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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The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA). A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.Aims
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Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy.Aims
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This study examined windswept deformity (WSD) of the knee, comparing prevalence and contributing factors in healthy and osteoarthritic (OA) cohorts. A case-control radiological study was undertaken comparing 500 healthy knees (250 adults) with a consecutive sample of 710 OA knees (355 adults) undergoing bilateral total knee arthroplasty. The mechanical hip-knee-ankle angle (mHKA), medial proximal tibial angle (MPTA), and lateral distal femoral angle (LDFA) were determined for each knee, and the arithmetic hip-knee-ankle angle (aHKA), joint line obliquity, and Coronal Plane Alignment of the Knee (CPAK) types were calculated. WSD was defined as a varus mHKA of < -2° in one limb and a valgus mHKA of > 2° in the contralateral limb. The primary outcome was the proportional difference in WSD prevalence between healthy and OA groups. Secondary outcomes were the proportional difference in WSD prevalence between constitutional varus and valgus CPAK types, and to explore associations between predefined variables and WSD within the OA group.Aims
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Shoulder arthroplasty is effective in the management of end-stage glenohumeral joint arthritis. However, it is major surgery and patients must balance multiple factors when considering the procedure. An understanding of patients’ decision-making processes may facilitate greater support of those considering shoulder arthroplasty and inform the outcomes of future research. Participants were recruited from waiting lists of three consultant upper limb surgeons across two NHS hospitals. Semi-structured interviews were conducted with 12 participants who were awaiting elective shoulder arthroplasty. Transcribed interviews were analyzed using a grounded theory approach. Systematic coding was performed; initial codes were categorized and further developed into summary narratives through a process of discussion and refinement. Data collection and analyses continued until thematic saturation was reached.Aims
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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
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In-hospital length of stay (LOS) and discharge dispositions following arthroplasty could act as surrogate measures for improvement in patient pathways, and have major cost saving implications for healthcare providers. With the ever-growing adoption of robotic technology in arthroplasty, it is imperative to evaluate its impact on LOS. The objectives of this study were to compare LOS and discharge dispositions following robotic arm-assisted total knee arthroplasty (RO TKA) and unicompartmental arthroplasty (RO UKA) versus conventional technique (CO TKA and UKA). This large-scale, single-institution study included patients of any age undergoing primary TKA (n = 1,375) or UKA (n = 337) for any cause between May 2019 and January 2023. Data extracted included patient demographics, LOS, need for post anaesthesia care unit (PACU) admission, anaesthesia type, readmission within 30 days, and discharge dispositions. Univariate and multivariate logistic regression models were also employed to identify factors and patient characteristics related to delayed discharge.Aims
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The primary aim was to estimate the cost-effectiveness of routine operative fixation for all patients with humeral shaft fractures. The secondary aim was to estimate the health economic implications of using a Radiographic Union Score for HUmeral fractures (RUSHU) of < 8 to facilitate selective fixation for patients at risk of nonunion. From 2008 to 2017, 215 patients (mean age 57 yrs (17 to 18), 61% female (n = 130/215)) with a nonoperatively managed humeral diaphyseal fracture were retrospectively identified. Union was achieved in 77% (n = 165/215) after initial nonoperative management, with 23% (n = 50/215) uniting after surgery for nonunion. The EuroQol five-dimension three-level health index (EQ-5D-3L) was obtained via postal survey. Multiple regression was used to determine the independent influence of patient, injury, and management factors upon the EQ-5D-3L. An incremental cost-effectiveness ratio (ICER) of < £20,000 per quality-adjusted life-year (QALY) gained was considered cost-effective.Aims
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The aim of this study was to determine satisfaction rates after hip and knee arthroplasty in patients who did not respond to postoperative patient-reported outcome measures (PROMs), characteristics of non-responders, and contact preferences to maximize response rates. A prospective cohort study of patients planned to undergo hip arthroplasty (n = 713) and knee arthroplasty (n = 737) at a UK university teaching hospital who had completed preoperative PROMs questionnaires, including the EuroQol five-dimension health-related quality of life score, and Oxford Hip Score (OHS) and Oxford Knee Score (OKS). Follow-up questionnaires were sent by post at one year, including satisfaction scoring. Attempts were made to contact patients who did not initially respond. Univariate, logistic regression, and receiver operator curve analysis was performed.Aims
