Aims. The underlying natural history of suspected
Aims. Occult (clinical) injuries represent 15% of all
Aims. Current National Institute for Health and Clinical Excellence (NICE) guidance advises that MRI direct from the emergency department (ED) should be considered for suspected
Aims. To explore individuals’ experience of a scaphoid waist fracture and its subsequent treatment. Methods. A purposive sample was created, consisting of 49 participants in the Scaphoid Waist Internal Fixation for Fractures Trial of initial surgery compared with plaster cast treatment for fractures of the scaphoid waist. The majority of participants were male (35/49) and more younger participants (28/49 aged under 30 years) were included. Participants were interviewed six weeks or 52 weeks post-recruitment to the trial, or at both timepoints. Interviews were semistructured and analyzed inductively to generate cross-cutting themes that typify experience of the injury and views upon the treatment options. Results. Data show that individual circumstances might exaggerate or mitigate the limitations associated with a
The aim of the Scaphoid Magnetic Resonance Imaging in Trauma (SMaRT) trial was to evaluate the clinical and cost implications of using immediate MRI in the acute management of patients with a suspected fracture of the scaphoid with negative radiographs. Patients who presented to the emergency department (ED) with a suspected fracture of the scaphoid and negative radiographs were randomized to a control group, who did not undergo further imaging in the ED, or an intervention group, who had an MRI of the wrist as an additional test during the initial ED attendance. Most participants were male (52% control, 61% intervention), with a mean age of 36.2 years (18 to 73) in the control group and 38.2 years (20 to 71) in the intervention group. The primary outcome was total cost impact at three months post-recruitment. Secondary outcomes included total costs at six months, the assessment of clinical findings, diagnostic accuracy, and the participants’ self-reported level of satisfaction. Differences in cost were estimated using generalized linear models with gamma errors.Aims
Patients and Methods
Aims. To determine the role of early MRI in the management of suspected
The October 2014 Wrist &
Hand Roundup360 looks at: pulsed electromagnetic field of no use in acute
The June 2014 Wrist &
Hand Roundup360 looks at: aart throwing not quite as we thought; two-gear, four-bar linkage in the wrist?; assessing outcomes in distal radial fractures; gold standard Swanson’s?; multistrand repairs of unclear benefit in flexor tendon release; for goodness’ sake, leave the thumb alone in
The December 2014 Wrist &
Hand Roundup360 looks at: ultrasound for carpal tunnel diagnosis; where we are at with management of undisplaced
The April 2015 Wrist &
Hand Roundup360 looks at: Non-operative hand fracture management; From the sublime to the ridiculous?; A novel approach to carpal tunnel decompression; Osteoporosis and functional scores in the distal radius; Ulnar variance and force distribution; Tourniquets in carpal tunnel under the spotlight;
The April 2013 Wrist &
Hand Roundup. 360 . looks at: whether botox is just for Hollywood; supercharging nerve repairs; YouTube research; options for Keinbock’s disease; volar plates; driving and plasters; symptomatic radial malunion; and MRI and acute
The December 2012 Wrist &
Hand Roundup. 360. looks at: the imaging of
The evidence demonstrating the superiority of early MRI has led to increased use of MRI in clinical pathways for acute wrist trauma. The aim of this study was to describe the radiological characteristics and the inter-observer reliability of a new MRI based classification system for scaphoid injuries in a consecutive series of patients. We identified 80 consecutive patients with acute scaphoid injuries at one centre who had presented within four weeks of injury. The radiographs and MRI scans were assessed by four observers, two radiologists, and two hand surgeons, using both pre-existing classifications and a new MRI based classification tool, the Oxford Scaphoid MRI Assessment Rating Tool (OxSMART). The OxSMART was used to categorize scaphoid injuries into three grades: contusion (grade 1); unicortical fracture (grade 2); and complete bicortical fracture (grade 3).Aims
Methods
The aim of this systematic review and meta-analysis was to gather epidemiological information on selected musculoskeletal injuries and to provide pooled injury-specific incidence rates. PubMed (National Library of Medicine) and Scopus (Elsevier) databases were searched. Articles were eligible for inclusion if they reported incidence rate (or count with population at risk), contained data on adult population, and were written in English language. The number of cases and population at risk were collected, and the pooled incidence rates (per 100,000 person-years) with 95% confidence intervals (CIs) were calculated by using either a fixed or random effects model.Aims
Methods
There is ambiguity surrounding the degree of scaphoid union required to safely allow mobilization following scaphoid waist fracture. Premature mobilization could lead to refracture, but late mobilization may cause stiffness and delay return to normal function. This study aims to explore the risk of refracture at different stages of scaphoid waist fracture union in three common fracture patterns, using a novel finite element method. The most common anatomical variant of the scaphoid was modelled from a CT scan of a healthy hand and wrist using 3D Slicer freeware. This model was uploaded into COMSOL Multiphysics software to enable the application of physiological enhancements. Three common waist fracture patterns were produced following the Russe classification. Each fracture had differing stages of healing, ranging from 10% to 90% partial union, with increments of 10% union assessed. A physiological force of 100 N acting on the distal pole was applied, with the risk of refracture assessed using the Von Mises stress.Aims
Methods
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
Methods
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: