Aims. This study identifies early risk factors for symptomatic nonunion of displaced midshaft fractures of the clavicle that aid identification of an at risk group who may benefit from surgery. . Methods . We performed a retrospective study of 88 patients aged between 16 and 60 years that were managed non-operatively. . Results . The rate of symptomatic nonunion requiring surgery was 14% (n = 13). Smoking (odds ratio (OR) 40.76, 95% confidence intervals (CI) 1.38 to 120.30) and the six week Disabilities of the Arm Shoulder and Hand (DASH) score (OR 1.11, 95% CI 1.01 to 1.22, for each point increase) were independent predictors of nonunion. A six week DASH score of 35 or more was identified as a threshold value to predict nonunion using receiver operating characteristic curve analysis. Smoking and the threshold value in the DASH and were additive risk factors for nonunion, when neither were present the risk of nonunion was 2%, if one or the other were present the nonunion rate was between 17% to 20%, and if both were present the rate increased to 44%. Discussion. Patients with either of these risk factors, which include approximately half of all patients sustaining displaced midshaft fractures of the clavicle, are at an increased risk of developing a symptomatic non-union. Take home message: Smoking and failure of functional return at six weeks are significant predictors of nonunion of the midshaft of the clavicle. Such patients warrant further investigation as to whether they would benefit from early surgical fixation in order to avoid the morbidity of a nonunion. Cite this article: Bone Joint J 2016;98-B:125–30

Aims. The aim of this study was to assess the ability of morphological spinal parameters to predict the outcome of bracing in patients with adolescent idiopathic scoliosis (AIS) and to establish a novel supine correction index (SCI) for guiding bracing treatment. Methods. Patients with AIS to be treated by bracing were prospectively recruited between December 2016 and 2018, and were followed until brace removal. In all, 207 patients with a mean age at recruitment of 12.8 years (SD 1.2) were enrolled. Cobb angles, supine flexibility, and the rate of in-brace correction were measured and used to predict curve progression at the end of follow-up. The SCI was defined as the ratio between correction rate and flexibility. Receiver operating characteristic (ROC) curve analysis was carried out to assess the optimal thresholds for flexibility, correction rate, and SCI in predicting a higher risk of progression, defined by a change in Cobb angle of ≥ 5° or the need for surgery. Results. The baseline Cobb angles were similar (p = 0.374) in patients whose curves progressed (32.7° (SD 10.7)) and in those whose curves remained stable (31.4° (SD 6.1)). High supine flexibility (odds ratio (OR) 0.947 (95% CI 0.910 to 0.984); p = 0.006) and correction rate (OR 0.926 (95% CI 0.890 to 0.964); p < 0.001) predicted a lower incidence of progression after adjusting for Cobb angle, Risser sign, curve type, menarche status, distal radius and ulna grading, and brace compliance. ROC curve analysis identified a cut-off of 18.1% for flexibility (sensitivity 0.682, specificity 0.704) and a cut-off of 28.8% for correction rate (sensitivity 0.773, specificity 0.691) in predicting a lower risk of curve progression. A SCI of greater than 1.21 predicted a lower risk of progression (OR 0.4 (95% CI 0.251 to 0.955); sensitivity 0.583, specificity 0.591; p = 0.036). Conclusion. A higher supine flexibility (18.1%) and correction rate (28.8%), and a SCI of greater than 1.21 predicted a lower risk of progression. These novel parameters can be used as a guide to optimize the outcome of bracing. Cite this article: Bone Joint J 2022;104-B(4):495–503

Aims. We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Methods. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature. Results. We identified three PMOP-related subtypes and four core modules. The muscle system process, muscle contraction, and actin filament-based movement were more active in the hub genes. We obtained five feature genes related to PMOP. Our analysis verified that the gene signature had good predictive power and applicability. The outcomes of the GSE56815 cohort were found to be consistent with the results of the earlier studies. qRT-PCR results showed that RAB2A and FYCO1 were amplified in clinical samples. Conclusion. The PMOP-related gene signature we developed and verified can accurately predict the risk of PMOP in patients. These results can elucidate the molecular mechanism of RAB2A and FYCO1 underlying PMOP, and yield new and improved treatment strategies, ultimately helping PMOP monitoring. Cite this article: Bone Joint Res 2022;11(8):548–560

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. Methods. A prognostic cross-sectional cohort study was conducted involving patients from a single centre who underwent hip arthroscopy between January 2013 and April 2021. Radiological metrics measured on conventional radiographs and magnetic resonance arthrography were systematically assessed. The study analyzed the relationship between these metrics and complication rates, revision rates, and patient-reported outcomes. Results. Out of 810 identified hip arthroscopies, 359 hips were included in the study. Radiological risk factors associated with unsatisfactory outcomes after cam resection included a dysplastic posterior wall, Tönnis grade 2 or higher, and over-correction of the α angle. The presence of acetabular retroversion and dysplasia were also significant predictors for worse surgical outcomes. Notably, over-correction of both cam and pincer deformities resulted in poorer outcomes than under-correction. Conclusion. We recommend caution in performing hip arthroscopy in patients who have three positive acetabular retroversion signs. Acetabular dysplasia with a lateral centre-edge angle of less than 20° should not be treated with isolated hip arthroscopy. Acetabular rim-trimming should be avoided in patients with borderline dysplasia, and care should be taken to avoid over-correction of a cam deformity and/or pincer deformity. Cite this article: Bone Joint J 2024;106-B(8):775–782

Aims. The preoperative grading of chondrosarcomas of bone that accurately predicts surgical management is difficult for surgeons, radiologists, and pathologists. There are often discrepancies in grade between the initial biopsy and the final histology. Recent advances in the use of imaging methods have shown promise in the ability to predict the final grade. The most important clinical distinction is between grade 1 chondrosarcomas, which are amenable to curettage, and resection-grade chondrosarcomas (grade 2 and 3) which require en bloc resection. The aim of this study was to evaluate the use of a Radiological Aggressiveness Score (RAS) to predict the grade of primary chondrosarcomas in long bones and thus to guide management. Methods. A total of 113 patients with a primary chondrosarcoma of a long bone presenting between January 2001 and December 2021 were identified on retrospective review of a single oncology centre’s prospectively collected database. The nine-parameter RAS included variables from radiographs and MRI scans. The best cut-off of parameters to predict the final grade of chondrosarcoma after resection was determined using a receiver operating characteristic curve (ROC), and this was correlated with the biopsy grade. Results. A RAS of ≥ four parameters was 97.9% sensitive and 90.5% specific in predicting resection-grade chondrosarcoma based on a ROC cut-off derived using the Youden index. Cronbach’s α of 0.897 was derived as the interclass correlation for scoring the lesions by four blinded reviewers who were surgeons. Concordance between resection-grade lesions predicted from the RAS and ROC cut-off with the final grade after resection was 96.46%. Concordance between the biopsy grade and the final grade was 63.8%. However, when the patients were analyzed based on surgical management, the initial biopsy was able to differentiate low-grade from resection-grade chondrosarcomas in 82.9% of biopsies. Conclusion. These findings suggest that the RAS is an accurate method for guiding the surgical management of patients with these tumours, particularly when the initial biopsy results are discordant with the clinical presentation. Cite this article: Bone Joint J 2023;105-B(7):808–814

Aim. Recurrence of bone and joint infection, despite appropriate therapy, is well recognised and stimulates ongoing interest in identifying host factors that predict infection recurrence. Clinical prediction models exist for those treated with DAIR, but to date no models with a low risk of bias predict orthopaedic infection recurrence for people with surgically excised infection and removed metalwork. The aims of this study were to construct and internally validate a risk prediction model for infection recurrence at 12 months, and to identify factors that predict recurrence. Predictive factors must be easy to check in pre-operative assessment and relevant across patient groups. Methods. Four prospectively collected datasets including 1173 participants treated in European centres between 2003 and 2021, followed up to 12 months after surgery for orthopaedic infections, were included in logistic regression modelling [1–3]. The definition of infection recurrence was identical and ascertained separately from baseline factors in three contributing cohorts. Eight predictive factors were investigated following a priori sample size calculation: age, gender, BMI, ASA score, the number of prior operations, immunosuppressive medication, glycosylated haemoglobin (HbA1c), and smoking. Missing data, including systematically missing predictors, were imputed using Multiple Imputation by Chained Equations. Weekly alcohol intake was not included in modelling due to low inter-observer reliability (mean reported intake 12 units per week, 95% CI for mean inter-rater error −16.0 to +15.4 units per week). Results. Participants were 64% male, with a median age of 60 years (range 18–95). 86% of participants had lower limb orthopaedic infections. 732 participants were treated for osteomyelitis, including FRI, and 432 for PJI. 16% of participants experienced treatment failure by 12 months. The full prediction model had moderate apparent discrimination: AUROC (C statistic) 0.67, Brier score 0.13, and reasonable apparent calibration. Of the predictors of interest, associations with failure were seen with prior operations at the same anatomical site (odds ratio for failure 1.51 for each additional prior surgery; 95% CI 1.02 to 2.22, p=0.06), and the current use of immunosuppressive medications (odds ratio for failure 2.94; 95% CI 0.89 to 9.77, p=0.08). Conclusions. This association between number of prior surgeries and treatment failure supports the urgent need to streamline referral pathways for people with orthopaedic infection to specialist multidisciplinary units

Acute Haematogenous Osteomyelitis (AHO) remains a cause of severe illness among children. Contemporary research aims to identify predictors of acute and chronic complications. Trends in C-reactive protein (CRP) following treatment initiation may predict disease course. We have sought to identify factors associated with acute and chronic complications in the New Zealand population. A retrospective review of all patients <16 years with presumed AHO presenting to a tertiary referral centre between 2008–2018 was performed. Multivariate was analysis used to identify factors associated with an acute or chronic complication. An “acute” complication was defined as need for two or more surgical procedures, hospital stay longer than 14-days, or recurrence despite IV antibiotics. A “chronic” complication was defined as growth or limb length discrepancy, avascular necrosis, chronic osteomyelitis, pathological fracture, frozen joint or dislocation. 151 cases met inclusion criteria. The median age was 8 years (69.5% male). Within this cohort, 53 (34%) experienced an acute complication and 18 (12%) a chronic complication. Regression analysis showed that contiguous disease, delayed presentation, and failure to reduce CRP by 50% at day 4/5 predicted an acutely complicated disease course. Chronic complication was predicted by need for surgical management and failed CRP reduction by 50% at day 4/5. We conclude that CRP trends over 96 hours following commencement of treatment differentiate patients with AHO likely to experience severe disease

Aims. The aim of this study was to evaluate the reliability and validity of a patient-specific algorithm which we developed for predicting changes in sagittal pelvic tilt after total hip arthroplasty (THA). Methods. This retrospective study included 143 patients who underwent 171 THAs between April 2019 and October 2020 and had full-body lateral radiographs preoperatively and at one year postoperatively. We measured the pelvic incidence (PI), the sagittal vertical axis (SVA), pelvic tilt, sacral slope (SS), lumbar lordosis (LL), and thoracic kyphosis to classify patients into types A, B1, B2, B3, and C. The change of pelvic tilt was predicted according to the normal range of SVA (0 mm to 50 mm) for types A, B1, B2, and B3, and based on the absolute value of one-third of the PI-LL mismatch for type C patients. The reliability of the classification of the patients and the prediction of the change of pelvic tilt were assessed using kappa values and intraclass correlation coefficients (ICCs), respectively. Validity was assessed using the overall mean error and mean absolute error (MAE) for the prediction of the change of pelvic tilt. Results. The kappa values were 0.927 (95% confidence interval (CI) 0.861 to 0.992) and 0.945 (95% CI 0.903 to 0.988) for the inter- and intraobserver reliabilities, respectively, and the ICCs ranged from 0.919 to 0.997. The overall mean error and MAE for the prediction of the change of pelvic tilt were -0.3° (SD 3.6°) and 2.8° (SD 2.4°), respectively. The overall absolute change of pelvic tilt was 5.0° (SD 4.1°). Pre- and postoperative values and changes in pelvic tilt, SVA, SS, and LL varied significantly among the five types of patient. Conclusion. We found that the proposed algorithm was reliable and valid for predicting the standing pelvic tilt after THA. Cite this article: Bone Joint J 2024;106-B(1):19–27

Aims. The aim of this study was to investigate the association between fracture displacement and survivorship of the native hip joint without conversion to a total hip arthroplasty (THA), and to determine predictors for conversion to THA in patients treated nonoperatively for acetabular fractures. Methods. A multicentre cross-sectional study was performed in 170 patients who were treated nonoperatively for an acetabular fracture in three level 1 trauma centres. Using the post-injury diagnostic CT scan, the maximum gap and step-off values in the weightbearing dome were digitally measured by two trauma surgeons. Native hip survival was reported using Kaplan-Meier curves. Predictors for conversion to THA were determined using Cox regression analysis. Results. Of 170 patients, 22 (13%) subsequently received a THA. Native hip survival in patients with a step-off ≤ 2 mm, > 2 to 4 mm, or > 4 mm differed at five-year follow-up (respectively: 94% vs 70% vs 74%). Native hip survival in patients with a gap ≤ 2 mm, > 2 to 4 mm, or > 4 mm differed at five-year follow-up (respectively: 100% vs 84% vs 78%). Step-off displacement > 2 mm (> 2 to 4 mm hazard ratio (HR) 4.9, > 4 mm HR 5.6) and age > 60 years (HR 2.9) were independent predictors for conversion to THA at follow-up. Conclusion. Patients with minimally displaced acetabular fractures who opt for nonoperative fracture treatment may be informed that fracture displacement (e.g. gap and step-off) up to 2 mm, as measured on CT images, results in limited risk on conversion to THA. Step-off ≥ 2 mm and age > 60 years are predictors for conversion to THA and can be helpful in the shared decision-making process. Cite this article: Bone Joint J 2023;105-B(9):1020–1029

External validation of machine learning predictive models is achieved through evaluation of model performance on different groups of patients than were used for algorithm development. This important step is uncommonly performed, inhibiting clinical translation of newly developed models. Recently, machine learning was used to develop a tool that can quantify revision risk for a patient undergoing primary anterior cruciate ligament (ACL) reconstruction (https://swastvedt.shinyapps.io/calculator_rev/). The source of data included nearly 25,000 patients with primary ACL reconstruction recorded in the Norwegian Knee Ligament Register (NKLR). The result was a well-calibrated tool capable of predicting revision risk one, two, and five years after primary ACL reconstruction with moderate accuracy. The purpose of this study was to determine the external validity of the NKLR model by assessing algorithm performance when applied to patients from the Danish Knee Ligament Registry (DKLR). The primary outcome measure of the NKLR model was probability of revision ACL reconstruction within 1, 2, and/or 5 years. For the index study, 24 total predictor variables in the NKLR were included and the models eliminated variables which did not significantly improve prediction ability - without sacrificing accuracy. The result was a well calibrated algorithm developed using the Cox Lasso model that only required five variables (out of the original 24) for outcome prediction. For this external validation study, all DKLR patients with complete data for the five variables required for NKLR prediction were included. The five variables were: graft choice, femur fixation device, Knee Injury and Osteoarthritis Outcome Score (KOOS) Quality of Life subscale score at surgery, years from injury to surgery, and age at surgery. Predicted revision probabilities were calculated for all DKLR patients. The model performance was assessed using the same metrics as the NKLR study: concordance and calibration. In total, 10,922 DKLR patients were included for analysis. Average follow-up time or time-to-revision was 8.4 (±4.3) years and overall revision rate was 6.9%. Surgical technique trends (i.e., graft choice and fixation devices) and injury characteristics (i.e., concomitant meniscus and cartilage pathology) were dissimilar between registries. The model produced similar concordance when applied to the DKLR population compared to the original NKLR test data (DKLR: 0.68; NKLR: 0.68-0.69). Calibration was poorer for the DKLR population at one and five years post primary surgery but similar to the NKLR at two years. The NKLR machine learning algorithm demonstrated similar performance when applied to patients from the DKLR, suggesting that it is valid for application outside of the initial patient population. This represents the first machine learning model for predicting revision ACL reconstruction that has been externally validated. Clinicians can use this in-clinic calculator to estimate revision risk at a patient specific level when discussing outcome expectations pre-operatively. While encouraging, it should be noted that the performance of the model on patients undergoing ACL reconstruction outside of Scandinavia remains unknown

Osteosynthesis aims to maintain fracture reduction until bone healing occurs, which is not achieved in case of mechanical fixation failure. One form of failure is plastic plate bending due to overloading, occurring in up to 17% of midshaft fracture cases and often necessitating reoperation. This study aimed to replicate in-vivo conditions in a cadaveric experiment and to validate a finite element (FE) simulation to predict plastic plate bending. Six cadaveric bones were used to replicate an established ovine tibial osteotomy model with locking plates in-vitro with two implant materials (titanium, steel) and three fracture gap sizes (30, 60, 80 mm). The constructs were tested monotonically until plastic plate deformation under axial compression. Specimen-specific FE models were created from CT images. Implant material properties were determined using uniaxial tensile testing of dog bone shaped samples. The experimental tests were replicated in the simulations. Stiffness, yield, and maximum loads were compared between the experiment and FE models. Implant material properties (Young's modulus and yield stress) for steel and titanium were 184 GPa and 875 MPa, and 105 GPa and 761 MPa, respectively. Yield and maximum loads of constructs ranged between 469–491 N and 652–683 N, and 759–995 N and 1252–1600 N for steel and titanium fixations, respectively. FE models accurately and quantitatively correctly predicted experimental results for stiffness (R2=0.96), yield (R2=0.97), and ultimate load (R2=0.97). FE simulations accurately predicted plastic plate bending in osteosynthesis constructs. Construct behavior was predominantly driven by the implant itself, highlighting the importance of modelling correct material properties of metal. The validated FE models could predict subject-specific load bearing capacity of osteosyntheses in vivo in preclinical or clinical studies. Acknowledgements: This study was supported by the AO Foundation via the AOTRAUMA Network (Grant No.: AR2021_03)

Several studies have reported the rate of post-operative mortality after the surgical treatment of a fracture of the hip, but few data are available regarding the delayed morbidity. In this prospective study, we identified 568 patients who underwent surgery for a fracture of the hip and who were followed for one year. Multivariate analysis was carried out to identify possible predictors of mortality and morbidity. The 30-day, four-month and one-year rates of mortality were 4.3%, 11.4%, and 18.8%, respectively. General complications and pre-operative comorbidities represented the basic predictors of mortality at any time interval (p < 0.01). In-hospital, four-month and one-year general complications occurred in 29.4%, 18.6% and 6.7% of patients, respectively. After adjusting for confounding variables, comorbidities and poor cognitive status determined the likelihood of early and delayed general complications, respectively (p < 0.001). Operative delay was the main predictor of the length of hospital stay (p < 0.001) and was directly related to in-hospital (p = 0.017) and four-month complications (p = 0.008). Cite this article: Bone Joint J 2015;97-B:383–90

Aims. Transfusion after primary total hip arthroplasty (THA) has become rare, and identification of causative factors allows preventive measures. The aim of this study was to determine patient-specific factors that increase the risk of needing a blood transfusion. Methods. All patients who underwent elective THA were analyzed retrospectively in this single-centre study from 2020 to 2021. A total of 2,892 patients were included. Transfusion-related parameters were evaluated. A multiple logistic regression was performed to determine whether age, BMI, American Society of Anesthesiologists (ASA) grade, sex, or preoperative haemoglobin (Hb) could predict the need for transfusion within the examined patient population. Results. The overall transfusion rate was 1.2%. Compared to the group of patients without blood transfusion, the transfused group was on average older (aged 73.8 years (SD 9.7) vs 68.6 years (SD 10.1); p = 0.020) and was mostly female (p = 0.003), but showed no significant differences in terms of BMI (28.3 kg/m. 2. (SD 5.9) vs 28.7 kg/m. 2. (SD 5.2); p = 0.720) or ASA grade (2.2 (SD 0.5) vs 2.1 (SD 0.4); p = 0.378). The regression model identified a cutoff Hb level of < 7.6 mmol/l (< 12.2 g/dl), aged > 73 years, and a BMI of 35.4 kg/m² or higher as the three most reliable predictors associated with postoperative transfusion in THA. Conclusion. The possibility of transfusion is predictable based on preoperatively available parameters. The proposed thresholds for preoperative Hb level, age, and BMI can help identify patients and take preventive measures if necessary. Cite this article: Bone Jt Open 2024;5(7):560–564

Aims. The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA). Methods. A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models. Results. There were significant correlations between the OKS and EQ-5D-3L preoperatively (r = 0.68; p < 0.001) and postoperatively (r = 0.77; p < 0.001) and for the change in the scores (r = 0.61; p < 0.001). Three different models (preoperative, postoperative, and change) were created. There were no significant differences between the actual and predicted mean EQ-5D-3L utilities at any timepoint or for change in the scores (p > 0.090) in the validation cohort. There was a significant correlation between the actual and predicted EQ-5D-3L utilities preoperatively (r = 0.63; p < 0.001) and postoperatively (r = 0.77; p < 0.001) and for the change in the scores (r = 0.56; p < 0.001). Bland-Altman plots demonstrated that a lower utility was overestimated, and higher utility was underestimated. The individual predicted EQ-5D-3L that was within ± 0.05 and ± 0.010 (minimal clinically important difference (MCID)) of the actual EQ-5D-3L varied between 13% to 35% and 26% to 64%, respectively, according to timepoint assessed and change in the scores, but was not significantly different between the modelling and validation cohorts (p ≥ 0.148). Conclusion. The OKS can be used to estimate EQ-5D-3L. Predicted individual patient utility error beyond the MCID varied from one-third to two-thirds depending on timepoint assessed, but the mean for a cohort did not differ and could be employed for this purpose. Cite this article: Bone Jt Open 2022;3(7):573–581

Single level discectomy (SLD) is one of the most commonly performed spinal surgery procedures. Two key drivers of their cost-of-care are duration of surgery (DOS) and postoperative length of stay (LOS). Therefore, the ability to preoperatively predict SLD DOS and LOS has substantial implications for both hospital and healthcare system finances, scheduling and resource allocation. As such, the goal of this study was to predict DOS and LOS for SLD using machine learning models (MLMs) constructed on preoperative factors using a large North American database. The American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for SLD procedures from 2014-2019. The dataset was split in a 60/20/20 ratio of training/validation/testing based on year. Various MLMs (traditional regression models, tree-based models, and multilayer perceptron neural networks) were used and evaluated according to 1) mean squared error (MSE), 2) buffer accuracy (the number of times the predicted target was within a predesignated buffer), and 3) classification accuracy (the number of times the correct class was predicted by the models). To ensure real world applicability, the results of the models were compared to a mean regressor model. A total of 11,525 patients were included in this study. During validation, the neural network model (NNM) had the best MSEs for DOS (0.99) and LOS (0.67). During testing, the NNM had the best MSEs for DOS (0.89) and LOS (0.65). The NNM yielded the best 30-minute buffer accuracy for DOS (70.9%) and ≤120 min, >120 min classification accuracy (86.8%). The NNM had the best 1-day buffer accuracy for LOS (84.5%) and ≤2 days, >2 days classification accuracy (94.6%). All models were more accurate than the mean regressors for both DOS and LOS predictions. We successfully demonstrated that MLMs can be used to accurately predict the DOS and LOS of SLD based on preoperative factors. This big-data application has significant practical implications with respect to surgical scheduling and inpatient bedflow, as well as major implications for both private and publicly funded healthcare systems. Incorporating this artificial intelligence technique in real-time hospital operations would be enhanced by including institution-specific operational factors such as surgical team and operating room workflow

Aims. The aim of this study was to review the current evidence surrounding curve type and morphology on curve progression risk in adolescent idiopathic scoliosis (AIS). Methods. A comprehensive search was conducted by two independent reviewers on PubMed, Embase, Medline, and Web of Science to obtain all published information on morphological predictors of AIS progression. Search items included ‘adolescent idiopathic scoliosis’, ‘progression’, and ‘imaging’. The inclusion and exclusion criteria were carefully defined. Risk of bias of studies was assessed with the Quality in Prognostic Studies tool, and level of evidence for each predictor was rated with the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. In all, 6,286 publications were identified with 3,598 being subjected to secondary scrutiny. Ultimately, 26 publications (25 datasets) were included in this review. Results. For unbraced patients, high and moderate evidence was found for Cobb angle and curve type as predictors, respectively. Initial Cobb angle > 25° and thoracic curves were predictive of curve progression. For braced patients, flexibility < 28% and limited in-brace correction were factors predictive of progression with high and moderate evidence, respectively. Thoracic curves, high apical vertebral rotation, large rib vertebra angle difference, small rib vertebra angle on the convex side, and low pelvic tilt had weak evidence as predictors of curve progression. Conclusion. For curve progression, strong and consistent evidence is found for Cobb angle, curve type, flexibility, and correction rate. Cobb angle > 25° and flexibility < 28% are found to be important thresholds to guide clinical prognostication. Despite the low evidence, apical vertebral rotation, rib morphology, and pelvic tilt may be promising factors. Cite this article: Bone Joint J 2022;104-B(4):424–432

Excessive resident duty hours (RDH) are a recognized issue with implications for physician well-being and patient safety. A major component of the RDH concern is on-call duty. While considerable work has been done to reduce resident call workload, there is a paucity of research in optimizing resident call scheduling. Call coverage is scheduled manually rather than demand-based, which generally leads to over-scheduling to prevent a service gap. Machine learning (ML) has been widely applied in other industries to prevent such issues of a supply-demand mismatch. However, the healthcare field has been slow to adopt these innovations. As such, the aim of this study was to use ML models to 1) predict demand on orthopaedic surgery residents at a level I trauma centre and 2) identify variables key to demand prediction. Daily surgical handover emails over an eight year (2012-2019) period at a level I trauma centre were collected. The following data was used to calculate demand: spine call coverage, date, and number of operating rooms (ORs), traumas, admissions and consults completed. Various ML models (linear, tree-based and neural networks) were trained to predict the workload, with their results compared to the current scheduling approach. Quality of models was determined by using the area under the receiver operator curve (AUC) and accuracy of the predictions. The top ten most important variables were extracted from the most successful model. During training, the model with the highest AUC and accuracy was the multivariate adaptive regression splines (MARS) model, with an AUC of 0.78±0.03 and accuracy of 71.7%±3.1%. During testing, the model with the highest AUC and accuracy was the neural network model, with an AUC of 0.81 and accuracy of 73.7%. All models were better than the current approach, which had an AUC of 0.50 and accuracy of 50.1%. Key variables used by the neural network model were (descending order): spine call duty, year, weekday/weekend, month, and day of the week. This was the first study attempting to use ML to predict the service demand on orthopaedic surgery residents at a major level I trauma centre. Multiple ML models were shown to be more appropriate and accurate at predicting the demand on surgical residents as compared to the current scheduling approach. Future work should look to incorporate predictive models with optimization strategies to match scheduling with demand in order to improve resident well being and patient care

Traditional staging systems for high grade osteosarcoma (Enneking, MSTS) are based largely on gross surgical margins and were developed before the widespread use of neoadjuvant chemotherapy. It is now well known that both microscopic margins and chemotherapy are predictors of local recurrence. However, neither of these variables are used in the traditional surgical staging and the precise safe margin distance is debated. Recently, a novel staging system utilizing a 2mm margin cutoff and incorporating precent necrosis was proposed and demonstrated improved prognostic value for local recurrence free survival (LRFS) when compared to the MSTS staging system. This staging system has not been validated beyond the original patient cohort. We propose to analyze this staging system in a cohort of patients with high-grade osteosarcoma, as well as evaluate the ability of additional variables to predict the risk of local recurrence and overall survival. A retrospective review of a prospectively collected database of all sarcoma patients between 1985 and 2020 at a tertiary sarcoma care center was performed. All patients with high-grade osteosarcoma receiving neo-adjuvant chemotherapy and with no evidence of metastatic disease on presentation were isolated and analyzed. A minimum of two year follow up was used for surviving patients. A total of 225 patients were identified meeting these criteria. Univariate analysis was performed to evaluate variable that were associated with LRFS. Multivariate analysis is used to further analyze factors associated with LRFS on univariate analysis. There were 20 patients (8.9%) who had locally recurrent disease. Five-year LRFS was significantly different for patients with surgical margins 2mm or less (77.6% v. 93.3%; p=0.006) and those with a central tumor location (67.9 v. 94.4; <0.001). A four-tiered staging system using 2mm surgical margins and a percent necrosis of 90% of greater was also a significant predictor of 5-year LRFS (p=0.019) in this cohort. Notably, percent necrosis in isolation was not a predictor of LRFS in this cohort (p=0.875). Tumor size, gender, and type of surgery (amputation v. limb salvage) were also analyzed and not associated with LRFS. The MSTS surgical margin staging system did not significantly stratify groups (0.066). A 2mm surgical margin cutoff was predictive of 5-year LRFS in this cohort of patients with localized high-grade osteosarcoma and a combination of a 2mm margin and percent necrosis outperformed the prognostic value of the traditional MSTS staging system. Utilization of this system may improve the ability of surgeons to stage thier patients. Additional variables may increase the value of this system and further validation is required

Distal radius fractures (DRFs) are common injuries that represent 17% of all adult upper extremity fractures. Some fractures deemed appropriate for nonsurgical management following closed reduction and casting exhibit delayed secondary displacement (greater than two weeks from injury) and require late surgical intervention. This can lead to delayed rehabilitation and functional outcomes. This study aimed to determine which demographic and radiographic features can be used to predict delayed fracture displacement. This is a multicentre retrospective case-control study using radiographs extracted from our Analytics Data Integration, Measurement and Reporting (DIMR) database, using diagnostic and therapeutic codes. Skeletally mature patients aged 18 years of age or older with an isolated DRF treated with surgical intervention between two and four weeks from initial injury, with two or more follow-up visits prior to surgical intervention, were included. Exclusion criteria were patients with multiple injuries, surgical treatment with fewer than two clinical assessments prior to surgical treatment, or surgical treatment within two weeks of injury. The proportion of patients with delayed fracture displacement requiring surgical treatment will be reported as a percentage of all identified DRFs within the study period. A multivariable conditional logistic regression analysis was used to assess case-control comparisons, in order to determine the parameters that are mostly likely to predict delayed fracture displacement leading to surgical management. Intra- and inter-rater reliability for each radiographic parameter will also be calculated. A total of 84 age- and sex-matched pairs were identified (n=168) over a 5-year period, with 87% being female and a mean age of 48.9 (SD=14.5) years. Variables assessed in the model included pre-reduction and post-reduction radial height, radial inclination, radial tilt, volar cortical displacement, injury classification, intra-articular step or gap, ulnar variance, radiocarpal alignment, and cast index, as well as the difference between pre- and post-reduction parameters. Decreased pre-reduction radial inclination (Odds Ratio [OR] = 0.54; Confidence Interval [CI] = 0.43 – 0.64) and increased pre-reduction volar cortical displacement (OR = 1.31; CI = 1.10 – 1.60) were significant predictors of delayed fracture displacement beyond a minimum of 2-week follow-up. Similarly, an increased difference between pre-reduction and immediate post reduction radial height (OR = 1.67; CI = 1.31 – 2.18) and ulnar variance (OR = 1.48; CI = 1.24 – 1.81) were also significant predictors of delayed fracture displacement. Cast immobilization is not without risks and delayed surgical treatment can result in a prolong recovery. Therefore, if reliable and reproducible radiographic parameters can be identified that predict delayed fracture displacement, this information will aid in earlier identification of patients with DRFs at risk of late displacement. This could lead to earlier, appropriate surgical management, rehabilitation, and return to work and function

Aims. Periprosthetic fractures (PPFs) around the knee are challenging injuries. This study aims to describe the characteristics of knee PPFs and the impact of patient demographics, fracture types, and management modalities on in-hospital mortality. Methods. Using a multicentre study design, independent of registry data, we included adult patients sustaining a PPF around a knee arthroplasty between 1 January 2010 and 31 December 2019. Univariate, then multivariable, logistic regression analyses were performed to study the impact of patient, fracture, and treatment on mortality. Results. Out of a total of 1,667 patients in the PPF study database, 420 patients were included. The in-hospital mortality rate was 6.4%. Multivariable analyses suggested that American Society of Anesthesiologists (ASA) grade, history of peripheral vascular disease (PVD), history of rheumatic disease, fracture around a loose implant, and cerebrovascular accident (CVA) during hospital stay were each independently associated with mortality. Each point increase in ASA grade independently correlated with a four-fold greater mortality risk (odds ratio (OR) 4.1 (95% confidence interval (CI) 1.19 to 14.06); p = 0.026). Patients with PVD have a nine-fold increase in mortality risk (OR 9.1 (95% CI 1.25 to 66.47); p = 0.030) and patients with rheumatic disease have a 6.8-fold increase in mortality risk (OR 6.8 (95% CI 1.32 to 34.68); p = 0.022). Patients with a fracture around a loose implant (Unified Classification System (UCS) B2) have a 20-fold increase in mortality, compared to UCS A1 (OR 20.9 (95% CI 1.61 to 271.38); p = 0.020). Mode of management was not a significant predictor of mortality. Patients managed with revision arthroplasty had a significantly longer length of stay (median 16 days; p = 0.029) and higher rates of return to theatre, compared to patients treated nonoperatively or with fixation. Conclusion. The mortality rate in PPFs around the knee is similar to that for native distal femur and neck of femur fragility fractures. Patients with certain modifiable risk factors should be optimized. A national PPF database and standardized management guidelines are currently required to understand these complex injuries and to improve patient outcomes. Cite this article: Bone Joint J 2024;106-B(2):158–165

Short cementless femoral stems are increasingly popular as they allow for less dissection for insertion. Use of such stems with the anterior approach (AA) may be associated with considerable per-operative fracture risk. This study's primary aim was to evaluate whether patient-specific femoral- and pelvic- morphology and surgical technique, influence per-operative fracture risk. In doing so, we aimed to describe important anatomical thresholds alerting surgeons. This is a single-center, multi-surgeon retrospective, case-control matched study. Of 1145 primary THAs with a short, cementless stem inserted via the AA, 39 periprosthetic fractures (3.4%) were identified. These were matched for factors known to increase fracture risk (age, gender, BMI, side, Dorr classification, stem offset and indication for surgery) with 78 THAs that did not sustain a fracture. Radiographic analysis was performed using validated software to measure femoral- (canal flare index [CFI], morphological cortical index [MCI], calcar-calcar ratio [CCR]) and pelvic- (Ilium-ischial ratio [IIR], ilium overhang, and ASIS to greater trochanter distance) morphologies and surgical technique (% canal fill). Multivariate and Receiver-Operator Curve (ROC) analysis was performed to identify predictors of fracture. Femoral factors that differed included CFI (3.7±0.6 vs 2.9±0.4, p3.17 and II ratio>3 (OR:29.2 95%CI: 9.5–89.9, p<0.001). Patient-specific anatomical parameters are important predictors of fracture-risk. When considering the use of short stems via the AA, careful radiographic analysis would help identify those at risk in order to consider alternative stem options

Identification of patients at risk of not achieving minimally clinically important differences (MCID) in patient reported outcome measures (PROMs) is important to ensure principled and informed pre-operative decision making. Machine learning techniques may enable the generation of a predictive model for attainment of MCID in hip arthroscopy. Aims: 1) to determine whether machine learning techniques could predict which patients will achieve MCID in the iHOT-12 PROM 6 months after arthroscopic management of femoroacetabular impingement (FAI), 2) to determine which factors contribute to their predictive power. Data from the UK Non-Arthroplasty Hip Registry database was utilised. We identified 1917 patients who had undergone hip arthroscopy for FAI with both baseline and 6 month follow up iHOT-12 and baseline EQ-5D scores. We trained three established machine learning algorithms on our dataset to predict an outcome of iHOT-12 MCID improvement at 6 months given baseline characteristics including demographic factors, disease characteristics and PROMs. Performance was assessed using area under the receiver operating characteristic (AUROC) statistics with 5-fold cross validation. The three machine learning algorithms showed quite different performance. The linear logistic regression model achieved AUROC = 0.59, the deep neural network achieved AUROC = 0.82, while a random forest model had the best predictive performance with AUROC 0.87. Of demographic factors, we found that BMI and age were key predictors for this model. We also found that removing all features except baseline responses to the iHOT-12 questionnaire had little effect on performance for the random forest model (AUROC = 0.85). Disease characteristics had little effect on model performance. Machine learning models are able to predict with good accuracy 6-month post-operative MCID attainment in patients undergoing arthroscopic management for FAI. Baseline scores from the iHOT-12 questionnaire are sufficient to predict with good accuracy whether a patient is likely to reach MCID in post-operative PROMs

Approximately 20% of patients feel unsatisfied 12 months after primary total knee arthroplasty (TKA). Current predictive tools for TKA focus on the clinician as the intended user rather than the patient. The aim of this study is to develop a tool that can be used by patients without clinician assistance, to predict health-related quality of life (HRQoL) outcomes 12 months after total knee arthroplasty (TKA). All patients with primary TKAs for osteoarthritis between 2012 and 2019 at a tertiary institutional registry were analysed. The predictive outcome was improvement in Veterans-RAND 12 utility score at 12 months after surgery. Potential predictors included patient demographics, co-morbidities, and patient reported outcome scores at baseline. Logistic regression and three machine learning algorithms were used. Models were evaluated using both discrimination and calibration metrics. Predictive outcomes were categorised into deciles from 1 being the least likely to improve to 10 being the most likely to improve. 3703 eligible patients were included in the analysis. The logistic regression model performed the best in out-of-sample evaluation for both discrimination (AUC = 0.712) and calibration (gradient = 1.176, intercept = -0.116, Brier score = 0.201) metrics. Machine learning algorithms were not superior to logistic regression in any performance metric. Patients in the lowest decile (1) had a 29% probability for improvement and patients in the highest decile (10) had an 86% probability for improvement. Logistic regression outperformed machine learning algorithms in this study. The final model performed well enough with calibration metrics to accurately predict improvement after TKA using deciles. An ongoing randomised controlled trial (ACTRN12622000072718) is evaluating the effect of this tool on patient willingness for surgery. Full results of this trial are expected to be available by April 2023. A free-to-use online version of the tool is available at . smartchoice.org.au.

Short cementless femoral stems are increasingly popular as they allow for less dissection for insertion. Use of such stems with the anterior approach (AA) may be associated with considerable per-operative fracture risk. This study's primary aim was to evaluate whether patient-specific femoral- and pelvic- morphology and surgical technique, influence per-operative fracture risk. In doing so, we aimed to describe important anatomical thresholds alerting surgeons. This is a single-centre, multi-surgeon retrospective, case-control matched study. Of 1145 primary THAs with a short, cementless stem inserted via the AA, 39 periprosthetic fractures (3.4%) were identified. These were matched for factors known to increase fracture risk (age, gender, BMI, side, Dorr classification, stem offset and indication for surgery) with 78 THAs that did not sustain a fracture. Radiographic analysis was performed using validated software to measure femoral- (canal flare index [CFI], morphological cortical index [MCI], calcar-calcar ratio [CCR]) and pelvic- (Ilium-ischial ratio [IIR], ilium overhang, and ASIS to greater trochanter distance) morphologies and surgical technique (% canal fill). Multivariate and Receiver-Operator Curve (ROC) analysis was performed to identify predictors of fracture. Femoral factors that differed included CFI (3.7±0.6 vs 2.9±0.4, p<0.001) and CCR (0.5±0.1 vs 0.4±0.1, p=0.006). The mean IIR was higher in fracture cases (3.3±0.6 vs 3.0±0.5, p<0.001). % Canal fill was reduced in fracture cases (82.8±7.6 vs 86.7±6.8, p=0.007). Multivariate analysis and ROC analyses revealed a threshold CFI of 3.17 was predictive of fracture (sensitivity:84.6% / specificity:75.6%). Fracture risk was 29 times higher when patients had CFI>3.17 and II ratio>3 (OR:29.2 95%CI: 9.5–89.9, p<0.001). Patient-specific anatomical parameters are important predictors of fracture-risk. When considering the use of short stems via the AA, careful radiographic analysis would help identify those at risk in order to consider alternative stem options

Intraoperative range of motion (ROM) radiographs are routinely taken during scaphoidectomy and four corner fusion surgery (S4CF) at our institution. It is not known if intraoperative ROM predicts postoperative ROM. We hypothesize that patients with a greater intra-operativeROM would have an improved postoperative ROM at one year, but that this arc would be less than that achieved intra- operatively. We retrospectively reviewed 56 patients that had undergone S4CF at our institution in the past 10 years. Patients less than 18, those who underwent the procedure for reasons other than arthritis, those less than one year from surgery, and those that had since undergone wrist arthrodesis were excluded. Intraoperative ROM was measured from fluoroscopic images taken in flexion and extension at the time of surgery. Patients that met criteria were then invited to take part in a virtual assessment and their ROM was measured using a goniometer. T-tests were used to measure differences between intraoperative and postoperative ROM, Pearson Correlation was used to measure associations, and linear regression was conducted to assess whether intraoperative ROM predicts postoperative ROM. Nineteen patients, two of whom had bilateral surgery, agreed to participate. Mean age was 54 and 14 were male and 5 were male. In the majority, surgical indication was scapholunate advanced collapse; however, two of the participants had scaphoid nonunion advanced collapse. No difference was observed between intraoperative and postoperative flexion. On average there was an increase of seven degrees of extension and 12° arc of motion postoperatively with p values reaching significance Correlation between intr-operative and postoperative ROM did not reach statistical significance for flexion, extension, or arc of motion. There were no statistically significant correlations between intraoperative and postoperative ROM. Intraoperative ROM radiographs are not useful at predicting postoperative ROM. Postoperative extension and arc of motion did increase from that measured intraoperatively

Total knee and hip arthroplasty (TKA and THA) are two of the highest volume and resource intensive surgical procedures. Key drivers of the cost of surgical care are duration of surgery (DOS) and postoperative inpatient length of stay (LOS). The ability to predict TKA and THA DOS and LOS has substantial implications for hospital finances, scheduling and resource allocation. The goal of this study was to predict DOS and LOS for elective unilateral TKAs and THAs using machine learning models (MLMs) constructed on preoperative patient factors using a large North American database. The American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for elective unilateral TKA and THA procedures from 2014-2019. The dataset was split into training, validation and testing based on year. Multiple conventional and deep MLMs such as linear, tree-based and multilayer perceptrons (MLPs) were constructed. The models with best performance on the validation set were evaluated on the testing set. Models were evaluated according to 1) mean squared error (MSE), 2) buffer accuracy (the number of times the predicted target was within a predesignated buffer of the actual target), and 3) classification accuracy (the number of times the correct class was predicted by the models). To ensure useful predictions, the results of the models were compared to a mean regressor. A total of 499,432 patients (TKA 302,490; THA 196,942) were included. The MLP models had the best MSEs and accuracy across both TKA and THA patients. During testing, the TKA MSEs for DOS and LOS were 0.893 and 0.688 while the THA MSEs for DOS and LOS were 0.895 and 0.691. The TKA DOS 30-minute buffer accuracy and ≤120 min, >120 min classification accuracy were 78.8% and 88.3%, while the TKA LOS 1-day buffer accuracy and ≤2 days, >2 days classification accuracy were 75.2% and 76.1%. The THA DOS 30-minute buffer accuracy and ≤120 min, >120 min classification accuracy were 81.6% and 91.4%, while the THA LOS 1-day buffer accuracy and ≤2 days, >2 days classification accuracy were 78.3% and 80.4%. All models across both TKA and THA patients were more accurate than the mean regressors for both DOS and LOS predictions across both buffer and classification accuracies. Conventional and deep MLMs have been effectively implemented to predict the DOS and LOS of elective unilateral TKA and THA patients based on preoperative patient factors using a large North American database with a high level of accuracy. Future work should include using operational factors to further refine these models and improve predictive accuracy. Results of this work will allow institutions to optimize their resource allocation, reduce costs and improve surgical scheduling. Acknowledgements:. The American College of Surgeons National Surgical Quality Improvement Program and the hospitals participating in the ACS NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors

Aims. The most important complication of treatment of developmental dysplasia of the hip (DDH) is avascular necrosis (AVN) of the femoral head, which can result in proximal femoral growth disturbances leading to pain, dysfunction, and eventually to early onset osteoarthritis. In this study, we aimed to identify morphological variants in hip joint development that are predictive of a poor outcome. Methods. We retrospectively reviewed all patients who developed AVN after DDH treatment, either by closed and/or open reduction, at a single institution between 1984 and 2007 with a minimal follow-up of eight years. Standard pelvis radiographs obtained at ages one, two, three, five, and eight years, and at latest follow-up were retrieved. The Bucholz-Ogden classification was used to determine the type of AVN on all radiographs. Poor outcome was defined by Severin classification grade 3 or above on the latest follow-up radiographs and/or the need for secondary surgery. With statistical shape modelling, we identified the different shape variants of the hip at each age. Logistic regression analysis was used to associate the different modes or shape variants with poor outcome. Results. In all, 135 patients with AVN were identified, with a minimum of eight years of follow-up. Mean age at time of surgery was 7.0 months (SD 0.45), and mean follow-up was 13.3 years (SD 3.7). Overall, 46% had AVN type 1 while 54% type 2 or higher. More than half of the patients (52.6%) had a poor outcome. We found 11 shape variants that were significantly associated with a poor outcome. These shape variants were predominantly linked to AVN type 2 or higher. Conclusion. Specific morphological characteristics on pelvis radiographs of AVN hips were predictive for poor outcome, at a very young age. There was an overall stronger association to Bucholz-Ogden types 2-3-4 with the exception of two modes at age two and five years, linked to AVN type 1. Cite this article: Bone Joint J 2021;103-B(5):999–1004

It has been reported that 60-85% of patients who undergo PAO have concomitant intraarticular pathology that cannot be addressed with PAO alone. Currently, there are limited diagnostic tools to determine which patients would benefit from hip arthroscopy at the time of PAO to address intra-articular pathology. This study aims to see if preoperative PROMs scores measured by IHOT-33 scores have predictive value in whether intra-articular pathology is addressed during PAO + scope. The secondary aim is to see how often surgeons at high-volume hip preservation centers address intra-articular pathology if a scope is performed during the same anesthesia event. A randomized, prospective Multicenter trial was performed on patients who underwent PAO and hip arthroscopy to treat hip dysplasia from 2019 to 2020. Preoperative PROMs and intraoperative findings and procedures were recorded and analyzed. A total of 75 patients, 84% Female, and 16% male, with an average age of 27 years old, were included in the study. Patients were randomized to have PAO alone 34 patients vs. PAO + arthroscopy 41 patients during the same anesthesia event. The procedures performed, including types of labral procedures and chondroplasty procedures, were recorded. Additionally, a two-sided student T-test was used to evaluate the difference in means of preoperative IHOT score among patients for whom a labral procedure was performed versus no labral procedure. A total of 82% of patients had an intra-articular procedure performed at the time of hip arthroscopy. 68% of patients who had PAO + arthroscopy had a labral procedure performed. The most common labral procedure was a labral refixation which was performed in 78% of patients who had a labral procedure performed. Femoral head-neck junction chondroplasty was performed in 51% of patients who had an intra-articular procedure performed. The mean IHOT score was 29.3 in patients who had a labral procedure performed and 33.63 in those who did not have a labral procedure performed P- value=0.24. Our findings demonstrate preoperative IHOT-33 scores were not predictive in determining whether intra-articular labral pathology was addressed at the time of surgery. Additionally, we found that if labral pathology was addressed, labral refixation was the most common repair performed. This study also provides valuable information on what procedures high-volume hip preservation centers are performing when performing PAO + arthroscopy

