Aims. Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. Methods. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp). Results. NIRS scans on both the inner (trabecular) surface or outer (cortical) surface accurately identified variations in bone collagen, water, mineral, and fat content, which then accurately predicted bone volume fraction (BV/TV, inner R. 2. = 0.91, outer R. 2. = 0.83), thickness (Tb.Th, inner R. 2. = 0.9, outer R. 2. = 0.79), and cortical thickness (Ct.Th, inner and outer both R. 2. = 0.90). NIRS scans also had 100% classification
Aims. 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. Methods. 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). Results. The CAT algorithms accurately estimated 12-item questionnaire scores from between four and nine items. Scores followed a very similar distribution between CAT and full-length assessments, with the mean score difference ranging from 0.03 to 0.26 out of 48 points. Pearson’s correlation coefficient and ICC were 0.98 for each 12-item scale and 0.95 or higher for the OES subscales. In over 95% of cases, a patient’s CAT score was within five points of the full-length questionnaire score for each 12-item questionnaire. Conclusion. Oxford Hip Score, Oxford Knee Score, Oxford Shoulder Score, and Oxford Elbow Score (including separate subscale scores) CATs all markedly reduce the burden of items to be completed without sacrificing score
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
Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles ( Cite this article:
Systematic reviews of randomized controlled trials (RCTs) are the highest level of evidence used to inform patient care. However, it has been suggested that the quality of randomization in RCTs in orthopaedic surgery may be low. This study aims to describe the quality of randomization in trials included in systematic reviews in orthopaedic surgery. Systematic reviews of RCTs testing orthopaedic procedures published in 2022 were extracted from PubMed, Embase, and the Cochrane Library. A random sample of 100 systematic reviews was selected, and all included RCTs were retrieved. To be eligible for inclusion, systematic reviews must have tested an orthopaedic procedure as the primary intervention, included at least one study identified as a RCT, been published in 2022 in English, and included human clinical trials. The Cochrane Risk of Bias-2 Tool was used to assess random sequence generation as ‘adequate’, ‘inadequate’, or ‘no information’; we then calculated the proportion of trials in each category. We also collected data to test the association between these categories and characteristics of the RCTs and systematic reviews.Aims
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Patient-reported outcome measures have become an important part of routine care. The aim of this study was to determine if Patient-Reported Outcomes Measurement Information System (PROMIS) measures can be used to create patient subgroups for individuals seeking orthopaedic care. This was a cross-sectional study of patients from Duke University Department of Orthopaedic Surgery clinics (14 ambulatory and four hospital-based). There were two separate cohorts recruited by convenience sampling (i.e. patients were included in the analysis only if they completed PROMIS measures during a new patient visit). Cohort #1 (n = 12,141; December 2017 to December 2018,) included PROMIS short forms for eight domains (Physical Function, Pain Interference, Pain Intensity, Depression, Anxiety, Sleep Quality, Participation in Social Roles, and Fatigue) and Cohort #2 (n = 4,638; January 2019 to August 2019) included PROMIS Computer Adaptive Testing instruments for four domains (Physical Function, Pain Interference, Depression, and Sleep Quality). Cluster analysis (K-means method) empirically derived subgroups and subgroup differences in clinical and sociodemographic factors were identified with one-way analysis of variance.Aims
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There is little published on the outcomes after restarting elective orthopaedic procedures following cessation of surgery due to the COVID-19 pandemic. During the pandemic, the reported perioperative mortality in patients who acquired SARS-CoV-2 infection while undergoing elective orthopaedic surgery was 18% to 20%. The aim of this study is to report the surgical outcomes, complications, and risk of developing COVID-19 in 2,316 consecutive patients who underwent elective orthopaedic surgery in the latter part of 2020 and comparing it to the same, pre-pandemic, period in 2019. A retrospective service evaluation of patients who underwent elective surgical procedures between 16 June 2020 and 12 December 2020 was undertaken. The number and type of cases, demographic details, American society of Anesthesiologists (ASA) grade, BMI, 30-day readmission rates, mortality, and complications at one- and six-week intervals were obtained and compared with patients who underwent surgery during the same six-month period in 2019.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
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Orthopaedic surgeries are complex, frequently performed procedures associated with significant haemorrhage and perioperative blood transfusion. Given refinements in surgical techniques and changes to transfusion practices, we aim to describe contemporary transfusion practices in orthopaedic surgery in order to inform perioperative planning and blood banking requirements. We performed a retrospective cohort study of adult patients who underwent orthopaedic surgery at four Canadian hospitals between 2014 and 2016. We studied all patients admitted to hospital for nonarthroscopic joint surgeries, amputations, and fracture surgeries. For each surgery and surgical subgroup, we characterized the proportion of patients who received red blood cell (RBC) transfusion, the mean/median number of RBC units transfused, and exposure to platelets and plasma.Aims
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This study aims to enhance understanding of clinical and radiological consequences and involved mechanisms that led to corrosion of the Precice Stryde (Stryde) intramedullary lengthening nail in the post market surveillance era of the device. Between 2018 and 2021 more than 2,000 Stryde nails have been implanted worldwide. However, the outcome of treatment with the Stryde system is insufficiently reported. This is a retrospective single-centre study analyzing outcome of 57 consecutive lengthening procedures performed with the Stryde nail at the authors’ institution from February 2019 until November 2020. Macro- and microscopic metallographic analysis of four retrieved nails was conducted. To investigate observed corrosion at telescoping junction, scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDX) were performed.Aims
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The ongoing COVID-19 pandemic has disrupted and delayed medical and surgical examinations where attendance is required in person. Our article aims to outline the validity of online assessment, the range of benefits to both candidate and assessor, and the challenges to its implementation. In addition, we propose pragmatic suggestions for its introduction into medical assessment. We reviewed the literature concerning the present status of online medical and surgical assessment to establish the perceived benefits, limitations, and potential problems with this method of assessment.Aims
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The increase in prescription opioid misuse and dependence is now a public health crisis in the UK. It is recognized as a whole-person problem that involves both the medical and the psychosocial needs of patients. Analyzing aspects of pathophysiology, emotional health, and social wellbeing associated with persistent opioid use after injury may inform safe and effective alleviation of pain while minimizing risk of misuse or dependence. Our objectives were to investigate patient factors associated with opioid use two to four weeks and six to nine months after an upper limb fracture. A total of 734 patients recovering from an isolated upper limb fracture were recruited in this study. Opioid prescription was documented retrospectively for the period preceding the injury, and prospectively at the two- to four-week post-injury visit and six- to nine-month post-injury visit. Bivariate and multivariate analysis sought factors associated with opioid prescription from demographics, injury-specific data, Patient Reported Outcome Measurement Instrumentation System (PROMIS), Depression computer adaptive test (CAT), PROMIS Anxiety CAT, PROMIS Instrumental Support CAT, the Pain Catastrophizing Scale (PCS), the Pain Self-efficacy Questionnaire (PSEQ-2), Tampa Scale for Kinesiophobia (TSK-11), and measures that investigate levels of social support.Aims
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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
Methods
Sickle cell disease (SCD) is an autosomal recessive inherited condition that presents with a number of clinical manifestations that include musculoskeletal manifestations (MM). MM may present differently in different individuals and settings and the predictors are not well known. Herein, we aimed at determining the predictors of MM in patients with SCD at the University Teaching Hospital, Lusaka, Zambia. An unmatched case-control study was conducted between January and May 2019 in children below the age of 16 years. In all, 57 cases and 114 controls were obtained by systematic sampling method. A structured questionnaire was used to collect data. The different MM were identified, staged, and classified according to the Standard Orthopaedic Classification Systems using radiological and laboratory investigations. The data was entered in Epidata version 3.1 and exported to STATA 15 for analysis. Multiple logistic regression was used to determine predictors and predictive margins were used to determine the probability of MM.Aims
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