Understanding spinopelvic mechanics is important for the success of total hip arthroplasty (THA). Despite significant advancements in appreciating spinopelvic balance, numerous challenges remain. It is crucial to recognize the individual variability and postoperative changes in spinopelvic parameters and their consequential impact on prosthetic component positioning to mitigate the risk of dislocation and enhance postoperative outcomes. This review describes the integration of advanced diagnostic approaches, enhanced technology, implant considerations, and surgical planning, all tailored to the unique anatomy and biomechanics of each patient. It underscores the importance of accurately predicting postoperative spinopelvic mechanics, selecting suitable imaging techniques, establishing a consistent nomenclature for spinopelvic stiffness, and considering implant-specific strategies. Furthermore, it highlights the potential of artificial intelligence to personalize care.

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

Aims. Developmental cervical spinal stenosis (DcSS) is a well-known predisposing factor for degenerative cervical myelopathy (DCM) but there is a lack of consensus on its definition. This study aims to define DcSS based on MRI, and its multilevel characteristics, to assess the prevalence of DcSS in the general population, and to evaluate the presence of DcSS in the prediction of developing DCM. Methods. This cross-sectional study analyzed MRI spine morphological parameters at C3 to C7 (including anteroposterior (AP) diameter of spinal canal, spinal cord, and vertebral body) from DCM patients (n = 95) and individuals recruited from the general population (n = 2,019). Level-specific median AP spinal canal diameter from DCM patients was used to screen for stenotic levels in the population-based cohort. An individual with multilevel (≥ 3 vertebral levels) AP canal diameter smaller than the DCM median values was considered as having DcSS. The most optimal cut-off canal diameter per level for DcSS was determined by receiver operating characteristic analyses, and multivariable logistic regression was performed for the prediction of developing DCM that required surgery. Results. A total of 2,114 individuals aged 64.6 years (SD 11.9) who underwent surgery from March 2009 to December 2016 were studied. The most optimal cut-off canal diameters for DcSS are: C3 < 12.9 mm, C4 < 11.8 mm, C5 < 11.9 mm, C6 < 12.3 mm, and C7 < 13.3 mm. Overall, 13.0% (262 of 2,019) of the population-based cohort had multilevel DcSS. Multilevel DcSS (odds ratio (OR) 6.12 (95% CI 3.97 to 9.42); p < 0.001) and male sex (OR 4.06 (95% CI 2.55 to 6.45); p < 0.001) were predictors of developing DCM. Conclusion. This is the first MRI-based study for defining DcSS with multilevel canal narrowing. Level-specific cut-off canal diameters for DcSS can be used for early identification of individuals at risk of developing DCM. Individuals with DcSS at ≥ three levels and male sex are recommended for close monitoring or early intervention to avoid traumatic spinal cord injuries from stenosis. Cite this article: Bone Joint J 2024;106-B(11):1333–1341

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The objective of this study was to compare simulated range of motion (ROM) for reverse total shoulder arthroplasty (rTSA) with and without adjustment for scapulothoracic orientation in a global reference system. We hypothesized that values for simulated ROM in preoperative planning software with and without adjustment for scapulothoracic orientation would be significantly different.

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The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population.

Aims. Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. Methods. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures. Results. Out of 1,160 studies initially identified, 39 were included. Most studies (85%) were published between 2020 and 2024, with 82% using publicly available datasets, primarily the Osteoarthritis Initiative. ML methods were predominantly supervised, with significant variability in the definitions of OA progression: most studies focused on structural changes (59%), while fewer addressed pain progression or both. Deep learning was used in 44% of studies, while automated ML was used in 5%. There was a lack of standardization in evaluation metrics and limited external validation. Interpretability was explored in 54% of studies, primarily using SHapley Additive exPlanations. Conclusion. Our systematic review demonstrates the feasibility of ML models in predicting OA progression, but also uncovers critical limitations that currently restrict their clinical applicability. Future priorities should include diversifying data sources, standardizing outcome measures, enforcing rigorous validation, and integrating more sophisticated algorithms. This paradigm shift from predictive modelling to actionable clinical tools has the potential to transform patient care and disease management in orthopaedic practice. Cite this article: Bone Joint J 2024;106-B(11):1216–1222

Aims. The risk factors for recurrent instability (RI) following a primary traumatic anterior shoulder dislocation (PTASD) remain unclear. In this study, we aimed to determine the rate of RI in a large cohort of patients managed nonoperatively after PTASD and to develop a clinical prediction model. Methods. A total of 1,293 patients with PTASD managed nonoperatively were identified from a trauma database (mean age 23.3 years (15 to 35); 14.3% female). We assessed the prevalence of RI, and used multivariate regression modelling to evaluate which demographic- and injury-related factors were independently predictive for its occurrence. Results. The overall rate of RI at a mean follow-up of 34.4 months (SD 47.0) was 62.8% (n = 812), with 81.0% (n = 658) experiencing their first recurrence within two years of PTASD. The median time for recurrence was 9.8 months (IQR 3.9 to 19.4). Independent predictors increasing risk of RI included male sex (p < 0.001), younger age at PTASD (p < 0.001), participation in contact sport (p < 0.001), and the presence of a bony Bankart (BB) lesion (p = 0.028). Greater tuberosity fracture (GTF) was protective (p < 0.001). However, the discriminative ability of the resulting predictive model for two-year risk of RI was poor (area under the curve (AUC) 0.672). A subset analysis excluding identifiable radiological predictors of BB and GTF worsened the predictive ability (AUC 0.646). Conclusion. This study clarifies the prevalence and risk factors for RI following PTASD in a large, unselected patient cohort. Although these data permitted the development of a predictive tool for RI, its discriminative ability was poor. Predicting RI remains challenging, and as-yet-undetermined risk factors may be important in determining the risk. Cite this article: Bone Joint J 2024;106-B(10):1111–1117

Advanced 3D imaging and CT-based navigation have emerged as valuable tools to use in total knee arthroplasty (TKA), for both preoperative planning and the intraoperative execution of different philosophies of alignment. Preoperative planning using CT-based 3D imaging enables more accurate prediction of the size of components, enhancing surgical workflow and optimizing the precision of the positioning of components. Surgeons can assess alignment, osteophytes, and arthritic changes better. These scans provide improved insights into the patellofemoral joint and facilitate tibial sizing and the evaluation of implant-bone contact area in cementless TKA. Preoperative CT imaging is also required for the development of patient-specific instrumentation cutting guides, aiming to reduce intraoperative blood loss and improve the surgical technique in complex cases. Intraoperative CT-based navigation and haptic guidance facilitates precise execution of the preoperative plan, aiming for optimal positioning of the components and accurate alignment, as determined by the surgeon’s philosophy. It also helps reduce iatrogenic injury to the periarticular soft-tissue structures with subsequent reduction in the local and systemic inflammatory response, enhancing early outcomes. Despite the increased costs and radiation exposure associated with CT-based navigation, these many benefits have facilitated the adoption of imaged based robotic surgery into routine practice. Further research on ultra-low-dose CT scans and exploration of the possible translation of the use of 3D imaging into improved clinical outcomes are required to justify its broader implementation. Cite this article: Bone Joint J 2024;106-B(9):892–897

Aims. Bacterial infection activates neutrophils to release neutrophil extracellular traps (NETs) in bacterial biofilms of periprosthetic joint infections (PJIs). The aim of this study was to evaluate the increase in NET activation and release (NETosis) and haemostasis markers in the plasma of patients with PJI, to evaluate whether such plasma induces the activation of neutrophils, to ascertain whether increased NETosis is also mediated by reduced DNaseI activity, to explore novel therapeutic interventions for NETosis in PJI in vitro, and to evaluate the potential diagnostic use of these markers. Methods. We prospectively recruited 107 patients in the preoperative period of prosthetic surgery, 71 with a suspicion of PJI and 36 who underwent arthroplasty for non-septic indications as controls, and obtained citrated plasma. PJI was confirmed in 50 patients. We measured NET markers, inflammation markers, DNaseI activity, haemostatic markers, and the thrombin generation test (TGT). We analyzed the ability of plasma from confirmed PJI and controls to induce NETosis and to degrade in vitro-generated NETs, and explored the therapeutic restoration of the impairment to degrade NETs of PJI plasma with recombinant human DNaseI. Finally, we assessed the contribution of these markers to the diagnosis of PJI. Results. Patients with confirmed PJI had significantly increased levels of NET markers (cfDNA (p < 0.001), calprotectin (p < 0.001), and neutrophil elastase (p = 0.022)) and inflammation markers (IL-6; p < 0.001) in plasma. Moreover, the plasma of patients with PJI induced significantly more neutrophil activation than the plasma of the controls (p < 0.001) independently of tumour necrosis factor alpha. Patients with PJI also had a reduced DNaseI activity in plasma (p < 0.001), leading to a significantly impaired degradation of NETs (p < 0.001). This could be therapeutically restored with recombinant human DNaseI to the level in the controls. We developed a model to improve the diagnosis of PJI with cfDNA, calprotectin, and the start tail of TGT as predictors, though cfDNA alone achieved a good prediction and is simpler to measure. Conclusion. We confirmed that patients with PJI have an increased level of NETosis in plasma. Their plasma both induced NET release and had an impaired ability to degrade NETs mediated by a reduced DNaseI activity. This can be therapeutically restored in vitro with the approved Dornase alfa, Pulmozyme, which may allow novel methods of treatment. A combination of NETs and haemostatic biomarkers could improve the diagnosis of PJI, especially those patients in whom this diagnosis is uncertain. Cite this article: Bone Joint J 2024;106-B(9):1021–1030

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Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA.

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The COVID-19 pandemic has disrupted the provision of arthroplasty services in England, Wales, and Northern Ireland. This study aimed to quantify the backlog, analyze national trends, and predict time to recovery.

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There is a lack of high-quality research investigating outcomes of Ponseti-treated idiopathic clubfeet and correlation with relapse. This study assessed clinical and quality of life (QoL) outcomes using a standardized core outcome set (COS), comparing children with and without relapse.