Introduction. Debridement, antibiotics irrigation and implant retention (DAIR) is a common management strategy for hip and knee prosthetic joint infections (PJI). However, failure rates remain high, which has led to the development of predictive tools to help determine success. These tools include KLIC and CRIME80 for acute-postoperative (AP) and acute haematogenous (AH) PJI respectively. We investigated whether these tools were applicable to a Waikato cohort. Method. We performed a retrospective cohort study that evaluated patients who underwent DAIR between January 2010 and June 2020 at Waikato Hospital. Pre-operative KLIC and CRIME80 scores were calculated and compared to success of operation. Failure was defined as: (i) need for further surgery, (ii) need for suppressive antibiotics, (iii) death due to the infection. Logistic regression models were used to calculate the area under the curve (AUC). Results. 117 eligible patients underwent DAIR, 53 in the AP cohort and 64 in the AH cohort. Failure rate at 2 years post-op was 43% in the AP cohort and 59% in the AH cohort. In the AP cohort a KLIC score of <4 had a DAIR failure rate of 28.6%, while those who scored ³4 had a failure rate of 72.2% (p=0.002). In the AH cohort a CRIME80 score of <3 had a DAIR failure rate of 48% while those who scored ³3 had a 100% failure rate (p<0.001). Discussion. This study represents the first external validation of the KLIC and CRIME80 scores for predicting DAIR failure in an Australasian population. The results indicate that both KLIC and CRIME80 scoring tools are valuable aids for the clinician seeking to determine the optimal management strategy in patients with AP or AH PJI

Aims. The aims of this study were to determine if an increasing serum cobalt (Co) and/or chromium (Cr) concentration is correlated with a decreasing Harris Hip Score (HHS) and Hip disability and Osteoarthritis Outcome Score (HOOS) in patients who received the Articular Surface Replacement (ASR) hip resurfacing arthroplasty (HRA), and to evaluate the ten-year revision rate and show if sex, inclination angle, and Co level influenced the revision rate. Methods. A total of 62 patients with an ASR-HRA were included and monitored yearly postoperatively. At follow-up, serum Co and Cr levels were measured and the HHS and the HOOS were scored. In addition, preoperative patient and implant variables and the need for revision surgery were recorded. We used a linear mixed model to relate the serum Co and Cr levels to different patient-reported outcome measures (PROMs). For the survival analyses we used the Kaplan-Meier and Cox regression model. Results. We found that an increase of one part per billion (ppb) in serum Co and Cr levels correlated significantly with worsening of the HHS in the following year. This significant correlation was also true for the HOOS-Pain and HOOS-quality of life sub scores. The overall ten-year survival rate in our cohort was 65% (95% confidence interval (CI) 52.5 to 77.6). Cox regression analysis showed a significant hazard ratio (HR) of 1.08 (95% CI 1.01 to 1.15; p = 0.028) for serum Co level. No significance was found with sex or inclination angle. Conclusion. This study shows that increasing serum Co and Cr levels measured in patients with an ASR-HRA are predictive for deterioration in HHS and HOOS subscales in the following year. Increasing serum Co and Cr should forewarn both surgeon and patient that there is a heightened risk of failure. Continued and regular review of patients with an ASR-HRA implant by measurement of serum Co/Cr levels and PROMs remains essential. Cite this article: Bone Joint J 2023;105-B(7):775–782

Aims. Intra-articular (IA) tumours around the knee are treated with extra-articular (EA) resection, which is associated with poor functional outcomes. We aim to evaluate the accuracy of MRI in predicting IA involvement around the knee. Methods. We identified 63 cases of high-grade sarcomas in or around the distal femur that underwent an EA resection from a prospectively maintained database (January 1996 to April 2020). Suspicion of IA disease was noted in 52 cases, six had IA pathological fracture, two had an effusion, two had prior surgical intervention (curettage/IA intervention), and one had an osseous metastasis in the proximal tibia. To ascertain validity, two musculoskeletal radiologists (R1, R2) reviewed the preoperative imaging (MRI) of 63 consecutive cases on two occasions six weeks apart. The radiological criteria for IA disease comprised evidence of tumour extension within the suprapatellar pouch, intercondylar notch, extension along medial/lateral retinaculum, and presence of IA fracture. The radiological predictions were then confirmed with the final histopathology of the resected specimens. Results. The resection histology revealed 23 cases (36.5%) showing IA disease involvement compared with 40 cases without (62%). The intraobserver variability of R1 was 0.85 (p < 0.001) compared to R2 with κ = 0.21 (p = 0.007). The interobserver variability was κ = 0.264 (p = 0.003). Knee effusion was found to be the most sensitive indicator of IA involvement, with a sensitivity of 91.3% but specificity of only 35%. However, when combined with a pathological fracture, this rose to 97.5% and 100% when disease was visible in Hoffa’s fat pad. Conclusion. MRI imaging can sometimes overestimate IA joint involvement and needs to be correlated with clinical signs. In the light of our findings, we would recommend EA resections when imaging shows effusion combined with either disease in Hoffa’s fat pad or retinaculum, or pathological fractures. Cite this article: Bone Joint J 2023;105-B(6):696–701

Aims. Neither a surgeon’s intraoperative impression nor the parameters of computer navigation have been shown to be predictive of the outcomes following total knee arthroplasty (TKA). The aim of this study was to determine whether a surgeon, with robotic assistance, can predict the outcome as assessed using the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain (KPS), one year postoperatively, and establish what factors correlate with poor KOOS scores in a well-aligned and balanced TKA. Methods. A total of 134 consecutive patients who underwent TKA using a dynamic ligament tensioning robotic system with a tibia first resection technique and a cruciate sacrificing ultracongruent TKA system were enrolled into a prospective study. Each TKA was graded based on the final mediolateral ligament balance at 10° and 90° of flexion: 1) < 1 mm difference in the thickness of the tibial insert and that which was planned (n = 75); 2) < 1 mm difference (n = 26); 3) between 1 mm to 2 mm difference (n = 26); and 4) > 2 mm difference (n = 7). The mean one-year KPS score for each grade of TKA was compared and the likelihood of achieving an KPS score of > 90 was calculated. Finally, the factors associated with lower KPS despite achieving a high-grade TKA (grade A and B) were analyzed. Results. Patients with a grade of A or B TKA had significantly higher mean one-year KPS scores compared with those with C or D grades (p = 0.031). There was no difference in KPS scores in grade A or B TKAs, but 33% of these patients did not have a KPS score of > 90. While there was no correlation with age, sex, preoperative deformity, and preoperative KOOS and Patient-Reported Outcomes Measurement Information System (PROMIS) physical scores, patients with a KPS score of < 90, despite a grade A or B TKA, had lower PROMIS mental health scores compared with those with KPS scores of > 90 (54.1 vs 50.8; p = 0.043). Patients with grade A and B TKAs with KPS > 90 were significantly more likely to respond with “my expectations were too low”, and with “the knee is performing better than expected” compared with patients with these grades of TKA who had a KPS score of < 90 (40% vs 22%; p = 0.004). Conclusion. A TKA balanced with robotic assistance to within 1 mm of difference between the medial and lateral sides in both flexion and extension had a higher KPS score one year postoperatively. Despite accurate ligament balance information, a robotic system could not guarantee excellent pain relief. Patient expectations and mental status also significantly affected the perceived success of TKA. Cite this article: Bone Joint J 2021;103-B(6 Supple A):67–73

Aims. We assessed the value of the Clinical Frailty Scale (CFS) in the prediction of adverse outcome after hip fracture. Methods. Of 1,577 consecutive patients aged > 65 years with a fragility hip fracture admitted to one institution, for whom there were complete data, 1,255 (72%) were studied. Clinicians assigned CFS scores on admission. Audit personnel routinely prospectively completed the Standardised Audit of Hip Fracture in Europe form, including the following outcomes: 30-day survival; in-hospital complications; length of acute hospital stay; and new institutionalization. The relationship between the CFS scores and outcomes was examined graphically and the visual interpretations were tested statistically. The predictive values of the CFS and Nottingham Hip Fracture Score (NHFS) to predict 30-day mortality were compared using receiver operating characteristic area under the curve (AUC) analysis. Results. Significant non-linear associations between CFS and outcomes were observed. Risk of death within 30 days rose linearly for CFS 1 to 5, but plateaued for CFS > 5. The incidence of complications and length of stay rose linearly for CFS 1 to 4, but plateaued for CFS > 4. In contrast, the risk of new institutionalization rose linearly for CFS 1 to 8. The AUCs for 30-day mortality for the CFS and NHFS were very similar: CFS AUC 0.63 (95% CI 0.57 to 0.69) and NHFS AUC 0.63 (95% CI 0.57 to 0.69). Conclusion. Use of the CFS may provide useful information on outcomes for fitter patients presenting with hip fracture, but completion of the CFS by the admitting orthopaedic team does not appear successful in distinguishing between higher CFS categories, which define patients with frailty. This makes a strong case for the role of the orthogeriatrician in the early assessment of these patients. Further work is needed to understand why patients assessed as being of mild, moderate, and severe frailty do not result in different outcomes. Cite this article: Bone Joint J 2022;104-B(8):980–986

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

Aims. The Uppföljningsprogram för cerebral pares (CPUP) Hip Score distinguishes between children with cerebral palsy (CP) at different levels of risk for displacement of the hip. The score was constructed using data from Swedish children with CP, but has not been confirmed in any other population. The aim of this study was to determine the calibration and discriminatory accuracy of this score in children with CP in Scotland. Methods. This was a total population-based study of children registered with the Cerebral Palsy Integrated Pathway Scotland. Displacement of the hip was defined as a migration percentage (MP) of > 40%. Inclusion criteria were children in Gross Motor Function Classification System (GMFCS) levels III to V. The calibration slope was estimated and Kaplan-Meier curves produced for five strata of CPUP scores to compare the observed with the predicted risk of displacement of the hip at five years. For discriminatory accuracy, the time-dependent area under the receiver operating characteristic curve (AUC) was estimated. In order to analyze differences in the performance of the score between cohorts, score weights, and subsequently the AUC, were re-estimated using the variables of the original score: the child’s age at the first examination, GMFCS level, head shaft angle, and MP of the worst hip in a logistic regression with imputation of outcomes for those with incomplete follow-up. Results. The discriminatory accuracy of the score in the new population of 367 children was high (AUC 0.78 (95% confidence interval (CI) 0.71 to 0.86)). The calibration of the score was insufficient (slope 0.48 (95% CI 0.31 to 0.65)), and the absolute risks of displacement of the hip in this population were overestimated. The AUC increased with re-estimated weights (0.85 (95% CI 0.79 to 0.91)). Conclusion. The CPUP Hip Score had a high ability to discriminate between children at different levels of risk for displacement of the hip. The score overestimated the absolute risks of displacement in this population, which may have resulted from differences in the way children were initially registered in the two programmes. The results are promising, but the score weights may need re-estimation before its clinical application in Scotland. Cite this article: Bone Joint J 2022;104-B(5):640–644

Anterior approach total hip arthroplasty (AA-THA) has a steep learning curve, with higher complication rates in initial cases. Proper surgical case selection during the learning curve can reduce early risk. This study aims to identify patient and radiographic factors associated with AA-THA difficulty using Machine Learning (ML). Consecutive primary AA-THA patients from two centres, operated by two expert surgeons, were enrolled (excluding patients with prior hip surgery and first 100 cases per surgeon). K- means prototype clustering – an unsupervised ML algorithm – was used with two variables - operative duration and surgical complications within 6 weeks - to cluster operations into difficult or standard groups. Radiographic measurements (neck shaft angle, offset, LCEA, inter-teardrop distance, Tonnis grade) were measured by two independent observers. These factors, alongside patient factors (BMI, age, sex, laterality) were employed in a multivariate logistic regression analysis and used for k-means clustering. Significant continuous variables were investigated for predictive accuracy using Receiver Operator Characteristics (ROC). Out of 328 THAs analyzed, 130 (40%) were classified as difficult and 198 (60%) as standard. Difficult group had a mean operative time of 106mins (range 99–116) with 2 complications, while standard group had a mean operative time of 77mins (range 69–86) with 0 complications. Decreasing inter-teardrop distance (odds ratio [OR] 0.97, 95% confidence interval [CI] 0.95–0.99, p = 0.03) and right-sided operations (OR 1.73, 95% CI 1.10–2.72, p = 0.02) were associated with operative difficulty. However, ROC analysis showed poor predictive accuracy for these factors alone, with area under the curve of 0.56. Inter-observer reliability was reported as excellent (ICC >0.7). Right-sided hips (for right-hand dominant surgeons) and decreasing inter-teardrop distance were associated with case difficulty in AA-THA. These data could guide case selection during the learning phase. A larger dataset with more complications may reveal further factors

Aims. Hip fractures are some of the most common fractures encountered in orthopaedic practice. We aimed to identify whether perioperative hypotension is a predictor of 30-day mortality, and to stratify patient groups that would benefit from closer monitoring and early intervention. While there is literature on intraoperative blood pressure, there are limited studies examining pre- and postoperative blood pressure. Methods. We conducted a prospective observational cohort study over a one-year period from December 2021 to December 2022. Patient demographic details, biochemical results, and haemodynamic observations were taken from electronic medical records. Statistical analysis was conducted with the Cox proportional hazards model, and the effects of independent variables estimated with the Wald statistic. Kaplan-Meier survival curves were estimated with the log-rank test. Results. A total of 528 patients were identified as suitable for inclusion. On multivariate analysis, postoperative hypotension of a systolic blood pressure (SBP) < 90 mmHg two to 24 hours after surgery showed an increased hazard ratio (HR) for 30-day mortality (HR 4.6 (95% confidence interval (CI) 2.3 to 8.9); p < 0.001) and was an independent risk factor accounting for sex (HR 2.7 (95% CI 1.4 to 5.2); p = 0.003), age (HR 1.1 (95% CI 1.0 to 1.1); p = 0.016), American Society of Anesthesiologists grade (HR 2.7 (95% CI 1.5 to 4.6); p < 0.001), time to theatre > 24 hours (HR 2.1 (95% CI 1.1 to 4.2); p = 0.025), and preoperative anaemia (HR 2.3 (95% CI 1.0 to 5.2); p = 0.043). A preoperative SBP of < 120 mmHg was close to achieving significance (HR 1.9 (95% CI 0.99 to 3.6); p = 0.052). Conclusion. Our study is the first to demonstrate that postoperative hypotension within the first 24 hours is an independent risk factor for 30-day mortality after hip fracture surgery. Clinicians should recognize patients who have a SBP of < 90 mmHg in the early postoperative period, and be aware of the increased mortality risk in this specific cohort who may benefit from a closer level of monitoring and early intervention. Cite this article: Bone Joint J 2024;106-B(2):189–194

Aims. A proximal femur fracture (PFF) is a common orthopaedic presentation, with an incidence of over 25,000 cases reported in the Australian and New Zealand Hip Fracture Registry (ANZHFR) in 2018. Hip fractures are known to have high mortality. The purpose of this study was to determine the utility of the Clinical Frailty Scale (CFS) in predicting 30-day and one-year mortality after a PFF in older patients. Methods. A retrospective review of all fragility hip fractures who met the inclusion/exclusion criteria of the ANZHFR between 2017 and 2018 was undertaken at a single large volume tertiary hospital. There were 509 patients included in the study with one-year follow-up obtained in 502 cases. The CFS was applied retrospectively to patients according to their documented pre-morbid function and patients were stratified into five groups according to their frailty score. The groups were compared using t-test, analysis of variance (ANOVA), and the chi-squared test. The discriminative ability of the CFS to predict mortality was then compared with American Society of Anaesthesiologists (ASA) classification and the patient’s chronological age. Results. A total of 38 patients were deceased at 30 days and 135 patients at one year. The 30-day mortality rate increased from 1.3% (CFS 1 to 3; 1/80) to 14.6% (CFS ≥ 7; 22/151), and the one-year mortality increased from 3.8% (CFS 1 to 3; 3/80) to 41.7% (CFS ≥ 7; 63/151). The CFS was demonstrated superior discriminative ability in predicting mortality after PFF (area under the curve (AUC) 0.699; 95% confidence interval (CI) 0.651 to 0.747) when compared with the ASA (AUC 0.634; 95% CI 0.576 to 0.691) and chronological age groups (AUC 0.585; 95% CI 0.523 to 0.648). Conclusion. The CFS demonstrated utility in predicting mortality after PFF fracture. The CFS can be easily performed by non-geriatricians and may help to reduce age related bias influencing surgical decision making. Cite this article: Bone Joint Open 2020;1-8:443–449

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

Several different algorithms attempt to estimate life expectancy for patients with metastatic spine disease. The Skeletal Oncology Research Group (SORG) has recently developed a nomogram to estimate survival of patients with metastatic spine disease. Whilst the use of the SORG nomogram has been validated in the international context, there has been no study to date that validates the use of the SORG nomogram in New Zealand. This study aimed to validate the use of the SORG nomogram in Aotearoa New Zealand. We collected data on 100 patients who presented to Waikato Hospital with a diagnosis of spinal metastatic disease. The SORG nomogram gave survival probabilities for each patient at each time point. Receiver Operating Characteristic (ROC) Area Under Curve (AUC) analysis was performed to assess the predictive accuracy of the SORG score. A calibration curve was also performed, and Brier scores calculated. A multivariate Cox regression analysis was performed. The SORG score was correlated with 30 day (AUC = 0.72) and 90-day mortality (AUC = 0.71). The correlation between the SORG score and 90-day mortality was weaker (AUC = 0.69). Using this method, the nomogram was correct for 79 (79%) patients at 30-days, 59 patients (59%) at 90-days, and 42 patients (42%) at 365-days. Calibration curves demonstrated poor forecasting of the SORG nomogram at 30 (Brier score = 0.65) and 365 days (Brier score = 0.33). The calibration curve demonstrated borderline forecasting of the SORG nomogram at 90 days (Brier score = 0.28). Several components of the SORG nomogram were not found to be correlated with mortality. In this New Zealand cohort the SORG nomogram demonstrated only acceptable discrimination at best in predicting life 30-, 90- or 356-day mortality in patients with metastatic spinal disease

Aims. The primary aim of this study was to assess whether the postoperative Oxford Knee Score (OKS) demonstrated a ceiling effect at one and/or two years after total knee arthroplasty (TKA). The secondary aim was to identify preoperative independent predictors for patients that achieved a ceiling score after TKA. Methods. A retrospective cohort of 5,857 patients undergoing a primary TKA were identified from an established arthroplasty database. Patient demographics, body mass index (BMI), OKS, and EuroQoL five-dimension (EQ-5D) general health scores were collected preoperatively and at one and two years postoperatively. Logistic regression analysis was used to identify independent preoperative predictors of patients achieving postoperative ceiling scores. Receiver operating characteristic curve was used to identify a preoperative OKS that predicted a postoperative ceiling score. Results. The ceiling effect was 4.6% (n = 272) at one year which increased significantly (odds ratio (OR) 40.3, 95% confidence interval (CI) 30.4 to 53.3; p < 0.001) to 6.2% (n = 363) at two years, when defined as those with a maximal score of 48 points. However, when the ceiling effect was defined as an OKS of 44 points or more, this increased to 26.3% (n = 1,540) at one year and further to 29.8% (n = 1,748) at two years (OR 21.6, 95% CI 18.7 to 25.1; p < 0.001). A preoperative OKS of 23 or more and 22 or more were predictive of achieving a postoperative ceiling OKS at one and two years when defined as a maximal score or a score of 44 or more, respectively. Conclusion. The postoperative OKS demonstrated a small ceiling effect when defined by a maximal score, but when defined by a postoperative OKS of 44 or more the ceiling effect was moderate and failed to meet standards. The preoperative OKS was an independent predictor of achieving a ceiling score. Cite this article: Bone Joint J 2020;102-B(11):1519–1526

Abstract. Objectives. Identifying risk factors for inferior outcomes after anterior cruciate ligament reconstruction (ACLR) is important for prognosis and patient information. This study aimed to ascertain if BMI, pre-operative scores, demographic data and concomitant injuries in patients undergoing ACLR affected patient-reported functional outcomes. Methods. A prospective review collected data from a single surgeon series of 278 patients who underwent arthroscopic ACLR. BMI, age, gender, graft choice, pre-op Lysholm score, meniscal and chondral injuries were recorded. The Lysholm score, hop test and KT1000 were used to measure post-op functional outcome at one year. Multiple regression analysis was used to determine factors that predicted Lysholm scores at one year. Results. The mean age was 29 years, with 58 female and 220 male patients. The mean pre-op Lysholm score was 53.8. One hunded and seventy-nine patients had meniscal injuries, of which 81 were medial, 60 lateral, and 38 bilateral. Eighteen patients also had chondral injury and 106 patients had no other associated injury. Age, gender, graft type and presence of meniscal or chondral injuries did not affect one-year post-operative Lysholm scores. A BMI greater than 30, physio compliance and preoperative Lysholm scores helped predict one-year post-operative Lysholm scores (p=0.02). Pearson's correlation found a direct link between BMI and post-operative Lysholm (p=0.03). Conclusions. BMI, physio compliance and pre-operative Lysholm scores are the most significant determinants of short-term functional outcome after ACLR. However, the effects of associated injuries may be apparent in the long-term as degenerative changes set in or the continued detriment resulting from the concomitant injury affect outcome. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aims. A retrospective longitudinal study was conducted to compare directly volumetric wear of retrieved polyethylene inserts to predicted volumetric wear modelled from individual gait mechanics of total knee arthroplasty (TKA) patients. Methods. In total, 11 retrieved polyethylene tibial inserts were matched with gait analysis testing performed on those patients. Volumetric wear on the articular surfaces was measured using a laser coordinate measure machine and autonomous reconstruction. Knee kinematics and kinetics from individual gait trials drove computational models to calculate medial and lateral tibiofemoral contact paths and forces. Sliding distance along the contact path, normal forces and implantation time were used as inputs to Archard’s equation of wear to predict volumetric wear from gait mechanics. Measured and modelled wear were compared for each component. Results. Volumetric wear rates on eight non-delaminated components measured 15.9 mm. 3. /year (standard error (SE) ± 7.7) on the total part, 11.4 mm. 3. /year (SE ± 6.4) on the medial side and 4.4 (SE ± 2.6) mm. 3. /year on the lateral side. Volumetric wear rates modelled from patient gait mechanics predicted 16.4 mm. 3. /year (SE 2.4) on the total part, 11.7 mm. 3. /year (SE 2.1) on the medial side and 4.7 mm. 3. /year (SE 0.4) on the lateral side. Measured and modelled wear volumes correlated significantly on the total part (p = 0.017) and the medial side (p = 0.012) but not on the lateral side (p = 0.154). Conclusion. In the absence of delamination, patient-specific knee mechanics during gait directly affect wear of the tibial component in TKA. Cite this article: Bone Joint J 2020;102-B(6 Supple A):129–137

It is anecdotally thought that a good outcome from the first of staged total hip arthroplasties (THAs) is predictive of benefit on the contralateral side. The objective was to determine whether outcome from the first THA could be used to predict outcome from the second, contralateral THA. A retrospective cohort study of consecutive patients undergoing staged THAs at a UK arthroplasty centre over 25-years (1995–2020). A control THA group was identified and matched for age, gender, BMI, implant and diagnosis. One-year patient-reported outcome data was available for 91% 1543/1700. 1700 patients who underwent staged THA were compared to 1700 matched controls. Preoperative status was comparable for pain, function, and modified Harris hip score (mHHS, mean 41 SD 13 for both groups). At one year, there was a 2% dissatisfaction rate in all groups (first of staged THAs, second of staged THAs and controls). Groups were similar in terms of pain, function and mHHS (mean 88 SD 11 for all groups). For every 100 patients undergoing staged THAs, 87 had a bilateral good outcome (mHHS >70 both), 11 had unilateral poor outcome (mHHS >70 one, <70 other) and 2 had bilateral poor outcome (mHHS <70 both). If the first THA had a good outcome, the relative risk of a bad outcome was 20% less than for controls (RR 0.8 95% CI 0.6–1.1). If the first THA had a poor outcome, the risk of a second poor outcome was 4.5 times higher (RR 4.5 95% CI 3.2–6.4), increasing from 6% to 29% (absolute risk). Patients undergoing staged THAs with a good outcome from the first THA were less likely to have a bad outcome with the second. Risk of a poor outcome after a previous successful THA was 6% but rose to almost 30% with a previous poor outcome. This remained after correcting for patient variables including gender, age, BMI and diagnosis, indicating a potentially novel independent risk factor for poor outcome from staged THA

Aims. The outcomes following nonoperative management of minimally displaced greater tuberosity (GT) fractures, and the factors which influence patient experience, remain poorly defined. We assessed the early patient-derived outcomes following these injuries and examined the effect of a range of demographic- and injury-related variables on these outcomes. Methods. In total, 101 patients (53 female, 48 male) with a mean age of 50.9 years (19 to 76) with minimally displaced GT fractures were recruited to a prospective observational cohort study. During the first year after injury, patients underwent experiential assessment using the Disabilities of the Arm, Shoulder and Hand (DASH) score and assessment of associated injuries using MRI performed within two weeks of injury. The primary outcome was the one-year DASH score. Multivariate analysis was used to assess the effect of patient demographic factors, complications, and associated injuries, on outcome. Results. The mean DASH score improved from 42.3 (SD 9.6) at six weeks post-injury, to 19.5 (SD 14.3) at one-year follow-up (p < 0.001), but outcomes were mixed, with 30 patients having a DASH score > 30 at one year. MRI revealed a range of associated injuries, with a full-thickness rotator cuff tear present in 19 patients (19%). Overall, 11 patients (11%) developed complications requiring further operative intervention; 20 patients (21%) developed post-traumatic secondary shoulder stiffness. Multivariate analysis revealed a high-energy mechanism (p = 0.009), tobacco consumption (p = 0.033), use of mobility aids (p = 0.047), a full-thickness rotator cuff tear (p = 0.002), and the development of post-traumatic secondary shoulder stiffness (p = 0.035) were independent predictors of poorer outcome. Conclusion. The results of nonoperative management of minimally displaced GT fractures are heterogeneous. While many patients have satisfactory early outcomes, a substantial subgroup fare much worse. There is a high prevalence of rotator cuff injuries and post-traumatic shoulder stiffness, and their presence is associated with poorer patient experience. Furthermore, patients who have a high-energy injury, smoke, or use walking aids, have worse outcomes. Cite this article: Bone Joint J 2023;105-B(5):534–542

Aims. To evaluate if union of clavicle fractures can be predicted at six weeks post-injury by the presence of bridging callus on ultrasound. Methods. Adult patients managed nonoperatively with a displaced mid-shaft clavicle were recruited prospectively. Ultrasound evaluation of the fracture was undertaken to determine if sonographic bridging callus was present. Clinical risk factors at six weeks were used to stratify patients at high risk of nonunion with a combination of Quick Disabilities of the Arm, Shoulder and Hand questionnaire (QuickDASH) ≥ 40, fracture movement on examination, or absence of callus on radiograph. Results. A total of 112 patients completed follow-up at six months with a nonunion incidence of 16.7% (n = 18/112). Sonographic bridging callus was detected in 62.5% (n = 70/112) of the cohort at six weeks post-injury. If present, union occurred in 98.6% of the fractures (n = 69/70). If absent, nonunion developed in 40.5% of cases (n = 17/42). The sensitivity to predict union with sonographic bridging callus at six weeks was 73.4% and the specificity was 94.4%. Regression analysis found that failure to detect sonographic bridging callus at six weeks was associated with older age, female sex, simple fracture pattern, smoking, and greater fracture displacement (Nagelkerke R. 2. = 0.48). Of the cohort, 30.4% (n = 34/112) had absent sonographic bridging callus in addition to one or more of the clinical risk factors at six weeks that predispose to nonunion. If one was present the nonunion rate was 35%, 60% with two, and 100% when combined with all three. Conclusion. Ultrasound combined with clinical risk factors can accurately predict fracture healing at six weeks following a displaced midshaft clavicle fracture. Cite this article: Bone Joint Res 2021;10(2):113–121

Introduction. Neither a surgeon's intraoperative impression or computer navigation parameters have been shown to be predictive of postoperative outcomes following TKA. The purpose of this study is to determine 1) whether a surgeon and a robot can predict the 1-year KOOS pain score (KPS) and 2) determine what factors correlate with poor KOOS scores in well aligned and balanced TKA. Methods. The data of 131 consecutive patients enrolled in a prospective trial was reviewed. All TKAs were performed using a dynamic ligament tensioning robotic system with a tibial first resection technique and a cruciate sacrificing ultracongruent knee implant. Each TKA was graded based on the final recorded mediolateral ligament balance at 10° and 90°: A) <1mm with an implanted insert thickness equal to planned (n=74); B) <1mm (n=25); C) <2mm (n=26); D) >2mm (n=6) (Table-1). The 1-year KPS for each knee grade were compared and the likelihood of achieving an KPS > 90 was calculated. Finally, the factors associated with lower KPS despite achieving a high grade TKA (A/B) was performed. The Mann-Whitney U test and Chi-squared analysis was performed. Results. Patients with a grade of A and B had higher 1-year KPS compared to knees rated C and D (p=0.031) (Fig-1). There was no difference in KPS in TKAs rated A or B, but 33% in this group did not report a KPS > 90. While there was no correlation with age, sex, preoperative deformity, and preoperative KOOS and PROMIS physical scores, patients with KPS < 90 despite a TKA rated A or B had lower PROMIS metal health scores compared to patients reporting KPS > 90 (54.1 vs. 50.8, p= 0.043). Finally, Grade A and B patients who scored KPS > 90 were more likely to respond with “my expectations were too low”, and they are performing better than expected compared to Grade A and B patients who scored KPS < 90 (40% vs 22%, p = 0.004). Summary. A robotic balanced knee is correlated with higher KPS at 1 year but not predictive. Despite accurate alignment, rotation, and ligament balance information, a robotic system could not guarantee excellent pain relief. Patient expectations and mental status also significantly affect the perceived success of TKA. For any figures or tables, please contact the authors directly

