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Gait Classification in Unilateral Cerebral Palsy.
Tsitlakidis, Stefanos; Horsch, Axel; Schaefer, Felix; Westhauser, Fabian; Goetze, Marco; Hagmann, Sebastien; Klotz, Matthias C M.
Afiliação
  • Tsitlakidis S; Clinic of Orthopedics and Trauma Surgery, Heidelberg University Hospital, Schlierbacher Landstrasse 200a, 69118 Heidelberg, Germany. stefanos.tsitlakidis@med.uni-heidelberg.de.
  • Horsch A; Clinic of Orthopedics and Trauma Surgery, Heidelberg University Hospital, Schlierbacher Landstrasse 200a, 69118 Heidelberg, Germany. axel.horsch@med.uni-heidelberg.de.
  • Schaefer F; Clinic of Orthopedics and Trauma Surgery, Heidelberg University Hospital, Schlierbacher Landstrasse 200a, 69118 Heidelberg, Germany. felix.schaefer@stud.uni-heidelberg.de.
  • Westhauser F; Clinic of Orthopedics and Trauma Surgery, Heidelberg University Hospital, Schlierbacher Landstrasse 200a, 69118 Heidelberg, Germany. fabian.westhauser@med.uni-heidelberg.de.
  • Goetze M; Clinic of Orthopedics and Trauma Surgery, Heidelberg University Hospital, Schlierbacher Landstrasse 200a, 69118 Heidelberg, Germany. marco.goetze@med.uni-heidelberg.de.
  • Hagmann S; Clinic of Orthopedics and Trauma Surgery, Heidelberg University Hospital, Schlierbacher Landstrasse 200a, 69118 Heidelberg, Germany. sebastien.hagmann@med.uni-heidelberg.de.
  • Klotz MCM; Clinic for Orthopedic & Trauma Surgery, Kepler University Hospital, Krankenhausstr. 9, 4020 Linz, Austria. Matthias.Klotz@kepleruniklinikum.at.
J Clin Med ; 8(10)2019 Oct 11.
Article em En | MEDLINE | ID: mdl-31614496
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article