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 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. 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

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

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

Aims

Hip arthroscopy has gained prominence as a primary surgical intervention for symptomatic femoroacetabular impingement (FAI). This study aimed to identify radiological features, and their combinations, that predict the outcome of hip arthroscopy for FAI.

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

In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method.

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.

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.

The June 2024 Hip & Pelvis Roundup³⁶⁰ looks at: Machine learning did not outperform conventional competing risk modelling to predict revision arthroplasty; Unravelling the risks: incidence and reoperation rates for femoral fractures post-total hip arthroplasty; Spinal versus general anaesthesia for hip arthroscopy: a COVID-19 pandemic- and opioid epidemic-driven study; Development and validation of a deep-learning model to predict total hip arthroplasty on radiographs; Ambulatory centres lead in same-day hip and knee arthroplasty success; Exploring the impact of smokeless tobacco on total hip arthroplasty outcomes: a deeper dive into postoperative complications.

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.

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.

Aims

Periacetabular osteotomy (PAO) is widely recognized as a demanding surgical procedure for acetabular reorientation. Reports about the learning curve have primarily focused on complication rates during the initial learning phase. Therefore, our aim was to assess the PAO learning curve from an analytical perspective by determining the number of PAOs required for the duration of surgery to plateau and the accuracy to improve.

Aims

It is important to analyze objectively the hammering sound in cup press-fit technique in total hip arthroplasty (THA) in order to better understand the change of the sound during impaction. We hypothesized that a specific characteristic would present in a hammering sound with successful fixation. We designed the study to quantitatively investigate the acoustic characteristics during cementless cup impaction in THA.

Aims

While internet search engines have been the primary information source for patients’ questions, artificial intelligence large language models like ChatGPT are trending towards becoming the new primary source. The purpose of this study was to determine if ChatGPT can answer patient questions about total hip (THA) and knee arthroplasty (TKA) with consistent accuracy, comprehensiveness, and easy readability.

Aims

Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort.

The February 2024 Children’s orthopaedics Roundup³⁶⁰ looks at: Hip impingement after in situ pinning causes decreased flexion and forced external rotation in flexion on 3D-CT; Triplane ankle fracture patterns in paediatric patients; Improved forearm rotation even after early conversion to below-elbow; Selective dorsal rhizotomy and cerebral palsy (CP) hip displacement; Abduction bracing following anterior open reduction for developmental dysplasia of the hip does not improve residual dysplasia or reduce secondary surgery; 40% risk of later total hip arthroplasty for in situ slipped capital femoral epiphysis (SCFE) pinning; Does brace treatment following closed reduction of developmental dysplasia of the hip improve acetabular coverage?; Waterproof hip spica casts for paediatric femur fractures.

Aims

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

Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.

The December 2023 Spine Roundup³⁶⁰ looks at: Does size matter in adolescent pedicle screws?; Effect of lumbar fusion and pelvic fixation rigidity on hip joint stress: a finite element analysis; Utility of ultrasonography in the diagnosis of lumbar spondylolysis in adolescent patients; Rett syndrome-associated scoliosis a national picture.

The December 2023 Research Roundup³⁶⁰ looks at: Tissue integration and chondroprotective potential of acetabular labral augmentation with autograft tendon: study of a porcine model; The Irish National Orthopaedic Register under cyberattack: what happened, and what were the consequences?; An overview of machine learning in orthopaedic surgery: an educational paper; Beware of the fungus…; New evidence for COVID-19 in patients undergoing joint replacement surgery.

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

Hip disease is common in children with cerebral palsy (CP) and can decrease quality of life and function. Surveillance programmes exist to improve outcomes by treating hip disease at an early stage using radiological surveillance. However, studies and surveillance programmes report different radiological outcomes, making it difficult to compare. We aimed to identify the most important radiological measurements and develop a core measurement set (CMS) for clinical practice, research, and surveillance programmes.

