Literature DB >> 33010093

3D gait analysis, haemophilia joint health score, leg muscle laterality and biomarkers of joint damage: A cross-sectional comparative assessment of haemophilic arthropathy.

Peter Putz1, Sebastian Durstberger1, Christina Kaufmann1, Meike Klinger1, Kerstin Plessl1, Judit Rejtö2, Klaus Widhalm1, Christoph Male3, Ingrid Pabinger2.   

Abstract

INTRODUCTION: 3D gait analysis has been proposed as a reproducible and valid method to assess abnormal gait patterns and to monitor disease progression in patients with haemophilia (PWH). AIM: This study aimed at comparing Gait Deviation Index (GDI) between adult PWH and healthy controls, and at assessing the agreement between outcome measures of haemophilic arthropathy.
METHODS: Male PWH aged 18-49 years (prespecified subgroups: 18-25 vs 26-49 years) on prophylactic replacement therapy, and male healthy age-matched controls passed through a cross-sectional assessment panel. Besides the 3D gait analysis derived GDI, secondary outcomes included kinematic, kinetic and spatio-temporal gait parameters, the Haemophilia Joint Health Score (HJHS), electric impedance derived leg muscle laterality and inflammatory biomarkers.
RESULTS: Patients with haemophilia (n = 18) walked slower, in shorter steps and accordingly with less functional range of motion in the hips and ankles, as compared to healthy controls (n = 24). Overall, PWH did not differ significantly in GDI and specific gait parameters. PWH had a higher mean HJHS (18.8 vs 2.6, P = .000) and leg muscle laterality (4.3% vs 1.5%, P = .004). A subgroup analysis revealed progressed gait pathology in PWH aged 26-49 years (not statistically significant). Leg muscle laterality was strongly correlated with HJHS (r = .76, P = .000), whereas GDI just moderately (r = -.39, P = .110). PWH had higher levels of the inflammatory markers CRP and IL-6.
CONCLUSION: Progressed gait pathology was found in PWH, mainly those aged 26-49 years. Leg muscle laterality correlated strongly with HJHS and was identified as a promising tool for detecting progression and physiological consequences of haemophilic joint arthropathy.
© 2020 JThe Authors. Haemophilia published by John Wiley & Sons Ltd.

Entities:  

Keywords:  3D gait analysis; adult; biomarker; electric impedance; haemophilia; haemophilia joint health score

Year:  2020        PMID: 33010093     DOI: 10.1111/hae.14154

Source DB:  PubMed          Journal:  Haemophilia        ISSN: 1351-8216            Impact factor:   4.287


  4 in total

1.  Gait Alteration Due to Haemophilic Arthropathies in Patients with Moderate Haemophilia.

Authors:  Alban Fouasson-Chailloux; Fabien Leboeuf; Yves Maugars; Marc Trossaert; Pierre Menu; François Rannou; Claire Vinatier; Jérome Guicheux; Raphael Gross; Marc Dauty
Journal:  Int J Environ Res Public Health       Date:  2022-06-20       Impact factor: 4.614

2.  Lower physical activity and altered body composition in patients with haemophilia compared with healthy controls.

Authors:  Peter Putz; Meike Klinger; Christoph Male; Ingrid Pabinger
Journal:  Haemophilia       Date:  2021-02-12       Impact factor: 4.287

3.  Biomechanical Gait Analysis of an Adult with Severe Hemophilia: A Case Report.

Authors:  Claudiane A Fukuchi; Alessandro R Zorzi; Reginaldo K Fukuchi; Janaina B S Ricciardi; Glenda Feldberg; Alberto Cliquet
Journal:  Hematol Rep       Date:  2022-03-31

Review 4.  Postural Assessment Systems in the Prevention of Haemophilic Arthropathy: A Narrative Review.

Authors:  Dalila Scaturro; Fabio Vitagliani; Sofia Tomasello; Maria Silvia Mangano; Gabriele Signa; Giulia Letizia Mauro
Journal:  J Funct Morphol Kinesiol       Date:  2022-09-07
  4 in total

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