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Cemented hemiarthroplasty is an effective form of treatment for most patients with an intracapsular fracture of the hip. However, it remains unclear whether there are subgroups of patients who may benefit from the alternative operation of a modern uncemented hemiarthroplasty – the aim of this study was to investigate this issue. Knowledge about the heterogeneity of treatment effects is important for surgeons in order to target operations towards specific subgroups who would benefit the most.

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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.

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To investigate the impact of consecutive perioperative care transitions on in-hospital recovery of patients who had primary total knee arthroplasty (TKA) over an 11-year period.

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The Birmingham Hip Resurfacing (BHR) was introduced in 1997 to address the needs of young active patients using a historically proven large-diameter metal-on-metal (MoM) bearing. A single designer surgeon’s consecutive series of 130 patients (144 hips) was previously reported at five and ten years, reporting three and ten failures, respectively. The aim of this study was to extend the follow-up of this original cohort at 25 years.

Aims. Surgical site infection (SSI) after soft-tissue sarcoma (STS) resection is a serious complication. The purpose of this retrospective study was to investigate the risk factors for SSI after STS resection, and to develop a nomogram that allows patient-specific risk assessment. Methods. A total of 547 patients with STS who underwent tumour resection between 2005 and 2021 were divided into a development cohort and a validation cohort. In the development cohort of 402 patients, the least absolute shrinkage and selection operator (LASSO) regression model was used to screen possible risk factors of SSI. To select risk factors and construct the prediction nomogram, multivariate logistic regression was used. The predictive power of the nomogram was evaluated by receiver operating curve (ROC) analysis in the validation cohort of 145 patients. Results. LASSO regression analysis selected possible risk factors for SSI, including age, diabetes, operating time, skin graft or flap, resected tumour size, smoking, and radiation therapy. Multivariate analysis revealed that age, diabetes, smoking during the previous year, operating time, and radiation therapy were independent risk factors for SSI. A nomogram was developed based on the results of multivariate logistic regression analysis. In the development cohort, the incidence of SSI was 4.5% in the low-risk group (risk score < 6.89) and 26.6% in the high-risk group (risk score ≥ 6.89; p < 0.001). In the validation cohort, the incidence of SSI was 2.0% in the low-risk group and 15.9% in the high-risk group (p = 0.004). Conclusion. Our nomogram will enable surgeons to assess the risk of SSI in patients with STS. In patients with high risk of SSI, frequent monitoring and aggressive interventions should be considered to prevent this. Cite this article: Bone Joint J 2024;106-B(5):492–500

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Frailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data.

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The study aimed to assess the clinical outcomes of arthroscopic debridement and partial excision in patients with traumatic central tears of the triangular fibrocartilage complex (TFCC), and to identify prognostic factors associated with unfavourable clinical outcomes.

Aims. Excessive posterior pelvic tilt (PT) may increase the risk of anterior instability after total hip arthroplasty (THA). The aim of this study was to investigate the changes in PT occurring from the preoperative supine to postoperative standing position following THA, and identify factors associated with significant changes in PT. Methods. Supine PT was measured on preoperative CT scans and standing PT was measured on preoperative and one-year postoperative standing lateral radiographs in 933 patients who underwent primary THA. Negative values indicate posterior PT. Patients with > 13° of posterior PT from preoperative supine to postoperative standing (ΔPT ≤ -13°) radiographs, which corresponds to approximately a 10° increase in functional anteversion of the acetabular component, were compared with patients with less change (ΔPT > -13°). Logistic regression analysis was used to assess preoperative demographic and spinopelvic parameters predictive of PT changes of ≤ -13°. The area under receiver operating characteristic curve (AUC) determined the diagnostic accuracy of the predictive factors. Results. PT changed from a mean of 3.8° (SD 6.0°)) preoperatively to -3.5° (SD 6.9°) postoperatively, a mean change of -7.4 (SD 4.5°; p < 0.001). A total of 95 patients (10.2%) had ≤ -13° change in PT from preoperative supine to postoperative standing. The strongest predictive preoperative factors of large changes in PT (≤ -13°) from preoperative supine to postoperative standing were a large posterior change in PT from supine to standing, increased supine PT, and decreased standing PT (p < 0.001). Flexed-seated PT (p = 0.006) and female sex (p = 0.045) were weaker significant predictive factors. When including all predictive factors, the accuracy of the AUC prediction was 84.9%, with 83.5% sensitivity and 71.2% specificity. Conclusion. A total of 10% of patients had > 13° of posterior PT postoperatively compared with their supine pelvic position, resulting in an increased functional anteversion of > 10°. The strongest predictive factors of changes in postoperative PT were the preoperative supine-to-standing differences, the anterior supine PT, and the posterior standing PT. Surgeons who introduce the acetabular component with the patient supine using an anterior approach should be aware of the potentially large increase in functional anteversion occurring in these patients. Cite this article: Bone Joint J 2024;106-B(3 Supple A):74–80