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Cognition and Cognitive Fatigability: Association with Employment Status in Multiple Sclerosis

Published online by Cambridge University Press:  25 October 2022

Elise S. MacAdam ,
Jason A. Berard Open the ORCID record for Jason A. Berard [Opens in a new window]  and
Lisa A.S. Walker Open the ORCID record for Lisa A.S. Walker [Opens in a new window]
Elise S. MacAdam
Affiliation:
Queen’s University, Kingston, Canada
Jason A. Berard*
Affiliation:
Ottawa Hospital Research Institute, Ottawa, Canada
Lisa A.S. Walker
Affiliation:
Ottawa Hospital Research Institute, Ottawa, Canada University of Ottawa Brain and Mind Research Institute, Ottawa, Canada
*
Corresponding author: Dr. Jason Berard, Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, K1H 8L6, Canada. Email: jberard@ohri.ca
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Abstract:

Background:

Slowed processing speed impacts employment status in people with multiple sclerosis (PwMS). Studies on the Multiple Sclerosis Functional Composite (MSFC), which includes the Paced Auditory Serial Addition Test (PASAT), have demonstrated that the combined score predicts employment status. Whether PASAT performance alone is associated with employment status is less clear. In addition, no studies have yet evaluated whether cognitive fatigability (CF), as measured with the PASAT, is associated with employment status. The aim of the current study was to examine the association between PASAT performance, CF, and employment status in PwMS.

Methods:

Hundred and eighty-six PwMS completed the PASAT as part of a larger neuropsychological battery. ANOVAs and chi-squares analyzed group differences between employed and unemployed participants with respect to demographics, PASAT performance scores, and CF. Linear regression determined whether PASAT performance and/or CF scores were associated with employment status.

Results:

After controlling for demographic influences, group differences were noted between employed vs. unemployed individuals on PASAT performance scores only. Employment status was associated with PASAT performance scores but not CF.

Conclusions:

The current study confirmed that PASAT performance is associated with employment status in MS. Given that CF was not associated, it seems difficulties with information processing speed (IPS) and working memory have more impact on a PwMS’s ability to remain employed rather than within-task performance decline.

Résumé :

RÉSUMÉ :

Cognition et fatigabilité cognitive : association avec la situation professionnelle dans le cas d’individus atteints de sclérose en plaques.

Contexte :

Le ralentissement de la vitesse de traitement cognitif a un impact sur la situation professionnelle d’individus atteints de sclérose en plaques (SP). Des études portant sur l’outil d’évaluation Studies on the Multiple Sclerosis Functional Composite (MSFC), lequel inclut le Paced Auditory Serial Addition Test (PASAT), ont ainsi démontré que le score combiné obtenu dans le cadre de cette évaluation permet de prédire la situation professionnelle d’un individu. Il est toutefois loin d’être clair que les résultats obtenus au PASAT puissent être associés à la situation professionnelle. De plus, aucune étude n’a encore évalué si la fatigabilité cognitive (FC), telle que mesurée par le PASAT, peut être associée à cette même situation. L’objectif de la présente étude a donc consisté à examiner l’association entre les résultats obtenus au PASAT, la fatigabilité cognitive et la situation professionnelle d’individus atteints de SP.

Méthodes :

Au total, 186 d’entre eux ont complété un PASAT dans le cadre d’une batterie de tests neurologiques plus vaste. Des tests d’analyse de la variance et du khi carré nous ont ainsi permis de nous pencher sur les différences entre les participants employés et chômeurs en ce qui regarde leurs caractéristiques démographiques, leurs résultats au PASAT et leur FC. La méthode de régression linéaire nous a enfin permis de déterminer si les résultats obtenus au PASAT et/ou les scores en matière de FC étaient associés à la situation professionnelle d’un individu.

Résultats :

Après avoir contrôlé des facteurs d’ordre démographique, des différences entre groupes ont été notées en ce qui regarde uniquement leurs résultats au PASAT. La situation professionnelle d’un individu peut en cela être associée à des résultats au PASAT mais pas à la FC.

Conclusions :

La présente étude a confirmé que des résultats au PASAT pouvaient être associés à la situation professionnelle d’individus atteints de SP. Étant donné que la FC n’y était pas associée, il semble que des difficultés liées à la vitesse de traitement de l’information (VTI) et à la mémoire au travail aient plus d’impact sur la capacité d’individus atteints de SP à conserver leur emploi que le déclin des performances liées à des tâches particulières.

