This prospective study reports longitudinal, within-patient, patient-reported outcome measures (PROMs) over a 15-year period following cemented single radius total knee arthroplasty (TKA). Secondary aims included reporting PROMs trajectory, 15-year implant survival, and patient attrition from follow-up. From 2006 to 2007, 462 consecutive cemented cruciate-retaining Triathlon TKAs were implanted in 426 patients (mean age 69 years (21 to 89); 290 (62.7%) female). PROMs (12-item Short Form Survey (SF-12), Oxford Knee Score (OKS), and satisfaction) were assessed preoperatively and at one, five, ten, and 15 years. Kaplan-Meier survival and univariate analysis were performed.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
The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA). A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.Aims
Methods
