Aims. Prior studies have identified that malseating of a modular dual mobility liner can occur, with previous reported incidences between 5.8% and 16.4%. The aim of this study was to determine the incidence of malseating in dual mobility implants at our institution, assess for risk factors for liner malseating, and investigate whether liner malseating has any impact on clinical outcomes after surgery. Methods. We retrospectively reviewed the
Aims. This study aimed to evaluate sagittal spinopelvic alignment (SSPA) in the early stage of rapidly destructive coxopathy (RDC) compared with hip osteoarthritis (HOA), and to identify risk factors of SSPA for destruction of the femoral head within 12 months after the disease onset. Methods. This study enrolled 34 RDC patients with joint space narrowing > 2 mm within 12 months after the onset of hip pain and 25 HOA patients showing femoral head destruction. Sharp angle was measured for acetabular coverage evaluation. Femoral head collapse ratio was calculated for assessment of the extent of femoral head collapse by RDC. The following parameters of SSPA were evaluated using the whole spinopelvic
Aims. This study aimed to investigate the relationship between changes in patellar height and clinical outcomes at a mean follow-up of 7.7 years (5 to 10) after fixed-bearing posterior-stabilized total knee arthroplasty (PS-TKA). Methods. We retrospectively evaluated knee
Aims. The lateral centre-edge angle (LCEA) is a plain radiological measure of superolateral cover of the femoral head. This study aims to establish the correlation between 2D radiological and 3D CT measurements of acetabular morphology, and to describe the relationship between LCEA and femoral head cover (FHC). Methods. This retrospective study included 353 periacetabular osteotomies (PAOs) performed between January 2014 and December 2017. Overall, 97 hips in 75 patients had 3D analysis by Clinical Graphics, giving measurements for LCEA, acetabular index (AI), and FHC. Roentgenographical LCEA, AI, posterior wall index (PWI), and anterior wall index (AWI) were measured from supine AP pelvis
Aims. The aim of this study was to establish a reliable method for producing 3D reconstruction of sonographic callus. Methods. A cohort of ten closed tibial shaft fractures managed with intramedullary nailing underwent ultrasound scanning at two, six, and 12 weeks post-surgery. Ultrasound capture was performed using infrared tracking technology to map each image to a 3D lattice. Using echo intensity, semi-automated mapping was performed to produce an anatomical 3D representation of the fracture site. Two reviewers independently performed 3D reconstructions and kappa coefficient was used to determine agreement. A further validation study was undertaken with ten reviewers to estimate the clinical application of this imaging technique using the intraclass correlation coefficient (ICC). Results. Nine of the ten patients achieved union at six months. At six weeks, seven patients had bridging callus of ≥ one cortex on the 3D reconstruction and when present all achieved union. Compared to six-week
Aims. Perthes’ disease (PD) often results in femoral head deformity and leg length discrepancy (LLD). Our objective was to analyze femoral morphology in PD patients at skeletal maturity to assess where the LLD originates, and evaluate the effect of contralateral epiphysiodesis for length equalization on proximal and subtrochanteric femoral lengths. Methods. All patients treated for PD in our institution between January 2013 and June 2020 were reviewed retrospectively. Patients with unilateral PD, LLD of ≥ 5 mm, and long-leg standing
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 use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
The April 2023 Wrist & Hand Roundup360 looks at: MRI-based classification for acute scaphoid injuries: the OxSMART; Deep learning for detection of scaphoid fractures?; Ulnar shortening osteotomy in adolescents; Cost-utility analysis of thumb carpometacarpal resection arthroplasty; Arthritis of the wrist following scaphoid fracture nonunion; Extensor hood injuries in elite boxers; Risk factors for reoperation after flexor tendon repair; Nonoperative versus operative treatment for displaced finger metacarpal shaft fractures.
Symptomatic spinal stenosis is a very common problem, and decompression surgery has been shown to be superior to nonoperative treatment in selected patient groups. However, performing an instrumented fusion in addition to decompression may avoid revision and improve outcomes. The aim of the SpInOuT feasibility study was to establish whether a definitive randomized controlled trial (RCT) that accounted for the spectrum of pathology contributing to spinal stenosis, including pelvic incidence-lumbar lordosis (PI-LL) mismatch and mobile spondylolisthesis, could be conducted. As part of the SpInOuT-F study, a pilot randomized trial was carried out across five NHS hospitals. Patients were randomized to either spinal decompression alone or spinal decompression plus instrumented fusion. Patient-reported outcome measures were collected at baseline and three months. The intended sample size was 60 patients.Aims
Methods
Despite limited clinical scientific backing, an additional trochanteric stabilizing plate (TSP) has been advocated when treating unstable trochanteric fractures with a sliding hip screw (SHS). We aimed to explore whether the TSP would result in less post operative fracture motion, compared to SHS alone. Overall, 31 patients with AO/OTA 31-A2 trochanteric fractures were randomized to either a SHS alone or a SHS with an additional TSP. To compare postoperative fracture motion, radiostereometric analysis (RSA) was performed before and after weightbearing, and then at four, eight, 12, 26, and 52 weeks. With the “after weightbearing” images as baseline, we calculated translations and rotations, including shortening and medialization of the femoral shaft.Aims
Methods
In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method. We retrospectively collected CT imaging data of 108 hips with non-traumatic osteonecrosis of the femoral head from 76 consecutive patients (mean age 34.3 years (SD 8.1), 56.58% male (n = 43)) in two clinical centres. The femoral head was divided into 288 standard units (based on the orientation of units within the femoral head, designated as N[Superior], S[Inferior], E[Anterior], and W[Posterior]) using a new measurement system called the longitude and latitude division system (LLDS). A computer-aided design (CAD) measurement tool was also developed to visualize the measurement of the spatial location of necrotic lesions in CT images. Two orthopaedic surgeons independently performed measurements, and the results were used to draw 2D and 3D heat maps of spatial distribution of necrotic lesions in the femoral head, and for statistical analysis.Aims
Methods
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
Methods
To investigate the extent of bone development around the scaffold of custom triflange acetabular components (CTACs) over time. We performed a single-centre historical prospective cohort study, including all patients with revision THA using the aMace CTAC between January 2017 and March 2021. A total of 18 patients (18 CTACs) were included. Models of the hemipelvis and the scaffold component of the CTACs were created by segmentation of CT scans. The CT scans were performed immediately postoperatively and at least one year after surgery. The amount of bone in contact with the scaffold was analyzed at both times, and the difference was calculated.Aims
Methods
Accurate skeletal age and final adult height prediction methods in paediatric orthopaedics are crucial for determining optimal timing of growth-guiding interventions and minimizing complications in treatments of various conditions. This study aimed to evaluate the accuracy of final adult height predictions using the central peak height (CPH) method with long leg X-rays and four different multiplier tables. This study included 31 patients who underwent temporary hemiepiphysiodesis for varus or valgus deformity of the leg between 2014 and 2020. The skeletal age at surgical intervention was evaluated using the CPH method with long leg radiographs. The true final adult height (FHTRUE) was determined when the growth plates were closed. The final height prediction accuracy of four different multiplier tables (1. Bayley and Pinneau; 2. Paley et al; 3. Sanders – Greulich and Pyle (SGP); and 4. Sanders – peak height velocity (PHV)) was then compared using either skeletal age or chronological age.Aims
Methods
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article: