Cite this article: Bone Joint Res 2024;13(12):790–792.

Aims

This cross-sectional study aimed to investigate the in vivo ankle kinetic alterations in patients with concomitant chronic ankle instability (CAI) and osteochondral lesion of the talus (OLT), which may offer opportunities for clinician intervention in treatment and rehabilitation.

The December 2024 Research Roundup³⁶⁰ looks at: Skeletal muscle composition, power, and mitochondrial energetics in older men and women with knee osteoarthritis; Machine-learning models to predict osteonecrosis in patients with femoral neck fractures undergoing internal fixation; Aetiology of patient dissatisfaction following primary total knee arthroplasty in the era of robotic-assisted technology; Efficacy and safety of commonly used thromboprophylaxis agents following hip and knee arthroplasty; The COVID-19 effect continues; Nickel allergy in knee arthroplasty: does self-reported sensitivity affect outcomes?; Tranexamic acid use and joint infection risk in total hip and knee arthroplasty.

Aims. Approximately 10% to 20% of knee arthroplasty patients are not satisfied with the result, while a clear indication for revision surgery might not be present. Therapeutic options for these patients, who often lack adequate quadriceps strength, are limited. Therefore, the primary aim of this study was to evaluate the clinical effect of a novel rehabilitation protocol that combines low-load resistance training (LL-RT) with blood flow restriction (BFR). Methods. Between May 2022 and March 2024, we enrolled 45 dissatisfied knee arthroplasty patients who lacked any clear indication for revision to this prospective cohort study. All patients were at least six months post-surgery and had undergone conventional physiotherapy previously. The patients participated in a supervised LL-RT combined with BFR in 18 sessions. Primary assessments included the following patient-reported outcome measures (PROMs): Knee injury and Osteoarthritis Outcome Score (KOOS); Knee Society Score: satisfaction (KSSs); the EuroQol five-dimension five-level questionnaire (EQ-5D-5L); and the pain catastrophizing scale (PCS). Functionality was assessed using the six-minute walk Test (6MWT) and the 30-second chair stand test (30CST). Follow-up timepoints were at baseline, six weeks, three months, and six months after the start. Results. Six weeks of BFR with LL-RT improved all the PROMs except the sports subscale of the KOOS compared to baseline. Highest improvements after six weeks were found for quality of life (QoL) (mean 28.2 (SD 17.2) vs 19 (SD 14.7); p = 0.002), activities of daily living (mean 54.7 (SD 18.7) vs 42.9 (SD 17.3); p < 0.001), and KSSs (mean 17.1 (SD 8.8) vs 12.8 (SD 6.7); p < 0.001). PROMs improvements continued to be present at three-month and six-month follow-up compared to baseline. However, no significant differences were observed in the paired comparisons of the six-week, three-month, and six-month follow-up. The same trends are observed for the 6MWT and 30CST. Conclusion. The reported regime demonstrates improved QoL and function of dissatisfied knee arthroplasty patients. In light of this, the pathway described may provide a valuable and safe treatment option for dissatisfied knee arthroplasty patients for whom therapeutic options are limited. Cite this article: Bone Joint J 2024;106-B(12):1416–1425

Aims

There has been limited literature regarding outcomes of acetabular rim syndrome (ARS) with persistent acetabular os in the setting of acetabular dysplasia. The purpose of this study was to characterize a cohort of adolescent and young adult patients with ARS with persistent os and compare their radiological and clinical outcomes to patients with acetabular dysplasia without an os.

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: Bone Joint J 2024;106-B(12):1431–1442.

Aims

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.

Aims

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.

Aims

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.

Aims

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.

Aims

This Delphi study assessed the challenges of diagnosing soft-tissue knee injuries (STKIs) in acute settings among orthopaedic healthcare stakeholders.

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: Bone Joint J 2024;106-B(11):1206–1215.

Aims

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.

Aims

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.

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 training methodology based on CT imaging with multi-rater consensus to serve as the reference standard, artificial intelligence-driven classification is insufficient for clinical implementation. The CNN exhibited poor diagnostic ability to detect greater tuberosity displacement ≥ 1 cm and failed to identify NSAs ≤ 100°, shaft translations, or articular fractures. Cite this article: Bone Joint J 2024;106-B(11):1348–1360

Aims

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.

Aims

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.

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 training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared. Results. At the time of the study, the CNN model showed an area under the receiver operating curve of 0.97. AI assistance improved the physician’s sensitivity (correct fracture detection) from 80% to 87%, and the specificity (correct fracture exclusion) from 91% to 95%. The overall error rate (combined false positive and false negative) was reduced from 14% without AI to 9% with AI. Conclusion. The use of a CNN model as a second opinion can improve the diagnostic accuracy of DRF detection in the study setting. Cite this article: Bone Joint Res 2024;13(10):588–595

Aims

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.