Debate remains whether the patella should be resurfaced during total knee replacement (TKR). For non-resurfaced TKRs, we estimated what the revision rate would have been if the patella had been resurfaced, and examined the risk of re-revision following secondary patellar resurfacing. A retrospective observational study of the National Joint Registry (NJR) was performed. All primary TKRs for osteoarthritis alone performed between 1 April 2003 and 31 December 2016 were eligible (n = 842,072). Patellar resurfacing during TKR was performed in 36% (n = 305,844). The primary outcome was all-cause revision surgery. Secondary outcomes were the number of excess all-cause revisions associated with using TKRs without (versus with) patellar resurfacing, and the risk of re-revision after secondary patellar resurfacing.Aims
Methods
Open reduction in developmental dysplasia of the hip (DDH) is regularly performed despite screening programmes, due to failure of treatment or late presentation. A protocol for open reduction of DDH has been refined through collaboration between surgical, anaesthetic, and nursing teams to allow same day discharge. The objective of this study was to determine the safety and feasibility of performing open reduction of DDH as a day case. A prospectively collected departmental database was visited. All consecutive surgical cases of DDH between June 2015 and March 2020 were collected. Closed reductions, bilateral cases, cases requiring corrective osteotomy, and children with comorbidities were excluded. Data collected included demographics, safety outcome measures (blood loss, complications, readmission, reduction confirmation), and feasibility for discharge according to the Face Legs Activity Cry Consolidability (FLACC) pain scale. A satisfaction questionnaire was filled by the carers. Descriptive statistics were used for analysis.Aims
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Richard Carey Smith is an orthopaedic oncology surgeon with fellowship
Injuries to the hamstring muscle complex are common in athletes, accounting for between 12% and 26% of all injuries sustained during sporting activities. Acute hamstring injuries often occur during sports that involve repetitive kicking or high-speed sprinting, such as American football, soccer, rugby, and athletics. They are also common in watersports, including waterskiing and surfing. Hamstring injuries can be career-threatening in elite athletes and are associated with an estimated risk of recurrence in between 14% and 63% of patients. The variability in prognosis and treatment of the different injury patterns highlights the importance of prompt diagnosis with magnetic resonance imaging (MRI) in order to classify injuries accurately and plan the appropriate management. Low-grade hamstring injuries may be treated with nonoperative measures including pain relief, eccentric lengthening exercises, and a graduated return to sport-specific activities. Nonoperative management is associated with highly variable times for convalescence and return to a pre-injury level of sporting function. Nonoperative management of high-grade hamstring injuries is associated with poor return to baseline function, residual muscle weakness and a high-risk of recurrence. Proximal hamstring avulsion injuries, high-grade musculotendinous tears, and chronic injuries with persistent weakness or functional compromise require surgical repair to enable return to a pre-injury level of sporting function and minimize the risk of recurrent injury. This article reviews the optimal diagnostic imaging methods and common classification systems used to guide the treatment of hamstring injuries. In addition, the indications and outcomes for both nonoperative and operative treatment are analyzed to provide an evidence-based management framework for these patients. Cite this article:
The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an anteroposterior pelvic radiograph deep learning system for diagnosing DDH in children and analyze the feasibility of its application. In total, 10,219 anteroposterior pelvic radiographs were retrospectively collected from April 2014 to December 2018. Clinicians labelled each radiograph using a uniform standard method. Radiographs were grouped according to age and into ‘dislocation’ (dislocation and subluxation) and ‘non-dislocation’ (normal cases and those with dysplasia of the acetabulum) groups based on clinical diagnosis. The deep learning system was trained and optimized using 9,081 radiographs; 1,138 test radiographs were then used to compare the diagnoses made by deep learning system and clinicians. The accuracy of the deep learning system was determined using a receiver operating characteristic curve, and the consistency of acetabular index measurements was evaluated using Bland-Altman plots.Aims
