Longitudinal trajectories of digital upper limb biomarkers for multiple sclerosis

• DOI: 10.1111/ene.70000
• Publication Date: 2024-12-23T14:40:31Z
• Authors: Yi Chao Foong; Daniel Merlo; Melissa Gresle; Chao Zhu; Katherine Buzzard; Jeannette Lechner...; Michael Barnett; Bruce V. Taylor; Tomas Kalincik; Trevor Kilpatrick; David Darby; Pamela Dobay; Johan van Beek; Robert Hyde; Steve Simpson‐Yap; Helmut Butzkueven; Anneke van der Walt
• Keywords: Longitudinal Study

Abstract Background Upper limb dysfunction is a common debilitating feature of relapsing‐remitting multiple sclerosis (RRMS). We aimed to examine the longitudinal trajectory iPad®‐based Manual Dexterity Test (MDT) and predictors change over time. Methods prospectively enrolled RRMS patients (limited Expanded Disability Status Scale (EDSS) < 4). Longitudinal data was analysed using mixed‐effect modelling latent class mixed models. then examined whether group membership in classes predicted confirmed slowing MDT. Results Seven hundred twenty‐one participants had complete for analysis. At population level, MDT remained stable No practice effect seen. Baseline disability T2 lesion volume were strongest performance. identified two trajectories The slower typified by greater variability weak association with worsening EDSS. When compared analysis stratified baseline MDT, (LCA) able identify those at risk slowing, signifying importance processes upper function pwMS. Conclusion In this cohort mild moderate RRMS, scores time no evidence level. Trajectory based on LCA progression domain specific worsening. Our findings demonstrate determining