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  • Title: Three-dimensional biomechanical gait characteristics at baseline are associated with progression to total knee arthroplasty.
    Author: Hatfield GL, Stanish WD, Hubley-Kozey CL.
    Journal: Arthritis Care Res (Hoboken); 2015 Jul; 67(7):1004-14. PubMed ID: 25708360.
    Abstract:
    OBJECTIVE: To determine if baseline 3-dimensional (3-D) biomechanical gait patterns differed between those patients with moderate knee osteoarthritis (OA) who progressed to total knee arthroplasty (TKA) and those that did not, and whether these differences had predictive value. METHODS: Fifty-four patients with knee OA had ground reaction forces and segment motions collected during gait. 3-D hip, knee, and ankle angles and moments were calculated over the gait cycle. Amplitude and temporal waveform characteristics were determined using principal component analysis. At followup 5-8 years later, 26 patients reported undergoing TKA. Unpaired t-tests were performed on baseline demographic and waveform characteristics between TKA and no-TKA groups. Receiver operating curve analysis, stepwise discriminate analysis, and logistic regression analysis determined the combination of features that best classified TKA and no-TKA groups and their predictive ability. RESULTS: Baseline demographic, symptomatic, and radiographic variables were similar, but 7 gait variables differed (P < 0.05) between groups. A multivariate model including overall knee adduction moment magnitude, knee flexion/extension moment difference, and stance-dorsiflexion moment had a 74% correct classification rate, with no overtraining based on cross-validation. A 1-unit increase in model score increased by 6-fold the odds of progression to TKA. CONCLUSION: In addition to the link between higher overall knee adduction magnitude and future TKA, an outcome of clear clinical importance, novel findings include altered sagittal plane moment patterns indicative of reduced ability to unload the joint during midstance. This combination of dynamic biomechanical factors had a 6-fold increased odds of future TKA; adding baseline demographic and clinical factors did not improve the model.
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