Multiple biochemical biomarkers have been previously investigated for the diagnosis, prognosis and response to treatment of articular cartilage damage, including osteoarthritis (OA). Synovial fluid (SF) biomarker measurement is a potential method to predict treatment response and effectiveness. However, the significance of different biomarkers and their correlation to clinical outcomes remains unclear. This systematic review evaluated current SF biomarkers used in investigation of cartilage degeneration or regeneration in the knee joint and correlated these biomarkers with clinical outcomes following cartilage repair or regeneration interventions. PubMed, Institute of Science Index, Scopus, Cochrane Central Register of Controlled Trials, and Embase databases were searched. Studies evaluating SF biomarkers and clinical outcomes following cartilage repair intervention were included. Two researchers independently performed data extraction and QUADAS-2 analysis. Biomarker inclusion, change following intervention and correlation with clinical outcome was compared. 9 studies were included. Study heterogeneity precluded meta-analysis. There was significant variation in sampling and analysis. 33 biomarkers were evaluated in addition to microRNA and catabolic/anabolic ratios. Five studies reported on correlation of biomarkers with six biomarkers significantly correlated with clinical outcomes following intervention. However, correlation was only demonstrated in isolated studies. This review demonstrates significant difficulties in drawing conclusions regarding the importance of SF biomarkers based on the available literature. Improved standardisation for collection and analysis of SF samples is required. Future publications should also focus on clinical outcome scores and seek to correlate biomarkers with progression to further understand the significance of identified markers in a clinical context

Aims. The distal radius is a major site of osteoporotic bone loss resulting in a high risk of fragility fracture. This study evaluated the capability of a cortical index (CI) at the distal radius to predict the local bone mineral density (BMD). Methods. A total of 54 human cadaver forearms (ten singles, 22 pairs) (19 to 90 years) were systematically assessed by clinical radiograph (XR), dual-energy X-ray absorptiometry (DXA), CT, as well as high-resolution peripheral quantitative CT (HR-pQCT). Cortical bone thickness (CBT) of the distal radius was measured on XR and CT scans, and two cortical indices mean average (CBTavg) and gauge (CBTg) were determined. These cortical indices were compared to the BMD of the distal radius determined by DXA (areal BMD (aBMD)) and HR-pQCT (volumetric BMD (vBMD)). Pearson correlation coefficient (r) and intraclass correlation coefficient (ICC) were used to compare the results and degree of reliability. Results. The CBT could accurately be determined on XRs and highly correlated to those determined on CT scans (r = 0.87 to 0.93). The CBTavg index of the XRs significantly correlated with the BMD measured by DXA (r = 0.78) and HR-pQCT (r = 0.63), as did the CBTg index with the DXA (r = 0.55) and HR-pQCT (r = 0.64) (all p < 0.001). A high correlation of the BMD and CBT was observed between paired specimens (r = 0.79 to 0.96). The intra- and inter-rater reliability was excellent (ICC 0.79 to 0.92). Conclusion. The cortical index (CBTavg) at the distal radius shows a close correlation to the local BMD. It thus can serve as an initial screening tool to estimate the local bone quality if quantitative BMD measurements are unavailable, and enhance decision-making in acute settings on fracture management or further osteoporosis screening. Cite this article: Bone Joint Res 2021;10(12):820–829

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. Methods. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation. Results. For THA, there were 5,558 patient radiology reports included, of which 4,137 were used for model training and testing, and 1,421 for external validation. Following training, model performance demonstrated average (mean across three folds) accuracy, F1 score, and area under the receiver operating curve (AUROC) values of 0.850 (95% confidence interval (CI) 0.833 to 0.867), 0.813 (95% CI 0.785 to 0.841), and 0.847 (95% CI 0.822 to 0.872), respectively. For TKA, 7,457 patient radiology reports were included, with 3,478 used for model training and testing, and 3,152 for external validation. Performance metrics included accuracy, F1 score, and AUROC values of 0.757 (95% CI 0.702 to 0.811), 0.543 (95% CI 0.479 to 0.607), and 0.717 (95% CI 0.657 to 0.778) respectively. There was a notable deterioration in performance on external validation in both cohorts. Conclusion. The use of routinely available preoperative radiology reports provides promising potential to help screen suitable candidates for THA, but not for TKA. The external validation results demonstrate the importance of further model testing and training when confronted with new clinical cohorts. Cite this article: Bone Joint J 2024;106-B(7):688–695

It is unclear whether patients with early radiographic osteoarthritis (OA) but severe hip symptoms benefit from total hip replacement (THR). We aimed to assess which factors were associated with successful THR in this patient group. From a consecutive series of 1,935 patients undergoing THR we identified 70 (3.6%) patients with early OA (Kellgren and Lawrence (KL) grades 0-2). These were compared with 200 patients with advanced OA (KL grades 3–4). Outcomes were Oxford Hip Scores (OHS), EQ5D and EQ-VAS scores; compared pre-operatively with one year post-operatively. We investigated which clinical and radiographic (plain x-ray, CT, MRI) features predicted successful THR in the early OA group. Success was defined as reaching a postoperative OHS≥42. The early OA group were significantly younger (61 vs 66 years; P=0.0035). There were no significant differences in body mass index, ASA grade or gender. After adjusting for confounders, the advanced OA group had a significantly greater percentage of possible change (PoPC) in OHS (75.8% versus 50.4%; P<0.0001) and improvement in EQ5D (0.151 versus 0.002; P<0.0001). There were no significant differences in complication, revision or readmission rates. In the early OA group, we identified 16/70 (22.9%) patients who had a ‘successful’ THR. Of those with early OA, 38 patients had pre-operative CT or MRI scans. Patients who had a ‘successful’ THR were significantly more likely to have subchondral cysts on CT/MRI (91.7% versus 57.7%; P=0.0362). The presence of cysts on CT/MRI was associated with a significantly greater PoPC in OHS (61.6% versus 38.2%; P=0.0353). The combination of cysts and joint space width (JSW) <1mm was associated with a PoPC of 68%. Plain radiographs were found to significantly underestimate the narrowest JSW compared to CT/MRI (2.4mm versus 1.0mm; P<0.0001). We advise caution in performing THRs in patients with early OA (KL grades 0-2) on plain radiographs. We advocate pre-operative cross-sectional imaging (CT or MRI) in these patients. In the absence of cysts on cross-sectional imaging, a THR seems unlikely to provide a satisfactory outcome

Aim. D-dimer is a widely available serum test that detects fibrinolytic activities that occur during infection. Prior studies have explored its utility for diagnosis of chronic periprosthetic joint infections (PJI), but not explored its prognostic value for prediction of subsequent treatment failure. The purpose of this study was to: (1) assess the ability of serum D-dimer and other standard-of-care serum biomarkers to predict failure following reimplantation, and (2) establish a new cutoff value for serum D-dimer for prognostic use prior to reimplantation. Method. This prospective study enrolled 92 patients undergoing reimplantation between April 2015 and March 2019 who had previously undergone total hip/knee resection arthroplasty with placement of an antibiotic spacer for treatment of chronic PJI. Serum D-dimer level, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) levels were measured preoperatively for all patients. Failure following implantation was defined per the Delphi consensus criteria. Optimal cutoffs for D-dimer, ESR, and CRP were calculated based on ROC curves and compared in their association with failure following reimplantation criteria at minimum 1-year follow-up. Results. 15/92(16.3%) patients failed reimplantation surgery at mean follow up of 2.9 years (range 1.0–4.8). Optimal thresholds for D-Dimer, ESR and CRP were determined to be 1300ng/mL, 30mm/hr, and 1mg/L, respectively. The failure rate in patient with positive D-dimer was significantly higher at 32.0% (8/25) compared to those with negative D-dimer 10.6% (7/66); p=0.024. In comparison, 17.8% (8/45) of patients with ESR above threshold failed, compared to 13.89% (5/41) below (p=0.555) and 16.0% (4/25) of patients with CRP above threshold failed, compared to 16.1% (10/62) below (p=1.000). Conclusions. Patients with elevated D-Dimer appear to be at higher risk of failure after reimplantation surgery. This serum marker may be used to generate an additional data point in patients undergoing reimplantation surgery, especially in circumstances when optimal timing of reimplantation cannot be determined based on clinical circumstances

In the Unites States, approximately 24% of people undergoing primary total knee or total hip arthroplasty (TKA, THA) are chronic opioid users pre-operatively. Few studies have examined the incidence of opioid use prior to TKA/THA and whether it predicts outcomes post-surgery in the Australian context. The aim was to determine: (i) the proportion of TKA and THA patients who use opioids regularly (daily) pre-surgery; (ii) if opioid use pre-surgery predicts (a) complication and readmission rates to 6-months post-surgery, (b) patient-reported outcomes to 6-months post-surgery. A retrospective cohort study was undertaken utilising linked individual patient-level data from two independent databases comprising approximately 3500 people. Patients had surgery between January 2013 and June 2018, inclusive at Fairfield and Bowral Hospitals. Following data linkage, analysis was completed on 1185 study participants (64% female, 69% TKA, mean age 67 (9.9)). 30% were using regular opioids pre-operatively. Unadjusted analyses resulted in the following rates in those who . were. vs . were not. using opioids pre-operatively (respectively); acute adverse events (39.1% vs 38.6%), acute significant adverse events (5.3% vs 5.7%), late adverse events: (6.9% vs 6.6%), total significant adverse events: (12.5% vs 12.4%), discharge to inpatient rehab (86.4% vs 88.6%), length of hospital stay (5.9 (3.0) vs 5.6 (3.0) days), 6-month post-op Oxford Score (38.8 (8.9) vs 39.5 (7.9)), 6 months post-op EQ-VAS (71.7 (20.2) vs 76.7 (18.2), p<0.001), success post-op described as “much better” (80.2% vs 81.3%). Adjusted regression analyses controlling for multiple co-variates indicated no significant association between pre-op opioid use and adverse events/patient-reported outcomes. Pre-operative opioid use was high amongst this Australian arthroplasty cohort and was not associated with increased risk of adverse events post-operatively. Further research is needed in assessing the relationship between the amount of pre-op opioid use and the risk of post-operative adverse events

Background. Low back pain can lead to neuroplastic changes in the central nervous system, known as nociplastic pain. As nociplastic pain may be provoked by premorbid sensory profiles, such profiles may be prognostic in the development of nociplastic pain over time. Objectives. To investigate whether four sensory profiles are prognostic in the development of symptoms of nociplastic pain in people with acute low back pain. Methods. A longitudinal type 2 prognostic factor research study was performed in accordance with the PROGRESS framework, using a baseline and a follow-up after 12 weeks, between the Adolescent/Adult Sensory Profile and the Central Sensitisation Inventory. Study participants were consecutively included from primary care physiotherapy practices randomly spread throughout the Netherlands. A multivariable regression analysis was performed to adjust sensory profiles by the level of pain, disability, age, and duration of low back pain. Results. After adjustment Low Registration B=0.41, 95%CI (0.37, 0.99), Sensory Seeking B=0.37, 95%CI (0.24, 0.73), Sensory Sensitive B=0.51, 95%CI (0.50, 1.06), Sensation Avoiding B=0.46, 95%CI (0.43, 0.99) were significantly associated with the development of nociplastic pain symptoms. Conclusion. Sensory profiles in people with acute low back pain predict symptoms of nociplastic pain after 12 weeks. Conflict of interest: No conflict of interest. Sources of funding: No funding obtained

Giant cell tumors of bone (GCTs) are locally aggressive tumors with recurrence potential that represent up to 10% of primary tumors of the bone. GCTs pathogenesis is driven by neoplastic mononuclear stromal cells that overexpress receptor activator of nuclear factor kappa-B/ligand (RANKL). Treatment with specific anti-RANKL antibody (denosumab) was recently introduced, used either as a neo-adjuvant in resectable tumors or as a stand-alone treatment in unresectable tumors. While denosumab has been increasingly used, a percentage of patients do not improve after treatment. Here, we aim to determine molecular and histological patterns that would help predicting GCTs response to denosumab to improve personalized treatment. Nine pre-treatment biopsies of patients with spinal GCT were collected at 2 centres. In 4 patients denosumab was used as a neo-adjuvant, 3 as a stand-alone and 2 received denosumab as adjuvant treatment. Clinical data was extracted retrospectively. Total mRNA was extracted by using a formalin-fixed paraffin-embedded extraction kit and we determined the transcript profile of 730 immune-oncology related genes by using the Pan Cancer Immune Profiling panel (Nanostring). The gene expression was compared between patients with good and poor response to Denosumab treatment by using the nSolver Analysis Software (Nanostring). Immunohistochemistry was performed in the tissue slides to characterize cell populations and immune response in CGTs. Two out of 9 patients showed poor clinical response with tumor progression and metastasis. Our analysis using unsupervised hierarchical clustering determined differences in gene expression between poor responders and good responders before denosumab treatment. Poor responding lesions are characterized by increased expression of inflammatory cytokines as IL8, IL1, interferon a and g, among a myriad of cytokines and chemokines (CCL25, IL5, IL26, IL25, IL13, CCL20, IL24, IL22, etc.), while good responders are characterized by elevated expression of platelets (CD31 and PECAM), coagulation (CD74, F13A1), and complement classic pathway (C1QB, C1R, C1QBP, C1S, C2) markers, together with extracellular matrix proteins (COL3A1, FN1,. Interestingly the T-cell response is also different between groups. Poor responding lesions have increased Th1 and Th2 component, but good responders have an increased Th17 component. Interestingly, the checkpoint inhibitor of the immune response PD1 (PDCD1) is increased ~10 fold in poor responders. This preliminary study using a novel experimental approach revealed differences in the immune response in GCTs associated with clinical response to denosumab. The increased activity of checkpoint inhibitor PD1 in poor responders to denosumab treatment may have implications for therapy, raising the potential to investigate immunotherapy as is currently used in other neoplasms. Further validation using a larger independent cohort will be required but these results could potentially identify the patients who would most benefit from denosumab therapy

Aims. Open fractures of the tibia are a heterogeneous group of injuries that can present a number of challenges to the treating surgeon. Consequently, few surgeons can reliably advise patients and relatives about the expected outcomes. The aim of this study was to determine whether these outcomes are predictable by using the Ganga Hospital Score (GHS). This has been shown to be a useful method of scoring open injuries to inform wound management and decide between limb salvage and amputation. Methods. We collected data on 182 consecutive patients with a type II, IIIA, or IIIB open fracture of the tibia who presented to our hospital between July and December 2016. For the purposes of the study, the patients were jointly treated by experienced consultant orthopaedic and plastic surgeons who determined the type of treatment. Separately, the study team (SP, HS, AD, JD) independently calculated the GHS and prospectively collected data on six outcomes for each patient. These included time to bony union, number of admissions, length of hospital stay, total length of treatment, final functional score, and number of operations. Spearman’s correlation was used to compare GHS with each outcome. Forward stepwise linear regression was used to generate predictive models based on components of the GHS. Five-fold cross-validation was used to prevent models from over-fitting. Results. The mean follow-up was 11.4 months (3 to 31). The mean time to union was 9.7 months (3 to 21), the mean number of operations was 2.8 (1 to 11), the mean time in hospital was 17.7 days (5 to 84), the mean length of treatment was 92.7 days (5 to 730), the mean number of admissions was 1.7 (1 to 6), and the mean functional score (Lower Extremity Functional Score (LEFS)) was 60.13 (33 to 80). There was a significant correlation between the GHS and each of the outcome measures. A predictive model was generated from which the GHS could be used to predict the various outcome measures. Conclusion. The GHS can be used to predict the outcome of patients who present with an open fracture of the tibia. Our model generates a numerical value for each outcome measure that can be used in clinical practice to inform the treating team and to advise patients. Cite this article: Bone Joint J 2020;102-B(1):26–32

Proximal humerus fractures are the third most common fragility fractures with treatment remaining challenging. Mechanical fixation failure rates of locked plating range up to 35%, with 80% of them being related to the screws perforating the glenohumeral joint. Secondary screw perforation is a complex and not yet fully understood process. Biomechanical testing and finite element (FE) analysis are expected to help understand the importance of various risk factors. Validated FE simulations could be used to predict perforation risk. This study aimed to (1) develop an experimental model for single screw perforation in the humeral head and (2) evaluate and compare the ability of bone density measures and FE simulations to predict the experimental findings. Screw perforation was investigated experimentally via quasi-static ramped compression testing of 20 cuboidal bone specimens at 1 mm/min. They were harvested from four fresh-frozen human cadaveric proximal humeri of elderly donors (aged 85 ± 5 years, f/m: 2/2), surrounded with cylindrical embedding and implanted with a single 3.5 mm locking screw (DePuy Synthes, Switzerland) centrally. Specimen-specific linear µFE (ParOSol, ETH Zurich) and nonlinear explicit µFE (Abaqus, SIMULIA, USA) models were generated at 38 µm and 76 µm voxel sizes, respectively, from pre- and post-implantation micro-Computed Tomography (µCT) images (vivaCT40, Scanco Medical, Switzerland). Bone volume (BV) around the screw and in front of the screw tip, and tip-to-joint distance (TJD) were evaluated on the µCT images. The µFE models and BV were used to predict the experimental force at the initial screw loosening and the maximum force until perforation. Initial screw loosening, indicated by the first peak of the load-displacement curve, occurred at a load of 64.7 ± 69.8 N (range: 10.2 – 298.8 N) and was best predicted by the linear µFE (R. 2. = 0.90), followed by BV around the screw (R. 2. = 0.87). Maximum load was 207.6 ± 107.7 N (range: 90.1 – 507.6 N) and the nonlinear µFE provided the best prediction (R. 2. = 0.93), followed by BV in front of the screw tip (R. 2. = 0.89). Further, the nonlinear µFE could better predict screw displacement at maximum force (R. 2. = 0.77) than TJD (R. 2. = 0.70). The predictions of non-linear µFE were quantitatively correct. Our results indicate that while density-based measures strongly correlate with screw perforation force, the predictions by the nonlinear explicit µFE models were even better and, most importantly, quantitatively correct. These models have high potential to be utilized for simulation of more realistic fixations involving multiple screws under various loading cases. Towards clinical applications, future studies should investigate if explicit FE models based on clinically available CT images could provide similar prediction accuracies

Aims. Rotational acetabular osteotomy (RAO) has been reported to be effective in improving symptoms and preventing osteoarthritis (OA) progression in patients with mild to severe develomental dysplasia of the hip (DDH). However, some patients develop secondary OA even when the preoperative joint space is normal; determining who will progress to OA is difficult. We evaluated whether the preoperative cartilage condition may predict OA progression following surgery using T2 mapping MRI. Methods. We reviewed 61 hips with early-stage OA in 61 patients who underwent RAO for DDH. They underwent preoperative and five-year postoperative radiological analysis of the hip. Those with a joint space narrowing of more than 1 mm were considered to have 'OA progression'. Preoperative assessment of articular cartilage was also performed using 3T MRI with the T2 mapping technique. The region of interest was defined as the weightbearing portion of the acetabulum and femoral head. Results. There were 16 patients with postoperative OA progression. The T2 values of the centre to the anterolateral region of the acetabulum and femoral head in the OA progression cases were significantly higher than those in patients without OA progression. The preoperative T2 values in those regions were positively correlated with the narrowed joint space width. The receiver operating characteristic analysis revealed that the T2 value of the central portion in the acetabulum provided excellent discrimination, with OA progression patients having an area under the curve of 0.858. Furthermore, logistic regression analysis showed T2 values of the centre to the acetabulum’s anterolateral portion as independent predictors of subsequent OA progression (p < 0.001). Conclusion. This was the first study to evaluate the relationship between intra-articular degeneration using T2 mapping MRI and postoperative OA progression. Our findings suggest that preoperative T2 values of the hip can be better prognostic factors for OA progression than radiological measures following RAO. Cite this article: Bone Joint J 2021;103-B(9):1472–1478

Persistent post-surgical pain and associated disability are common after a traumatic fracture repair. Preliminary evidence suggests that patients' beliefs and perceptions may influence their prognosis. We sought to explore this association. We used data from the Fluid Lavage of Open Wounds trial to determine, in 1560 open fracture patients undergoing surgical repair, the association between Somatic PreOccupation and Coping (captured by the SPOC questionnaire) and recovery at 1 year. Of the 1218 open fracture patients with complete data available for analysis, 813 (66.7%) reported moderate to extreme pain at 1 yr. The addition of SPOC scores to an adjusted regression model to predict persistent pain improved the concordance statistic from 0.66 to 0.74, and found the greatest risk was associated with high SPOC scores [odds ratio: 5.63, 99% confidence interval (CI): 3.59–8.84, absolute risk increase 40.6%, 99% CI: 30.8%, 48.6%]. Thirty-eight per cent (484 of 1277) reported moderate to extreme pain interference at 1 yr. The addition of SPOC scores to an adjusted regression model to predict pain interference improved the concordance statistic from 0.66 to 0.75, and the greatest risk was associated with high SPOC scores (odds ratio: 6.06, 99% CI: 3.97–9.25, absolute risk increase: 18.3%, 95% CI: 11.7%, 26.7%). In our adjusted multivariable regression models, SPOC scores at 6 weeks post-surgery accounted for 10% of the variation in short form-12 physical component summary scores and 14% of short form-12 mental component summary scores at 1 yr. Amongst patients undergoing surgical repair of open extremity fractures, high SPOC questionnaire scores at 6 weeks post-surgery were predictive of persistent pain, reduced quality of life, and pain interference at 1 yr

Aims. The primary aim of this study was to develop a reliable, effective radiological score to assess the healing of humeral shaft fractures, the Radiographic Union Score for HUmeral fractures (RUSHU). The secondary aim was to assess whether the six-week RUSHU was predictive of nonunion at six months after the injury. Patients and Methods. Initially, 20 patients with radiographs six weeks following a humeral shaft fracture were selected at random from a trauma database and scored by three observers, based on the Radiographic Union Scale for Tibial fractures system. After refinement of the RUSHU criteria, a second group of 60 patients with radiographs six weeks after injury, 40 with fractures that united and 20 with fractures that developed nonunion, were scored by two blinded observers. Results. After refinement, the interobserver intraclass correlation coefficient (ICC) was 0.79 (95% confidence interval (CI) 0.67 to 0.87), indicating substantial agreement. At six weeks after injury, patients whose fractures united had a significantly higher median score than those who developed nonunion (10 vs 7; p < 0.001). A receiver operating characteristic curve determined that a RUSHU cut-off of < 8 was predictive of nonunion (area under the curve = 0.84, 95% CI 0.74 to 0.94). The sensitivity was 75% and specificity 80% with a positive predictive value (PPV) of 65% and a negative predictive value of 86%. Patients with a RUSHU < 8 (n = 23) were more likely to develop nonunion than those with a RUSHU ≥ 8 (n = 37, odds ratio 12.0, 95% CI 3.4 to 42.9). Based on a PPV of 65%, if all patients with a RUSHU < 8 underwent fixation, the number of procedures needed to avoid one nonunion would be 1.5. Conclusion. The RUSHU is reliable and effective in identifying patients at risk of nonunion of a humeral shaft fracture at six weeks after injury. This tool requires external validation but could potentially reduce the morbidity associated with delayed treatment of an established nonunion. Cite this article: Bone Joint J 2019;101-B:1300–1306

Aims. The COVID-19 pandemic has caused unprecedented disruption to elective orthopaedic services. The primary objective of this study was to examine changes in functional scores in patients awaiting total hip arthroplasty (THA), total knee arthroplasty (TKA), and unicompartmental knee arthroplasty (UKA). Secondary objectives were to investigate differences between these groups and identify those in a health state ‘worse than death’ (WTD). Methods. In this prospective cohort study, preoperative Oxford hip and knee scores (OHS/OKS) were recorded for patients added to a waiting list for THA, TKA, or UKA, during the initial eight months of the COVID-19 pandemic, and repeated at 14 months into the pandemic (mean interval nine months (SD 2.84)). EuroQoL five-dimension five-level health questionnaire (EQ-5D-5L) index scores were also calculated at this point in time, with a negative score representing a state WTD. OHS/OKS were analyzed over time and in relation to the EQ-5D-5L. Results. A total of 174 patients (58 THA, 74 TKA, 42 UKA) were eligible, after 27 were excluded (one died, seven underwent surgery, 19 non-responders). The overall mean OHS/OKS deteriorated from 15.43 (SD 6.92), when patients were added to the waiting list, to 11.77 (SD 6.45) during the pandemic (p < 0.001). There were significantly worse EQ-5D-5L index scores in the THA group (p = 0.005), with 22 of these patients (38%) in a health state WTD, than either the TKA group (20 patients; 27% WTD), or the UKA group (nine patients; 21% WTD). A strong positive correlation between the EQ-5D-5L index score and OHS/OKS was observed (r = 0.818; p < 0.001). Receiver operating characteristic analysis revealed that an OHS/OKS lower than nine predicted a health state WTD (88% sensitivity and 73% specificity). Conclusion. OHS/OKS deteriorated significantly among patients awaiting lower limb arthroplasty during the COVID-19 pandemic. Overall, 51 patients were in a health state WTD, representing 29% of our entire cohort, which is considerably worse than existing pre-pandemic data. Cite this article: Bone Jt Open 2023;4(3):138–145

Introduction. Forward solution joint models (FSMs) can be powerful tools, leading to fast and cost-efficient simulation revealing in vivo mechanics that can be used to predict implant longevity. Unlike most joint analysis methods, mathematical modeling allows for nearly instantaneous evaluations, yielding more rapid surgical technique and implant design iterations as well as earlier insight into the follow-up outcomes used to better assess potential success. The current knee FSM has been developed to analyze both the kinematics and kinetics of commercial TKA designs as well as novel implant designs. Objective. The objective of this study was to use the knee FSM to predict the condylar translations and axial rotation of both fixed- and mobile-bearing TKA designs during a deep knee bend activity and to compare these kinematics to known fluoroscopy evaluations. Methods. The knee joint is modeled mathematically using Kane's dynamics, incorporating muscle controllers to predict the muscle forces, contact detection algorithms to compute the knee joint forces, and nonlinear ligaments at the knee joint. The tibiofemoral kinematics data for 20 subjects implanted with fixed-bearing (FB) PS TKA and 20 subjects implanted with mobile-bearing (MB) PS TKA were collected using fluoroscopy data during a deep knee bend (DKB) activity from full extension to 120° of flexion. All subjects were implanted by the same surgeon. The same CAD models for these implanted were incorporated in the FSM to predict the tibiofemoral kinematics. The average component placement from fluoroscopy data were used as an initial condition for the placement of the component in the mathematical model. Results. Overall, fluoroscopy results showed patients experienced 6.8 mm and 6.4 mm posterior rollback of the lateral femoral condyle for FB and MB PS TKA groups, respectively. The FSM predicted 5.9 mm and 6.3 mm of lateral posterior rollback for FB and MB PS TKA models, respectively (Figure 1). On average, media condyle translated posteriorly −2.9 mm and −2.5 mm, for FB and MB subjects, respectively. The mathematical model prediction for FB and MB models was −1.4 mm and −2.4 mm, respectively (Figure 2). The overall axial rotation was 5.1° and 4.5°, for FB and MB subjects from fluoroscopy, respectively. The axial rotation prediction using the FSM was 6.0° and 4.2°, for FB and MB models, respectively (Figure 3). Conclusion. Overall, it is clear that the FSM can accurately predict both the patterns and magnitudes of fixed- and mobile-bearing TKA condylar translations and axial rotations, showing consistent rollback of the lateral condyle, less translation of the medial condyle, and consistent axial rotation throughout flexion, all of which were also observed in the fluoroscopy data. The correlation between the theoretically predicted and experimentally confirmed kinematic patterns demonstrates the viability of forward solution modeling as a valuable and accurate method to evaluate total joint replacement mechanics. For any figures or tables, please contact the authors directly

Background. Although there are predictive equations that estimate the total fat mass obtained from multiple-site ultrasound (US) measurements, the predictive equation of total fat mass has not been investigated solely from abdominal subcutaneous fat thickness. Therefore, the aims of this study were; (1) to develop regression-based prediction equations based on abdominal subcutaneous fat thickness for predicting fat mass in young- and middle-aged adults, and (2) to investigate the validity of these equations to be developed. Methods. The study was approved by the Local Research Ethics Committee (Decision number: GO 19/788). Twenty-seven males (30.3 ± 8.7 years) and eighteen females (32.4 ± 9.5 years) were randomly divided into two groups as the model prediction group (19 males and 12 females) and the validation group (8 males and 6 females). Total body fat mass was determined by dual-energy X-ray absorptiometry (DXA). Abdominal subcutaneous fat thickness was measured by US. The predictive equations for total fat mass from US were determined as fat thickness (in mm) × standing height (in m). Statistical analyses were performed using R version 4.0.0. The association between the total fat mass and the abdominal subcutaneous fat thickness was interpreted using the Pearson test. The linear regression analysis was used to predict equations for total body fat mass from the abdominal subcutaneous fat thickness acquired by US. Then these predictive equations were applied to the validation group. The paired t-test was used to examine the difference between the measured and the predicted fat masses, and Lin's concordance correlation coefficient (CCC) was used as a further measure of agreement. Results. There was a significant positive moderate correlation between the total fat mass and the abdominal subcutaneous fat thickness × height in the model prediction group of males (r = 0.588, p = 0.008), whereas significant positive very strong correlation was observed in the model prediction group of females (r = 0.896, p < 0.001). Predictive equations for DXA-measured total body fat mass from abdominal subcutaneous fat thickness using US were as follows: for males “Fat mass-DXA = 0.276 × (Fat thickness-US × Height) + 17.221” (R. 2. = 0.35, SEE = 3.6, p = 0.008); for females “Fat mass-DXA = 0.694 x (Fat thickness-US × Height) + 7.085” (R. 2. = 0.80, SEE = 2.8, p < 0.001). When fat mass prediction equations were applied to the validation groups, measured- and estimated-total fat masses in males and females were found similar (p = 0.9, p = 0.5, respectively). A good level of agreement between measurements in males and females was attained (CCC = 0.84, CCC = 0.76, respectively). Conclusion. We developed and validated prediction equations that are convenient for determining total fat masses in young- and middle-aged adults using abdominal subcutaneous fat thickness obtained from the US. The abdominal subcutaneous fat thickness obtained from a single region by US might provide a noninvasive quick and easy evaluation not only in clinical settings but also on the field

