Aims. There is inconsistent evidence on whether prior spinal fusion surgery adversely impacts outcomes following total hip arthroplasty (THA). We conducted a systematic review and meta-analysis to assess the association between pre-existing spinal fusion surgery and the rate of complications following primary THA. Methods. We searched MEDLINE, Embase, Web of Science, and Cochrane Library up to October 2019 for randomized controlled trials (RCTs) and observational studies comparing outcomes of dislocation, revision, or reasons for revision in patients following primary THA with or without pre-existing spinal fusion surgery. Furthermore, we compared short (two or less levels) or long (three or more levels) spinal fusions to no fusion. Summary measures of association were relative risks (RRs) (with 95% confidence intervals (CIs)). Results. We identified ten articles corresponding to nine unique observational studies comprising of 1,992,366
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
This study aimed to compare the effect of antibiotic-loaded bone cement (ALBC) versus plain bone cement (PBC) on revision rates for periprosthetic joint infection (PJI) and all-cause revisions following primary elective total hip arthroplasty (THA) and total knee arthroplasty (TKA). MEDLINE, Embase, Web of Science, and Cochrane databases were systematically searched for studies comparing ALBC versus PBC, reporting on revision rates for PJI or all-cause revision following primary elective THA or TKA. A random-effects meta-analysis was performed. The study was registered in the International Prospective Register of Systematic Reviews (PROSPERO ID CRD42018107691).Aims
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