Gait classification in unilateral cerebral palsy

• Verfasst von: Tsitlakidis, Stefanos [VerfasserIn]
• Verfasst von: Horsch, Axel [VerfasserIn]
• Verfasst von: Schäfer, Felix [VerfasserIn]
• Verfasst von: Westhauser, Fabian [VerfasserIn]
• Verfasst von: Götze, Marco [VerfasserIn]
• Verfasst von: Hagmann, Sébastien [VerfasserIn]
• Verfasst von: Klotz, Matthias C. M. [VerfasserIn]
• Titel: Gait classification in unilateral cerebral palsy
• Verf.angabe: Stefanos Tsitlakidis, Axel Horsch, Felix Schaefer, Fabian Westhauser, Marco Goetze, Sebastien Hagmann and Matthias C. M. Klotz
• E-Jahr: 2019
• Jahr: 11 October 2019
• Umfang: 9 S.
• Fussnoten: Gesehen am 10.12.2019
• Titel Quelle: Enthalten in: Journal of Clinical Medicine
• Ort Quelle: Basel : MDPI, 2012
• Jahr Quelle: 2019
• Band/Heft Quelle: 8(2019,10) Artikel-Nummer 1652, 9 Seiten
• ISSN Quelle: 2077-0383
• DOI: doi:10.3390/jcm8101652
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: classification systems
• Sach-SW: gait patterns
• Sach-SW: lower extremity
• Sach-SW: unilateral cerebral palsy
• K10plus-PPN: 1684992109
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

As unilateral cerebral palsy represents a complex disorder, gait classification is difficult. Knowledge of the most frequent gait patterns and functional impairment is crucial for proper decision-making. This study analyzes the prevalence of gait patterns as well as the relation of different gait patterns and the Gross Motor Function Classification System (GMFCS). Eighty-nine patients were classified retrospectively using the GMFCS, the classification of Winters, Gage, and Hicks (WGH), and Sutherland et al. The distribution of GMFCS levels among the different gait patterns was analyzed using Chi-squared test. The most common subtypes were GMFCS level I, WGH type I, and recurvatum knee. Seventeen percent (WGH) and 59% (Sutherland) of the patients did not match any criteria. Applying both classifications complementarily reduced the number of unclassified patients significantly. There was no significant difference concerning the distribution of GMFCS levels or age among the different gait patterns. A combined use of various classification systems is beneficial for proper decision-making. Unclassified patients seem to be a heterogeneous subgroup concerning functional impairment. There is a need of further characterization of the unclassifiable gait patterns and the caused functional impairment. Instrumented gait analysis remains the gold standard and should be broadly used for future studies and in clinical practice.