Sagittal lumbar pelvic alignment alters with posterior pelvic tilt (PT) following total hip arthroplasty (THA) for developmental dysplasia of the hip (DDH). The individual value of pelvic sagittal inclination (PSI) following rebalancing of lumbar-pelvic alignment is unknown. In different populations, PT regresses in a linear relationship with pelvic incidence (PI). PSI and PT have a direct relationship to each other via a fixed individual angle ∠γ. This study aimed to investigate whether the new PI created by acetabular component positioning during THA also has a linear regression relationship with PT/PSI when lumbar-pelvic alignment rebalances postoperatively in patients with Crowe type III/IV DDH. Using SPINEPARA software, we measured the pelvic sagittal parameters including PI, PT, and PSI in 61 patients with Crowe III/IV DDH. Both PSI and PT represent the pelvic tilt state, and the difference between their values is ∠γ (PT = PSI + ∠γ). The regression equation between PI and PT at one year after THA was established. By substituting ∠γ, the relationship between PI and PSI was also established. The Bland-Altman method was used to evaluate the consistency between the PSI calculated by the linear regression equation (ePSI) and the actual PSI (aPSI) measured one year postoperatively.Aims
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Prolonged waits for hip and knee arthroplasty have raised questions about the equity of current approaches to waiting list prioritization for those awaiting surgery. We therefore set out to understand key stakeholder (patient and surgeon) preferences for the prioritization of patients awaiting such surgery, in order to guide future waiting list redesign. A combined qualitative/quantitative approach was used. This comprised a Delphi study to first inform which factors patients and surgeons designate as important for prioritization of patients on hip and knee arthroplasty waiting lists, followed by a discrete choice experiment (DCE) to determine how the factors should be weighed against each other. Coefficient values for each included DCE attribute were used to construct a ‘priority score’ (weighted benefit score) that could be used to rank individual patients waiting for surgery based on their respective characteristics.Aims
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The Clavien-Dindo (CD) classification and Comprehensive Complication Index (CCI) have been validated primarily among general surgical procedures. To date, the validity of these measures has not been assessed in patients undergoing arthroplasty. This retrospective cohort study included patients undergoing primary total hip and knee arthroplasty between April 2013 and December 2019. Complications within 90 days of surgery were graded using the CD classification and converted to CCI. Validity was established by assessing the association between both measures and discharge to inpatient rehabilitation, length of stay, and costs.Aims
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Periprosthetic joint infection (PJI) represents a complex challenge in orthopaedic surgery associated with substantial morbidity and healthcare expenditures. The debridement, antibiotics, and implant retention (DAIR) protocol is a viable treatment, offering several advantages over exchange arthroplasty. With the evolution of treatment strategies, considerable efforts have been directed towards enhancing the efficacy of DAIR, including the development of a phased debridement protocol for acute PJI management. This article provides an in-depth analysis of DAIR, presenting the outcomes of single-stage, two-stage, and repeated DAIR procedures. It delves into the challenges faced, including patient heterogeneity, pathogen identification, variability in surgical techniques, and antibiotics selection. Moreover, critical factors that influence the decision-making process between single- and two-stage DAIR protocols are addressed, including team composition, timing of the intervention, antibiotic regimens, and both anatomical and implant-related considerations. By providing a comprehensive overview of DAIR protocols and their clinical implications, this annotation aims to elucidate the advancements, challenges, and potential future directions in the application of DAIR for PJI management. It is intended to equip clinicians with the insights required to effectively navigate the
Lisfranc injuries were previously described as fracture-dislocations of the tarsometatarsal joints. With advancements in modern imaging, subtle Lisfranc injuries are now more frequently recognized, revealing that their true incidence is much higher than previously thought. Injury patterns can vary widely in severity and anatomy. Early diagnosis and treatment are essential to achieve good outcomes. The original classification systems were anatomy-based, and limited as tools for guiding treatment. The current review, using the best available evidence, instead introduces a stability-based classification system, with weightbearing radiographs and CT serving as key diagnostic tools. Stable injuries generally have good outcomes with nonoperative management, most reliably treated with immobilization and non-weightbearing for six weeks. Displaced or comminuted injuries require surgical intervention, with open reduction and internal fixation (ORIF) being the most common approach, with a consensus towards bridge plating. While ORIF generally achieves satisfactory results, its effectiveness can vary, particularly in high-energy injuries. Primary arthrodesis remains niche for the treatment of acute injuries, but may offer benefits such as lower rates of post-traumatic arthritis and hardware removal. Novel fixation techniques, including suture button fixation, aim to provide flexible stabilization, which theoretically could improve midfoot biomechanics and reduce complications. Early findings suggest promising functional outcomes, but further studies are required to validate this method compared with established techniques. Future research should focus on refining stability-based classification systems, validation of weightbearing CT, improving rehabilitation protocols, and optimizing surgical techniques for various injury patterns to ultimately enhance patient outcomes. Cite this article:
Understanding spinopelvic mechanics is important for the success of total hip arthroplasty (THA). Despite significant advancements in appreciating spinopelvic balance, numerous challenges remain. It is crucial to recognize the individual variability and postoperative changes in spinopelvic parameters and their consequential impact on prosthetic component positioning to mitigate the risk of dislocation and enhance postoperative outcomes. This review describes the integration of advanced diagnostic approaches, enhanced technology, implant considerations, and surgical planning, all tailored to the unique anatomy and biomechanics of each patient. It underscores the importance of accurately predicting postoperative spinopelvic mechanics, selecting suitable imaging techniques, establishing a consistent nomenclature for spinopelvic stiffness, and considering implant-specific strategies. Furthermore, it highlights the potential of artificial intelligence to personalize care. Cite this article:
We aimed to compare reoperations following distal radial fractures (DRFs) managed with early fixation versus delayed fixation following initial closed reduction (CR). We used administrative databases in Ontario, Canada, to identify DRF patients aged 18 years or older from 2003 to 2016. We used procedural and fee codes within 30 days to determine which patients underwent early fixation (≤ seven days) or delayed fixation following CR. We grouped patients in the delayed group by their time to definitive fixation (eight to 14 days, 15 to 21 days, and 22 to 30 days). We used intervention and diagnostic codes to identify reoperations within two years. We used multivariable regression to compare the association between early versus delayed fixation and reoperation for all patients and stratified by age (18 to 60 years and > 60 years).Aims
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The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs. The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%).Aims
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Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.Aims
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Our aim was to estimate the total costs of all hospitalizations for treating periprosthetic joint infection (PJI) by main management strategy within 24 months post-diagnosis using activity-based costing. Additionally, we investigated the influence of individual PJI treatment pathways on hospital costs within the first 24 months. Using admission and procedure data from a prospective observational cohort in Australia and New Zealand, Australian Refined Diagnosis Related Groups were assigned to each admitted patient episode of care for activity-based costing estimates of 273 hip PJI patients and 377 knee PJI patients. Costs were aggregated at 24 months post-diagnosis, and are presented in Australian dollars.Aims
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This study aimed to gather insights from elbow experts using the Delphi method to evaluate the influence of patient characteristics and fracture morphology on the choice between operative and nonoperative treatment for coronoid fractures. A three-round electronic (e-)modified Delphi survey study was performed between March and December 2023. A total of 55 elbow surgeons from Asia, Australia, Europe, and North America participated, with 48 completing all questionnaires (87%). The panellists evaluated the factors identified as important in literature for treatment decision-making, using a Likert scale ranging from "strongly influences me to recommend nonoperative treatment" (1) to "strongly influences me to recommend operative treatment" (5). Factors achieving Likert scores ≤ 2.0 or ≥ 4.0 were deemed influential for treatment recommendation. Stable consensus is defined as an agreement of ≥ 80% in the second and third rounds.Aims
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The optimal bearing surface design for medial unicompartmental knee arthroplasty (UKA) remains controversial. The aim of this study was to compare outcomes of fixed-bearing (FB) and mobile-bearing (MB) UKAs from a single high-volume institution. Prospectively collected data were reviewed for all primary cemented medial UKAs performed by seven surgeons from January 2006 to December 2022. A total of 2,999 UKAs were identified, including 2,315 FB and 684 MB cases. The primary outcome measure was implant survival. Secondary outcomes included 90-day and cumulative complications, reoperations, component revisions, conversion arthroplasties, range of motion, and patient-reported outcome measures. Overall mean age at surgery was 65.7 years (32.9 to 94.3), 53.1% (1,593/2,999) of UKAs were implanted in female patients, and demographics between groups were similar (p > 0.05). The mean follow-up for all UKAs was 3.7 years (0.0 to 15.6).Aims
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Rotator cuff tears are common in middle-aged and elderly patients. Despite advances in the surgical repair of rotator cuff tears, the rates of recurrent tear remain high. This may be due to the
Hip arthroscopy has gained prominence as a primary surgical intervention for symptomatic femoroacetabular impingement (FAI). This study aimed to identify radiological features, and their combinations, that predict the outcome of hip arthroscopy for FAI. A prognostic cross-sectional cohort study was conducted involving patients from a single centre who underwent hip arthroscopy between January 2013 and April 2021. Radiological metrics measured on conventional radiographs and magnetic resonance arthrography were systematically assessed. The study analyzed the relationship between these metrics and complication rates, revision rates, and patient-reported outcomes.Aims
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Given the possible radiation damage and inaccuracy of radiological investigations, particularly in children, ultrasound and superb microvascular imaging (SMI) may offer alternative methods of evaluating new bone formation when limb lengthening is undertaken in paediatric patients. The aim of this study was to assess the use of ultrasound combined with SMI in monitoring new bone formation during limb lengthening in children. In this retrospective cohort study, ultrasound and radiograph examinations were performed every two weeks in 30 paediatric patients undergoing limb lengthening. Ultrasound was used to monitor new bone formation. The number of vertical vessels and the blood flow resistance index were compared with those from plain radiographs.Aims
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Historically, patients undergoing surgery for adolescent idiopathic scoliosis (AIS) have been nursed postoperatively in a critical care (CC) setting because of the challenges posed by prone positioning, extensive exposures, prolonged operating times, significant blood loss, major intraoperative fluid shifts, cardiopulmonary complications, and difficulty in postoperative pain management. The primary aim of this paper was to determine whether a scoring system, which uses Cobb angle, forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and number of levels to be fused, is a valid method of predicting the need for postoperative critical care in AIS patients who are to undergo scoliosis correction with posterior spinal fusion (PSF). We retrospectively reviewed all AIS patients who had undergone PSF between January 2018 and January 2020 in a specialist tertiary spinal referral centre. All patients were assessed preoperatively in an anaesthetic clinic. Postoperative care was defined as ward-based (WB) or critical care (CC)Aims
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To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation.Aims
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The aim of the present study was to assess the outcomes of the induced membrane technique (IMT) for the management of infected segmental bone defects, and to analyze predictive factors associated with unfavourable outcomes. Between May 2012 and December 2020, 203 patients with infected segmental bone defects treated with the IMT were enrolled. The digital medical records of these patients were retrospectively analyzed. Factors associated with unfavourable outcomes were identified through logistic regression analysis.Aims
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