The aims were to assess whether joint-specific outcome after total knee arthroplasty (TKA) was influenced by implant design over a 12-year follow-up period, and whether patient-related factors were associated with loss to follow-up and mortality risk. Long-term follow-up of a randomized controlled trial was undertaken. A total of 212 patients were allocated a Triathlon or a Kinemax TKA. Patients were assessed preoperatively, and one, three, eight, and 12 years postoperatively using the Oxford Knee Score (OKS). Reasons for patient lost to follow-up, mortality, and revision were recorded.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
