Aims. Scapular notching is thought to have an adverse effect on the outcome of reverse total shoulder arthroplasty (RTSA). However, the matter is still controversial. The aim of this study was to determine the clinical impact of scapular notching on outcomes after RTSA. Methods. Three electronic databases (PubMed, Cochrane Database, and EMBASE) were searched for studies which evaluated the influence of scapular notching on clinical outcome after RTSA. The quality of each study was assessed. Functional outcome scores (the Constant-Murley scores (CMS), and the American Shoulder and Elbow Surgeons (ASES) scores), and postoperative range of movement (forward flexion (FF), abduction, and external rotation (ER)) were extracted and subjected to meta-analysis. Effect sizes were expressed as weighted mean differences (WMD). Results. In all, 11 studies (two level III and nine level IV) were included in the meta-analysis. All analyzed variables indicated that scapular notching has a negative effect on the outcome of RTSA . Statistical significance was found for the CMS (WMD –3.11; 95% confidence interval (CI) –4.98 to –1.23), the
The primary aim of this prospective, multicentre study is to describe the rates of returning to golf following hip, knee, ankle, and shoulder arthroplasty in an active golfing population. Secondary aims will include determining the timing of return to golf, changes in ability, handicap, and mobility, and assessing joint-specific and health-related outcomes following surgery. This is a multicentre, prospective, longitudinal study between the Hospital for Special Surgery, (New York City, New York, USA) and Edinburgh Orthopaedics, Royal Infirmary of Edinburgh, (Edinburgh, UK). Both centres are high-volume arthroplasty centres, specializing in upper and lower limb arthroplasty. Patients undergoing hip, knee, ankle, or shoulder arthroplasty at either centre, and who report being golfers prior to arthroplasty, will be included. Patient-reported outcome measures will be obtained at six weeks, three months, six months, and 12 months. A two-year period of recruitment will be undertaken of arthroplasty patients at both sites.Aims
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The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
It is important to understand the rate of complications associated with the increasing burden of revision shoulder arthroplasty. Currently, this has not been well quantified. This review aims to address that deficiency with a focus on complication and reoperation rates, shoulder outcome scores, and comparison of anatomical and reverse prostheses when used in revision surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review was performed to identify clinical data for patients undergoing revision shoulder arthroplasty. Data were extracted from the literature and pooled for analysis. Complication and reoperation rates were analyzed using a meta-analysis of proportion, and continuous variables underwent comparative subgroup analysis.Aims
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