Aims Some patients presenting with hip pain and instability and underlying acetabular dysplasia (AD) do not experience resolution of symptoms after surgical management. Hip-spine syndrome is a possible underlying cause. We hypothesized that there is a higher frequency of radiological spine anomalies in patients with AD. We also assessed the relationship between radiological severity of AD and frequency of spine anomalies. Methods In a retrospective analysis of registry data, 122 hips in 122 patients who presented with hip pain and and a final diagnosis of AD were studied. Two observers analyzed hip and spine variables using standard radiographs to assess AD. The frequency of lumbosacral transitional vertebra (LSTV), along with associated Castellvi grade, pars interarticularis defect, and spinal morphological measurements were recorded and correlated with radiological severity of AD. Results Out of 122 patients, 110 (90.2%) were female and 12 (9.8%) were male. We analyzed the radiographs of 122 hips (59 (48.4%) symptomatic left hips, and 63 (51.6%) symptomatic right hips). Average age at time of presentation was 34.2 years (SD 11.2). Frequency of LSTV was high (39% to 43%), compared to historic records from the general population, with Castellvi type 3b being the most common (60% to 63%). Patients with AD have increased L4 and L5 interpedicular distance compared to published values. Frequency of pars interarticularis defect was 4%. Intraclass correlation coefficient for hip and spine variables assessed ranged from good (0.60 to 0.75) to excellent (0.75 to 1.00). Severity of AD did not demonstrate significant correlation with frequency of radiological spine anomalies. Conclusion Patients with AD have increased frequency of spinal anomalies seen on standard hip radiographs. However, there exists no correlation between radiological severity of AD and frequency of spine anomalies. In managing AD patients, clinicians should also assess spinal anomalies that are easily found on standard hip radiographs. Cite this article: Bone Joint J 2021;103-B(8):1351–1357.

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Background: Femoral head osteonecrosis (FHON) is a well-recognised complication in patients with human immunodeficiency virus (HIV) infection. Total hip arthroplasty (THA) is a reliable solution to FHON and has provided functional improvement and pain relief in these patients. Higher complication rates, in particular infections, have been reported in the series of THAs done in the HIV-positive patients. The purpose of this study was to evaluate the complication rate of THA for FHON in HIV-positive patients managed with the highly active antiretroviral therapy (HAART) protocols. Methods: A retrospective review was performed of HIV-positive patients with FHON who underwent THAs over a 10-year period at a single institution. Results: A total of 56 THAs (44 patients) met the inclusion criteria. The mean age at the time of THAs was 47 (range 34–60) years. Of the 44 patients, 39 (88.6%) were males. The mean follow-up was 6.6 (range 2.0–11.3) years. The overall complication rate was 12.5%, with 2 (3.6%) cases of deep periprosthetic infections. Conclusions: HIV-positive patients with FHON undergoing THAs do have a considerable complication rate (12.5%). The deep periprosthetic infection rate (3.6%) in these patients, however, has decreased with contemporary disease modification protocols.

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Algorithmic fairness in the context of personalized recommendation presents significantly different challenges to those commonly encountered in classification tasks. Researchers studying classification have generally considered fairness to be a matter of achieving equality of outcomes between a protected and unprotected group, and built algorithmic interventions on this basis. We argue that fairness in real-world application settings in general, and especially in the context of personalized recommendation, is much more complex and multi-faceted, requiring a more general approach. We propose a model to formalize multistakeholder fairness in recommender systems as a two stage social choice problem. In particular, we express recommendation fairness as a novel combination of an allocation and an aggregation problem, which integrate both fairness concerns and personalized recommendation provisions, and derive new recommendation techniques based on this formulation. Simulations demonstrate the ability of the framework to integrate multiple fairness concerns in a dynamic way. CCS Concepts: • Information systems → Recommender systems; • Computing methodologies → Multi-agent systems; • Social and professional topics → User characteristics.