Aims

Psychological status may be an important predictor of outcome after periacetabular osteotomy (PAO). The aim of this study was to investigate the influence of psychological distress on postoperative health-related quality of life, joint function, self-assessed pain, and sports ability in patients undergoing PAO.

The October 2023 Wrist & Hand Roundup³⁶⁰ looks at: Distal radius fracture management: surgeon factors markedly influence decision-making; Fracture-dislocation of the radiocarpal joint: bony and capsuloligamentar management, outcomes, and long-term complications; Exploring the role of artificial intelligence chatbot in the management of scaphoid fractures; Role of ultrasonography for evaluation of nerve recovery in repaired median nerve lacerations; Four weeks versus six weeks of immobilization in a cast following closed reduction for displaced distal radial fractures in adult patients: a multicentre randomized controlled trial; Rehabilitation following flexor tendon injury in Zone 2: a randomized controlled study; On the road again: return to driving following minor hand surgery; Open versus single- or dual-portal endoscopic carpal tunnel release: a meta-analysis of randomized controlled trials.

The October 2023 Hip & Pelvis Roundup³⁶⁰ looks at: Femoroacetabular impingement syndrome at ten years – how do athletes do?; Venous thromboembolism in patients following total joint replacement: are transfusions to blame?; What changes in pelvic sagittal tilt occur 20 years after total hip arthroplasty?; Can stratified care in hip arthroscopy predict successful and unsuccessful outcomes?; Hip replacement into your nineties; Can large language models help with follow-up?; The most taxing of revisions – proximal femoral replacement for periprosthetic joint infection – what’s the benefit of dual mobility?

The October 2023 Children’s orthopaedics Roundup³⁶⁰ looks at: Outcomes of open reduction in children with developmental hip dislocation: a multicentre experience over a decade; A torn discoid lateral meniscus impacts lower-limb alignment regardless of age; Who benefits from allowing the physis to grow in slipped capital femoral epiphysis?; Consensus guidelines on the management of musculoskeletal infection affecting children in the UK; Diagnosis of developmental dysplasia of the hip by ultrasound imaging using deep learning; Outcomes at a mean of 13 years after proximal humeral fracture during adolescence; Clubfeet treated according to Ponseti at four years; Controlled ankle movement boot provides improved outcomes with lower complications than short leg walking cast.

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

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

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.

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?

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

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

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

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 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.

Aims

It is important to analyze objectively the hammering sound in cup press-fit technique in total hip arthroplasty (THA) in order to better understand the change of the sound during impaction. We hypothesized that a specific characteristic would present in a hammering sound with successful fixation. We designed the study to quantitatively investigate the acoustic characteristics during cementless cup impaction in THA.

The February 2023 Knee Roundup³⁶⁰ looks at: Machine-learning models: are all complications predictable?; Positive cultures can be safely ignored in revision arthroplasty patients that do not meet the 2018 International Consensus Meeting Criteria; Spinal versus general anaesthesia in contemporary primary total knee arthroplasty; Preoperative pain and early arthritis are associated with poor outcomes in total knee arthroplasty; Risk factors for infection and revision surgery following patellar tendon and quadriceps tendon repairs; Supervised versus unsupervised rehabilitation following total knee arthroplasty; Kinematic alignment has similar outcomes to mechanical alignment: a systematic review and meta-analysis; Lifetime risk of revision after knee arthroplasty influenced by age, sex, and indication; Risk factors for knee osteoarthritis after traumatic knee injury.

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.

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.

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. 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

There is no consensus regarding optimum timing and frequency of ultrasound (US) for monitoring response to Pavlik harness (PH) treatment in developmental dysplasia of the hip (DDH). The purpose of our study was to determine if a limited-frequency hip US assessment had an adverse effect on treatment outcomes compared to traditional comprehensive US monitoring.

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.

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. 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

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Acetabular retroversion is a recognized cause of hip impingement and can be influenced by pelvic tilt (PT), which changes in different functional positions. Positional changes in PT have not previously been studied in patients with acetabular retroversion.

