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 systematic review and meta-analysis was conducted to compare open reduction and internal fixation (ORIF) with primary arthrodesis (PA) in the treatment of Lisfranc injuries, regarding patient-reported outcome measures (PROMs), and risk of secondary surgery. The aim was to conclusively determine the best available treatment based on the most complete and recent evidence available. A systematic search was conducted in PubMed, Cochrane Controlled Register of Trials (CENTRAL), EMBASE, CINAHL, PEDro, and SPORTDiscus. Additionally, ongoing trial registers and reference lists of included articles were screened. Risk of bias (RoB) and level of evidence were assessed using the Cochrane risk of bias tools and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool. The random and fixed-effect models were used for the statistical analysis.Aims
Methods
Aims. The principle strategies of fracture-related infection (FRI) treatment are debridement, antimicrobial therapy, and implant retention (DAIR) or debridement, antimicrobial therapy, and
Despite its intrinsic ability to regenerate form and function after injury, bone tissue can be challenged by a multitude of pathological conditions. While innovative approaches have helped to unravel the cascades of bone healing, this knowledge has so far not improved the clinical outcomes of bone defect treatment. Recent findings have allowed us to gain in-depth knowledge about the physiological conditions and biological principles of bone regeneration. Now it is time to transfer the lessons learned from bone healing to the challenging scenarios in defects and employ innovative technologies to enable biomaterial-based strategies for bone defect healing. This review aims to provide an overview on endogenous cascades of bone material formation and how these are transferred to new perspectives in biomaterial-driven approaches in bone regeneration. Cite this article: T. Winkler, F. A. Sass, G. N. Duda, K. Schmidt-Bleek. A review of biomaterials in bone defect healing, remaining shortcomings and future opportunities for bone tissue engineering: The unsolved challenge.