Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests.Aims
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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. A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias.Aims
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This systematic review aimed to summarize the full range of complications reported following ankle arthroscopy and the frequency at which they occur. A computer-based search was performed in PubMed, Embase, Emcare, and ISI Web of Science. Two-stage title/abstract and full-text screening was performed independently by two reviewers. English-language original research studies reporting perioperative complications in a cohort of at least ten patients undergoing ankle arthroscopy were included. Complications were pooled across included studies in order to derive an overall complication rate. Quality assessment was performed using the Oxford Centre for Evidence-Based Medicine levels of evidence classification.Aims
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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:
The aim of this study was to assess the effect of time to surgical intervention from admission on mortality and morbidity for patients with hip fractures. MEDLINE and Embase were searched from inception to June 2020. Reference lists were manually assessed to identify additional papers. Primary comparative research studies that recruited patients aged over 60 years, with non-pathological primary proximal femoral fractures that were treated surgically, were included. Studies that did not include a group operated on within 24 hours or which reported time to surgery in calendar days were excluded. Two investigators extracted data on study characteristics, methods, and outcomes. The pre-defined primary outcome was 30-day mortality. Secondary outcomes were complications and mortality at other time points. Relative risks (RRs) with 95% confidence intervals (CIs) were aggregated and were grouped by study-level characteristics.Aims
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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. We searched MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to 14 October 2019 to identify studies directly comparing outcomes among hip fracture patients receiving direct oral anticoagulants (DOACs) or vitamin K antagonists (VKAs) prior to hospital admission to hip fracture patients not on OACs. Random effects meta-analyses were used to pool all outcomes (TTS, in-hospital mortality, and 30-day mortality).Aims
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