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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.

Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.

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

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines.

Cite this article: Bone Joint J 2021;103-B(12):1754–1758.

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

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The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs?

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The effect of pelvic tilt (PT) and sagittal balance in hips with pincer-type femoroacetabular impingement (FAI) with acetabular retroversion (AR) is controversial. It is unclear if patients with AR have a rotational abnormality of the iliac wing. Therefore, we asked: are parameters for sagittal balance, and is rotation of the iliac wing, different in patients with AR compared to a control group?; and is there a correlation between iliac rotation and acetabular version?

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Periacetabular osteotomy (PAO) is an established treatment for acetabular dysplasia. It has also been proposed as a treatment for patients with acetabular retroversion. By reviewing a large cohort, we aimed to test whether outcome is equivalent for both types of morphology and identify factors that influenced outcome.

In recent years, machine learning (ML) and artificial neural networks (ANNs), a particular subset of ML, have been adopted by various areas of healthcare. A number of diagnostic and prognostic algorithms have been designed and implemented across a range of orthopaedic sub-specialties to date, with many positive results. However, the methodology of many of these studies is flawed, and few compare the use of ML with the current approach in clinical practice. Spinal surgery has advanced rapidly over the past three decades, particularly in the areas of implant technology, advanced surgical techniques, biologics, and enhanced recovery protocols. It is therefore regarded an innovative field. Inevitably, spinal surgeons will wish to incorporate ML into their practice should models prove effective in diagnostic or prognostic terms. The purpose of this article is to review published studies that describe the application of neural networks to spinal surgery and which actively compare ANN models to contemporary clinical standards allowing evaluation of their efficacy, accuracy, and relatability. It also explores some of the limitations of the technology, which act to constrain the widespread adoption of neural networks for diagnostic and prognostic use in spinal care. Finally, it describes the necessary considerations should institutions wish to incorporate ANNs into their practices. In doing so, the aim of this review is to provide a practical approach for spinal surgeons to understand the relevant aspects of neural networks.

Cite this article: Bone Joint J 2021;103-B(9):1442–1448.

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

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The objective of this study was to evaluate the clinical and radiological outcomes of patients younger than six months of age with developmental dysplasia of the hip (DDH) managed by either a Pavlik harness or Tübingen hip flexion splint.

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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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The ongoing COVID-19 pandemic has disrupted and delayed medical and surgical examinations where attendance is required in person. Our article aims to outline the validity of online assessment, the range of benefits to both candidate and assessor, and the challenges to its implementation. In addition, we propose pragmatic suggestions for its introduction into medical assessment.

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Optimal exposure through the direct anterior approach (DAA) for total hip arthroplasty (THA) conducted on a regular operating theatre table is achieved with a standardized capsular releasing sequence in which the anterior capsule can be preserved or resected. We hypothesized that clinical outcomes and implant positioning would not be different in case a capsular sparing (CS) technique would be compared to capsular resection (CR).

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

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We aimed to determine hip-related quality of life and clinical findings following treatment for neonatal hip instability (NHI) compared with age- and sex-matched controls. We hypothesized that NHI would predispose to hip discomfort in long-term follow-up.

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The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an anteroposterior pelvic radiograph deep learning system for diagnosing DDH in children and analyze the feasibility of its application.

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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The goal of closed reduction (CR) in the treatment of developmental dysplasia of the hip (DDH) is to achieve and maintain concentricity of the femoral head in the acetabulum. However, concentric reduction is not immediately attainable in all hips and it remains controversial to what degree a non-concentric reduction is acceptable. This prospective study is aimed at investigating the dynamic evolution of the hip joint space after CR in DDH using MRI.

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The aim of the current study was to assess the reliability of the Ottawa classification for symptomatic acetabular dysplasia.

