Aims. Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. Methods. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with orthopaedic surgeons. AI-based implant identification achieved AUC 0.992 to 1, and most algorithms reported an accuracy > 90%, using 550 to 320,000 training radiographs. AI prediction of dislocation risk post-THA, determined after five-year follow-up, was satisfactory (AUC 76.67; 8,500 training radiographs). Diagnosis of hip implant loosening was good (accuracy 88.3%; 420 training radiographs) and measurement of postoperative acetabular angles was comparable to humans (mean absolute difference 1.35° to 1.39°). However, 11 of the 12 studies had several methodological limitations introducing a high risk of bias. None of the studies were externally validated. Conclusion. These studies show that AI is promising. While it already has the ability to analyze images with significant precision, there is currently insufficient high-level evidence to support its widespread clinical use. Further research to design robust studies that follow standard reporting guidelines should be encouraged to develop AI models that could be easily translated into real-world conditions. Cite this article: Bone Joint J 2022;104-B(8):929–937

Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’). Cite this article: Bone Joint J 2022;104-B(8):911–914

Aims

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.

Aims. The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons. Methods. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes. Results. The four intersecting themes identified were: 1) validity in traditional research, 2) confusion around the definition of AI, 3) an inability to validate AI research, and 4) cautious optimism about AI research. Underpinning these themes is the notion of a validity heuristic that is strongly rooted in traditional research teaching and embedded in medical and surgical training. Conclusion. Research involving AI sometimes challenges the accepted traditional evidence-based framework. This can give rise to confusion among orthopaedic surgeons, who may be unable to confidently validate findings. In our study, the impact of this was mediated by cautious optimism based on an ingrained validity heuristic that orthopaedic surgeons develop through their medical training. Adding to this, the integration of AI into everyday life works to reduce suspicion and aid acceptance. Cite this article: Bone Jt Open 2023;4(9):696–703

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: Bone Joint Res 2023;12(7):447–454

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: Bone Joint J 2022;104-B(12):1292–1303

Aims. Hip dysplasia (HD) leads to premature osteoarthritis. Timely detection and correction of HD has been shown to improve pain, functional status, and hip longevity. Several time-consuming radiological measurements are currently used to confirm HD. An artificial intelligence (AI) software named HIPPO automatically locates anatomical landmarks on anteroposterior pelvis radiographs and performs the needed measurements. The primary aim of this study was to assess the reliability of this tool as compared to multi-reader evaluation in clinically proven cases of adult HD. The secondary aims were to assess the time savings achieved and evaluate inter-reader assessment. Methods. A consecutive preoperative sample of 130 HD patients (256 hips) was used. This cohort included 82.3% females (n = 107) and 17.7% males (n = 23) with median patient age of 28.6 years (interquartile range (IQR) 22.5 to 37.2). Three trained readers’ measurements were compared to AI outputs of lateral centre-edge angle (LCEA), caput-collum-diaphyseal (CCD) angle, pelvic obliquity, Tönnis angle, Sharp’s angle, and femoral head coverage. Intraclass correlation coefficients (ICC) and Bland-Altman analyses were obtained. Results. Among 256 hips with AI outputs, all six hip AI measurements were successfully obtained. The AI-reader correlations were generally good (ICC 0.60 to 0.74) to excellent (ICC > 0.75). There was lower agreement for CCD angle measurement. Most widely used measurements for HD diagnosis (LCEA and Tönnis angle) demonstrated good to excellent inter-method reliability (ICC 0.71 to 0.86 and 0.82 to 0.90, respectively). The median reading time for the three readers and AI was 212 (IQR 197 to 230), 131 (IQR 126 to 147), 734 (IQR 690 to 786), and 41 (IQR 38 to 44) seconds, respectively. Conclusion. This study showed that AI-based software demonstrated reliable radiological assessment of patients with HD with significant interpretation-related time savings. Cite this article: Bone Jt Open 2022;3(11):877–884

