The standard of wide tumour-like resection for chronic osteomyelitis (COM) has been challenged recently by adequate debridement. This paper reviews the evolution of surgical debridement for long bone COM, and presents the outcome of adequate debridement in a tertiary bone infection unit. We analyzed the retrospective record review from 2014 to 2020 of patients with long bone COM. All were managed by multidisciplinary infection team (MDT) protocol. Adequate debridement was employed for all cases, and no case of wide resection was included.Aims
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The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales. We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID).Aims
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Tuberculosis (TB) is one of the biggest communicable causes of mortality worldwide. While incidence in the UK has continued to fall since 2011, Bradford retains one of the highest TB rates in the UK. This study aims to examine the local disease burden of musculoskeletal (MSK) TB, by analyzing common presenting factors within the famously diverse population of Bradford. An observational study was conducted, using data from the Bradford Teaching Hospitals TB database of patients with a formal diagnosis of MSK TB between January 2005 and July 2017. Patient data included demographic data (including nationality/date of entry to the UK), disease focus, microbiology, and management strategies. Disease incidence was calculated using population data from the Office for National Statistics. Poisson confidence intervals were calculated to demonstrate the extent of statistical error. Disease incidence and nationality were also analyzed, and correlation sought, using the chi-squared test.Aims
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Restarting planned surgery during the COVID-19 pandemic is a clinical and societal priority, but it is unknown whether it can be done safely and include high-risk or complex cases. We developed a Surgical Prioritization and Allocation Guide (SPAG). Here, we validate its effectiveness and safety in COVID-free sites. A multidisciplinary surgical prioritization committee developed the SPAG, incorporating procedural urgency, shared decision-making, patient safety, and biopsychosocial factors; and applied it to 1,142 adult patients awaiting orthopaedic surgery. Patients were stratified into four priority groups and underwent surgery at three COVID-free sites, including one with access to a high dependency unit (HDU) or intensive care unit (ICU) and specialist resources. Safety was assessed by the number of patients requiring inpatient postoperative HDU/ICU admission, contracting COVID-19 within 14 days postoperatively, and mortality within 30 days postoperatively.Aims
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Currently, there is no single, comprehensive national guideline for analgesic strategies for total joint replacement. We compared inpatient and outpatient opioid requirements following total hip arthroplasty (THA) versus total knee arthroplasty (TKA) in order to determine risk factors for increased inpatient and outpatient opioid requirements following total hip or knee arthroplasty. Outcomes after 92 primary total knee (n = 49) and hip (n = 43) arthroplasties were analyzed. Patients with repeat surgery within 90 days were excluded. Opioid use was recorded while inpatient and 90 days postoperatively. Outcomes included total opioid use, refills, use beyond 90 days, and unplanned clinical encounters for uncontrolled pain. Multivariate modelling determined the effect of surgery, regional nerve block (RNB) or neuraxial anesthesia (NA), and non-opioid medications after adjusting for demographics, ength of stay, and baseline opioid use.Aims
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It is unusual, if not unique, for three major research papers concerned with the management of the fractured neck of femur (FNOF) to be published in a short period of time, each describing large prospective randomized clinical trials. These studies were conducted in up to 17 countries worldwide, involving up to 80 surgical centers and include large numbers of patients (up to 2,900) with FNOF. Each article investigated common clinical dilemmas; the first paper comparing total hip arthroplasty versus hemiarthroplasty for FNOF, the second as to whether ‘fast track’ care offers improved clinical outcomes and the third, compares sliding hip with multiple cancellous hip screws. Each paper has been deemed of sufficient quality and importance to warrant publication in The Lancet or the New England Journal of Medicine. Although ‘premier’ journals, they only occationally contain orthopaedic studies and thus may not be routinely read by the busy orthopaedic/surgical clinician of any grade. It is therefore our intention with this present article to accurately summarize and combine the results of all three papers, presenting, in our opinion, the most important clinically relevant facts. Cite this article:
The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments. Based on a clinical series of 479 primary total knees and 1,305 associated surgical decisions, various ML models were developed. These models identified the indicated surgical decision based on available, intra-operative alignment, and tibiofemoral load data.Aims
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