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Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
The primary aim of this study was to identify independent predictors associated with nonunion and delayed union of tibial diaphyseal fractures treated with intramedullary nailing. The secondary aim was to assess the Radiological Union Scale for Tibial fractures (RUST) score as an early predictor of tibial fracture nonunion. A consecutive series of 647 patients who underwent intramedullary nailing for tibial diaphyseal fractures were identified from a trauma database. Demographic data, comorbidities, smoking status, alcohol consumption, use of non-steroidal anti-inflammatory drugs (NSAIDs), and steroid use were documented. Details regarding mechanism of injury, fracture classification, complications, and further surgery were recorded. Nonunion was defined as the requirement for revision surgery to achieve union. Delayed union was defined as a RUST score < 10 at six months postoperatively.Aims
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It is unclear whether acute plate fixation facilitates earlier return of normal shoulder function following a displaced mid-shaft clavicular fracture compared with nonoperative management when union occurs. The primary aim of this study was to establish whether acute plate fixation was associated with a greater return of normal shoulder function when compared with nonoperative management in patients who unite their fractures. The secondary aim was to investigate whether there were identifiable predictors associated with return of normal shoulder function in patients who achieve union with nonoperative management. Patient data from a randomized controlled trial were used to compare acute plate fixation with nonoperative management of united fractures. Return of shoulder function was based on the age- and sex-matched Disabilities of the Arm, Shoulder and Hand (DASH) scores for the cohort. Independent predictors of an early recovery of normal shoulder function were investigated using a separate prospective series of consecutive nonoperative displaced mid-shaft clavicular fractures recruited over a two-year period (aged ≥ 16 years). Patient demographics and functional recovery were assessed over the six months post-injury using a standardized protocol.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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There are reports of a marked increase in perioperative mortality in patients admitted to hospital with a fractured hip during the COVID-19 pandemic in the UK, USA, Spain, and Italy. Our study aims to describe the risk of mortality among patients with a fractured neck of femur in England during the early stages of the COVID-19 pandemic. We completed a multicentre cohort study across ten hospitals in England. Data were collected from 1 March 2020 to 6 April 2020, during which period the World Health Organization (WHO) declared COVID-19 to be a pandemic. Patients ≥ 60 years of age admitted with hip fracture and a minimum follow-up of 30 days were included for analysis. Primary outcome of interest was mortality at 30 days post-surgery or postadmission in nonoperative patients. Secondary outcomes included length of hospital stay and discharge destination.Aims
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Studies have addressed the issue of increasing prevalence of work-related musculoskeletal (MSK) pain among different occupations. However, contributing factors to MSK pain have not been fully investigated among orthopaedic surgeons. Thus, this study aimed to approximate the prevalence and predictors of MSK pain among Saudi orthopaedic surgeons working in Riyadh, Saudi Arabia. A cross-sectional study using an electronic survey was conducted in Riyadh. The questionnaire was distributed through email among orthopaedic surgeons in Riyadh hospitals. Standardized Nordic questionnaires for the analysis of musculoskeletal symptoms were used. Descriptive measures for categorical and numerical variables were presented. Student’s t-test and Pearson’s χ2 test were used. The level of statistical significance was set at p ≤ 0.05.Introduction
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The aim of this study was to describe variation in hip fracture treatment in Norway expressed as adherence to international and national evidence-based treatment guidelines, to study factors influencing deviation from guidelines, and to analyze consequences of non-adherence. International and national guidelines were identified and treatment recommendations extracted. All 43 hospitals routinely treating hip fractures in Norway were characterized. From the Norwegian Hip Fracture Register (NHFR), hip fracture patients aged > 65 years and operated in the period January 2014 to December 2018 for fractures with conclusive treatment guidelines were included (n = 29,613: femoral neck fractures (n = 21,325), stable trochanteric fractures (n = 5,546), inter- and subtrochanteric fractures (n = 2,742)). Adherence to treatment recommendations and a composite indicator of best practice were analyzed. Patient survival and reoperations were evaluated for each recommendation.Aims
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