Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37491
Title: The relationship between processing speed and verbal and non-verbal new learning and memory in progressive multiple sclerosis
Authors: Chiaravalloti, Nancy D.
DeLuca, John
Salter, Amber
Amato, Maria Pia
Brichetto, Giampaolo
Chataway, Jeremy
Dalgas, Ulrik
Farrell, Rachel
FEYS, Peter 
Filippi, Massimo
Freeman, Jennifer
Inglese, Matilde
Meza, Cecilia
Moore, Nancy B.
Motl, Robert W.
Rocca, Maria Assunta
Sandroff, Brian M.
Cutter, Gary
Feinstein, Anthony
Issue Date: 2022
Publisher: SAGE PUBLICATIONS LTD
Source: Multiple Sclerosis Journal,
Status: Early view
Abstract: Objective: Processing speed (PS) deficits are the most common cognitive deficits in multiple sclerosis (MS), followed by learning and memory deficits, and are often an early cognitive problem. It has been argued that impaired PS is a primary consequence of MS, which in turn decreases learning. The current analysis examined the association between PS and learning in a large cohort of individuals with progressive MS. Methods: Baseline data from a randomized clinical trial on rehabilitation taking place at 11 centers across North America and Europe were analyzed. Participants included 275 individuals with clinically definite progressive MS (primary, secondary) consented into the trial. Results: Symbol Digit Modalities Test (SDMT) significantly correlated with California Verbal Learning Test-II (CVLT-II) (r = 0.21, p = 0.0003) and Brief Visuospatial Memory Test-Revised (BVMT-R) (r = 0.516, p < 0.0001). Receiver operating characteristic (ROC) analysis of the SDMT z score to distinguish between impaired and non-impaired CVLT-II performance demonstrated an area under the curve (AUC) of 0.61 (95% confidence interval (CI): 0.55-0.68) and a threshold of -1.62. ROC analysis between SDMT and BVMT-R resulted in an AUC of 0.77 (95% CI: 0.71-0.83) and threshold of -1.75 for the SDMT z score to predict impaired BVMT-R. Conclusion: Results indicate little ability beyond chance to predict CVLT-II from SDMT (61%), albeit statistically significant. In contrast, there was a 77% chance that the model could distinguish between impaired and non-impaired BVMT-R. Several potential explanations are discussed.
Notes: Chiaravalloti, ND (corresponding author), Kessler Fdn, 120 Eagle Rock Ave,Suite 100, E Hanover, NJ 07936 USA.
nchiaravalloti@kesslerfoundation.org
Keywords: Progressive multiple sclerosis; BICAMS; cognition; SDMT; processing;speed; memory
Document URI: http://hdl.handle.net/1942/37491
ISSN: 1352-4585
e-ISSN: 1477-0970
DOI: 10.1177/13524585221088190
ISI #: WOS:000797736100001
Rights: © The Author(s), 2022. Article reuse guidelines: sagepub.com/journalspermissions
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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