Gait comparison of unicompartmental and total knee arthroplasties with healthy controls

Abstract

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.

Results: 92% of the healthy controls were classified by the decision tree as a UKA, 5% as a TKA, and 3% were unclassified. There was no significant difference in OKS between the UKA and TKA patients (p = 0.077). Top walking speed in TKA patients (1.6 m/s; 1.3 to 2.1) was significantly lower than that of both the UKA group (2.2 m/s; 1.8 to 2.7) and healthy controls (2.2 m/s; 1.5 to 2.7; p < 0.001).

Conclusion: UKA results in a more physiological gait compared with TKA, and a higher top walking speed. This difference in function was not detected by the OKS. Cite this article: Bone Joint J 2016;98-B(10 Suppl B):16-21.

Keywords: Gait; Patient-reported outcome measures; Total knee arthroplasty; Unicompartmental knee arthroplasty.

Fig. 1

Decision tree at 4 km/h trained with unicompartmental and total knee arthroplasty (UKA and TKA) data to classify gait in a binary fashion. First peak force and maximum force (normalised, therefore dimensionless), and mean anteroposterior centre of pressure (cm) values were selected by the algorithm. Gait data from each healthy control at 4 km/h was then processed by this decision tree, and classified as either a UKA or TKA. This was repeated at all eight walking speeds.

Fig. 2

Graph showing mean force time curve for unicompartmental and total knee arthroplasty (UKA and TKA) and healthy controls at 4 km/h. Healthy control data are displayed with 95% confidence intervals. † represents heel strike, ∆ represents mid-stance, and § represents toe-off.

Fig. 3

Box-plots of top walking speeds showing median (red line), upper and lower quartiles (box), minimum and maximum values (whiskers). *Total knee arthroplasty (TKA) patients were significantly slower than unicompartmental knee arthroplasty (UKA) patients, and healthy controls (p < 0.001)

Fig. 4

During level walking by patients who had anterior cruciate (ACL) deficiency, an external extension moment about the knee persisted throughout most of the stance phase. In the presence of this moment, there is no need for activity of the quadriceps while the knee is near full extension. Normally, the necessary extension moment is produced by the quadriceps and is resisted by the anterior cruciate ligament. The asterisks identify the time during stance phase when the moments about knee of the control subjects and the patients were significantly different. Please see the original for the definitions of net quadriceps and net hamstring moments used in this study (reproduced from Berchuck et al with permission).