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Healthcare systems have been rapidly restructured to meet COVID-19 demand. Clinicians are working to novel clinical guidelines, treating new patient cohorts and working in unfamiliar environments. Trauma and orthopaedics (T&O) has experienced cancellation of routine clinics and operating, with redistribution of the workload and human resources. To date, no studies have evaluated the mental health impact of these changes on the T&O workforce. We report the results of a novel survey on the impact of the pandemic on the mental health of our orthopaedic workforce and the contributory factors. A 20-question survey-based cross-sectional study of orthopaedic team members was conducted during the COVID-19 pandemic. The primary objective was to identify the impact of the pandemic on mental health in the form of major depressive disorder (MDD) and general anxiety disorder (GAD). The survey incorporated the patient health questionnaire (PHQ-2), which is validated for screening of MDD, and the generalized anxiety disorder questionnaire (GAD-2), which is validated for screening of GAD.Aims
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Virtual fracture clinics (VFCs) are advocated by recent British Orthopaedic Association Standards for Trauma and Orthopaedics (BOASTs) to efficiently manage injuries during the COVID-19 pandemic. The primary aim of this national study is to assess the impact of these standards on patient satisfaction and clinical outcome amid the pandemic. The secondary aims are to determine the impact of the pandemic on the demographic details of injuries presenting to the VFC, and to compare outcomes and satisfaction when the BOAST guidelines were first introduced with a subsequent period when local practice would be familiar with these guidelines. This is a national cross-sectional cohort study comprising centres with VFC services across the UK. All consecutive adult patients assessed in VFC in a two-week period pre-lockdown (6 May 2019 to 19 May 2019) and in the same two-week period at the peak of the first lockdown (4 May 2020 to 17 May 2020), and a randomly selected sample during the ‘second wave’ (October 2020) will be eligible for the study. Data comprising local VFC practice, patient and injury characteristics, unplanned re-attendances, and complications will be collected by local investigators for all time periods. A telephone questionnaire will be used to determine patient satisfaction and patient-reported outcomes for patients who were discharged following VFC assessment without face-to-face consultation.Aims
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The purpose of this study was to compare the radiological outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Postoperative radiological outcomes from 86 consecutive robotic-assisted UKAs (RAUKA group) from a single academic centre were retrospectively reviewed and compared to 253 manual UKAs (MUKA group) drawn from a prior study at our institution. Femoral coronal and sagittal angles (FCA, FSA), tibial coronal and sagittal angles (TCA, TSA), and implant overhang were radiologically measured to identify outliers.Aims
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The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance. A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset.Aims
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The adequate provision of personal protective equipment (PPE) for healthcare workers has come under considerable scrutiny during the COVID-19 pandemic. This study aimed to evaluate staff awareness of PPE guidance, perceptions of PPE measures, and concerns regarding PPE use while caring for COVID-19 patients. In addition, responses of doctors, nurses, and other healthcare professionals (OHCPs) were compared. The inclusion criteria were all staff working in clinical areas of the hospital. Staff were invited to take part using a link to an online questionnaire advertised by email, posters displayed in clinical areas, and social media. Questions grouped into the three key themes - staff awareness, perceptions, and concerns - were answered using a five-point Likert scale. The Kruskal-Wallis test was used to compare results across all three groups of staff.Aims
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Failure of irrigation and debridement (I&D) for prosthetic joint infection (PJI) is influenced by numerous host, surgical, and pathogen-related factors. We aimed to develop and validate a practical, easy-to-use tool based on machine learning that may accurately predict outcome following I&D surgery taking into account the influence of numerous factors. This was an international, multicentre retrospective study of 1,174 revision total hip (THA) and knee arthroplasties (TKA) undergoing I&D for PJI between January 2005 and December 2017. PJI was defined using the Musculoskeletal Infection Society (MSIS) criteria. A total of 52 variables including demographics, comorbidities, and clinical and laboratory findings were evaluated using random forest machine learning analysis. The algorithm was then verified through cross-validation.Aims
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To establish whether there was a consensus among the members of the Hip Society (HS) on the role of direct anterior approach (DAA) contemporary primary total hip arthroplasty (THA). An online survey was sent to all 112 active and senior members of the HS, to which 71 members responded. The survey was constructed to determine whether they believed that evidence-based medicine proves, in modern clinical practice, that the DAA has significant benefits compared to risks when contrasted with other approaches. In addition, they were asked if they currently used the DAA.Aims
