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:
To determine whether obesity and malnutrition have a synergistic effect on outcomes from skeletal trauma or elective orthopaedic surgery. Electronic databases including MEDLINE, Global Health, Embase, Web of Science, ScienceDirect, and PEDRo were searched up to 14 April 2024, as well as conference proceedings and the reference lists of included studies. Studies were appraised using tools according to study design, including the Oxford Levels of Evidence, the Institute of Health Economics case series quality appraisal checklist, and the CLARITY checklist for cohort studies. Studies were eligible if they reported the effects of combined malnutrition and obesity on outcomes from skeletal trauma or elective orthopaedic surgery.Aims
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Sarcopenia is characterized by a generalized progressive loss of skeletal muscle mass, strength, and physical performance. This systematic review primarily evaluated the effects of sarcopenia on postoperative functional recovery and mortality in patients undergoing orthopaedic surgery, and secondarily assessed the methods used to diagnose and define sarcopenia in the orthopaedic literature. A systematic search was conducted in MEDLINE, EMBASE, and Google Scholar databases according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Studies involving sarcopenic patients who underwent defined orthopaedic surgery and recorded postoperative outcomes were included. The quality of the criteria by which a diagnosis of sarcopenia was made was evaluated. The quality of the publication was assessed using Newcastle-Ottawa Scale.Aims
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