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Early detection of cognitive dysfunction in patients with multiple sclerosis: Implications on outcome

  • Maged Abdel Naseer (a1), Shereen Fathi (a1), Dalia M. Labib (a1), Dalia H. Khalil (a2), Alshaimaa M. Aboulfotooh (a1) and Rehab Magdy (a1)...



Cognitive impairment in multiple sclerosis (MS) has a complex relationship with disease progression and neurodegeneration. The aim of this study was to shed light on the importance of early detection of cognitive impairment in MS patients.


The study comprised two groups of definite MS patients, relapsing remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS), each with 25 patients. Physical disability was assessed using the Expanded Disability Status Scale (EDSS), while the risk of secondary progression was assessed using the Bayesian Risk Estimate for Multiple Sclerosis (BREMS). Cognitive functions were assessed using the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and Controlled Oral Word Association Test (COWAT). Assessment of neurodegeneration was done using optical coherence tomography (OCT) via quantification of retinal nerve fiber layer (RNFL).


MS patients with higher RNFL thickness demonstrated a larger learning effect size than patients who had lower values in RNFL thickness regardless of MS type. RRMS patients showed significant improvement in delayed recall after giving cues than SPMS. The symbol digit modalities test was the only neuropsychological test that showed a significant negative correlation with EDSS (P = 0.009). There was a statistically significant negative correlation between BREMS scores and performance in all neuropsychological tests.


Inclusion of neurocognitive evaluation in the periodic assessment of MS patients is mandatory to detect patients at increased risk of secondary progression. The thickness of RNFL is suggested as a method to estimate the expected benefit of cognitive rehabilitation, regardless of MS type.