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Despite the increase in the surgical repair of proximal hamstring tears, there exists a lack of consensus in the optimal timing for surgery. There is also disagreement on how partial tears managed surgically compare with complete tears repaired surgically. This study aims to compare the mid-term functional outcomes in, and operating time required for, complete and partial proximal hamstring avulsions, that are repaired both acutely and chronically. This is a prospective series of 156 proximal hamstring surgical repairs, with a mean age of 48.9 years (21.5 to 78). Functional outcomes were assessed preinjury, preoperatively, and postoperatively (six months and minimum three years) using the Sydney Hamstring Origin Rupture Evaluation (SHORE) score. Operating time was recorded for every patient.Aims
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The application of robotics in the operating theatre for knee arthroplasty remains controversial. As with all new technology, the introduction of new systems might be associated with a learning curve. However, guidelines on how to assess the introduction of robotics in the operating theatre are lacking. This systematic review aims to evaluate the current evidence on the learning curve of robot-assisted knee arthroplasty. An extensive literature search of PubMed, Medline, Embase, Web of Science, and Cochrane Library was conducted. Randomized controlled trials, comparative studies, and cohort studies were included. Outcomes assessed included: time required for surgery, stress levels of the surgical team, complications in regard to surgical experience level or time needed for surgery, size prediction of preoperative templating, and alignment according to the number of knee arthroplasties performed. A total of 11 studies met the inclusion criteria. Most were of medium to low quality. The operating time of robot-assisted total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA) is associated with a learning curve of between six to 20 cases and six to 36 cases respectively. Surgical team stress levels show a learning curve of seven cases in TKA and six cases for UKA. Experience with the robotic systems did not influence implant positioning, preoperative planning, and postoperative complications. Robot-assisted TKA and UKA is associated with a learning curve regarding operating time and surgical team stress levels. Future evaluation of robotics in the operating theatre should include detailed measurement of the various aspects of the total operating time, including total robotic time and time needed for preoperative planning. The prior experience of the surgical team should also be evaluated and reported. Cite this article:
Upper limb amputations, ranging from transhumeral to partial hand, can be devastating for patients, their families, and society. Modern paradigm shifts have focused on reconstructive options after upper extremity limb loss, rather than considering the amputation an ablative procedure. Surgical advancements such as targeted muscle reinnervation and regenerative peripheral nerve interface, in combination with technological development of modern prosthetics, have expanded options for patients after amputation. In the near future, advances such as osseointegration, implantable myoelectric sensors, and implantable nerve cuffs may become more widely used and may expand the options for prosthetic integration, myoelectric signal detection, and restoration of sensation. This review summarizes the current advancements in surgical techniques and prosthetics for upper limb amputees. Cite this article:
This observational study examines the effect of the COVID-19 pandemic upon the paediatric trauma burden of a district general hospital. We aim to compare the nature and volume of the paediatric trauma during the first 2020 UK lockdown period with the same period in 2019. Prospective data was collected from 23 March 2020 to 14 June 2020 and compared with retrospective data collected from 23 March 2019 to 14 June 2019. Patient demographics, mechanism of injury, nature of the injury, and details of any surgery were tabulated and statistically analyzed using the independent-samples Aims
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Urgent referral to a specialist centre for patients with a soft-tissue sarcoma (STS) has been recommended by the National Institute for Health and Care Excellence (NICE) in the UK since 2006. However, the impact of this recommendation on the prognosis for these patients remains unclear. We aimed to determine the impact of the NICE guidelines on the disease-specific survival (DSS) of patients with an STS. A total of 2,427 patients with an STS referred to a supraregional centre in the ten-year periods before (n = 1,386) and after (n = 1,041) the issue of the NICE guidelines were evaluated.Aims
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The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.Aims
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