Aims. Abduction bracing is commonly used to treat developmental dysplasia of the hip (DDH) following closed reduction and spica casting, with little evidence to support or refute this practice. The purpose of this study was to determine the efficacy of abduction bracing after closed reduction in improving acetabular index (AI) and reducing secondary surgery for residual hip dysplasia. Methods. We performed a retrospective review of patients treated with closed reduction for DDH at a single tertiary referral centre. Demographic data were obtained including severity of dislocation based on the International Hip Dysplasia Institute (IHDI) classification, age at reduction, and casting duration. Patients were prescribed no abduction bracing, part-time, or full-time wear post-reduction and casting. AI measurements were obtained immediately upon cast removal and from two- and four-year follow-up radiographs. Results. A total of 243 hips underwent closed reduction and 82% (199/243) were treated with abduction bracing. There was no difference between those treated with or without bracing with regard to sex, age at reduction, severity of dislocation, spica duration, or immediate post-casting AI (all p > 0.05). There was no difference in hips treated with or without abduction brace with regard to AI at two years post-reduction (32.4° (SD 5.3°) vs 30.9° (SD 4.6°), respectively; p = 0.099) or at four years post-reduction (26.4° (SD 5.2°) vs 25.4° (SD 5.1°), respectively; p = 0.231). Multivariate analysis revealed only IHDI grade predicted AI at two years post-reduction (p = 0.004). There was no difference in overall rate of secondary surgery for residual dysplasia between hips treated with or without bracing (32% vs 39%, respectively; p = 0.372). However, there was an increased risk of early secondary surgery (< two years post-reduction) in the non-braced group (11.4% vs 2.5%; p = 0.019). Conclusion. Abduction bracing following closed reduction for DDH treatment is not associated with decreased residual dysplasia at two or four years post-reduction but may reduce rates of early secondary surgery. A prospective study is indicated to provide more definitive recommendations. Cite this article: Bone Joint J 2023;105-B(12):1327–1332

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. 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 radiographs. The correlation between CT and roentgenographical measurements was calculated. Sequential multiple linear regression was performed to determine the relationship between roentgenographical measurements and CT FHC. Results. CT-measured LCEA and AI correlated strongly with roentgenographical LCEA (r = 0.92; p < 0.001) and AI (r = 0.83; p < 0.001). Radiological LCEA correlated very strongly with CT FHC (r = 0.92; p < 0.001). The sum of AWI and PWI also correlated strongly with CTFHC (r = 0.73; p < 0.001). CT measurements of LCEA and AI were 3.4° less and 2.3° greater than radiological LCEA and AI measures. There was a linear relation between radiological LCEA and CT FHC. The linear regression model statistically significantly predicted FHC from LCEA, F(1,96) = 545.1 (p < 0.001), adjusted R. 2. = 85.0%, with the prediction equation: CT FHC(%) = 42.1 + 0.77(XRLCEA). Conclusion. CT and roentgenographical measurement of acetabular parameters are comparable. Currently, a radiological LCEA greater than 25° is considered normal. This study demonstrates that those with hip pain and normal radiological acetabular parameters may still have deficiencies in FHC. More sophisticated imaging techniques such as 3D CT should be considered for those with hip pain to identify deficiencies in FHC. Cite this article: Bone Jt Open 2022;3(1):12–19

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

Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles (. https://www.ideal-collaboration.net/. ). Adherence to the framework would provide a robust evidence-based mechanism for developing trust in AI applications, where the underlying algorithms are unlikely to be fully understood by clinical teams. Cite this article: Bone Joint Res 2024;13(9):507–512

The April 2023 Research Roundup. 360. looks at: Ear protection for orthopaedic surgeons?; Has arthroscopic meniscectomy use changed in response to the evidence?; Time to positivity of cultures obtained for periprosthetic joint infection; Bisphosphonates for post-COVID-19 osteonecrosis of the femoral head; Missing missed fractures: is AI the answer?; Congenital insensitivity to pain and correction of the knee; YouTube and paediatric elbow injuries

The OpenAI chatbot ChatGPT is an artificial intelligence (AI) application that uses state-of-the-art language processing AI. It can perform a vast number of tasks, from writing poetry and explaining complex quantum mechanics, to translating language and writing research articles with a human-like understanding and legitimacy. Since its initial release to the public in November 2022, ChatGPT has garnered considerable attention due to its ability to mimic the patterns of human language, and it has attracted billion-dollar investments from Microsoft and PricewaterhouseCoopers. The scope of ChatGPT and other large language models appears infinite, but there are several important limitations. This editorial provides an introduction to the basic functionality of ChatGPT and other large language models, their current applications and limitations, and the associated implications for clinical practice and research. Cite this article: Bone Joint J 2023;105-B(6):587–589

