Evaluation of a self-administered iPad
Cognition
Cognitive assessment
MRI
Multiple sclerosis
Processing speed
iPad®-based test
Journal
Journal of neurology
ISSN: 1432-1459
Titre abrégé: J Neurol
Pays: Germany
ID NLM: 0423161
Informations de publication
Date de publication:
05 Mar 2024
05 Mar 2024
Historique:
received:
08
01
2024
accepted:
23
02
2024
revised:
21
02
2024
medline:
5
3
2024
pubmed:
5
3
2024
entrez:
5
3
2024
Statut:
aheadofprint
Résumé
Limited resources often hinder regular cognitive assessment of people with multiple sclerosis (pwMS) in standard clinical care. A self-administered iPad®-based cognitive screening-tool (Processing Speed Test; PST) might mitigate this problem. To evaluate the PST in clinical routine. We investigated the feasibility of the PST in both a quiet and a waiting room setting. We assessed the validity of the PST in comparison with the established Symbol Digit Modalities Test (SDMT). We explored associations between processing speed assessments and the Brief International Cognitive Assessment for MS (BICAMS), magnetic resonance imaging (MRI) parameters, and psychological factors. Additionally, we explored the ability of the PST to detect impairment in processing speed compared to the SDMT. The PST was feasible in the waiting room setting. PST and SDMT correlated comparably with the BICAMS, MRI parameters, and psychological variables. Of 172 pwMS, 50 (30.8%) showed cognitive impairment according to the BICAMS; respective values were 47 (27.3%) for the SDMT and 9 (5.2%) for the PST. The PST performed in a waiting room setting correlates strongly with established cognitive tests. It thus may be used to assess processing speed in a resource-efficient manner and complement cognitive assessment in clinical routine. Despite comparable validity of the PST and SDMT, we identified more pwMS with impaired processing speed using normative data of the SDMT compared to the PST and advise caution, that the common cut-off score of - 1.5 SD from the current PST is not appropriate in Europe.
Sections du résumé
BACKGROUND
BACKGROUND
Limited resources often hinder regular cognitive assessment of people with multiple sclerosis (pwMS) in standard clinical care. A self-administered iPad®-based cognitive screening-tool (Processing Speed Test; PST) might mitigate this problem.
OBJECTIVE
OBJECTIVE
To evaluate the PST in clinical routine.
METHODS
METHODS
We investigated the feasibility of the PST in both a quiet and a waiting room setting. We assessed the validity of the PST in comparison with the established Symbol Digit Modalities Test (SDMT). We explored associations between processing speed assessments and the Brief International Cognitive Assessment for MS (BICAMS), magnetic resonance imaging (MRI) parameters, and psychological factors. Additionally, we explored the ability of the PST to detect impairment in processing speed compared to the SDMT.
RESULTS
RESULTS
The PST was feasible in the waiting room setting. PST and SDMT correlated comparably with the BICAMS, MRI parameters, and psychological variables. Of 172 pwMS, 50 (30.8%) showed cognitive impairment according to the BICAMS; respective values were 47 (27.3%) for the SDMT and 9 (5.2%) for the PST.
CONCLUSIONS
CONCLUSIONS
The PST performed in a waiting room setting correlates strongly with established cognitive tests. It thus may be used to assess processing speed in a resource-efficient manner and complement cognitive assessment in clinical routine. Despite comparable validity of the PST and SDMT, we identified more pwMS with impaired processing speed using normative data of the SDMT compared to the PST and advise caution, that the common cut-off score of - 1.5 SD from the current PST is not appropriate in Europe.
Identifiants
pubmed: 38441609
doi: 10.1007/s00415-024-12274-8
pii: 10.1007/s00415-024-12274-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Biogen
ID : AT-MSG-11729
Informations de copyright
© 2024. The Author(s).
