Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy.Aims
Methods
We present the development of a day-case total hip arthroplasty (THA) pathway in a UK National Health Service institution in conjunction with an extensive evidence-based summary of the interventions used to achieve successful day-case THA to which the protocol is founded upon. We performed a prospective audit of day-case THA in our institution as we reinitiate our full capacity elective services. In parallel, we performed a review of the literature reporting complication or readmission rates at ≥ 30-day postoperative following day-case THA. Electronic searches were performed using four databases from the date of inception to November 2020. Relevant studies were identified, data extracted, and qualitative synthesis performed.Aims
Methods
The rate of dislocation when traditional single bearing implants are used in revision total hip arthroplasty (THA) has been reported to be between 8% and 10%. The use of dual mobility bearings can reduce this risk to between 0.5% and 2%. Dual mobility bearings are more expensive, and it is not clear if the additional clinical benefits constitute value for money for the payers. We aimed to estimate the cost-effectiveness of dual mobility compared with single bearings for patients undergoing revision THA. We developed a Markov model to estimate the expected cost and benefits of dual mobility compared with single bearing implants in patients undergoing revision THA. The rates of revision and further revision were calculated from the National Joint Registry of England and Wales, while rates of transition from one health state to another were estimated from the literature, and the data were stratified by sex and age. Implant and healthcare costs were estimated from local procurement prices and national tariffs. Quality-adjusted life-years (QALYs) were calculated using published utility estimates for patients undergoing THA.Aims
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