All Title Author
Keywords Abstract

Cognitive Impairment in Relapsing Remitting and Secondary Progressive Multiple Sclerosis Patients: Efficacy of a Computerized Cognitive Screening Battery

DOI: 10.1155/2014/151379

Full-Text   Cite this paper   Add to My Lib


Objective. To investigate the pattern of cognitive impairment in relapsing remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS) patients using a computerized battery. Methods. RRMS patients , SPMS patients , and controls were assessed by Central Nervous System Vital Signs (CNS VS) computerized battery, Trail Making Tests (TMT) A and B, and semantic and phonological verbal fluency tasks. Results. The overall prevalence of cognitive dysfunction was 53.75% (RRMS 38%, SPMS 80%). RRMS patients differed from controls with large effect size on reaction time, medium effect size on TMT A and small on TMT B, phonological verbal fluency, composite memory, psychomotor speed, and cognitive flexibility. SPMS patients differed from controls in all neuropsychological measures (except complex attention) with large effect sizes on TMT A and B, phonological verbal fluency, composite memory, psychomotor speed, reaction time, and cognitive flexibility. Between patient groups, medium effect sizes were present on TMT B and psychomotor speed, while small effect sizes were present on composite memory and processing speed. Conclusion. CNS VS is sensitive in detecting cognitive impairment in RRMS and SPMS patients. Significant impairment in episodic memory, executive function, and processing speed were identified, with gradual increment of the frequency as disease progresses. 1. Introduction The functional consequences of cognitive impairment in multiple sclerosis (MS) patients can be devastating. Cognitive impairment has a direct impact on health-related quality of life at all stages of MS [1]. It reduces physical independence and social activities [2], competence in daily activities [3], personal and community independence [4], medication adherence [5], rehabilitation potential [6], and driving safety [7]. Cognitive impaired MS patients are more likely to be unemployed, while employed MS patients are cognitive preserved [8]. Large studies of MS patients have reported cognitive impairment prevalence rates between 40 and 70% [9, 10]. Cognitive impairment has been demonstrated at all stages and in all subtypes of the disease: clinically isolated syndrome (CIS), relapsing remitting multiple sclerosis (RRMS), secondary progressive multiple sclerosis (SPMS), primary progressive multiple sclerosis (PPMS), and even benign multiple sclerosis [11]. However, the more severe levels of cognitive impairment tend to occur in the progressive phase [12]. Although almost all types of cognitive deficits can be observed in MS [13], the typical profile is


