Evidence map›Paper›PMID 41245861›Full record

ArticleFrontiers in neurology2025

Validating wearable step counts in multiple sclerosis research: a replication study.

Myla D Goldman, Shanshan Chen, Bhavana Kunisetty, Jeffrey M Gelfand, Bruce A C Cree, Valerie J Block

Abstract read
In one paragraph

Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Myla D GoldmanDepartment of Neurology, Virginia Commonwealth University School of Medicine, Richmond, VA, United States.
Shanshan ChenDepartment of Biostatistics, School of Public Health, Virginia Commonwealth University, Richmond, VA, United States.
Bhavana KunisettyDivision of Neuroimmunology and Glial Biology, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Jeffrey M GelfandDivision of Neuroimmunology and Glial Biology, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Bruce A C CreeDivision of Neuroimmunology and Glial Biology, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Valerie J BlockDivision of Neuroimmunology and Glial Biology, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: For people with multiple sclerosis (MS), mobility impairment is common and a significant contributor to reduced quality of life. With advancements in wearable technology, step count data has emerged as a promising method to track mobility and monitor functional decline. However, studies comparing the replicability of wearable mobility data using varying devices remain limited in MS populations. Methods: This study investigates the reliability of step count data and its associations with clinical outcomes in MS patients using two independent cohorts with different wearable devices: California (CA) ( Results: Analysis of the VA cohort revealed similar average daily step counts to those seen in the CA cohort (6,010 vs. 5,478 steps/day). Step count variability (standard deviation) decreased with increasing EDSS in both cohorts. Step counts in the VA cohort were significantly correlated with EDSS ( Discussion: The step count analyses from two different wearable devices show replicable associations with clinical and patient-reported outcomes in MS, highlighting their promise as digital biomarkers for clinical monitoring and care, rehabilitation, and patient self-management.

Indexed as

accelerometeractivity monitoringExpanded Disability Status Scale [EDSS]multiple sclerosiswearables

Identifiers

PMID41245861
PMCPMC12611647

What OpenQuestion holds

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Registered trials

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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.