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临床试验/NCT04142671
NCT04142671Unknown不适用

Determining Individualised Gait Modification Strategies to Reduce Knee Joint Moments in Alkaptonuria Patients Using Real-time Feedback

Liverpool John Moores University0 个研究点目标入组 30 人开始时间: 2021年10月最近更新:
适应症

试验速览

阶段
不适用
入组人数
30
主要终点
Change from baseline 3D knee joint moment impulse after intervention

研究概览

简要总结

This study evaluates the efficacy of a gait modification intervention using real-time biofeedback on reducing the knee joint loading in Alkaptonuria patients during treadmill walking. It will also assess whether the individualised adopted gait modification can be retained without feedback and during over ground walking.

详细描述

Alkaptonuria (AKU) is a degenerative disease affecting the cartilage of the joints. The disease affects movement function, particularly walking/gait which is an important activity of daily living. It is believed that increased joint loading measured by the moments acting upon the joints, contributes to the degeneration of joint cartilage in Alkaptonuria, particularly in the weight bearing joints such as the knee and hips, resulting in accelerated progression of painful symptoms. Currently there is no cure for Alkaptonuria and the current management includes joint replacement surgery. Gait modification strategy interventions could be a non-invasive alternative which could delay the time to surgical interventions by reducing or altering joint loading and stalling the progression of disease.

The aims of this study are 1) to determine if individualised gait modification strategies can be used to reduce the 3D knee joint loading, 2) to determine if the gait modifications can be retained without feedback during over ground walking and 3) to determine the individualised gait modification strategies adopted by AKU patients.

Gait data will be measured and quantified using the non-invasive typical clinical gait analysis set up, using 3D motion capture combined with force data whereby joint angles, moments and powers can be calculated in all 3 planes of motion during treadmill walking. The intervention will involve real-time biofeedback using Motek's M-Gait treadmill. Due to the heterogeneity of the sample, each AKU patient will act as their own control. Gait data will be compared pre- and post-intervention and a validated pain score will be used to identify any patterns with knee pain and adopted gait modifications.

研究设计

研究类型
Interventional
分配方式
Na
干预模型
Single Group
主要目的
Basic Science
盲法
None

入排标准

年龄范围
18 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • The diagnosis of Alkaptonuria
  • Able to understand written and spoken English.
  • Willing and able to give informed consent to participate
  • Above the age of 18.

排除标准

  • The reliance on or use of a walking aid.
  • Any previous lower limb joint replacements.
  • Any severe pain or unable to walk comfortably and consecutively for 20 minutes.

结局指标

主要结局

Change from baseline 3D knee joint moment impulse after intervention

时间窗: At baseline and immediately after the intervention

This represents the knee joint load during walking measured from kinematic and kinetic data obtained during the 3D gait analysis

次要结局

  • Change from baseline joint moments after intervention(At baseline and immediately after the intervention)
  • Knee injury and Osteoarthritis Outcome Score(Pre-intervention)
  • Change from baseline joint angles after intervention(At baseline and immediately after the intervention)
  • Change from baseline joint powers after intervention(At baseline and immediately after the intervention)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Hannah Shepherd

Associate Lecturer in Clinical Biomechanics

Liverpool John Moores University

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