Unicompartmental knee arthroplasty (UKA) is a bone-preserving treatment option for osteoarthritis localized to a single compartment in the knee. The success of the procedure is sensitive to patient selection and alignment errors. Robotic arm-assisted UKA provides technological assistance to intraoperative bony resection accuracy, which is thought to improve ligament balancing. This paper presents the five-year outcomes of a comparison between manual and robotically assisted UKAs. The trial design was a prospective, randomized, parallel, single-centre study comparing surgical alignment in patients undergoing UKA for the treatment of medial compartment osteoarthritis (ISRCTN77119437). Participants underwent surgery using either robotic arm-assisted surgery or conventional manual instrumentation. The primary outcome measure (surgical accuracy) has previously been reported, and, along with secondary outcomes, were collected at one-, two-, and five-year timepoints. Analysis of five-year results and longitudinal analysis for all timepoints was performed to compare the two groups.Aims
Methods
Limb alignment in total knee arthroplasty (TKA) influences periarticular soft-tissue tension, biomechanics through knee flexion, and implant survival. Despite this, there is no uniform consensus on the optimal alignment technique for TKA. Neutral mechanical alignment facilitates knee flexion and symmetrical component wear but forces the limb into an unnatural position that alters native knee kinematics through the arc of knee flexion. Kinematic alignment aims to restore native limb alignment, but the safe ranges with this technique remain uncertain and the effects of this alignment technique on component survivorship remain unknown. Anatomical alignment aims to restore predisease limb alignment and knee geometry, but existing studies using this technique are based on cadaveric specimens or clinical trials with limited follow-up times. Functional alignment aims to restore the native plane and obliquity of the joint by manipulating implant positioning while limiting soft tissue releases, but the results of high-quality studies with long-term outcomes are still awaited. The drawbacks of existing studies on alignment include the use of surgical techniques with limited accuracy and reproducibility of achieving the planned alignment, poor correlation of intraoperative data to long-term functional outcomes and implant survivorship, and a paucity of studies on the safe ranges of limb alignment. Further studies on alignment in TKA should use surgical adjuncts (e.g. robotic technology) to help execute the planned alignment with improved accuracy, include intraoperative assessments of knee biomechanics and periarticular soft-tissue tension, and correlate alignment to long-term functional outcomes and survivorship.
The aim of the British Association for Surgery of the Knee (BASK) Meniscal Consensus Project was to develop an evidence-based treatment guideline for patients with meniscal lesions of the knee. A formal consensus process was undertaken applying nominal group, Delphi, and appropriateness methods. Consensus was first reached on the terminology relating to the definition, investigation, and classification of meniscal lesions. A series of simulated clinical scenarios was then created and the appropriateness of arthroscopic meniscal surgery or nonoperative treatment in each scenario was rated by the group. The process was informed throughout by the latest published, and previously unpublished, clinical and epidemiological evidence. Scenarios were then grouped together based upon the similarity of clinical features and ratings to form the guideline for treatment. Feedback on the draft guideline was sought from the entire membership of BASK before final revisions and approval by the consensus group.Aims
Materials and 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