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Albanese, M., Zagaglia, S., Landi, D., Boffa, L., Nicoletti, C. G., Marciani, M. G., … Centonze, D. (2016). Cerebrospinal fluid lactate is associated with multiple sclerosis disease progression. Journal of Neuroinflammation, 13, 36. doi: 10.1186/s12974-016-0502-1.
American Psychiatric Publishing. (2013). Diagnostic and statistical manual of mental disorders (DSM-5) (5th ed.). Arlington, VA: American Psychiatric Publishing.
Bartels, C., Wegrzyn, M., Wiedl, A., Ackermann, V., & Ehrenreich, H. (2010). Practice effects in healthy adults: A longitudinal study on frequent repetitive cognitive testing. BMC Neuroscience, 11, 118. doi: 10.1186/1471-2202-11-118.
Benedict, R. (1997). Brief visuospatial memory test-revised professional manual. Odessa: Psychological Assessment Resources.
Benedict, R. H., Amato, M. P., Boringa, J., Brochet, B., Foley, F., Fredrikson, S., … Langdon, D. (2012). Brief International Cognitive Assessment for MS (BICAMS): International standards for validation. BMC Neurology, 12, 55. doi: 10.1186/1471-2377-12-55.
Benton, A. L., Hamsher, S. K., & Sivan, A. B. (1983). Multilingual aplasia examination (2nd ed.). Iowa City, IA: AJA Associates.
Bergamaschi, R., Quaglini, S., Tavazzi, E., Amato, M. P., Paolicelli, D., Zipoli, V., … Trojano, M. (2016). Immunomodulatory therapies delay disease progression in multiple sclerosis. Multiple Sclerosis, 22(13), 17321740. doi: 10.1177/1352458512445941.
Bergamaschi, R., Quaglini, S., Trojano, M., Amato, M. P., Tavazzi, E., Paolicelli, D., … Cosi, V. (2007). Early prediction of the long term evolution of multiple sclerosis: The Bayesian Risk Estimate for Multiple Sclerosis (BREMS) score. Journal of Neurology, Neurosurgery, and Psychiatry, 78(7), 757759. doi: 10.1136/jnnp.2006.107052.
Bonavita, S., Sacco, R., Della Corte, M., Esposito, S., Sparaco, M., d’Ambrosio, A., … Tedeschi, G. (2015). Computer-aided cognitive rehabilitation improves cognitive performances and induces brain functional connectivity changes in relapsing remitting multiple sclerosis patients: An exploratory study. Journal of Neurology, 262(1), 91100. doi: 10.1007/s00415-014-7528-z.
Brochet, B., Deloire, M. S., Bonnet, M., Salort-Campana, E., Ouallet, J. C., Petry, K. G., & Dousset, V. (2008). Should SDMT substitute for PASAT in MSFC? A 5-year longitudinal study. Multiple Sclerosis, 14(9), 12421249. doi: 10.1177/1352458508094398.
Chiaravalloti, N. D., & DeLuca, J. (2008). Cognitive impairment in multiple sclerosis. Lancet Neurology, 7(12), 11391151. doi: 10.1016/s1474-4422(08)70259-x.
Delis, D., Kramer, J., Kaplan, E., & Ober, B. (2000). The California verbal learning test (2nd ed.). San Antonio: Psychological Corporation. Adult Version.
Dendrou, C. A., Fugger, L., & Friese, M. A. (2015). Immunopathology of multiple sclerosis. Nature Reviews Immunology, 15(9), 545558. doi: 10.1038/nri3871.
Fiol, M. P., Ysrraelit, M. C., Gaitán, M. I., & Correale, J. (2016). Progressive multiple sclerosis: From pathogenic mechanisms to treatment. Brain, 140(3), 527546. doi: 10.1093/brain/aww258.
Frau, J., Fenu, G., Signori, A., Coghe, G., Lorefice, L., Barracciu, M. A., … Cocco, E. (2018). A cross-sectional and longitudinal study evaluating brain volumes, RNFL, and cognitive functions in MS patients and healthy controls. BMC Neurology, 18(1), 67. doi: 10.1186/s12883-018-1065-9.
Gold, R., Wolinsky, J. S., Amato, M. P., & Comi, G. (2010). Evolving expectations around early management of multiple sclerosis. Therapeutic Advances in Neurological Disorders, 3(6), 351367. doi: 10.1177/1756285610385608.
Hulst, H. E., Geurts, J. J. G., Meijer, K. A., Steenwijk, M. D., Schoonheim, M. M., van Geest, Q., … Uitdehaag, B. M. J. (2018). Predicting cognitive decline in multiple sclerosis: A 5-year follow-up study. Brain, 141(9), 26052618. doi: 10.1093/brain/awy202.
IBM. (2011). IBM SPSS statistics for windows (20.0 ed.). Armonk, NY: IBM Corp.
Kalmar, J. H., Gaudino, E. A., Moore, N. B., Halper, J., & Deluca, J. (2008). The relationship between cognitive deficits and everyday functional activities in multiple sclerosis. Neuropsychology, 22(4), 442449. doi: 10.1037/0894-4105.22.4.442.
Kurtzke, J. F. (1983). Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology, 33(11), 14441452.
Matlach, J., Wagner, M., Malzahn, U., & Gobel, W. (2014). Repeatability of peripapillary retinal nerve fiber layer and inner retinal thickness among two spectral domain optical coherence tomography devices. Investigative Ophthalmology & Visual Science, 55(10), 65366546. doi: 10.1167/iovs.14-15072.
Mattioli, F., Stampatori, C., Zanotti, D., Parrinello, G., & Capra, R. (2010). Efficacy and specificity of intensive cognitive rehabilitation of attention and executive functions in multiple sclerosis. Journal of the Neurological Sciences, 288(1–2), 101105. doi: 10.1016/j.jns.2009.09.024.
Medaglia, J. D., Pasqualetti, F., Hamilton, R. H., Thompson-Schill, S. L., & Bassett, D. S. (2017). Brain and cognitive reserve: Translation via network control theory. Neuroscience & Biobehavioral Reviews, 75, 5364. doi: 10.1016/j.neubiorev.2017.01.016.
Moccia, M., Lanzillo, R., Palladino, R., Chang, K. C., Costabile, T., Russo, C., … Brescia Morra, V. (2016). Cognitive impairment at diagnosis predicts 10-year multiple sclerosis progression. Multiple Sclerosis, 22(5), 659667. doi: 10.1177/1352458515599075.
Muller, S., Saur, R., Greve, B., Melms, A., Hautzinger, M., Fallgatter, A. J., & Leyhe, T. (2013). Similar autobiographical memory impairment in long-term secondary progressive multiple sclerosis and Alzheimer’s disease. Multiple Sclerosis, 19(2), 225232. doi: 10.1177/1352458512450352.
Nutter-Upham, K. E., Saykin, A. J., Rabin, L. A., Roth, R. M., Wishart, H. A., Pare, N., & Flashman, L. A. (2008). Verbal fluency performance in amnestic MCI and older adults with cognitive complaints. Archives of Clinical Neuropsychology, 23(3), 229241. doi: 10.1016/j.acn.2008.01.005.
Pitteri, M., Romualdi, C., Magliozzi, R., Monaco, S., & Calabrese, M. (2017). Cognitive impairment predicts disability progression and cortical thinning in MS: An 8-year study. Multiple Sclerosis, 23(6), 848854. doi: 10.1177/1352458516665496.
Polman, C. H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M., … Wolinsky, J. S. (2011). Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Annals of Neurology, 69(2), 292302. doi: 10.1002/ana.22366.
Rao, J. A., Jenkins, L. M., Hymen, E., Feigon, M., Weisenbach, S. L., Zubieta, J. K., & Langenecker, S. A. (2016). Differential resting state connectivity patterns and impaired semantically cued list learning test performance in early course remitted major depressive disorder. Journal of the International Neuropsychological Society, 22(2), 225239. doi: 10.1017/s1355617716000011.
Rouleau, I., Dagenais, E., Tremblay, A., Demers, M., Roger, E., Jobin, C., & Duquette, P. (2018). Prospective memory impairment in multiple sclerosis: A review. The Clinical Neuropsychologist, 32(5), 922936. doi: 10.1080/13854046.2017.1361473.
Sicotte, N. L., Kern, K. C., Giesser, B. S., Arshanapalli, A., Schultz, A., Montag, M., … Bookheimer, S. Y. (2008). Regional hippocampal atrophy in multiple sclerosis. Brain, 131(Pt. 4), 11341141. doi: 10.1093/brain/awn030.
Smith, A. (2002). Symbol digit modalities test: Manual. Los Angeles, CA: Western Psychological Corporation: Western Psychological Services (Firm).
Turken, A., Whitfield-Gabrieli, S., Bammer, R., Baldo, J. V., Dronkers, N. F., & Gabrieli, J. D. (2008). Cognitive processing speed and the structure of white matter pathways: Convergent evidence from normal variation and lesion studies. Neuroimage, 42(2), 10321044. doi: 10.1016/j.neuroimage.2008.03.057.
Wang, H. X., MacDonald, S. W., & Dekhtyar, S. (2017). Association of lifelong exposure to cognitive reserve-enhancing factors with dementia risk: A community-based cohort study. PLoS Medicine, 14(3), e1002251. doi: 10.1371/journal.pmed.1002251.


Early detection of cognitive dysfunction in patients with multiple sclerosis: Implications on outcome

  • Maged Abdel Naseer (a1), Shereen Fathi (a1), Dalia M. Labib (a1), Dalia H. Khalil (a2), Alshaimaa M. Aboulfotooh (a1) and Rehab Magdy (a1)...


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