ArticleEuropean journal of neurology2025
Longitudinal trajectories of digital upper limb biomarkers for multiple sclerosis.
Article in European journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
3 citing papers in PubMed.
- Detecting progressing events in multiple sclerosis clinics in real-time is possible: Commentary.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026Article
- Longitudinal Trajectories of Digital Cognitive Biomarkers for Multiple Sclerosis.Annals of clinical and translational neurology · 2025Observational
- Longitudinal trajectories of digital upper limb biomarkers for multiple sclerosis.European journal of neurology · 2025Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
backgroundUpper limb dysfunction is a common debilitating feature of relapsing-remitting multiple sclerosis (RRMS). We aimed to examine the longitudinal trajectory of the iPad®-based Manual Dexterity Test (MDT) and predictors of change over time.
methodsWe prospectively enrolled RRMS patients (limited to Expanded Disability Status Scale (EDSS) < 4). Longitudinal data was analysed using mixed-effect modelling and latent class mixed models. We then examined whether group membership in latent classes predicted confirmed slowing in MDT.
resultsSeven hundred and twenty-one participants had complete data for analysis. At a population level, MDT remained stable over time. No practice effect was seen. Baseline disability and T2 lesion volume were the strongest predictors of longitudinal MDT performance. We identified two latent class trajectories of MDT. The slower latent class was typified by greater variability and a weak association with confirmed worsening of MDT and EDSS. When compared to trajectory analysis stratified by baseline MDT, latent class analysis (LCA) was able to identify those at greater risk of confirmed slowing, signifying the importance of latent processes in upper limb function in pwMS.
conclusionIn this cohort of mild to moderate RRMS, MDT scores remained stable over time with no evidence of a practice effect at a population level. Trajectory analysis based on LCA identified a cohort with greater variability and risk of disability progression and domain specific worsening. Our findings demonstrate the importance of latent processes in determining upper limb function in pwMS.
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Registered trials
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