Methods

Classification categories were proposed by a surgical consensus group, then ranked by patients, according to perceived invasiveness and implications for recovery. In round one, 26 revision cases were classified by the consensus group. Results were tested for inter-rater reliability. In round two, four additional cases were added for clarity. Round three repeated the survey one month later, subject to inter- and intrarater reliability testing. In round four, five additional expert partial knee arthroplasty surgeons were asked to classify the 30 cases according to the proposed revision partial knee classification (RPKC) system.

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.