[1]  A. J. Mitchell, J. Benito-León, J. M. González, and J. Rivera-Navarro, “Quality of life and its assessment in multiple sclerosis: integrating physical and psychological components of wellbeing,” The Lancet Neurology, vol. 4, no. 9, pp. 556–566, 2005.
[2]  S. M. Rao, G. J. Leo, L. Ellington, T. Nauertz, L. Bernardin, and F. Unverzagt, “Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning,” Neurology, vol. 41, no. 5, pp. 692–696, 1991.
[3]  Y. Goverover, H. M. Genova, F. G. Hillary, and J. DeLuca, “The relationship between neuropsychological measures and the timed instrumental activities of daily living task in multiple sclerosis,” Multiple Sclerosis, vol. 13, no. 5, pp. 636–644, 2007.
[4]  M. P. Amato, G. Ponziani, G. Pracucci, L. Bracco, G. Siracusa, and L. Amaducci, “Cognitive impairment in early-onset multiple sclerosis: pattern, predictors, and impact on everyday life in a 4-year follow-up,” Archives of Neurology, vol. 52, no. 2, pp. 168–172, 1995.
[5]  J. M. Bruce, L. M. Hancock, P. Arnett, and S. Lynch, “Treatment adherence in multiple sclerosis: association with emotional status, personality, and cognition,” Journal of Behavioral Medicine, vol. 33, no. 3, pp. 219–227, 2010.
[6]  D. W. Langdon and A. J. Thompson, “Multiple sclerosis: a preliminary study of selected variables affecting rehabilitation outcome,” Multiple Sclerosis, vol. 5, no. 2, pp. 94–100, 1999.
[7]  T. D. Marcotte, T. J. Rosenthal, E. Roberts et al., “The contribution of cognition and spasticity to driving performance in multiple sclerosis,” Archives of Physical Medicine and Rehabilitation, vol. 89, no. 9, pp. 1753–1758, 2008.
[8]  K. Honarmand, N. Akbar, N. Kou, and A. Feinstein, “Predicting employment status in multiple sclerosis patients: the utility of the MS functional composite,” Journal of Neurology, vol. 258, no. 2, pp. 244–249, 2011.
[9]  N. D. Chiaravalloti and J. DeLuca, “Cognitive impairment in multiple sclerosis,” The Lancet Neurology, vol. 7, no. 12, pp. 1139–1151, 2008.
[10]  S. M. Rao, G. J. Leo, L. Bernardin, and F. Unverzagt, “Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction,” Neurology, vol. 41, no. 5, pp. 685–691, 1991.
[11]  D. W. Langdon, “Cognition in multiple sclerosis,” Current Opinion in Neurology, vol. 24, no. 3, pp. 244–249, 2011.
[12]  D. R. Denney, L. A. Sworowski, and S. G. Lynch, “Cognitive impairment in three subtypes of multiple sclerosis,” Archives of Clinical Neuropsychology, vol. 20, no. 8, pp. 967–981, 2005.
[13]  R. S. Prakash, E. M. Snook, J. M. Lewis, R. W. Motl, and A. F. Kramer, “Cognitive impairments in relapsing-remitting multiple sclerosis: a meta-analysis,” Multiple Sclerosis, vol. 14, no. 9, pp. 1250–1261, 2008.
[14]  C. Smestad, L. Sandvik, N. I. Landr?, and E. G. Celius, “Cognitive impairment after three decades of multiple sclerosis,” European Journal of Neurology, vol. 17, no. 3, pp. 499–505, 2010.
[15]  M. P. Amato, E. Portaccio, B. Goretti et al., “Relevance of cognitive deterioration in early relapsing-remitting MS: a 3-year follow-up study,” Multiple Sclerosis, vol. 16, no. 12, pp. 1474–1482, 2010.
[16]  S. G. Lynch, B. A. Parmenter, and D. R. Denney, “The association between cognitive impairment and physical disability in multiple sclerosis,” Multiple Sclerosis, vol. 11, no. 4, pp. 469–476, 2005.
[17]  V. Zipoli, B. Goretti, B. Hakiki et al., “Cognitive impairment predicts conversion to multiple sclerosis in clinically isolated syndromes,” Multiple Sclerosis, vol. 16, no. 1, pp. 62–67, 2010.
[18]  M. Deloire, A. Ruet, D. Hamel, M. Bonnet, and B. Brochet, “Early cognitive impairment in multiple sclerosis predicts disability outcome several years later,” Multiple Sclerosis, vol. 16, no. 5, pp. 581–587, 2010.
[19]  A. Achiron, G. M. Doniger, Y. Harel, N. Appleboim-Gavish, M. Lavie, and E. S. Simon, “Prolonged response times characterize cognitive performance in multiple sclerosis,” European Journal of Neurology, vol. 14, no. 10, pp. 1102–1108, 2007.
[20]  W. I. McDonald, A. Compston, G. Edan et al., “Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis,” Annals of Neurology, vol. 50, no. 1, pp. 121–127, 2001.
[21]  J. F. Kurtzke, “Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS),” Neurology, vol. 33, no. 11, pp. 1444–1452, 1983.
[22]  I. Zalonis, E. Kararizou, N. I. Triantafyllou et al., “A normative study of the trail making test A and B in Greek adults,” Clinical Neuropsychologist, vol. 22, no. 5, pp. 842–850, 2007.
[23]  M. H. Kosmidis, C. H. Vlahou, P. Panagiotaki, and G. Kiosseoglou, “The verbal fluency task in the Greek population: normative data, and clustering and switching strategies,” Journal of the International Neuropsychological Society, vol. 10, no. 2, pp. 164–172, 2004.
[24]  M. R. Basso, S. Beason-Hazen, J. Lynn, K. Rammohan, and R. A. Bornstein, “Screening for cognitive dysfunction in multiple sclerosis,” Archives of Neurology, vol. 53, no. 10, pp. 980–984, 1996.
[25]  L. Messinis, M. H. Kosmidis, E. Lyros, and P. Papathanasopoulos, “Assessment and rehabilitation of cognitive impairment in multiple sclerosis,” International Review of Psychiatry, vol. 22, no. 1, pp. 22–34, 2010.
[26]  S. C. J. Huijbregts, N. F. Kalkers, L. M. J. de Sonneville, V. de Groot, I. E. W. Reuling, and C. H. Polman, “Differences in cognitive impairment of relapsing remitting, secondary, and primary progressive MS,” Neurology, vol. 63, no. 2, pp. 335–339, 2004.
[27]  K. K. Zakzanis, “Distinct neurocognitive profiles in multiple sclerosis subtypes,” Archives of Clinical Neuropsychology, vol. 15, no. 2, pp. 115–136, 2000.
[28]  J. A. Wilken, R. Kane, C. L. Sullivan et al., “The utility of computerized neuropsychological assessment of cognitive dysfunction in patients with relapsing-remitting multiple sclerosis,” Multiple Sclerosis, vol. 9, no. 2, pp. 119–127, 2003.
[29]  N. Akbar, K. Honarmand, N. Kou, and A. Feinstein, “Validity of a computerized version of the symbol digit modalities test in multiple sclerosis,” Journal of Neurology, vol. 258, no. 3, pp. 373–379, 2011.
[30]  H. Lapshin, K. L. Lanctot, P. O'Connor, and A. Feinstein, “Assessing the validity of a computer-generated cognitive screening instrument for patients with multiple sclerosis,” Multiple Sclerosis, vol. 19, no. 14, pp. 1905–1912, 2013.
[31]  A. Ruet, M. S. Deloire, J. Charre-Morin, D. Hamel, and B. Brochet, “A new computerized cognitive test for the detection of information processing speed impairment in multiple sclerosis,” Multiple Sclerosis, vol. 19, no. 12, pp. 1665–1672, 2013.
[32]  H. Lapshin, B. Audet, and A. Feinstein, “Detecting cognitive dysfunction in a busy multiple sclerosis clinical setting: a computer generated approach,” European Journal of Neurology, 2013.
[33]  M. R. Piras, I. Magnano, E. D. G. Canu et al., “Longitudinal study of cognitive dysfunction in multiple sclerosis: neuropsychological, neuroradiological, and neurophysiological findings,” Journal of Neurology Neurosurgery and Psychiatry, vol. 74, no. 7, pp. 878–885, 2003.
[34]  E. Woo, “Computerized neuropsychological assessments,” CNS Spectrums, vol. 13, no. 10, supplement 16, pp. 14–17, 2008.
[35]  A. N. Cernich, D. M. Brennana, L. M. Barker, and J. Bleiberg, “Sources of error in computerized neuropsychological assessment,” Archives of Clinical Neuropsychology, vol. 22, no. 1, pp. 39–48, 2007.


comments powered by Disqus