With up to 40% of patients having patellofemoral joint osteoarthritis (PFJ OA), the two arthroplasty options are to replace solely the patellofemoral joint via patellofemoral arthroplasty (PFA), or the entire knee via total knee arthroplasty (TKA). The aim of this study was to assess postoperative success of second-generation PFAs compared to TKAs for patients treated for PFJ OA using patient-reported outcome measures (PROMs) and domains deemed important by patients following a patient and public involvement meeting. MEDLINE, EMBASE via OVID, CINAHL, and EBSCO were searched from inception to January 2022. Any study addressing surgical treatment of primary patellofemoral joint OA using second generation PFA and TKA in patients aged above 18 years with follow-up data of 30 days were included. Studies relating to OA secondary to trauma were excluded. ROB-2 and ROBINS-I bias tools were used.Aims
Methods
The aim of this study was to determine the risk of tibial eminence avulsion intraoperatively for bi-unicondylar knee arthroplasty (Bi-UKA), with consideration of the effect of implant positioning, overstuffing, and sex, compared to the risk for isolated medial unicondylar knee arthroplasty (UKA-M) and bicruciate-retaining total knee arthroplasty (BCR-TKA). Two experimentally validated finite element models of tibia were implanted with UKA-M, Bi-UKA, and BCR-TKA. Intraoperative loads were applied through the condyles, anterior cruciate ligament (ACL), medial collateral ligament (MCL), and lateral collateral ligament (LCL), and the risk of fracture (ROF) was evaluated in the spine as the ratio of the 95th percentile maximum principal elastic strains over the tensile yield strain of proximal tibial bone.Aims
Methods
Unicompartmental and total knee arthroplasty (UKA and TKA) are successful treatments for osteoarthritis, but the solid metal implants disrupt the natural distribution of stress and strain which can lead to bone loss over time. This generates problems if the implant needs to be revised. This study investigates whether titanium lattice UKA and TKA implants can maintain natural load transfer in the proximal tibia. In a cadaveric model, UKA and TKA procedures were performed on eight fresh-frozen knee specimens, using conventional (solid) and titanium lattice tibial implants. Stress at the bone-implant interfaces were measured and compared to the native knee.Aims
Methods
Joint registries classify all further arthroplasty procedures to a knee with an existing partial arthroplasty as revision surgery, regardless of the actual procedure performed. Relatively minor procedures, including bearing exchanges, are classified in the same way as major operations requiring augments and stems. A new classification system is proposed to acknowledge and describe the detail of these procedures, which has implications for risk, recovery, and health economics. 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.Aims
Methods
To compare the gait of unicompartmental knee arthroplasty (UKA)
and total knee arthroplasty (TKA) patients with healthy controls,
using a machine-learning approach. 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.Aims
Patients and Methods
