Cite this article: Bone Jt Open 2024;5(12):1120–1122.

Aims

The involvement of long non-coding RNA (lncRNA) in bone marrow mesenchymal stem cell (MSC) osteogenic differentiation during osteoporosis (OP) development has attracted much attention. In this study, we aimed to disclose how LINC01089 functions in human mesenchymal stem cell (hMSC) osteogenic differentiation, and to study the mechanism by which LINC01089 regulates MSC osteogenesis.

Aims

Mesenchymal stem cells (MSCs) are usually cultured in a normoxic atmosphere (21%) in vitro, while the oxygen concentrations in human tissues and organs are 1% to 10% when the cells are transplanted in vivo. However, the impact of hypoxia on MSCs has not been deeply studied, especially its translational application.

Aims. Functional alignment (FA) in total knee arthroplasty (TKA) aims to achieve balanced gaps by adjusting implant positioning while minimizing changes to constitutional joint line obliquity (JLO). Although FA uses kinematic alignment (KA) as a starting point, the final implant positions can vary significantly between these two approaches. This study used the Coronal Plane Alignment of the Knee (CPAK) classification to compare differences between KA and final FA positions. Methods. A retrospective analysis compared pre-resection and post-implantation alignments in 2,116 robotic-assisted FA TKAs. The lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) were measured to determine the arithmetic hip-knee-ankle angle (aHKA = MPTA – LDFA), JLO (JLO = MPTA + LDFA), and CPAK type. The primary outcome was the proportion of knees that varied ≤ 2° for aHKA and ≤ 3° for JLO from their KA to FA positions, and direction and magnitude of those changes per CPAK phenotype. Secondary outcomes included proportion of knees that maintained their CPAK phenotype, and differences between sexes. Results. Overall, 71.6% had an aHKA change ≤ 2°, and 87.0% a JLO change ≤ 3°. Mean aHKA changed from -1.1° (SD 2.8°) in KA to -1.9° (SD 2.3°) in FA (mean difference (MD) -0.83 (SD 2.0); p < 0.001). Mean JLO changed from 173.9° (SD 3.0°) in KA to 174.2° (SD 2.6°) in FA (MD 0.38 (SD 2.3); p < 0.001). CPAK type was maintained in 58.1% of knees, with the proportion highest for Types I (73.9%), II (61.1%), and IV (51.2%). In valgus knees, 67.5% of Type III and 71.7% of Type VI were shifted to neutral phenotypes. There was minimal change to constitutional JLO across all CPAK types (MDs -2.0° to 1.2°). Conclusion. Functional alignment may alter CPAK type, but does not significantly change JLO. A kinematic starting point minimizes changes to native anatomy, while final position with FA provides an optimally balanced TKA. Cite this article: Bone Jt Open 2024;5(12):1081–1091

Addressing bone defects is a complex medical challenge that involves dealing with various skeletal conditions, including fractures, osteoporosis (OP), bone tumours, and bone infection defects. Despite the availability of multiple conventional treatments for these skeletal conditions, numerous limitations and unresolved issues persist. As a solution, advancements in biomedical materials have recently resulted in novel therapeutic concepts. As an emerging biomaterial for bone defect treatment, graphene oxide (GO) in particular has gained substantial attention from researchers due to its potential applications and prospects. In other words, GO scaffolds have demonstrated remarkable potential for bone defect treatment. Furthermore, GO-loaded biomaterials can promote osteoblast adhesion, proliferation, and differentiation while stimulating bone matrix deposition and formation. Given their favourable biocompatibility and osteoinductive capabilities, these materials offer a novel therapeutic avenue for bone tissue regeneration and repair. This comprehensive review systematically outlines GO scaffolds’ diverse roles and potential applications in bone defect treatment.

Cite this article: Bone Joint Res 2024;13(12):725–740.

The December 2024 Wrist & Hand Roundup. 360. looks at: Variability in thumb ulnar collateral ligament rupture management across the UK: survey insights; Identifying five distinct hand osteoarthritis pain phenotypes highlights the impact of biopsychosocial factors; Long-term outcomes of MAÏA TMC joint prosthesis for osteoarthritis: a possible alternative to trapeziectomy; Diagnostic and management strategies for malignant melanoma of the hand; Early versus delayed surgery for distal radius fractures: comparable outcomes but higher complications in delayed treatment; Perioperative anticoagulant and antiplatelet use does not increase complications in wide-awake hand surgery; Variability in treatment of metacarpal shaft fractures highlights need for standardized care; Low-intensity pulsed ultrasound ineffective in reducing time to union for scaphoid nonunion post-surgery

As advancements in total knee arthroplasty progress at an exciting pace, two areas are of special interest, as they directly impact implant design and surgical decision making. Knee morphometry considers the three-dimensional shape of the articulating surfaces within the knee joint, and knee phenotyping provides the ability to categorize alignment into practical groupings that can be used in both clinical and research settings. This annotation discusses the details of these concepts, and the ways in which they are helping us better understand the individual subtleties of each patient’s knee. Cite this article: Bone Joint J 2024;106-B(12):1363–1368

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

Developmental cervical spinal stenosis (DcSS) is a well-known predisposing factor for degenerative cervical myelopathy (DCM) but there is a lack of consensus on its definition. This study aims to define DcSS based on MRI, and its multilevel characteristics, to assess the prevalence of DcSS in the general population, and to evaluate the presence of DcSS in the prediction of developing DCM.

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 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

This study aimed to define the histopathology of degenerated humeral head cartilage and synovial inflammation of the glenohumeral joint in patients with omarthrosis (OmA) and cuff tear arthropathy (CTA). Additionally, the potential of immunohistochemical tissue biomarkers in reflecting the degeneration status of humeral head cartilage was evaluated.

Aims

This study examined windswept deformity (WSD) of the knee, comparing prevalence and contributing factors in healthy and osteoarthritic (OA) cohorts.

Aims. The Coronal Plane Alignment of the Knee (CPAK) classification has been developed to predict individual variations in inherent knee alignment. The impact of preoperative and postoperative CPAK classification phenotype on the postoperative clinical outcomes of total knee arthroplasty (TKA) remains elusive. This study aimed to examine the effect of postoperative CPAK classification phenotypes (I to IX), and their pre- to postoperative changes on patient-reported outcome measures (PROMs). Methods. A questionnaire was administered to 340 patients (422 knees) who underwent primary TKA for osteoarthritis (OA) between September 2013 and June 2019. A total of 231 patients (284 knees) responded. The ­Knee Society Score 2011 (KSS 2011), Knee injury and Osteoarthritis Outcome Score-12 (KOOS-12), and Forgotten Joint Score-12 (FJS-12) were used to assess clinical outcomes. Using preoperative and postoperative anteroposterior full-leg radiographs, the arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) were calculated and classified based on the CPAK classification. To investigate the impact on PROMs, multivariable regression analyses using stepwise selection were conducted, considering factors such as age at surgery, time since surgery, BMI, sex, implant use, postoperative aHKA classification, JLO classification, and changes in aHKA and JLO classifications from preoperative to postoperative. Results. The preoperative and postoperative CPAK classifications were predominantly phenotype I (155 knees; 55%) and phenotype V (73 knees; 26%), respectively. The change in the preoperative to postoperative aHKA classification was a significant negative predictive factor for KOOS-12 and FJS-12, while postoperative apex proximal JLO was a significant negative predictive factor for KSS 2011 and KOOS-12. Conclusion. In primary TKA for OA, preoperative and postoperative CPAK phenotypes were associated with PROMs. Alteration in varus/valgus alignment from preoperative to postoperative was recognized as a negative predictive factor for both KOOS-12 and FJS-12. Moreover, the postoperative apex proximal JLO was identified as a negative factor for KSS 2011 and KOOS-12. Determining the target alignment for each preoperative phenotype with reproducibility could improve PROMs. Cite this article: Bone Joint J 2024;106-B(10):1059–1066

Aims

To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design.

Aims

Rotator cuff tear (RCT) is the leading cause of shoulder pain, primarily associated with age-related tendon degeneration. This study aimed to elucidate the potential differential gene expressions in tendons across different age groups, and to investigate their roles in tendon degeneration.

Bone regeneration and repair are crucial to ambulation and quality of life. Factors such as poor general health, serious medical comorbidities, chronic inflammation, and ageing can lead to delayed healing and nonunion of fractures, and persistent bone defects. Bioengineering strategies to heal bone often involve grafting of autologous bone marrow aspirate concentrate (BMAC) or mesenchymal stem cells (MSCs) with biocompatible scaffolds. While BMAC shows promise, variability in its efficacy exists due to discrepancies in MSC concentration and robustness, and immune cell composition. Understanding the mechanisms by which macrophages and lymphocytes – the main cellular components in BMAC – interact with MSCs could suggest novel strategies to enhance bone healing. Macrophages are polarized into pro-inflammatory (M1) or anti-inflammatory (M2) phenotypes, and influence cell metabolism and tissue regeneration via the secretion of cytokines and other factors. T cells, especially helper T1 (Th1) and Th17, promote inflammation and osteoclastogenesis, whereas Th2 and regulatory T (Treg) cells have anti-inflammatory pro-reconstructive effects, thereby supporting osteogenesis. Crosstalk among macrophages, T cells, and MSCs affects the bone microenvironment and regulates the local immune response. Manipulating the proportion and interactions of these cells presents an opportunity to alter the local regenerative capacity of bone, which potentially could enhance clinical outcomes. Cite this article: Bone Joint Res 2024;13(9):462–473

Aims. 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. Methods. 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. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential. Cite this article: Bone Jt Open 2024;5(8):671–680

The August 2024 Wrist & Hand Roundup³⁶⁰ looks at: Methotrexate shows potential in reducing pain for hand osteoarthritis with synovitis; Circumferential casting versus plaster splinting in adult distal radius fractures: the CAST study findings; Surgery shows superior long-term success for Dupuytren contracture compared to needle fasciotomy and collagenase injection; Evolving trends in surgical management of wrist arthritis: a decade-long national analysis; Mid-term outcomes of three commonly used surgical reconstructions for scapholunate instability; SLAC and SNAC: what is the evidence for treatment?; Steroids for trapeziometacarpal osteoarthritis?; When is it safe to return to driving after distal radius fracture fixation? A prospective study.

Aims

The aims of this study were: 1) to describe extended restricted kinematic alignment (E-rKA), a novel alignment strategy during robotic-assisted total knee arthroplasty (RA-TKA); 2) to compare residual medial compartment tightness following virtual surgical planning during RA-TKA using mechanical alignment (MA) and E-rKA, in the same set of osteoarthritic varus knees; 3) to assess the requirement of soft-tissue releases during RA-TKA using E-rKA; and 4) to compare the accuracy of surgical plan execution between knees managed with adjustments in component positioning alone, and those which require additional soft-tissue releases.