Références
Penner IK (2016) Evaluation of cognition and fatigue in multiple sclerosis: daily practice and future directions. Acta Neurol Scand 134:19–23. https://doi.org/10.1111/ane.12651
doi: 10.1111/ane.12651
pubmed: 27580902
Benedict RHB, Amato MP, DeLuca J, Geurts JJG (2020) Cognitive impairment in multiple sclerosis: clinical management, MRI, and therapeutic avenues. Lancet Neurol 19:860–871. https://doi.org/10.1016/S1474-4422(20)30277-5
doi: 10.1016/S1474-4422(20)30277-5
pubmed: 32949546
pmcid: 10011205
Campbell J, Rashid W, Cercignani M, Langdon D (2017) Cognitive impairment among patients with multiple sclerosis: associations with employment and quality of life. Postgrad Med J 93:143–147. https://doi.org/10.1136/postgradmedj-2016-134071
doi: 10.1136/postgradmedj-2016-134071
pubmed: 27512050
Costa SL, Genova HM, Deluca J, Chiaravalloti ND (2017) Information processing speed in multiple sclerosis: past, present, and future. Mult Scler 23:772–789. https://doi.org/10.1177/1352458516645869
doi: 10.1177/1352458516645869
pubmed: 27207446
Benedict RHB, DeLuca J, Phillips G et al (2017) Validity of the symbol digit modalities test as a cognition performance outcome measure for multiple sclerosis. Mult Scler J 23:721–733. https://doi.org/10.1177/1352458517690821
doi: 10.1177/1352458517690821
Strober LB, DeLuca J, Benedict RH et al (2019) Symbol digit modalities test: a valid clinical trial endpoint for measuring cognition in multiple sclerosis. Mult Scler J 25:1781–1790. https://doi.org/10.1177/1352458518808204
doi: 10.1177/1352458518808204
Hechenberger S, Helmlinger B, Ropele S et al (2022) Information processing speed as a prognostic marker of physical impairment and progression in patients with multiple sclerosis. Mult Scler Relat Disord 57:103353. https://doi.org/10.1016/j.msard.2021.103353
doi: 10.1016/j.msard.2021.103353
pubmed: 35158430
Parmenter BA, Weinstock-Guttman B, Garg N et al (2007) Screening for cognitive impairment in multiple sclerosis using the symbol digit modalities test. Mult Scler 13:52–57. https://doi.org/10.1177/1352458506070750
doi: 10.1177/1352458506070750
pubmed: 17294611
Rao SM, Martin AL, Huelin R et al (2014) Correlations between MRI and information processing speed in MS: a meta-analysis. Mult Scler Int. https://doi.org/10.1155/2014/975803
doi: 10.1155/2014/975803
pubmed: 24795824
pmcid: 3984845
Benedict RHB, Amato MP, Boringa J et al (2012) Brief international cognitive assessment for MS (BICAMS): international standards for validation. BMC Neurol 12:1. https://doi.org/10.1186/1471-2377-12-55
doi: 10.1186/1471-2377-12-55
Sumowski JF, Benedict R, Enzinger C et al (2018) Cognition in multiple sclerosis: state of the field and priorities for the future. Neurology 90:278–288. https://doi.org/10.1212/WNL.0000000000004977
doi: 10.1212/WNL.0000000000004977
pubmed: 29343470
pmcid: 5818015
Ruet A, Deloire MSA, Charré-Morin J et al (2013) A new computerised cognitive test for the detection of information processing speed impairment in multiple sclerosis. Mult Scler J 19:1665–1672. https://doi.org/10.1177/1352458513480251
doi: 10.1177/1352458513480251
Rao SM, Losinski G, Mourany L et al (2017) Processing speed test: validation of a self-administered, iPad
doi: 10.1177/1352458516688955
pubmed: 28080262
Galioto R, Macaron G, Lace JW et al (2021) Is computerized screening for processing speed impairment sufficient for identifying MS-related cognitive impairment in a clinical setting? Mult Scler Relat Disord 54:103106. https://doi.org/10.1016/j.msard.2021.103106
doi: 10.1016/j.msard.2021.103106
pubmed: 34217998
Biogen Inc. (2022) CogEval (Version 1.4.2) [Mobile App]. App Store. https://apps.apple.com/us/app/cogeval/id1366437045
Kalb R, Beier M, Benedict RHB et al (2018) Recommendations for cognitive screening and management in multiple sclerosis care. Mult Scler J 24:1665–1680. https://doi.org/10.1177/1352458518803785
doi: 10.1177/1352458518803785
Rao SM, Sokolowski M, Strober LB et al (2022) Multiple sclerosis performance test (MSPT): normative study of 428 healthy participants ages 18 to 89. Mult Scler Relat Disord 59:103644. https://doi.org/10.1016/j.msard.2022.103644
doi: 10.1016/j.msard.2022.103644
pubmed: 35182881
Filser M, Schreiber H, Pöttgen J et al (2018) The brief International cognitive assessment in multiple sclerosis (BICAMS): results from the German validation study. J Neurol 265:2587–2593. https://doi.org/10.1007/s00415-018-9034-1
doi: 10.1007/s00415-018-9034-1
pubmed: 30171410
Scherer P, Baum K, Bauer H et al (2004) Normierung der Brief repeatable battery of neuropsychological tests (BRB-N) für den deutschsprachigen Raum. Anwendung bei schubförmig remittierenden und sekundär progredienten multiple-sklerose-patienten. Nervenarzt 75:984–990. https://doi.org/10.1007/s00115-004-1729-0
