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 main advantage of 3D-printed, off-the-shelf acetabular implants is the potential to promote enhanced bony fixation due to their controllable porous structure. In this study we investigated the extent of osseointegration in retrieved 3D-printed acetabular implants. We compared two groups, one made via 3D-printing (n = 7) and the other using conventional techniques (n = 7). We collected implant details, type of surgery and removal technique, patient demographics, and clinical history. Bone integration was assessed by macroscopic visual analysis, followed by sectioning to allow undecalcified histology on eight sections (~200 µm) for each implant. The outcome measures considered were area of bone attachment (%), extent of bone ingrowth (%), bone-implant contact (%), and depth of ingrowth (%), and these were quantified using a line-intercept method.Aims
Methods
Assessment of bone mineral density (BMD) with dual-energy X-ray absorptiometry (DXA) is a well-established clinical technique, but it is not available in the acute trauma setting. Thus, it cannot provide a preoperative estimation of BMD to help guide the technique of fracture fixation. Alternative methods that have been suggested for assessing BMD include: 1) cortical measures, such as cortical ratios and combined cortical scores; and 2) aluminium grading systems from preoperative digital radiographs. However, limited research has been performed in this area to validate the different methods. The aim of this study was to investigate the evaluation of BMD from digital radiographs by comparing various methods against DXA scanning. A total of 54 patients with distal radial fractures were included in the study. Each underwent posteroanterior (PA) and lateral radiographs of the injured wrist with an aluminium step wedge. Overall 27 patients underwent routine DXA scanning of the hip and lumbar spine, with 13 undergoing additional DXA scanning of the uninjured forearm. Analysis of radiographs was performed on ImageJ and Matlab with calculations of cortical measures, cortical indices, combined cortical scores, and aluminium equivalent grading.Aims
Methods
The primary purpose of this meta-analysis was to determine whether statin usage could reduce the risk of glucocorticoid-related osteonecrosis in animal models. A systematic literature search up to May 2015 was carried out using the PubMed, Ovid, EBM reviews, ISI Web of Science, EBSCO, CBM, CNKI databases with the term and boolean operators: statins and osteonecrosis in all fields. Risk ratio (RR), as the risk estimate of specific outcome, was calculated along with 95% confidence intervals (CI). The methodological quality of individual studies was assessed using a quantitative tool based on the updated Stroke Therapy Academic Industry Roundtable (STAIR) recommendations.Objectives
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