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When the present study was initiated, we changed the treatment for late-detected developmental dislocation of the hip (DDH) from several weeks of skin traction to markedly shorter traction time. The aim of this prospective study was to evaluate this change, with special emphasis on the rate of stable closed reduction according to patient age, the development of the acetabulum, and the outcome at skeletal maturity.

Introduction

Studies have addressed the issue of increasing prevalence of work-related musculoskeletal (MSK) pain among different occupations. However, contributing factors to MSK pain have not been fully investigated among orthopaedic surgeons. Thus, this study aimed to approximate the prevalence and predictors of MSK pain among Saudi orthopaedic surgeons working in Riyadh, Saudi Arabia.

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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.

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A borderline dysplastic hip can behave as either stable or unstable and this makes surgical decision making challenging. While an unstable hip may be best treated by acetabular reorientation, stable hips can be treated arthroscopically. Several imaging parameters can help to identify the appropriate treatment, including the Femoro-Epiphyseal Acetabular Roof (FEAR) index, measured on plain radiographs. The aim of this study was to assess the reliability and the sensitivity of FEAR index on MRI compared with its radiological measurement.

This annotation briefly reviews the history of artificial intelligence and machine learning in health care and orthopaedics, and considers the role it will have in the future, particularly with reference to statistical analyses involving large datasets.

Cite this article: Bone Joint J 2019;101-B:1476–1478

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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The aim of this study was to compare patient-reported outcome measures (PROMs), radiological measurements, and total hip arthroplasty (THA)-free survival in patients who underwent periacetabular osteotomy (PAO) for mild, moderate, or severe developmental dysplasia of the hip.

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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.

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The aim of this study was to utilize a national paediatric inpatient database to determine whether obesity influences the operative management and inpatient outcomes of paediatric limb fractures.

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In patients with a rotator cuff tear, tear pattern and tendon involvement are known risk factors for the development of pseudoparalysis of the shoulder. It remains unclear, however, why similar tears often have very different functional consequences. The present study hypothesizes that individual shoulder anatomy, specifically the moment arms (MAs) of the rotator cuff (RC) and the deltoid muscle, as well as their relative recruitment during shoulder abduction, plays a central role in pseudoparalysis.

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What represents clinically significant acetabular undercoverage in patients with symptomatic cam-type femoroacetabular impingement (FAI) remains controversial. The aim of this study was to examine the influence of the degree of acetabular coverage on the functional outcome of patients treated arthroscopically for cam-type FAI.

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Open reduction is required following failed conservative treatment of developmental dysplasia of the hip (DDH). The Ludloff medial approach is commonly used, but poor results have been reported, with rates of the development of avascular necrosis (AVN) varying between 8% and 54%. This retrospective cohort study evaluates the long-term radiographic and clinical outcome of dislocated hips treated using this approach.

Adolescent idiopathic scoliosis (AIS) is a complex 3D deformity of the spine. Its prevalence is between 2% and 3% in the general population, with almost 10% of patients requiring some form of treatment and up to 0.1% undergoing surgery. The cosmetic aspect of the deformity is the biggest concern to the patient and is often accompanied by psychosocial distress. In addition, severe curves can cause cardiopulmonary distress. With proven benefits from surgery, the aims of treatment are to improve the cosmetic and functional outcomes. Obtaining correction in the coronal plane is not the only important endpoint anymore. With better understanding of spinal biomechanics and the long-term effects of multiplanar imbalance, we now know that sagittal balance is equally, if not more, important. Better correction of deformities has also been facilitated by an improvement in the design of implants and a better understanding of metallurgy. Understanding the unique character of each deformity is important. In addition, using the most appropriate implant and applying all the principles of correction in a bespoke manner is important to achieve optimum correction.

In this article, we review the current concepts in AIS surgery.

Cite this article: Bone Joint J 2018;100-B:415–24.

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This study sought to establish the prevalence of the cross over sign (COS) and posterior wall sign (PWS) in relation to the anterior pelvic plane (APP) in an asymptomatic population through reliable and accurate 3D-CT based assessment.