manouchehrinia
Leszek Stawiarz
Tomas Olsson
Jan Hillert
Katharina Fink
Source :
Annals of neurology. 91(3)
Publication Year :
2022

Abstract

The purpose of this study was to explore the longitudinal relationship between multiple sclerosis (MS) relapses and information processing efficiency among persons with relapsing-remitting MS.We conducted a Swedish nationwide cohort study of persons with incident relapsing-remitting MS (2001-2019). Relapse information and symbol digit modalities test (SDMT) scores were obtained from the Swedish MS Registry. Follow-up was categorized into 2 periods based on relapse status: "relapse" (90 days pre-relapse to 730 days post-relapse, subdivided into 10 periods) and "remission." Linear mixed models compared SDMT scores during the relapse periods to SDMT scores recorded during remission (reference) with results reported as β-coefficients and 95% confidence intervals (CIs), adjusted for age, sex, SDMT type (written vs oral), time-varying, disease-modifying therapy exposure and sequence of SDMT.Over a mean (SD) follow-up of 10.7 (4.3) years, 31,529 distinct SDMTs were recorded among 3,877 persons with MS. There was a significant decline in information processing efficiency that lasted from 30 days pre-relapse up to 550 days post-relapse, with the largest decline occurring 0 to 30 days post-relapse (β-coefficient: -4.00 (95% CI = -4.61 to -3.39), relative to the period of remission.We found evidence of cognitive change up to 1 month prior to relapse onset. The reduction in SDMT lasted 1.5 years and was clinically significant up to 3 months post-relapse. These results suggest that the effects of a relapse on cognition are longer than previously thought and highlight the importance of reducing relapse rates as a potential means of preserving cognitive function. ANN NEUROL 2022;91:417-423.

Details

ISSN :
15318249
Volume :
91
Issue :
3
Database :
OpenAIRE
Journal :
Annals of neurology
Accession number :
edsair.doi.dedup.....8719380df0d0d8b7e8717b30451631c6