Aims. This study reports mid-term outcomes after periacetabular osteotomy (PAO) exclusively in a borderline hip dysplasia (BHD) population to provide a contrast to published outcomes for arthroscopic surgery of the hip in BHD. Methods. We identified 42 hips in 40 patients treated between January 2009 and January 2016 with BHD defined as a lateral centre-edge angle (LCEA) of ≥ 18° but < 25°. A minimum five-year follow-up was available. Patient-reported outcomes (PROMs) including Tegner score, subjective hip value (SHV), modified Harris Hip Score (mHHS), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were assessed. The following morphological parameters were evaluated: LCEA, acetabular index (AI), α angle, Tönnis staging, acetabular retroversion, femoral version, femoroepiphyseal acetabular roof index (FEAR), iliocapsularis to rectus femoris ratio (IC/RF), and labral and ligamentum teres (LT) pathology. Results. The mean follow-up was 96 months (67 to 139). The SHV, mHHS, WOMAC, and Tegner scores significantly improved (p < 0.001) at last follow-up. According to SHV and mHHS, there were three hips (7%) with poor results (SHV < 70), three (7%) with a fair score (70 to 79), eight (19%) with good results (80 to 89), and 28 (67%) who scored excellent (> 90) at the last follow-up. There were 11 subsequent operations: nine implant removals due to local irritation, one resection of postoperative heterotopic ossification, and one hip arthroscopy for intra-articular adhesions. No hips were converted to total hip arthroplasty at last follow-up. The presence of preoperative labral lesions or LT lesions did not influence any PROMs at last follow-up. From the three hips that had poor PROMs, two have developed severe osteoarthritis (> Tönnis II), presumably due to surgical overcorrection (postoperative AI < -10°). Conclusion. PAO is reliable in treating BHD with favourable mid-term outcomes. Concomitant LT and labral lesions did not negatively influence outcomes in our cohort. Technical accuracy with avoidance of overcorrection is essential in achieving successful outcomes. Cite this article: Bone Joint J 2023;105-B(7):735–742

Aims. The aims of this study were to compare clinically relevant measurements of hip dysplasia on radiographs taken in the supine and standing position, and to compare Hip2Norm software and Picture Archiving and Communication System (PACS)-derived digital radiological measurements. Methods. Preoperative supine and standing radiographs of 36 consecutive patients (43 hips) who underwent periacetabular osteotomy surgery were retrospectively analyzed from a single-centre, two-surgeon cohort. Anterior coverage (AC), posterior coverage (PC), lateral centre-edge angle (LCEA), acetabular inclination (AI), sharp angle (SA), pelvic tilt (PT), retroversion index (RI), femoroepiphyseal acetabular roof (FEAR) index, femoroepiphyseal horizontal angle (FEHA), leg length discrepancy (LLD), and pelvic obliquity (PO) were analyzed using both Hip2Norm software and PACS-derived measurements where applicable. Results. Analysis of supine and standing radiographs resulted in significant variation for measurements of PT (p < 0.001) and AC (p = 0.005). The variation in PT correlated with the variation in AC in a limited number of patients (R. 2. = 0.378; p = 0.012). Conclusion. The significant variation in PT and AC between supine and standing radiographs suggests that it may benefit surgeons to have both radiographs when planning surgical correction of hip dysplasia. We also recommend using PACS-derived measurements of AI and SA due to the poor interobserver error on Hip2Norm. Cite this article: Bone Joint J 2021;103-B(11):1662–1668

