Aims. There are comparatively few randomized studies evaluating knee arthroplasty prostheses, and fewer still that report longer-term functional outcomes. The aim of this study was to evaluate mid-term outcomes of an existing implant trial cohort to document changing patient function over time following total knee arthroplasty using longitudinal analytical techniques and to determine whether implant design chosen at time of surgery influenced these outcomes. Methods. A mid-term follow-up of the remaining 125 patients from a randomized cohort of total knee arthroplasty patients (initially comprising 212 recruited patients), comparing modern (Triathlon) and traditional (Kinemax) prostheses was undertaken. Functional outcomes were assessed with the Oxford Knee Score (OKS), knee range of movement, pain numerical rating scales, lower limb power output, timed functional assessment battery, and satisfaction survey. Data were linked to earlier assessment timepoints, and analyzed by repeated measures analysis of variance (ANOVA) mixed models, incorporating longitudinal change over all assessment timepoints. Results. The mean follow-up of the 125 patients was 8.12 years (7.3 to 9.4). There was a reduction in all assessment parameters relative to earlier assessments. Longitudinal models highlight changes over time in all parameters and demonstrate large effect sizes. Significant between-group differences were seen in measures of knee flexion (medium-effect size), lower limb power output (large-effect size), and report of worst daily pain experienced (large-effect size) favouring the Triathlon group. No longitudinal between-group differences were observed in mean OKS, average daily pain report, or timed
The aim of this study was to compare a bicruciate-retaining (BCR) total knee arthroplasty (TKA) with a posterior cruciate-retaining (CR) TKA design in terms of kinematics, measured using fluoroscopy and stability as micromotion using radiostereometric analysis (RSA). A total of 40 patients with end-stage osteoarthritis were included in this randomized controlled trial. All patients performed a step-up and lunge task in front of a monoplane fluoroscope one year postoperatively. Femorotibial contact point (CP) locations were determined at every flexion angle and compared between the groups. RSA images were taken at baseline, six weeks, three, six, 12, and 24 months postoperatively. Clinical and functional outcomes were compared postoperatively for two years.Aims
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The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance. A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset.Aims
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