doi: 10.1007/s00115-004-1729-0
pubmed: 15118827
Helmstaedter C, Lendt M, Lux M (2001) VLMT - Verbaler Lern- und Merkfähigkeitstest, 1st edn. Hogrefe, Göttingen
Benedict RH (1997) Brief visuospatial memory test- revised: Professional manual. Psychological Assessment Resources, Odessa
Herrmann-Lingen C, Buss U, Snaith RP (2011) HADS-D - Hospital Anxiety and Depression Scale - Deutsche Version – Hogrefe, Verlag für Psychologie
Penner IK, Raselli C, Stöcklin M et al (2009) The fatigue scale for motor and cognitive functions (FSMC): validation of a new instrument to assess multiple sclerosis-related fatigue. Mult Scler 15:1509–1517. https://doi.org/10.1177/1352458509348519
doi: 10.1177/1352458509348519
pubmed: 19995840
Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33:1444–1452
doi: 10.1212/WNL.33.11.1444
pubmed: 6685237
Schmidt P (2017) Bayesian inference for structured additive regression models for large-scale problems with applications to medical imaging. Ludwig-Maximilians-Universität, München
Smith SM, Jenkinson M, Woolrich MW et al (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23:208–219. https://doi.org/10.1016/j.neuroimage.2004.07.051
doi: 10.1016/j.neuroimage.2004.07.051
Battaglini M, Jenkinson M, De Stefano N (2012) Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp 33:2062–2071. https://doi.org/10.1002/hbm.21344
doi: 10.1002/hbm.21344
pubmed: 21882300
Smith SM, Zhang Y, Jenkinson M et al (2002) Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 17:479–489. https://doi.org/10.1006/nimg.2002.1040
doi: 10.1006/nimg.2002.1040
pubmed: 12482100
Patenaude B, Smith SM, Kennedy DN, Jenkinson M (2011) A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 56:907–922. https://doi.org/10.1016/j.neuroimage.2011.02.046
doi: 10.1016/j.neuroimage.2011.02.046
pubmed: 21352927
Niino M, Miyazaki Y, Altincatal A et al (2023) Processing speed test: Results from a Japanese normative sample of healthy participants compared with a US normative sample. Clin Neurol Neurosurg 230:107790. https://doi.org/10.1016/j.clineuro.2023.107790
doi: 10.1016/j.clineuro.2023.107790
pubmed: 37229953
Roivainen E (2019) European and American WAIS IV norms: Cross-national differences in perceptual reasoning, processing speed and working memory subtest scores. Scand J Psychol 60:513–519. https://doi.org/10.1111/sjop.12581
doi: 10.1111/sjop.12581
pubmed: 31587302
Woelfle T, Pless S, Wiencierz A et al (2021) Practice effects of mobile tests of cognition, dexterity, and mobility on patients with multiple sclerosis: data analysis of a smartphone-based observational study. J Med Internet Res 23:e30394. https://doi.org/10.2196/30394
doi: 10.2196/30394
pubmed: 34792480
pmcid: 8663564
Fuchs TA, Gillies J, Jaworski MG et al (2022) Repeated forms, testing intervals, and SDMT performance in a large multiple sclerosis dataset. Mult Scler Relat Disord 68:104375. https://doi.org/10.1016/j.msard.2022.104375
doi: 10.1016/j.msard.2022.104375
pubmed: 36544304
Roar M, Illes Z, Sejbaek T (2016) Practice effect in symbol digit modalities test in multiple sclerosis patients treated with natalizumab. Mult Scler Relat Disord 10:116–122. https://doi.org/10.1016/j.msard.2016.09.009
doi: 10.1016/j.msard.2016.09.009
pubmed: 27919477
Koenig KA, Rao SM, Lowe MJ et al (2019) The role of the thalamus and hippocampus in episodic memory performance in patients with multiple sclerosis. MSJ 25:574–584. https://doi.org/10.1177/1352458518760716.The
doi: 10.1177/1352458518760716.The
Pinter D, Khalil M, Pirpamer L et al (2021) Long-term course and morphological MRI correlates of cognitive function in multiple sclerosis. Mult Scler J 27:954–963. https://doi.org/10.1177/1352458520941474
doi: 10.1177/1352458520941474
Wybrecht D, Reuter F, Pariollaud F et al (2017) New brain lesions with no impact on physical disability can impact cognition in early multiple sclerosis: A ten-year longitudinal study. PLoS ONE. https://doi.org/10.1371/journal.pone.0184650
doi: 10.1371/journal.pone.0184650
pubmed: 29149177
pmcid: 5693435
Cohen R, Swerdlik M (2009) Psychological testing and assessment: an introduction to tests and measurement, 7th edn. McGraw-Hill, New York
Wallis O, Bol Y, Köhler S, van Heugten C (2020) Anxiety in multiple sclerosis is related to depressive symptoms and cognitive complaints. Acta Neurol Scand 141:212–218. https://doi.org/10.1111/ane.13191
doi: 10.1111/ane.13191
pubmed: 31693750
Niino M, Fukumoto S, Okuno T et al (2022) Correlation of the symbol digit modalities test with the quality of life and depression in Japanese patients with multiple sclerosis. Mult Scler Relat Disord 57:103427. https://doi.org/10.1016/j.msard.2021.103427
doi: 10.1016/j.msard.2021.103427
pubmed: 34861614