Aims. The burden of revision total hip arthroplasty (rTHA) continues to grow. The surgery is complex and associated with significant costs. Regional rTHA networks have been proposed to improve outcomes and to reduce re-revisions, and therefore costs. The aim of this study was to accurately quantify the cost and reimbursement for a rTHA service, and to assess the financial impact of case complexity at a tertiary referral centre within the NHS. Methods. A retrospective analysis of all revision hip procedures was performed at this centre over two consecutive financial years (2018 to 2020). Cases were classified according to the Revision Hip Complexity Classification (RHCC) and whether they were infected or non-infected. Patients with an American Society of Anesthesiologists (ASA) grade ≥ III or BMI ≥ 40 kg/m. 2. are considered “high risk” by the RHCC. Costs were calculated using the Patient Level Information and Costing System (PLICS), and remuneration based on Healthcare Resource Groups (HRG) data. The primary outcome was the financial difference between tariff and cost per patient episode. Results. In all, 199 revision episodes were identified in 168 patients: 25 (13%) least complex revisions (H1); 110 (55%) complex revisions (H2); and 64 (32%) most complex revisions (H3). Of the 199, 76 cases (38%) were due to infection, and 78 patients (39%) were “high risk”. Median length of stay increased significantly with case complexity from four days to six to eight days (p = 0.006) and for revisions performed for infection (9 days vs 5 days; p < 0.001). Cost per episode increased significantly between complexity groups (p < 0.001) and for infected revisions (p < 0.001). All groups demonstrated a mean deficit but this significantly increased with revision complexity (£97, £1,050, and £2,887 per case; p = 0.006) and for infected failure (£2,629 vs £635; p = 0.032). The total deficit to the NHS Trust over two years was £512,202. Conclusion. Current NHS reimbursement for rTHA is inadequate and should be more closely aligned to complexity. An increase in the most complex rTHAs at major revision centres will likely place a greater financial burden on these units. Cite this article: Bone Jt Open 2023;4(8):559–566

Aims. Advances in surgical technique and implant design may influence the incidence and mechanism of failure resulting in revision total hip arthroplasty (rTHA). The purpose of the current study was to characterize aetiologies requiring rTHA, and to determine whether temporal changes existed in these aetiologies over a ten-year period. Methods. All rTHAs performed at a single institution from 2009 to 2019 were identified. Demographic information and mode of implant failure was obtained for all patients. Data for rTHA were stratified into two time periods to assess for temporal changes: 2009 to 2013, and 2014 to 2019. Operative reports, radiological imaging, and current procedural terminology (CPT) codes were cross-checked to ensure the accurate classification of revision aetiology for each patient. Results. In all, 2,924 patients with a mean age of 64.6 years (17 to 96) were identified. There were 1,563 (53.5%) female patients, and the majority of patients were Caucasian (n = 2,362, 80.8%). The three most frequent rTHA aetiologies were infection (27.2%), aseptic loosening (25.2%), and wear (15.2%). The frequency of rTHA for adverse local tissue reaction (ALTR) was significantly greater from 2014 to 2019 (4.7% vs 10.0%; p < 0.001), while the frequency of aseptic loosening was significantly greater from 2009 to 2013 (28.6% vs 21.9%; p < 0.001). Conclusion. Periprosthetic joint infection was the most common cause for rTHA in the current cohort of patients. Complications associated with ALTR necessitating rTHA was more frequent between 2014 to 2019, while aseptic loosening necessitating rTHA was significantly more frequent between 2009 to 2013. Optimizing protocols for prevention and management of infection and ALTR after THA may help to avoid additional financial burden to institutions and healthcare systems. Cite this article: Bone Joint Open 2020;2(1):16–21

Aims

To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials.