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The Bone & Joint Journal
Vol. 101-B, Issue 11 | Pages 1423 - 1430
1 Nov 2019
Wiik AV Lambkin R Cobb JP

Aims. The aim of this study was to assess the functional gain achieved following hip resurfacing arthroplasty (HRA). Patients and Methods. A total of 28 patients (23 male, five female; mean age, 56 years (25 to 73)) awaiting Birmingham HRA volunteered for this prospective gait study, with an age-matched control group of 26 healthy adults (16 male, ten female; mean age, 56 years (33 to 84)). The Oxford Hip Score (OHS) and gait analysis using an instrumented treadmill were used preoperatively and more than two years postoperatively to measure the functional change attributable to the intervention. Results. The mean OHS improved significantly from 27 to 46 points (p < 0.001) at a mean of 29 months (12 to 60) after HRA. The mean metal ion levels at a mean 32 months (13 to 60) postoperatively were 1.71 (0.77 to 4.83) µg/l (ppb) and 1.77 (0.68 to 4.16) µg/l (ppb) for cobalt and chromium, respectively. When compared with healthy controls, preoperative patients overloaded the contralateral good hip, limping significantly. After HRA, patients walked at high speeds, with symmetrical gait, statistically indistinguishable from healthy controls over almost all characteristics. The control group could only be distinguished by an increased push-off force at higher speeds, which may reflect the operative approach. Conclusion. Patients undergoing HRA improved their preoperative gait pattern of a significant limp to a symmetrical gait at high speeds and on inclines, almost indistinguishable from normal controls. HRA with an approved device offers substantial functional gains, almost indistinguishable from healthy controls. Cite this article: Bone Joint J 2019;101-B:1423–1430


The Bone & Joint Journal
Vol. 98-B, Issue 10_Supple_B | Pages 16 - 21
1 Oct 2016
Jones GG Kotti M Wiik AV Collins R Brevadt MJ Strachan RK Cobb JP

Aims

To compare the gait of unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) patients with healthy controls, using a machine-learning approach.

Patients and Methods

145 participants (121 healthy controls, 12 patients with cruciate-retaining TKA, and 12 with mobile-bearing medial UKA) were recruited. The TKA and UKA patients were a minimum of 12 months post-operative, and matched for pattern and severity of arthrosis, age, and body mass index.

Participants walked on an instrumented treadmill until their maximum walking speed was reached. Temporospatial gait parameters, and vertical ground reaction force data, were captured at each speed. Oxford knee scores (OKS) were also collected. An ensemble of trees algorithm was used to analyse the data: 27 gait variables were used to train classification trees for each speed, with a binary output prediction of whether these variables were derived from a UKA or TKA patient. Healthy control gait data was then tested by the decision trees at each speed and a final classification (UKA or TKA) reached for each subject in a majority voting manner over all gait cycles and speeds. Top walking speed was also recorded.