Aims

Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.

Aims. The aim of this study was to perform a systematic review of the evidence for the use of intraoperative cell salvage in patients undergoing revision hip arthroplasty, and specifically to analyze the available data in order to quantify any associated reduction in the use of allogenic blood transfusion, and the volume which is used. Methods. An electronic search of MEDLINE (PubMed), Embase, Scopus, and the Cochrane Library was completed from the date of their inception to 24 February 2022, using a search strategy and protocol created in conjunction with the PRISMA statement. Inclusion criteria were patients aged > 18 years who underwent revision hip arthroplasty when cell salvage was used. Studies in which pre-donated red blood cells were used were excluded. A meta-analysis was also performed using a random effects model with significance set at p = 0.05. Results. Of the 283 studies which were identified, 11 were included in the systematic review, and nine in the meta-analysis. There was a significant difference (p < 0.001) in the proportion of patients requiring allogenic transfusion between groups, with an odds ratio of 0.331 (95% confidence interval (CI) 0.165 to 0.663) associated with the use of cell salvage. For a total of 561 patients undergoing revision hip arthroplasty who were treated with cell salvage, 247 (44.0%) required allogenic transfusion compared with 418 of 643 patients (65.0%) who were treated without cell salvage. For those treated with cell salvage, the mean volume of allogenic blood which was required was 1.95 units (390 ml) per patient (0.7 to 4.5 units), compared with 3.25 units (650 ml) per patient (1.2 to 7.0 units) in those treated without cell salvage. The mean difference of -1.91 units (95% CI -4.0 to 0.2) in the meta-analysis was also significant (p = 0.003). Conclusion. We found a a significant reduction in the need for allogenic blood transfusion when cell salvage was used in patients undergoing revision hip arthroplasty, supporting its routine use in these patients. Further research is required to determine whether this effect is associated with types of revision arthroplasty of differing complexity. Cite this article: Bone Joint J 2023;105-B(10):1038–1044

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: Bone Joint J 2022;104-B(12):1292–1303.

Aims

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.

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Current guidelines recommend surgery within 48 hours among patients presenting with hip fractures; however, optimal surgical timing for patients on oral anticoagulants (OACs) remains unclear. Individual studies are limited by small sample sizes and heterogeneous outcomes. The aim of this study was to conduct a systematic review and meta-analysis to summarize the effect of pre-injury OACs on time-to-surgery (TTS) and all-cause mortality among older adults with hip fracture treated surgically.

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A systematic literature review focusing on how long before surgery concurrent viral or bacterial infections (respiratory and urinary infections) should be treated in hip fracture patients, and if there is evidence for delaying this surgery.

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We conducted a systematic review and meta-analysis to compare the mortality, morbidity, and functional outcomes of cemented versus uncemented hemiarthroplasty in the treatment of intracapsular hip fractures, analyzing contemporary and non-contemporary implants separately.