Aims. Accurate identification of the ankle joint centre is critical for estimating tibial coronal alignment in total knee arthroplasty (TKA). The purpose of the current study was to leverage artificial intelligence (AI) to determine the accuracy and effect of using different radiological anatomical landmarks to quantify mechanical alignment in relation to a traditionally defined radiological ankle centre. Methods. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A sub-cohort of 250 radiographs were annotated for landmarks relevant to knee alignment and used to train a deep learning (U-Net) workflow for angle calculation on the entire database. The radiological ankle centre was defined as the midpoint of the superior talus edge/tibial plafond. Knee alignment (hip-knee-ankle angle) was compared against 1) midpoint of the most prominent malleoli points, 2) midpoint of the soft-tissue overlying malleoli, and 3) midpoint of the soft-tissue sulcus above the malleoli. Results. A total of 932 bilateral full-limb radiographs (1,864 knees) were measured at a rate of 20.63 seconds/image. The knee alignment using the radiological ankle centre was accurate against ground truth radiologist measurements (inter-class correlation coefficient (ICC) = 0.99 (0.98 to 0.99)). Compared to the radiological ankle centre, the mean midpoint of the malleoli was 2.3 mm (SD 1.3) lateral and 5.2 mm (SD 2.4) distal, shifting alignment by 0.34. o. (SD 2.4. o. ) valgus, whereas the midpoint of the soft-tissue sulcus was 4.69 mm (SD 3.55) lateral and 32.4 mm (SD 12.4) proximal, shifting alignment by 0.65. o. (SD 0.55. o. ) valgus. On the intermalleolar line, measuring a point at 46% (SD 2%) of the intermalleolar width from the medial malleoli (2.38 mm medial adjustment from midpoint) resulted in knee alignment identical to using the radiological ankle centre. Conclusion. The current study leveraged AI to create a consistent and objective model that can estimate patient-specific adjustments necessary for optimal landmark usage in extramedullary and computer-guided navigation for tibial coronal alignment to match radiological planning. Cite this article: Bone Jt Open 2022;3(10):767–776

Aims

To provide normative data that can assess spinal-related disability and the prevalence of back or leg pain among adults with no spinal conditions in the UK using validated questionnaires.

The development of spinal deformity in children with underlying neurodisability can affect their ability to function and impact on their quality of life, as well as compromise provision of nursing care. Patients with neuromuscular spinal deformity are among the most challenging due to the number and complexity of medical comorbidities that increase the risk for severe intraoperative or postoperative complications. A multidisciplinary approach is mandatory at every stage to ensure that all nonoperative measures have been applied, and that the treatment goals have been clearly defined and agreed with the family. This will involve input from multiple specialities, including allied healthcare professionals, such as physiotherapists and wheelchair services. Surgery should be considered when there is significant impact on the patients’ quality of life, which is usually due to poor sitting balance, back or costo-pelvic pain, respiratory complications, or problems with self-care and feeding. Meticulous preoperative assessment is required, along with careful consideration of the nature of the deformity and the problems that it is causing. Surgery can achieve good curve correction and results in high levels of satisfaction from the patients and their caregivers. Modern modular posterior instrumentation systems allow an effective deformity correction. However, the risks of surgery remain high, and involvement of the family at all stages of decision-making is required in order to balance the risks and anticipated gains of the procedure, and to select those patients who can mostly benefit from spinal correction.

Aims. Guided growth has been used to treat coxa valga for cerebral palsy (CP) children. However, there has been no study on the optimal position of screw application. In this paper we have investigated the influence of screw position on the outcomes of guided growth. Methods. We retrospectively analyzed 61 hips in 32 CP children who underwent proximal femoral hemi epiphysiodesis between July 2012 and September 2017. The hips were divided into two groups according to the transphyseal position of the screw in the coronal plane: across medial quarter (Group 1) or middle quarter (Group 2) of the medial half of the physis. We compared pre- and postoperative radiographs in head-shaft angle (HSA), Reimer’s migration percentage (MP), acetabular index (AI), and femoral anteversion angle (FAVA), as well as incidences of the physis growing-off the screw within two years. Linear and Cox regression analysis were conducted to identify factors related to HSA correction and risk of the physis growing-off the screw. Results. A total of 37 hips in Group 1 and 24 hips in Group 2 were compared. Group 1 showed a more substantial decrease in the HSA (p = 0.003) and the MP (p = 0.032). Both groups had significant and similar improvements in the AI (p = 0.809) and the FAVA (p = 0.304). Group 1 presented a higher incidence of the physis growing-off the screw (p = 0.038). Results of the regression analysis indicated that the eccentricity of screw position correlated with HSA correction and increases the risk of the physis growing-off the screw. Conclusion. Guided growth is effective in improving coxa valga and excessive femoral anteversion in CP children. For younger children, despite compromised efficacy of varus correction, we recommend a more centered screw position, at least across the middle quarter of the medial physis, to avoid early revision. Cite this article: Bone Joint J 2020;102-B(9):1242–1247

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To report the outcome of spinal deformity correction through anterior spinal fusion in wheelchair-bound patients with myelomeningocele.

