This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate.Aims
Methods
The June 2014 Hip &
Pelvis Roundup360 looks at: Modular femoral necks: early signs are not good; is corrosion to blame for modular neck failures; metal-on-metal is not quite a closed book; no excess failures in fixation of displaced femoral neck fractures; noise no problem in hip replacement; heterotopic ossification after hip arthroscopy: are NSAIDs the answer?; thrombotic and bleeding events surprisingly low in total joint replacement; and the elephant in the room: complications and surgical volume.
