Nomogram in Knee Instability: 3D Gait Analysis of Knee Osteoarthritis Patients
Nomogram in Knee Instability: 3D Gait Analysis of Knee Osteoarthritis Patients
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DOI：
10.1007/s43465-022-00644-1
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发表时间：
2022-06-20
影响因子：
1
通讯作者：
Fu, Ming
中科院分区：
文献类型：
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作者：
Gu, Cheng;Mao, Yurong;Fu, Ming
背景：通过症状、体格检查和影像学来测量膝关节稳定性并不能准确反映膝关节运动的状况。因此，本研究旨在介绍一种用于评估膝关节骨关节炎（OA）患者行走过程中膝关节稳定性的模型。目的应用三维步态分析系统对患者步态进行量化分析，并以诺模图的形式显示膝关节不稳的临床诊断模型，指导临床诊断和治疗。方法这项横断面研究对93名膝关节OA参与者和40名健康对照者进行了3D步态分析。多元线性回归分析研究步态参数和膝关节伸展/屈曲稳定性之间的相关性。应用多项Logistic回归分析建立预测模型，并采用校正图、C指数、决策曲线分析、Bootstrapping验证等方法对预测诺模图的临床实用性和内部效度进行评价。结果多元线性回归分析显示膝关节伸直稳定性与步行速度相关（β = 0.256，P = 0.006），膝伸肌力量（β =-0.196，P = 0.03），静态HKA（β = 0.218，P = 0.016），股骨干宽度（β =-0.282，P = 0.002）和WOMAC评分（β = 0.281，P = 0.002）;然而，膝关节屈曲稳定性与步行速度相关（β = 0.340，P < 0.001），膝屈肌强度（β =-0.327，P < 0.001），胫骨后倾角（PTS）（β = 0.291，P < 0.001）、膝关节屈伸活动度（ROM）（β = 0.177，P = 0.018）和HSS评分（β =-0.173，P = 0.028）。我们开发并内部验证了膝关节OA患者的膝关节不稳定风险诺模图。结论应用三维运动分析系统对膝关节不稳定进行定量分析是可行的。目前的预测模型可以作为一个可靠的工具，量化膝关节不稳定的可能性，在OA患者。
Background Measures of knee stability by symptoms, physical examination, and imaging do not accurately reflect the condition of knee movement. Therefore, this study aimed to introduce a model for assessing knee stability during walking in patients with knee osteoarthritis (OA). Aims Three dimensional(3D) gait analysis system was used to quantify the gait of patients and display the clinical diagnosis model of knee instability with nomogram to guide clinical diagnosis and treatment. Methods This cross-sectional study performed a 3D gait analysis in 93 participants with knee OA and 40 healthy control subjects. Multiple linear regression analysis investigated the correlation between gait parameters and knee extension/flexion stability. The predicting models were built applied multinomial logistic regression analysis and calibration plot, C-index, decision curve analysis, bootstrapping validation were used to assess the predicting nomograms' clinical usefulness and internal validation. Results Multiple linear regression analysis indicated knee extension stability was correlated with walking speed (beta = 0.256, P = 0.006), knee extensor strength (beta = -0.196, P = 0.03), static HKA (beta = 0.218, P = 0.016), width of the femoral diaphysis (beta = -0.282, P = 0.002) and WOMAC score (beta = 0.281, P = 0.002); however, knee flexion stability was correlated with walking speed (beta = 0.340, P < 0.001), knee flexor strength (beta = -0.327, P < 0.001), posterior tibial slope (PTS) (beta = 0.291, P < 0.001), knee flexion/extension range of motion (ROM) (beta = 0.177, P = 0.018) and HSS score (beta = -0.173, P = 0.028). We developed and internally validated a knee instability risk nomogram in patients with knee OA. Conclusions These results indicated that using the 3D motion analysis system is feasible to quantify knee instability. The current prediction models could serve as a reliable tool to quantify the possibility of knee instability in OA patients.