Adolescent idiopathic scoliosis (AIS), defined by an age at presentation of 11 to 18 years, has a prevalence of 0.47% and accounts for approximately 90% of all cases of idiopathic scoliosis. Despite decades of research, the exact aetiology of AIS remains unknown. It is becoming evident that it is the result of a complex interplay of genetic, internal, and environmental factors. It has been hypothesized that genetic variants act as the initial trigger that allow epigenetic factors to propagate AIS, which could also explain the wide phenotypic variation in the presentation of the disorder. A better understanding of the underlying aetiological mechanisms could help to establish the diagnosis earlier and allow a more accurate prediction of deformity progression. This, in turn, would prompt imaging and therapeutic intervention at the appropriate time, thereby achieving the best clinical outcome for this group of patients.

Cite this article: Bone Joint J 2022;104-B(8):915–921.

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To report the surgical outcome of patients with severe Scheuermann’s kyphosis treated using a consistent technique and perioperative management.

Aims

Large acetabular bone defects encountered in revision total hip arthroplasty (THA) are challenging to restore. Metal constructs for structural support are combined with bone graft materials for restoration. Autograft is restricted due to limited volume, and allogenic grafts have downsides including cost, availability, and operative processing. Bone graft substitutes (BGS) are an attractive alternative if they can demonstrate positive remodelling. One potential product is a biphasic injectable mixture (Cerament) that combines a fast-resorbing material (calcium sulphate) with the highly osteoconductive material hydroxyapatite. This study reviews the application of this biomaterial in large acetabular defects.

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The aim of this study was to characterize the influence of social deprivation on the rate of complications, readmissions, and revisions following primary total shoulder arthroplasty (TSA), using the Social Deprivation Index (SDI). The SDI is a composite measurement, in percentages, of seven demographic characteristics: living in poverty, with < 12 years of education, single-parent households, living in rented or overcrowded housing, households without a car, and unemployed adults aged < 65 years.

Aims. This study of patients with osteoarthritis (OA) of the hip aimed to: 1) characterize the contribution of the hip, spinopelvic complex, and lumbar spine when moving from the standing to the sitting position; 2) assess whether abnormal spinopelvic mobility is associated with worse symptoms; and 3) identify whether spinopelvic mobility can be predicted from static anatomical radiological parameters. Patients and Methods. A total of 122 patients with end-stage OA of the hip awaiting total hip arthroplasty (THA) were prospectively studied. Patient-reported outcome measures (PROMs; Oxford Hip Score, Oswestry Disability Index, and Veterans RAND 12-Item Health Survey Score) and clinical data were collected. Sagittal spinopelvic mobility was calculated as the change from the standing to sitting position using the lumbar lordosis angle (LL), sacral slope (SS), pelvic tilt (PT), pelvic-femoral angle (PFA), and acetabular anteinclination (AI) from lateral radiographs. The interaction of the different parameters was assessed. PROMs were compared between patients with normal spinopelvic mobility (10° ≤ ∆PT ≤ 30°) or abnormal spinopelvic mobility (stiff: ∆PT < ± 10°; hypermobile: ∆PT > ± 30°). Multiple regression and receiver operating characteristic (ROC) curve analyses were used to test for possible predictors of spinopelvic mobility. Results. Standing to sitting, the hip flexed by a mean of 57° (. sd. 17°), the pelvis tilted backwards by a mean of 20° (. sd. 12°), and the lumbar spine flexed by a mean of 20° (. sd. 14°); strong correlations were detected. There was no difference in PROMs between patients in the different spinopelvic mobility groups. Maximum hip flexion, standing PT, and standing AI were independent predictors of spinopelvic mobility (R. 2. = 0.42). The combined thresholds for standing was PT ≥ 13° and hip flexion ≥ 88° in the clinical examination, and had 90% sensitivity and 63% specificity of predicting spinopelvic stiffness, while SS ≥ 42° had 84% sensitivity and 67% specificity of predicting spinopelvic hypermobility. Conclusion. The hip, on average, accounts for three-quarters of the standing-to-sitting movement, but there is great variation. Abnormal spinopelvic mobility cannot be screened with PROMs. However, clinical and standing radiological features can predict spinopelvic mobility with good enough accuracy, allowing them to be used as reliable screening tools. Cite this article: Bone Joint J 2019;101-B:902–909

