This multicentre retrospective observational study’s aims were to investigate whether there are differences in the occurrence of radiolucent lines (RLLs) following total knee arthroplasty (TKA) between the conventional Attune baseplate and its successor, the novel Attune S+, independent from other potentially influencing factors; and whether tibial baseplate design and presence of RLLs are associated with differing risk of revision. A total of 780 patients (39% male; median age 70.7 years (IQR 62.0 to 77.2)) underwent cemented TKA using the Attune Knee System) at five centres, and with the latest radiograph available for the evaluation of RLL at between six and 36 months from surgery. Univariate and multivariate logistic regression models were performed to assess associations between patient and implant-associated factors on the presence of tibial and femoral RLLs. Differences in revision risk depending on RLLs and tibial baseplate design were investigated with the log-rank test.Aims
Methods
To identify unanswered questions about the prevention, diagnosis, treatment, and rehabilitation and delivery of care of first-time soft-tissue knee injuries (ligament injuries, patella dislocations, meniscal injuries, and articular cartilage) in children (aged 12 years and older) and adults. The James Lind Alliance (JLA) methodology for Priority Setting Partnerships was followed. An initial survey invited patients and healthcare professionals from the UK to submit any uncertainties regarding soft-tissue knee injury prevention, diagnosis, treatment, and rehabilitation and delivery of care. Over 1,000 questions were received. From these, 74 questions (identifying common concerns) were formulated and checked against the best available evidence. An interim survey was then conducted and 27 questions were taken forward to the final workshop, held in January 2023, where they were discussed, ranked, and scored in multiple rounds of prioritization. This was conducted by healthcare professionals, patients, and carers.Aims
Methods
To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.Aims
Methods
To map literature on prognostic factors related to outcomes of revision total knee arthroplasty (rTKA), to identify extensively studied factors and to guide future research into what domains need further exploration. We performed a systematic literature search in MEDLINE, Embase, and Web of Science. The search string included multiple synonyms of the following keywords: "revision TKA", "outcome" and "prognostic factor". We searched for studies assessing the association between at least one prognostic factor and at least one outcome measure after rTKA surgery. Data on sample size, study design, prognostic factors, outcomes, and the direction of the association was extracted and included in an evidence map.Aims
Methods
Aims. Accurate identification of the ankle joint centre is critical for estimating tibial coronal alignment in total knee arthroplasty (TKA). The purpose of the current study was to leverage
This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.Aims
Methods
The anterior cruciate ligament (ACL) is known to have a poor wound healing capacity, whereas other ligaments outside of the knee joint capsule such as the medial collateral ligament (MCL) apparently heal more easily. Plasmin has been identified as a major component in the synovial fluid that varies among patients. The aim of this study was to test whether plasmin, a component of synovial fluid, could be a main factor responsible for the poor wound healing capacity of the ACL. The effects of increasing concentrations of plasmin (0, 0.1, 1, 10, and 50 µg/ml) onto the wound closing speed (WCS) of primary ACL-derived ligamentocytes (ACL-LCs) were tested using wound scratch assay and time-lapse phase-contrast microscopy. Additionally, relative expression changes (quantitative PCR (qPCR)) of major LC-relevant genes and catabolic genes were investigated. The positive controls were 10% fetal calf serum (FCS) and platelet-derived growth factor (PDGF).Aims
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