Rethinking EDSS-based ambulation assessment in multiple sclerosis using continuous variable monitoring.

Area of Science:

• Neurology
• Digital Health
• Biomedical Engineering

Background:

• Multiple sclerosis (MS) is a chronic CNS inflammatory disease causing progressive disability.
• Current disability assessment (EDSS) relies on subjective walking ability estimates.
• Digital health technologies (DHTs) offer continuous, objective monitoring of real-world function.

Purpose of the Study:

• To compare patient-estimated walking distance with objective measures in MS.
• To evaluate the utility of smartwatch data for assessing mobility and disability in MS patients.
• To investigate the variability of clinical assessments in MS.

Main Methods:

• Prospective observational study at two German centers.
• Patients with relapsing-remitting MS (RRMS) assessed at baseline and follow-up.
• Compared patient-estimated walking distance, clinical measurements (measuring wheel, pedometer), and smartwatch-derived activity metrics.

Main Results:

• Patient-estimated walking distance showed moderate correlation with clinical measures.
• A significant proportion of patients misjudged walking distances relative to EDSS thresholds.
• Smartwatch-derived metrics (daily walking distance, step count) correlated negatively with EDSS scores.
• Clinical assessments showed substantial intra-individual variability over the study duration.

Conclusions:

• Patient estimates of walking distance are moderately accurate but frequently misalign with disability thresholds.
• Single clinical assessments may not capture the full picture of MS-related mobility changes.
• Smartwatch data provide objective, real-world mobility insights that align with clinical status and disability scores in MS.