Smartphone monitoring of cognition in people with multiple sclerosis: A systematic review

Foong, Yi Chao; Bridge, Francesca; Merlo, Daniel; Gresle, Melissa; Zhu, Chao; Buzzard, Katherine; Butzkueven, Helmut; Walt, Anneke van der

doi:10.1016/j.msard.2023.104674

Cited by 7 publications

(1 citation statement)

References 35 publications

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“…Attrition remains a major stumbling block. 8 The same interface quandries arise with computerised testing, at home or in the clinic, although some assessment programmes are building psychometric credibility. 9 Virtual reality paradigms offer more ecological validity and sensitivity to how cognitive difficulties play out in everyday life.…”

mentioning

confidence: 97%

Neuropsychological assessment in MS is outdated and in need for innovation: NO

Langdon

2024

Mult Scler

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mentioning

confidence: 97%

Neuropsychological assessment in MS is outdated and in need for innovation: NO

Langdon

2024

Mult Scler

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Digital outcome measures are associated with brain atrophy in patients with multiple sclerosis

Molenaar,

Noteboom,

van Nederpelt

et al. 2024

J Neurol

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Background Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression. Objective To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS. Methods In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates. Results In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12. Conclusion Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.

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