Aims. Young adults undergoing
Aims. Postoperative length of stay (LOS) and discharge dispositions following arthroplasty can be used as surrogate measurements for improvements in patients’ pathways and costs. With the increasing use of robotic technology in arthroplasty, it is important to assess its impact on LOS. The aim of this study was to identify factors associated with decreased LOS following robotic arm-assisted
Aims. The aim of this study was to evaluate the suitability of the tapered cone stem in
Aims. Obesity is associated with an increased risk of hip osteoarthritis, resulting in an increased number of
Aims. The aim of this study was to evaluate the reliability and validity of a patient-specific algorithm which we developed for predicting changes in sagittal pelvic tilt after
Aims. The aim of this study was to compare the early postoperative mortality and morbidity in older patients with a fracture of the femoral neck, between those who underwent
Aims. For displaced femoral neck fractures (FNFs) in geriatric patients, there remains uncertainty regarding the effect of
Aims. Osteoporosis is common in
Aims. A revision for periprosthetic joint infection (PJI) in
Aims. Adult patients with history of childhood infection pose a surgical challenge for
Aims. The prevalence of obesity is increasing substantially around the world. Elevated BMI increases the risk of complications following
Aims. Excessive posterior pelvic tilt (PT) may increase the risk of anterior instability after
Aims. Mechanical impingement of the iliopsoas (IP) tendon accounts for 2% to 6% of persistent postoperative pain after
Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
Aims. Osteoporosis can determine surgical strategy for
Aims. Despite higher rates of revision after
Aims. Surgery is often delayed in patients who sustain a hip fracture and are treated with a
Aims. Oxidized zirconium (OxZi) and highly cross-linked polyethylene (HXLPE) were developed to minimize wear and risk of osteolysis in
Aims. This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after