Pain is the most frequent complaint associated with osteonecrosis of the femoral head (ONFH), but the factors contributing to such pain are poorly understood. This study explored diverse demographic, clinical, radiological, psychological, and neurophysiological factors for their potential contribution to pain in patients with ONFH. This cross-sectional study was carried out according to the “STrengthening the Reporting of OBservational studies in Epidemiology” statement. Data on 19 variables were collected at a single timepoint from 250 patients with ONFH who were treated at our medical centre between July and December 2023 using validated instruments or, in the case of hip pain, a numerical rating scale. Factors associated with pain severity were identified using hierarchical multifactor linear regression.Aims
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For rare cases when a tumour infiltrates into the hip joint, extra-articular resection is required to obtain a safe margin. Endoprosthetic reconstruction following tumour resection can effectively ensure local control and improve postoperative function. However, maximizing bone preservation without compromising surgical margin remains a challenge for surgeons due to the complexity of the procedure. The purpose of the current study was to report clinical outcomes of patients who underwent extra-articular resection of the hip joint using a custom-made osteotomy guide and 3D-printed endoprosthesis. We reviewed 15 patients over a five-year period (January 2017 to December 2022) who had undergone extra-articular resection of the hip joint due to malignant tumour using a custom-made osteotomy guide and 3D-printed endoprosthesis. Each of the 15 patients had a single lesion, with six originating from the acetabulum side and nine from the proximal femur. All patients had their posterior column preserved according to the surgical plan.Aims
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The incidence of limb fractures in patients living with HIV (PLWH) is increasing. However, due to their immunodeficiency status, the operation and rehabilitation of these patients present unique challenges. Currently, it is urgent to establish a standardized perioperative rehabilitation plan based on the concept of enhanced recovery after surgery (ERAS). This study aimed to validate the effectiveness of ERAS in the perioperative period of PLWH with limb fractures. A total of 120 PLWH with limb fractures, between January 2015 and December 2023, were included in this study. We established a multidisciplinary team to design and implement a standardized ERAS protocol. The demographic, surgical, clinical, and follow-up information of the patients were collected and analyzed retrospectively.Aims
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Lower limb fractures are common in low- and middle-income countries (LMICs) and represent a significant burden to the existing orthopaedic surgical infrastructure. In high income country (HIC) settings, internal fixation is the standard of care due to its superior outcomes. In LMICs, external fixation is often the surgical treatment of choice due to limited supplies, cost considerations, and its perceived lower complication rate. The aim of this systematic review protocol is identifying differences in rates of infection, nonunion, and malunion of extra-articular femoral and tibial shaft fractures in LMICs treated with either internal or external fixation. This systematic review protocol describes a broad search of multiple databases to identify eligible papers. Studies must be published after 2000, include at least five patients, patients must be aged > 16 years or treated as skeletally mature, and the paper must describe a fracture of interest and at least one of our primary outcomes of interest. We did not place restrictions on language or journal. All abstracts and full texts will be screened and extracted by two independent reviewers. Risk of bias and quality of evidence will be analyzed using standardized appraisal tools. A random-effects meta-analysis followed by a subgroup analysis will be performed, given the anticipated heterogeneity among studies, if sufficient data are available.Aims
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This Delphi study assessed the challenges of diagnosing soft-tissue knee injuries (STKIs) in acute settings among orthopaedic healthcare stakeholders. This modified e-Delphi study consisted of three rounds and involved 32 orthopaedic healthcare stakeholders, including physiotherapists, emergency nurse practitioners, sports medicine physicians, radiologists, orthopaedic registrars, and orthopaedic consultants. The perceived importance of diagnostic components relevant to STKIs included patient and external risk factors, clinical signs and symptoms, special clinical tests, and diagnostic imaging methods. Each round required scoring and ranking various items on a ten-point Likert scale. The items were refined as each round progressed. The study produced rankings of perceived importance across the various diagnostic components.Aims
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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:
The aim of this study was to review the provision of total elbow arthroplasties (TEAs) in England, including the incidence, the characteristics of the patients and the service providers, the types of implant, and the outcomes. We analyzed the primary TEAs recorded in the National Joint Registry (NJR) between April 2012 and December 2022, with mortality data from the Civil Registration of Deaths dataset. Linkage with Hospital Episode Statistics-Admitted Patient Care (HES-APC) data provided further information not collected by the NJR. The incidences were calculated using estimations of the populations from the Office for National Statistics. The annual number of TEAs performed by surgeons and hospitals was analyzed on a national and regional basis.Aims
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The objective of this study was to compare simulated range of motion (ROM) for reverse total shoulder arthroplasty (rTSA) with and without adjustment for scapulothoracic orientation in a global reference system. We hypothesized that values for simulated ROM in preoperative planning software with and without adjustment for scapulothoracic orientation would be significantly different. A statistical shape model of the entire humerus and scapula was fitted into ten shoulder CT scans randomly selected from 162 patients who underwent rTSA. Six shoulder surgeons independently planned a rTSA in each model using prototype development software with the ability to adjust for scapulothoracic orientation, the starting position of the humerus, as well as kinematic planes in a global reference system simulating previously described posture types A, B, and C. ROM with and without posture adjustment was calculated and compared in all movement planes.Aims
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Aims. 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. Methods. 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%). Results. For detection and classification, the algorithm was trained on 1,709 radiographs (n = 803), tested on 567 radiographs (n = 244), and subsequently externally validated on 535 radiographs (n = 227). For characterization, healthy shoulders and glenohumeral dislocation were excluded. The overall accuracy for fracture detection was 94% (area under the receiver operating characteristic curve (AUC) = 0.98) and for classification 78% (AUC 0.68 to 0.93). Accuracy to detect greater tuberosity fracture displacement ≥ 1 cm was 35.0% (AUC 0.57). The CNN did not recognize NSAs ≤ 100° (AUC 0.42), nor fractures with ≥ 75% shaft translation (AUC 0.51 to 0.53), or with ≥ 15% articular involvement (AUC 0.48 to 0.49). For all objectives, the model’s performance on the external dataset showed similar accuracy levels. Conclusion. CNNs proficiently rule out proximal humerus fractures on plain radiographs. Despite rigorous
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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The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics.Aims
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Aims. The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. Methods. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in
This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
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The aim of this study was to gain a consensus for best practice of the assessment and management of children with idiopathic toe walking (ITW) in order to provide a benchmark for practitioners and guide the best consistent care. An established Delphi approach with predetermined steps and degree of agreement based on a standardized protocol was used to determine consensus. The steering group members and Delphi survey participants included members from the British Society of Children’s Orthopaedic Surgery (BSCOS) and the Association of Paediatric Chartered Physiotherapists (APCP). The statements included definition, assessment, treatment indications, nonoperative and operative interventions, and outcomes. Descriptive statistics were used for analysis of the Delphi survey results. The AGREE checklist was followed for reporting the results.Aims
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The Cochrane Collaboration has produced three new reviews relevant to bone and joint surgery since the publication of the last Cochrane Corner. These are relevant to a wide range of musculoskeletal specialists, and include reviews in lateral elbow pain, osteoarthritis of the big toe joint, and cervical spine injury in paediatric trauma patients.
The October 2024 Wrist & Hand Roundup360 looks at: Circumferential casting versus plaster splinting in preventing redisplacement of distal radial fractures; Comparable outcomes for operative versus nonoperative treatment of scapholunate ligament injuries in distal radius fractures; Perceived pain during the reduction of Colles fracture without anaesthesia; Diagnostic delays and physician
This study evaluates the association between consultant and hospital volume and the risk of re-revision and 90-day mortality following first-time revision of primary hip arthroplasty for aseptic loosening. We conducted a cohort study of first-time, single-stage revision hip arthroplasties (RHAs) performed for aseptic loosening and recorded in the National Joint Registry (NJR) data for England, Wales, Northern Ireland, and the Isle of Man between 2003 and 2019. Patient identifiers were used to link records to national mortality data, and to NJR data to identify subsequent re-revision procedures. Multivariable Cox proportional hazard models with restricted cubic splines were used to define associations between volume and outcome.Aims
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