ArticleBMC neurology2020
A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS).
Article in BMC neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Impact of frailty, mild cognitive impairment and cognitive frailty on adverse health outcomes among community-dwelling older adults: A systematic review and meta-analysis.Frontiers in medicine · 2022Pooled it
- Review
- Review
- Development and validation of an electronic Symbol-Digit Modalities Test for remote monitoring of people with multiple sclerosis.European journal of neurology · 2025Article
- Relationship between sleep disorders and information processing speed in multiple sclerosis.Clinics (Sao Paulo, Brazil) · 2025Article
- Digital remote monitoring of people with multiple sclerosis.Frontiers in immunology · 2025Review
- The SLaM Brain Health Clinic: remote biomarker enhanced memory clinic for people with mild cognitive impairment within a National Health Service mental health trust.BJPsych open · 2024Article
- Remyelinating Drugs at a Crossroad: How to Improve Clinical Efficacy and Drug Screenings.Cells · 2024Review
- SpEx: a German-language dataset of speech and executive function performance.Scientific reports · 2024Article
- Review
- Health economic analysis of the integrated cognitive assessment tool to aid dementia diagnosis in the United Kingdom.Frontiers in public health · 2023Article
- The use of the integrated cognitive assessment to improve the efficiency of primary care referrals to memory services in the accelerating dementia pathway technologies study.Frontiers in aging neuroscience · 2023Article
- The Use of a Computerized Cognitive Assessment to Improve the Efficiency of Primary Care Referrals to Memory Services: Protocol for the Accelerating Dementia Pathway Technologies (ADePT) Study.JMIR research protocols · 2022Article
- Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment.PloS one · 2022Article
- Assessing Cognitive Function in Multiple Sclerosis With Digital Tools: Observational Study.Journal of medical Internet research · 2021Observational
- Machine Learning Use for Prognostic Purposes in Multiple Sclerosis.Life (Basel, Switzerland) · 2021Review
- Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia.Frontiers in psychiatry · 2021Article
- Implementing Remote Memory Clinics to Enhance Clinical Care During and After COVID-19.Frontiers in psychiatry · 2020Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCognitive impairment is common in patients with multiple sclerosis (MS). Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity.
methodsWe developed a 5-min computerized test to measure cognitive dysfunction in patients with MS. The proposed test - named the Integrated Cognitive Assessment (ICA) - is self-administered and language-independent. Ninety-one MS patients and 83 healthy controls (HC) took part in Substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA's test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In Substudy 2, we recruited 48 MS patients, 38 of which had received an 8-week physical and cognitive rehabilitation programme and 10 MS patients who did not. We examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores and Symbol Digit Modalities Test (SDMT) scores pre- and post-rehabilitation.
resultsThe ICA demonstrated excellent test-retest reliability (r = 0.94), with no learning bias, and showed a high level of convergent validity with BICAMS. The ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r = - 0.79) between ICA score and the level of NfL in MS patients before and after rehabilitation.
conclusionsThe ICA has the potential to be used as a digital marker of cognitive impairment and to monitor response to therapeutic interventions. In comparison to standard cognitive tools for MS, the ICA is shorter in duration, does not show a learning bias, and is independent of language.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.