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1000 Titel
  • Gait variability as digital biomarker of disease severity in Huntington’s disease
1000 Autor/in
  1. Gaßner, Heiko |
  2. Jensen, Dennis |
  3. Marxreiter, F. |
  4. Kletsch, Anja |
  5. Bohlen, Stefan |
  6. Schubert, Robin |
  7. Muratori, Lisa M. |
  8. Eskofier, Bjoern |
  9. Klucken, Jochen |
  10. Winkler, Jürgen |
  11. Reilmann, Ralf |
  12. Kohl, Zacharias |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-02-11
1000 Erschienen in
1000 Quellenangabe
  • 267(6):1594-1601
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s00415-020-09725-3 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293689/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!Impaired 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.!##!Objective!#!To 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).!##!Methods!#!Patients 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).!##!Results!#!Stride 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!##!Conclusions!#!Sensor-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.
1000 Sacherschließung
lokal Female [MeSH]
lokal Regularity of gait
lokal Biomechanical Phenomena/physiology [MeSH]
lokal Adult [MeSH]
lokal Gait Disorders, Neurologic/diagnosis [MeSH]
lokal Humans [MeSH]
lokal Gait Disorders, Neurologic/etiology [MeSH]
lokal Gait Disorders, Neurologic/physiopathology [MeSH]
lokal Severity of Illness Index [MeSH]
lokal Middle Aged [MeSH]
lokal Huntington’s disease
lokal Wearable sensors
lokal Male [MeSH]
lokal Gait analysis
lokal Machine Learning [MeSH]
lokal Huntington Disease/complications [MeSH]
lokal Biomarkers [MeSH]
lokal Original Communication
lokal Gait variability
lokal Huntington Disease/physiopathology [MeSH]
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-2037-9460|https://frl.publisso.de/adhoc/uri/SmVuc2VuLCBEZW5uaXM=|https://frl.publisso.de/adhoc/uri/TWFyeHJlaXRlciwgRi4=|https://frl.publisso.de/adhoc/uri/S2xldHNjaCwgQW5qYQ==|https://frl.publisso.de/adhoc/uri/Qm9obGVuLCBTdGVmYW4=|https://frl.publisso.de/adhoc/uri/U2NodWJlcnQsIFJvYmlu|https://frl.publisso.de/adhoc/uri/TXVyYXRvcmksIExpc2EgTS4=|https://frl.publisso.de/adhoc/uri/RXNrb2ZpZXIsIEJqb2Vybg==|https://frl.publisso.de/adhoc/uri/S2x1Y2tlbiwgSm9jaGVu|https://frl.publisso.de/adhoc/uri/V2lua2xlciwgSsO8cmdlbg==|https://frl.publisso.de/adhoc/uri/UmVpbG1hbm4sIFJhbGY=|https://frl.publisso.de/adhoc/uri/S29obCwgWmFjaGFyaWFz
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1000 Erstellt am 2023-11-18T00:30:41.887+0100
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