Evidence map›Paper›PMID 32048014›Full record

Observational studyJournal of neurology2020

Gait variability as digital biomarker of disease severity in Huntington's disease.

Heiko Gaßner, Dennis Jensen, F Marxreiter, Anja Kletsch, Stefan Bohlen, Robin Schubert, Lisa M Muratori, Bjoern Eskofier, Jochen Klucken, Jürgen Winkler and 2 more

Erratum issuedOpen access · hybridAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Journal of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 6% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026
    Review
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
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  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. The Role of Clinical Assessment in the Era of Biomarkers.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Heiko GaßnerDepartment of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany.ORCID http://orcid.org/0000-0003-2037-9460
Dennis JensenDepartment of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany.
F MarxreiterDepartment of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany.
Anja KletschGeorge-Huntington Institute (GHI) GmbH, Münster, Germany.
Stefan BohlenGeorge-Huntington Institute (GHI) GmbH, Münster, Germany.
Robin SchubertGeorge-Huntington Institute (GHI) GmbH, Münster, Germany.
Lisa M MuratoriGeorge-Huntington Institute (GHI) GmbH, Münster, Germany.
Bjoern EskofierMachine Learning and Data Analytics Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Jochen KluckenDepartment of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany.
Jürgen WinklerDepartment of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany.
Ralf ReilmannGeorge-Huntington Institute (GHI) GmbH, Münster, Germany.
Zacharias KohlDepartment of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany. Zacharias.Kohl@klinik.uni-regensburg.de.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEGeorge Huntington Institute · DEUniversity of Münster · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImpaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments.

objectiveTo objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington's Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC).

methodsPatients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defined gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV).

resultsStride length (- 15%) and gait velocity (- 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ r

conclusionsSensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.

Indexed as

Machine LearningAdultBiomarkersBiomechanical PhenomenaFemaleGait Disorders, NeurologicHumansHuntington DiseaseMaleMiddle AgedSeverity of Illness IndexBiomarkersGait analysisGait variabilityHuntington’s diseaseRegularity of gaitWearable sensors

Identifiers

PMID32048014
PMCPMC7293689
OpenAlexW3006354599

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.