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High-grade dysplastic spondylolisthesis is a disabling disorder for which many different operative techniques have been described. The aim of this study is to evaluate Scoliosis Research Society 22-item (SRS-22r) scores, global balance, and regional spino-pelvic alignment from two to 25 years after surgery for high-grade dysplastic spondylolisthesis using an all-posterior partial reduction, transfixation technique.

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Severe spinal deformity in growing patients often requires surgical management. We describe the incidence of spinal deformity surgery in a National Health Service.

Aims

The aims of this study were to determine the change in pelvic sagittal alignment before, during, and after total hip arthroplasty (THA) undertaken with the patient in the lateral decubitus position, and to determine the impact of these changes on acetabular component position.

The medial approach for the treatment of children with developmental dysplasia of the hip (DDH) in whom closed reduction has failed requires minimal access with negligible blood loss. In the United Kingdom, there is a preference for these children to be treated using an anterolateral approach after the appearance of the ossific nucleus. In this study we compared these two protocols, primarily for the risk of osteonecrosis. Data were gathered prospectively for protocols involving the medial approach (26 hips in 22 children) and the anterolateral approach (22 hips in 21 children) in children aged <  24 months at the time of surgery. Osteonecrosis of the femoral head was assessed with validated scores. The acetabular index (AI) and centre–edge angle (CEA) were also measured. . The mean age of the children at the time of surgery was 11 months (3 to 24) for the medial approach group and 18 months (12 to 24) for the anterolateral group, and the combined mean follow-up was 70 months (26 to 228). Osteonecrosis of the femoral head was evident or asphericity predicted in three of 26 hips (12%) in the medial approach group and four of 22 (18%) in the anterolateral group (p = 0.52). The mean improvement in AI was 8.8° (4° to 12°) and 7.9° (6° to 10°), respectively, at two years post-operatively (p = 0.18). There was no significant difference in CEA values of affected hips between the two groups. Children treated using an early medial approach did not have a higher risk of developing osteonecrosis at early to mid-term follow-up than those treated using a delayed anterolateral approach. The rates of acetabular remodelling were similar for both protocols. Cite this article: Bone Joint J 2014;96-B:406–13

Cite this article: Bone Joint Res 2023;12(8):494–496.

The June 2024 Wrist & Hand Roundup³⁶⁰ looks at: One-year outcomes of the anatomical front and back reconstruction for scapholunate dissociation; Limited intercarpal fusion versus proximal row carpectomy in the treatment of SLAC or SNAC wrist: results after 3.5 years; Prognostic factors for clinical outcomes after arthroscopic treatment of traumatic central tears of the triangular fibrocartilage complex; The rate of nonunion in the MRI-detected occult scaphoid fracture: a multicentre cohort study; Does correction of carpal malalignment influence the union rate of scaphoid nonunion surgery?; Provision of a home-based video-assisted therapy programme in thumb carpometacarpal arthroplasty; Is replantation associated with better hand function after traumatic hand amputation than after revision amputation?; Diagnostic performance of artificial intelligence for detection of scaphoid and distal radius fractures: a systematic review.

Aims

Periacetabular osteotomy (PAO) is the preferred treatment for symptomatic acetabular dysplasia in adolescents and young adults. There remains a lack of consensus regarding whether intra-articular procedures such as labral repair or improvement of femoral offset should be performed at the time of PAO or addressed subsequent to PAO if symptoms warrant. The purpose was to determine the rate of subsequent hip arthroscopy (HA) in a contemporary cohort of patients, who underwent PAO in isolation without any intra-articular procedures.