Keywords

Multiple sclerosisCognitionNeuropsychologyCognitive fatigabilityPASAT
Type
Original Article
Information
Canadian Journal of Neurological Sciences , Volume 50 , Issue 6 , November 2023 , pp. 870 - 875
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Canadian Neurological Sciences Federation

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References

Morrow, SA, Drake, A, Zivadinov, R, Munschauer, F, Weinstock-Guttman, B, Benedict, RH. Predicting loss of employment over three years in multiple sclerosis: clinically meaningful cognitive decline. Clin Neuropsychol. 2010;24:1131–45.CrossRefGoogle ScholarPubMed
Amato, MP, Prestipino, E, Bellinvia, A, et al. Cognitive impairment in multiple sclerosis: an exploratory analysis of environmental and lifestyle risk factors. PLoS One. 2019;14:e0222929.CrossRefGoogle ScholarPubMed
Nasios, G, Bakirtzis, C, Messinis, L. Cognitive impairment and brain reorganization in MS: underlying mechanisms and the role of neurorehabilitation. Front Neurol. 2020;11:147.CrossRefGoogle ScholarPubMed
Ghasemi, N, Razavi, S, Nikzad, E. Multiple sclerosis: pathogenesis, symptoms, diagnoses and cell-based therapy. Cell J. 2017;19:1–10.Google ScholarPubMed
Walker, LAS, Lindsay-Brown, AP, Berard, JA. Cognitive fatigability interventions in neurological conditions: a systematic review. Neurol Ther. 2019;8:251–71.CrossRefGoogle ScholarPubMed
Brassington, JC, Marsh, NV. Neuropsychological aspects of multiple sclerosis. Neuropsychol Rev. 1998;8:43–77.CrossRefGoogle ScholarPubMed
Minden, SL, Frankel, D, Hadden, L, Perloffp, J, Srinath, KP, Hoaglin, DC. The Sonya Slifka Longitudinal Multiple Sclerosis Study: methods and sample characteristics. Mult Scler. 2006;12:24–38.CrossRefGoogle ScholarPubMed
Schwid, SR, Covington, M, Segal, BM, Goodman, AD. Fatigue in multiple sclerosis: current understanding and future directions. J Rehabil Res Dev. 2002;39:211–24.Google ScholarPubMed
Krupp, LB, Alvarez, LA, LaRocca, NG, Scheinberg, LC. Fatigue in multiple sclerosis. Arch Neurol. 1988;45:435–7.10.1001/archneur.1988.00520280085020CrossRefGoogle ScholarPubMed
Krupp, LB, LaRocca, NG, Muir-Nash, J, Steinberg, AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46:1121–3.10.1001/archneur.1989.00520460115022CrossRefGoogle ScholarPubMed
Fisk, JD, Ritvo, PG, Ross, L, Haase, DA, Marrie, TJ, Schlech, WF. Measuring the functional impact of fatigue: initial validation of the fatigue impact scale. Clin Infect Dis. 1994;18:S79–83.CrossRefGoogle ScholarPubMed
Mills, RJ, Young, CA, Pallant, JF, Tennant, A. Development of a patient reported outcome scale for fatigue in multiple sclerosis: The Neurological Fatigue Index (NFI-MS). Health Qual Life Outcomes. 2010;8:22.CrossRefGoogle ScholarPubMed
Berard, JA, Fang, Z, Walker, LAS, et al. Imaging cognitive fatigability in multiple sclerosis: objective quantification of cerebral blood flow during a task of sustained attention using ASL perfusion fMRI. Brain Imaging Behav. 2020;14:2417–28.10.1007/s11682-019-00192-7CrossRefGoogle ScholarPubMed
Kluger, BM, Krupp, LB, Enoka, RM. Fatigue and fatigability in neurologic illnesses: proposal for a unified taxonomy. Neurology. 2013;80:409–16.CrossRefGoogle ScholarPubMed
Bryant, D, Chiaravalloti, ND, DeLuca, J. Objective measurement of cognitive fatigue in multiple sclerosis. Rehabil Psychol. 2004;49:114–22.CrossRefGoogle Scholar
Walker, LA, Berard, JA, Berrigan, LI, Rees, LM, Freedman, MS. Detecting cognitive fatigue in multiple sclerosis: method matters. J Neurol Sci. 2012;316:86–92.CrossRefGoogle ScholarPubMed
Berard, JA, Smith, AM, Walker, LAS. A longitudinal evaluation of cognitive fatigue on a task of sustained attention in early relapsing-remitting multiple sclerosis. Int J MS Care. 2018;20:55–61.CrossRefGoogle ScholarPubMed
Linnhoff, S, Fiene, M, Heinze, HJ, Zaehle, T. Cognitive fatigue in multiple sclerosis: an objective approach to diagnosis and treatment by transcranial electrical stimulation. Brain Sci. 2019;9:100.CrossRefGoogle ScholarPubMed
Tombaugh, TN. A comprehensive review of the Paced Auditory Serial Addition Test (PASAT). Arch Clin Neuropsychol. 2006;21:53–76.CrossRefGoogle ScholarPubMed
Berard, JA, Smith, AM, Walker, LAS. Predictive models of cognitive fatigue in multiple sclerosis. Arch Clin Neuropsychol. 2019;34:31–8.CrossRefGoogle ScholarPubMed
Morrow, SA, Rosehart, H, Johnson, AM. Diagnosis and quantification of cognitive fatigue in multiple sclerosis. Cogn Behav Neurol. 2015;28:27–32.CrossRefGoogle ScholarPubMed
Clemens, L, Langdon, D. How does cognition relate to employment in multiple sclerosis? A systematic review. Mult Scler Relat Disord. 2018;26:183–91.CrossRefGoogle ScholarPubMed
Kobelt, G, Thompson, A, Berg, J, Gannedahl, M, Eriksson, J. New insights into the burden and costs of multiple sclerosis in Europe. Mult Scler. 2017;23:1123–36.CrossRefGoogle ScholarPubMed
Coyne, KS, Boscoe, AN, Currie, BM, Landrian, AS, Wandstrat, TL. Understanding drivers of employment changes in a multiple sclerosis population. Int J MS Care. 2015;17:245–52.CrossRefGoogle Scholar
Ford, DV, Jones, KH, Middleton, RM, et al. The feasibility of collecting information from people with Multiple Sclerosis for the UK MS Register via a web portal: characterising a cohort of people with MS. BMC Med Inform Decis Mak. 2012;12:73.CrossRefGoogle Scholar
Kavaliunas, A, Wiberg, M, Tinghog, P, et al. Earnings and financial compensation from social security systems correlate strongly with disability for multiple sclerosis patients. PLoS One. 2015;10:e0145435.CrossRefGoogle ScholarPubMed
Krause, I, Kern, S, Horntrich, A, Ziemssen, T. Employment status in multiple sclerosis: impact of disease-specific and non-disease-specific factors. Mult Scler. 2013;19:1792–9.CrossRefGoogle ScholarPubMed
Honarmand, K, Akbar, N, Kou, N, Feinstein, A. Predicting employment status in multiple sclerosis patients: the utility of the MS functional composite. J Neurol. 2011;258:244–9.CrossRefGoogle Scholar
Strober, L, Chiaravalloti, N, Moore, N, DeLuca, J. Unemployment in multiple sclerosis (MS): utility of the MS Functional Composite and cognitive testing. Mult Scler. 2014;20:112–5.CrossRefGoogle ScholarPubMed
Cutter, GR, Baier, ML, Rudick, RA, et al. Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain. 1999;122:871–82.CrossRefGoogle ScholarPubMed
Fisk, JD, Archibald, CJ. Limitations of the Paced Auditory Serial Addition Test as a measure of working memory in patients with multiple sclerosis. J Int Neuropsychol Soc. 2001;7:363–72.CrossRefGoogle ScholarPubMed
Scheinberg, L, Holland, N, Larocca, N, Laitin, P, Bennett, A, Hall, H. Multiple sclerosis; earning a living. N Y State J Med. 1980;80:1395–400.Google ScholarPubMed
Pompeii, LA, Moon, SD, McCrory, DC. Measures of physical and cognitive function and work status among individuals with multiple sclerosis: a review of the literature. J Occup Rehabil. 2005;15:69–84.CrossRefGoogle ScholarPubMed
LaRocca, N, Kalb, R, Kendall, P, Scheinberg, L. The role of disease and demographic factors in the employment of patients with multiple sclerosis. Arch Neurol. 1982;39:256.CrossRefGoogle ScholarPubMed
Vijayasingham, L, Mairami, FF. Employment of patients with multiple sclerosis: the influence of psychosocial-structural coping and context. Degener Neurol Neuromuscul Dis. 2018;8:15–24.Google ScholarPubMed
Cadden, M, Arnett, P. Factors associated with employment status in individuals with multiple sclerosis. Int J MS Care. 2015;17:284–91.CrossRefGoogle ScholarPubMed
Costa, SL, Genova, HM, DeLuca, J, Chiaravalloti, ND. Information processing speed in multiple sclerosis: past, present, and future. Mult Scler. 2017;23:772–89.CrossRefGoogle ScholarPubMed
Eizaguirre, MB, Vanotti, S, Merino, A, et al. The role of information processing speed in clinical and social support variables of patients with multiple sclerosis. J Clin Neurol. 2018;14:472–7.CrossRefGoogle ScholarPubMed
Landmeyer, NC, Burkner, P, Wiendl, H, Ruck, T, Hartune, H, et al. Disease-modifying treatments and cognition in relpasing-remitting multiple sclerosi: a meta-analysis. Neurology. 2020;94:e2373–e2383.CrossRefGoogle ScholarPubMed
Chen, MH, Goverover, Y, Genova, HM, DeLuca, J. Cognitive efficacy of pharmcologic treatments in multiple sclerosis: a systematic review. CNS Drugs. 2020;34:599–628.CrossRefGoogle Scholar
Putzki, N, Katsarava, Z, Vago, S, Diener, HC, Limmroth, V. Prevelance and severity of multiple-sclerosi-assciated fatigue in treated and untreated patients. Eur Neurol. 2008;59:136–42.CrossRefGoogle Scholar
Hadjimichael, O, Vollmer, T, Oleen-Burkey, M. Fatigue characteristics in multiple sclerosis: the North American Research Committee on Multiple Sclerosis (NARCOMS) survey. Health Qual Life Outcomes. 2008;6:100.CrossRefGoogle ScholarPubMed
Iriarte, J, Subira, ML, Castro, P. Modalities of fatigue in multiple sclerosis: correlation with clinical and biological factors. Mult Scler. 2000;6:124–30.CrossRefGoogle ScholarPubMed