Evidence map›Paper›PMID 36755463›Full record

ArticleMultiple sclerosis (Houndmills, Basingstoke, England)2023

Personalized monitoring of ambulatory function with a smartphone 2-minute walk test in multiple sclerosis.

Ka-Hoo Lam, Ioan Gabriel Bucur, Pim van Oirschot, Frank de Graaf, Eva Strijbis, Bernard Uitdehaag, Tom Heskes, Joep Killestein, Vincent de Groot

Open access · hybridAbstract read
In one paragraph

Article in Multiple sclerosis (Houndmills, Basingstoke, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Sensors in Multiple Sclerosis.Current neurology and neuroscience reports · 2025
    Review
  3. Article
  4. Review
  5. 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

9 authors at 2 institutions in 1 country.

Ka-Hoo LamDepartment of Neurology, Amsterdam University Medical Centers, Universiteit Amsterdam, Amsterdam, The Netherlands/MS Center Amsterdam, Amsterdam, The Netherlands/Amsterdam Neuroscience, Amsterdam, The Netherlands.ORCID 0000-0003-0926-1445
Ioan Gabriel BucurInstitute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands.
Pim van OirschotMS Sherpa BV, Nijmegen, The Netherlands.
Frank de GraafOrikami Digital Health Products, Nijmegen, The Netherlands.
Eva StrijbisDepartment of Neurology, Amsterdam University Medical Centers, Universiteit Amsterdam, Amsterdam, The Netherlands/MS Center Amsterdam, Amsterdam, The Netherlands/Amsterdam Neuroscience, Amsterdam, The Netherlands.ORCID 0000-0001-6705-5864
Bernard UitdehaagDepartment of Neurology, Amsterdam University Medical Centers, Universiteit Amsterdam, Amsterdam, The Netherlands/MS Center Amsterdam, Amsterdam, The Netherlands/Amsterdam Neuroscience, Amsterdam, The Netherlands.
Tom HeskesInstitute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands.
Joep KillesteinDepartment of Neurology, Amsterdam University Medical Centers, Universiteit Amsterdam, Amsterdam, The Netherlands/MS Center Amsterdam, Amsterdam, The Netherlands/Amsterdam Neuroscience, Amsterdam, The Netherlands.
Vincent de GrootMS Center Amsterdam, Amsterdam, The Netherlands/Amsterdam Neuroscience, Amsterdam, The Netherlands/Department of Rehabilitation Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Amsterdam Neuroscience · NLRadboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRemote smartphone-based 2-minute walking tests (s2MWTs) allow frequent and potentially sensitive measurements of ambulatory function.

objectiveTo investigate the s2MWT on assessment of, and responsiveness to change in ambulatory function in MS.

methodsOne hundred two multiple sclerosis (MS) patients and 24 healthy controls (HCs) performed weekly s2MWTs on self-owned smartphones for 12 and 3 months, respectively. The timed 25-foot walk test (T25FW) and Expanded Disability Status Scale (EDSS) were assessed at 3-month intervals. Anchor-based (using T25FW and EDSS) and distribution-based (curve fitting) methods were used to assess responsiveness of the s2MWT. A local linear trend model was used to fit weekly s2MWT scores of individual patients.

resultsA total of 4811 and 355 s2MWT scores were obtained in patients (

conclusionsIn group-level analyses, clinically relevant change was insufficiently detected due to large variability with sporadic measurements. Individual-level curve fitting reduced the variability in s2MWT, enabling the detection of statistically reliable change in ambulatory function.

Indexed as

Multiple SclerosisDisability EvaluationHumansSmartphoneWalkingWalk Testambulatory functiondigital technologyMultiple sclerosisoutpatient monitoringpatient-specific modelingsmartphone

Identifiers

PMID36755463
PMCPMC10152211
OpenAlexW4319656921

What OpenQuestion holds

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LicenceCC BY
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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.