The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes.Aims
Methods
Chronic osteomyelitis (COM) of the lower limb in adults can be surgically managed by either limb reconstruction or amputation. This scoping review aims to map the outcomes used in studies surgically managing COM in order to aid future development of a core outcome set. A total of 11 databases were searched. A subset of studies published between 1 October 2020 and 1 January 2011 from a larger review mapping research on limb reconstruction and limb amputation for the management of lower limb COM were eligible. All outcomes were extracted and recorded verbatim. Outcomes were grouped and categorized as per the revised Williamson and Clarke taxonomy.Aims
Methods
This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms. We analyzed microarray data from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA), machine learning, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify common genetic factors between POMP and sarcopenia. Further validation was done via differential gene expression in a new cohort. Single-cell analysis identified high expression cell subsets, with mononuclear macrophages in osteoporosis and muscle stem cells in sarcopenia, among others. A competitive endogenous RNA network suggested regulatory elements for these genes.Aims
Methods
As the world continues to fight successive waves of COVID-19 variants, we have seen worldwide infections surpass 100 million. London, UK, has been severely affected throughout the pandemic, and the resulting impact on the NHS has been profound. The aim of this study is to evaluate the impact of COVID-19 on theatre productivity across London’s four major trauma centres (MTCs), and to assess how the changes to normal protocols and working patterns impacted trauma theatre efficiency. This was a collaborative study across London’s MTCs. A two-month period was selected from 5 March to 5 May 2020. The same two-month period in 2019 was used to provide baseline data for comparison. Demographic information was collected, as well as surgical speciality, procedure, time to surgery, type of anaesthesia, and various time points throughout the patient journey to theatre.Aims
Methods