The August 2023 Research Roundup³⁶⁰ looks at: Can artificial intelligence improve the readability of patient education materials?; What is the value of radiology input during a multidisciplinary orthopaedic oncology conference?; Periprosthetic joint infection in patients with multiple arthroplasties; Orthopedic Surgery and Anesthesiology Surgical Improvement Strategies Project - Phase III outcomes; Knot tying in arthroplasty and arthroscopy causes lesions to surgical gloves: a potential risk of infection; Vascular calcification of the ankle in plain radiographs equals diabetes mellitus?

Aims

We present the results of correcting a double or triple curve adolescent idiopathic scoliosis using a convex segmental pedicle screw technique.

Aims

This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model.

The June 2024 Research Roundup³⁶⁰ looks at: Do the associations of daily steps with mortality and incident cardiovascular disease differ by sedentary time levels?; Large-scale assessment of ChatGPT in benign and malignant bone tumours imaging report diagnosis and its potential for clinical applications; Long-term effects of diffuse idiopathic skeletal hyperostosis on physical function: a longitudinal analysis; Effect of intramuscular fat in the thigh muscles on muscle architecture and physical performance in the middle-aged females with knee osteoarthritis; Preoperative package of care for osteoarthritis an opportunity not to be missed?; Superiority of kinematic alignment over mechanical alignment in total knee arthroplasty during medium- to long-term follow-up: a meta-analysis and trial sequential analysis.

Aims

Eccentric reductions may become concentric through femoral head ‘docking’ (FHD) following closed reduction (CR) for developmental dysplasia of the hip (DDH). However, changes regarding position and morphology through FHD are not well understood. We aimed to assess these changes using serial MRI.

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.

We describe 13 patients with cerebral palsy and lordoscoliosis/hyperlordosis of the lumbar spine who underwent a posterior spinal fusion at a mean age of 14.5 years (10.8 to 17.4) to improve sitting posture and relieve pain. The mean follow-up was 3.3 years (2.2 to 6.2).

The mean pre-operative lumbar lordosis was 108^° (80 to 150^°) and was corrected to 62^° (43^° to 85^°); the mean thoracic kyphosis from 17^° (-23^° to 35^°) to 47^° (25^° to 65^°); the mean scoliosis from 82^° (0^° to 125^°) to 22^° (0^° to 40^°); the mean pelvic obliquity from 21^° (0^° to 38^°) to 3^° (0^° to 15^°); the mean sacral slope from 79^° (54^° to 90^°) to 50^° (31^° to 66^°). The mean pre-operative coronal imbalance was 5 cm (0 cm to 8.9 cm) and was corrected to 0.6 cm (0 to 3.2). The mean sagittal imbalance of -8 cm (-16 cm to 7.8 cm) was corrected to -1.6 cm (-4 cm to 2.5 cm). The mean operating time was 250 minutes (180 to 360 minutes) and intra-operative blood loss 0.8 of estimated blood volume (0.3 to 2 estimated blood volume). The mean intensive care and hospital stay were 3.5 days (2 to 8) and 14.5 days (10 to 27), respectively. Three patients lost a significant amount of blood intra-operatively and subsequently developed chest or urinary infections and superior mesenteric artery syndrome.

An increased pre-operative lumbar lordosis and sacral slope were associated with increased peri-operative morbidity: scoliosis and pelvic obliquity were not. A reduced lumbar lordosis and increased thoracic kyphosis correlated with better global sagittal balance at follow-up. All patients and their parents reported excellent surgical outcomes.

Lordoscoliosis and hyperlordosis are associated with significant morbidity in quadriplegic patients. They are rare deformities and their treatment is challenging. Sagittal imbalance is the major component: it can be corrected by posterior fusion of the spine with excellent functional results.

Cite this article: Bone Joint J 2014;96-B:800–6.

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.

Aims

Brace treatment is the cornerstone of managing developmental dysplasia of the hip (DDH), yet there is a lack of evidence-based treatment protocols, which results in wide variations in practice. To resolve this, we have developed a comprehensive nonoperative treatment protocol conforming to published consensus principles, with well-defined a priori criteria for inclusion and successful treatment.