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首页> 外文期刊>Journal of orthopaedic research >Biomechanical gait features associated with hip osteoarthritis: Towards a better definition of clinical hallmarks
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Biomechanical gait features associated with hip osteoarthritis: Towards a better definition of clinical hallmarks

机译：与髋骨关节炎相关的生物力学步态特征：更好地定义临床标志

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摘要

Critical appraisal of the literature highlights that the discriminative power of gait-related features in patients with hip osteoarthritis (OA) has not been fully explored. We aimed to reduce the number of gait-related features and define the most discriminative ones comparing the three-dimensional gait analysis of 20 patients with hip osteoarthritis (OA) with those of 17 healthy peers. First, principal component analysis was used to reduce the high-dimensional gait data into a reduced set of interpretable variables for further analysis, including tests for group differences. These differences were indicative for the selection of the top 10 variables to be included into linear discriminant analysis models (LDA). Our findings demonstrated the successful data reduction of hip osteoarthritic-related gait features with a high discriminatory power. The combination of the top variables into LDA models clearly separated groups, with a maximum misclassification error rate of 19%, estimated by cross-validation. Decreased hip/knee extension, hip flexion and internal rotation moment were gait features with the highest discriminatory power. This study listed the most clinically relevant gait features characteristics of hip OA. Moreover, it will help clinicians and physiotherapists understand the movement pathomechanics related to hip OA useful in the management and design of rehabilitation intervention. (c) 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 33:1498-1507, 2015.
机译：对文献的严格评估表明，对髋骨关节炎（OA）患者的步态相关特征的判别能力尚未得到充分研究。我们旨在减少步态相关特征的数量，并通过比较20例髋骨关节炎（OA）患者和17个健康同伴的三维步态分析来定义最具区分性的特征。首先，使用主成分分析将高维步态数据简化为减少的可解释变量集，以进行进一步分析，包括测试组差异。这些差异表明选择了线性判别分析模型（LDA）中的前10个变量。我们的发现表明，具有高判别力的数据成功降低了髋骨关节炎相关步态特征。将顶级变量组合到LDA模型中可以清楚地将各个组分开，通过交叉验证估计最大错误分类错误率为19％。髋/膝伸直，髋部屈曲和内旋力矩减少是具有最高辨别力的步态特征。这项研究列出了髋骨关节炎最临床相关的步态特征。此外，它将帮助临床医生和物理治疗师了解与髋骨OA相关的运动病理力学，对康复干预的管理和设计很有用。 （c）2015骨科研究学会。由Wiley Periodicals，Inc. J Orthop Res 33：1498-1507，2015年出版。

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