Introduction. Machine learning is a relatively novel method to orthopaedics which can be used to evaluate complex associations and patterns in outcomes and healthcare data. The purpose of this study is to utilize 3 different supervised machine learning algorithms to evaluate outcomes from a multi-center international database of a single shoulder prosthesis to evaluate the accuracy of each model to predict post-operative outcomes of both aTSA and rTSA. Methods. Data from a multi-center international database consisting of 6485 patients who received primary total shoulder arthroplasty using a single shoulder prosthesis (Equinoxe, Exactech, Inc) were analyzed from 19,796 patient visits in this study. Specifically, demographic, comorbidity, implant type and implant size, surgical technique, pre-operative PROMs and ROM measures, post-operative PROMs and ROM measures, pre-operative and post-operative radiographic data, and also adverse event and complication data were obtained for 2367 primary aTSA patients from 8042 visits at an average follow-up of 22 months and 4118 primary rTSA from 11,754 visits at an average follow-up of 16 months were analyzed to create a predictive model using 3 different supervised machine learning techniques: 1) linear regression, 2) random forest, and 3) XGBoost. Each of these 3 different machine learning techniques evaluated the pre-operative parameters and created a predictive model which targeted the post-operative composite score, which was a 100 point score consisting of 50% post-operative composite outcome score (calculated from 33.3% ASES + 33.3% UCLA + 33.3% Constant) and 50% post-operative composite ROM score (calculated from S curves weighted by 70% active forward flexion + 15% internal rotation score + 15% active external rotation). 3 additional predictive models were created to control for the time required for patient improvement after surgery, to do this, each primary aTSA and primary rTSA cohort was subdivided to only include patient data follow-up visits >20 months after surgery, this yielded 1317 primary aTSA patients from 2962 visits at an average follow-up of 50 months and 1593 primary rTSA from 3144 visits at an average follow-up of 42 months. Each of these 6 predictive models were trained using a random selection of 80% of each cohort, then each model predicted the outcomes of the remaining 20% of the data based upon the demographic, comorbidity, implant type and implant size, surgical technique, pre-operative PROMs and ROM measures inputs of each 20% cohort. The error of all 6 predictive models was calculated from the root mean square error (RMSE) between the actual and predicted post-op composite score. The accuracy of each model was determined by subtracting the percent difference of each RMSE value from the average composite score associated with each cohort. Results. For all patient visits, the XGBoost decision tree algorithm was the most accurate model for both aTSA & rTSA patients, with an accuracy of ∼89.5% for both aTSA and rTSA. However for patients with 20+ month visits only, the random forest decision tree algorithm was the most accurate model for both aTSA & rTSA patients, with an accuracy of ∼89.5% for both aTSA and rTSA. The linear regression model was the least accurate predictive model for each of the cohorts analyzed. However, it should be noted that all 3 machine learning models provided accuracy of ∼85% or better and a RMSE <12. (Table 1) Figures 1 and 2 depict the typical spread and RMSE of the actual vs. predicted total composite score associated with the 3 models for aTSA (Figure 1) and rTSA (Figure 2). Discussion. The results of this study demonstrate that multiple different machine learning algorithms can be utilized to create models that predict outcomes with higher accuracy for both aTSA and rTSA, for numerous timepoints after surgery. Future research should test this model on different datasets and using different machine learning methods in order to reduce over- and under-fitting model errors. For any figures or tables, please contact the authors directly

Aim. One of the surgical therapeutic options for periprosthetic joint infection (PJI) includes debridement, antibiotics, and implant retention (DAIR). Prognostically favorable criteria for DAIR include short duration of symptoms, stable implant, pathogen susceptible to a ‘biofilm-active’ antimicrobial agent, and intact soft-tissue conditions. Despite this, there is a proportion of failures after DAIR, possibly because the duration of infection is underestimated. With the hypothesis that the duration of infection correlates with the bacterial load, and hence, the bacterial load is associated with failure after DAIR, we aimed to investigate the association of bacterial load in the sonication fluid of mobile parts and clinical outcome after DAIR. Method. From our PJI cohort (2010–2021), patients with DAIR (both palliative and curative approaches) were reviewed retrospectively. Patients with hip, knee or shoulder arthroplasties fulfilling infection definition, available sonication results, and ≥2 years follow-up were included. Sonication results were categorized in ≤ or >1000 cfu/mL. Univariate analysis was performed to identify predictors for DAIR failure. Results. Out of 209 PJIs, we identified 96 patients (100 PJIs, 47.8%) with DAIR. In 67 (69.8%) patients with 71 PJIs, there was a follow-up of ≥2 years. The mean age was 72.7 (SD 12.99) years, 50% were male. The infection affected 36 hips (50.7%), 32 knees (45.1%) and 3 shoulders (4.2%). At follow-up, there were 29 (40.8%) cured and 42 (59.2%) failed cases. When comparing failed and cured cases, we found no difference in comorbidities and previously defined risk factors for PJI, ASA score, Charlson score, anatomic location, no. of previous surgeries, pathogenesis of infection or laboratory values. The proportion of patients with high bacterial load on mobile parts (i.e. >1000 cfu/mL) was significantly higher in the failed DAIR group than it was in the cured group (61.9% vs 20.7%, p<0.001). Conclusions. In this study, a high bacterial load in sonication fluid of mobile parts was associated with failure after DAIR in patients with PJI. Sonication may help to differentiate acute hematogenous seeding to the implant and late reactivation of a previously silent implant-associated infection

INTRODUCTION. Statistical shape models (SSM) have become a common tool to create reference models for design input and verification of total joint implants. In a recent discussion paper around Artificial Intelligence and Machine Learning, the FDA emphasizes the importance of independent test data [1]. A leave-one-out test is a standard way to evaluate the generalization ability of an SSM [2]; however, this test does not fulfill the independence requirement of the FDA. In this study, we constructed an SSM of the knee (femur and tibia). Next to the standard leave-one-out validation, we used an independent test set of patients from a different geographical region than the patients used to build the SSM. We assessed the ability of the SSM to predict the shapes of knees in this independent test set. METHODS. A dataset of 82 computed tomography (CT) scans of Caucasian patients (42 male, 40 female) from 11 different geographic locations in France, Germany, Austria, Italy and Australia were used as training set to make an SSM of the femur and tibia. A leave-one-out test was performed to assess the ability of the SSM to predict shapes within the training set. A test dataset of 4 CT scans of Caucasian patients from Russia were used for the validation. The SSM was fitted onto each of the femur and tibia shapes and the root mean square error (RMSE) was measured. RESULTS. The leave-one-out tests showed that the femur and tibia SSMs were able to predict patients in the input population with an RMSE of 0.59 ± 0.1 mm (average ± standard deviation) for the femur and 0.70 ± 0.1 mm for the tibia. The validation test showed that the femur and tibia SSMs were able to predict the shapes of the Russian patients with an RMSE 0.62 ± 0.1 mm for the femur and 0.71 ± 0.1 mm for the tibia. DISCUSSION. There were no significant differences in the ability of the SSM to predict femur and tibia shapes of patients in a new geographic region compared to the ability of the SSM to predict shapes within the training set. CONCLUSIONS. Based on this study, 11 different geographic locations in France, Germany, Austria, Italy and Australia provide a complete sample of the Caucasian population. Using an independent set of CT scans is a valuable tool to further validate the generalization ability of an SSM. For any figures or tables, please contact authors directly

Objectives. Researchers continue to seek easier ways to evaluate the quality of bone and screen for osteoporosis and osteopenia. Until recently, radiographic images of various parts of the body, except the distal femur, have been reappraised in the light of dual-energy X-ray absorptiometry (DXA) findings. The incidence of osteoporotic fractures around the knee joint in the elderly continues to increase. The aim of this study was to propose two new radiographic parameters of the distal femur for the assessment of bone quality. Methods. Anteroposterior radiographs of the knee and bone mineral density (BMD) and T-scores from DXA scans of 361 healthy patients were prospectively analyzed. The mean cortical bone thickness (CBTavg) and the distal femoral cortex index (DFCI) were the two parameters that were proposed and measured. Intra- and interobserver reliabilities were assessed. Correlations between the BMD and T-score and these parameters were investigated and their value in the diagnosis of osteoporosis and osteopenia was evaluated. Results. The DFCI, as a ratio, had higher reliability than the CBTavg. Both showed significant correlation with BMD and T-score. When compared with DFCI, CBTavg showed better correlation and was better for predicting osteoporosis and osteopenia. Conclusion. The CBTavg and DFCI are simple and reliable screening tools for the prediction of osteoporosis and osteopenia. The CBTavg is more accurate but the DFCI is easier to use in clinical practice. Cite this article: Q-F. He, H. Sun, L-Y. Shu, Y. Zhu, X-T. Xie, Y. Zhan, C-F. Luo. Radiographic predictors for bone mineral loss: Cortical thickness and index of the distal femur. Bone Joint Res 2018;7:468–475. DOI: 10.1302/2046-3758.77.BJR-2017-0332.R1

Aims. The aim of this study was to assess the prognostic value of the modified three-group Stulberg classification, which is based on the sphericity of the femoral head, in patients with Perthes’ disease. Methods. A total of 88 patients were followed from the time of diagnosis until a mean follow-up of 21 years. Anteroposterior pelvic and frog-leg lateral radiographs were obtained at diagnosis and at follow-up of one, five, and 21 years. At the five- and 21-year follow-up, the femoral heads were classified using a modified three-group Stulberg classification (round, ovoid, or flat femoral head). Further radiological endpoints at long-term follow-up were osteoarthritis (OA) of the hip and the requirement for total hip arthroplasty (THA). Results. There were 71 males (81%) and 17 females. A total of 13 patients had bilateral Perthes’ disease; thus 101 hips were analyzed. At five-year follow-up, 37 hips were round, 38 ovoid, and 26 flat. At that time, 66 hips (65%) were healed and 91 (90%) were skeletally immature. At long-term follow-up, when the mean age of the patients was 28 years (24 to 34), 20 hips had an unsatisfactory outcome (seven had OA and 13 had required THA). There was a strongly significant association between the modified Stulberg classification applied atfive-year follow-up and an unsatisfactory outcome at long-term follow-up (p < 0.001). Between the five- and 21-year follow-up, 67 hips (76%) stayed in their respective modified Stulberg group, indicating a strongly significant association between the Stulberg classifications at these follow-ups (p < 0.001). Conclusion. The modified Stulberg classification is a strong predictor of long-term radiological outcome in patients with Perthes’ disease. It can be applied at the healing stage, which is usually reached five years after the diagnosis is made and before skeletal maturity. Cite this article: Bone Joint J 2021;103-B(12):1815–1820

Aims. The primary aim of this study was to assess the rate of patient satisfaction one year after total knee arthroplasty (TKA) according to the focus of the question asked. The secondary aims were to identify independent predictors of patient satisfaction according to the focus of the question. Patients and Methods. A retrospective cohort of 2521 patients undergoing a primary unilateral TKA were identified from an established regional arthroplasty database. Patient demographics, comorbidities, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and 12-Item Short-Form Health Survey (SF-12) scores were collected preoperatively and one year postoperatively. Patient satisfaction was assessed using four questions, which focused on overall outcome, activity, work, and pain. Logistic regression analysis was used to identify independent preoperative predictors of increased stiffness when adjusting for confounding variables. Results. Using patient satisfaction with the overall outcome (n = 2265, 89.8%) as the standard, there was no difference in the rate of satisfaction for pain relief (n = 2277, odds ratio (OR) 0.95, 95% confident intervals (CI) 0.79 to 1.14, p = 0.60), but patients were more likely to be dissatisfied with activities (79.3%, n = 2000/2521, OR 2.22, 95% CI 1.96 to 2.70, p < 0.001) and work (85.8%, n = 2163/2521, OR 1.47, 95% CI 1.23 to 1.75, p < 0.001). Logistic regression analysis identified different predictors of satisfaction for each of the focused satisfaction questions. Overall satisfaction was influenced by diabetes (p = 0.03), depression (p = 0.004), back pain (p < 0.001), and SF-12 physical (p = 0.008) and mental (p = 0.01) components. Satisfaction with activities was influenced by depression (p = 0.001), back pain (p < 0.001), WOMAC stiffness score (p = 0.03), and SF-12 physical (p < 0.001) and mental (p < 0.001) components. Satisfaction with work was influenced by depression (p = 0.007), back pain (p < 0.001), WOMAC function (p = 0.04) and stiffness (p = 0.05) scores, and SF-12 physical (p < 0.001) and mental (p < 0.001) components. Satisfaction with pain relief was influenced by diabetes (p < 0.001), back pain (p < 0.001), and SF-12 mental component (p = 0.04). Conclusion. The focus of the satisfaction question significantly influences the rate and the predictors of patient satisfaction after TKA. Cite this article: Bone Joint J 2018;100-B:740–8

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. We quantitatively compared the 3D bone density distributions on CT scans performed on scaphoid waist fractures subacutely that went on to union or nonunion, and assessed whether 2D CT evaluations correlate with 3D bone density evaluations. Methods. We constructed 3D models from 17 scaphoid waist fracture CTs performed between four to 18 weeks after fracture that did not unite (nonunion group), 17 age-matched scaphoid waist fracture CTs that healed (union group), and 17 age-matched control CTs without injury (control group). We measured the 3D bone density for the distal and proximal fragments relative to the triquetrum bone density and compared findings among the three groups. We then performed bone density measurements using 2D CT and evaluated the correlation with 3D bone densities. We identified the optimal cutoff with diagnostic values of the 2D method to predict nonunion with receiver operating characteristic (ROC) curves. Results. In the nonunion group, both the distal (100.2%) and proximal (126.6%) fragments had a significantly higher bone density compared to the union (distal: 85.7%; proximal: 108.3%) or control groups (distal: 91.6%; proximal: 109.1%) using the 3D bone density measurement, which were statistically significant for all comparisons. 2D measurements were highly correlated to 3D bone density measurements (Spearman’s correlation coefficient (R) = 0.85 to 0.95). Using 2D measurements, ROC curve analysis revealed the optimal cutoffs of 90.8% and 116.3% for distal and proximal fragments. This led to a sensitivity of 1.00 if either cutoff is met and a specificity of 0.82 when both cutoffs are met. Conclusion. Using 3D modelling software, nonunions were found to exhibit bone density increases in both the distal and proximal fragments in CTs performed between four to 18 weeks after fracture during the course of treatment. 2D bone density measurements using standard CT scans correlate well with 3D models. In patients with scaphoid fractures, CT bone density measurements may be useful in predicting the likelihood of nonunion. Cite this article: Bone Joint J 2020;102-B(9):1200–1209

Aims. To identify the prevalence of neuropathic pain after lower limb fracture surgery, assess associations with pain severity, quality of life and disability, and determine baseline predictors of chronic neuropathic pain at three and at six months post-injury. Methods. Secondary analysis of a UK multicentre randomized controlled trial (Wound Healing in Surgery for Trauma; WHiST) dataset including adults aged 16 years or over following surgery for lower limb major trauma. The trial recruited 1,547 participants from 24 trauma centres. Neuropathic pain was measured at three and six months using the Doleur Neuropathique Questionnaire (DN4); 701 participants provided a DN4 score at three months and 781 at six months. Overall, 933 participants provided DN4 for at least one time point. Physical disability (Disability Rating Index (DRI) 0 to 100) and health-related quality-of-life (EuroQol five-dimension five-level; EQ-5D-5L) were measured. Candidate predictors of neuropathic pain included sex, age, BMI, injury mechanism, concurrent injury, diabetes, smoking, alcohol, analgaesia use pre-injury, index surgery location, fixation type, Injury Severity Score, open injury, and wound care. Results. The median age of the participants was 51 years (interquartile range 35 to 64). At three and six months post-injury respectively, 32% (222/702) and 30% (234/787) had neuropathic pain, 56% (396/702) and 53% (413/787) had chronic pain without neuropathic characteristics, and the remainder were pain-free. Pain severity was higher among those with neuropathic pain. Linear regression analyses found that those with neuropathic pain at six months post-injury had more physical disability (DRI adjusted mean difference 11.49 (95% confidence interval (CI) 7.84 to 15.14; p < 0.001) and poorer quality of life (EQ-5D utility -0.15 (95% CI -0.19 to -0.11); p < 0.001) compared to those without neuropathic characteristics. Logistic regression identified that prognostic factors of younger age, current smoker, below knee fracture, concurrent injuries, and regular analgaesia pre-injury were associated with higher odds of post-injury neuropathic pain. Conclusion. Pain with neuropathic characteristics is common after lower limb fracture surgery and persists to six months post-injury. Persistent neuropathic pain is associated with substantially poorer recovery. Further attention to identify neuropathic pain post-lower limb injury, predicting patients at risk, and targeting interventions, is indicated. Cite this article: Bone Joint J 2021;103-B(6):1047–1054

Aims. The aim of this study was to assess whether supine flexibility predicts the likelihood of curve progression in patients with adolescent idiopathic scoliosis (AIS) undergoing brace treatment. Methods. This was a retrospective analysis of patients with AIS prescribed with an underarm brace between September 2008 to April 2013 and followed up until 18 years of age or required surgery. Patients with structural proximal curves that preclude underarm bracing, those who were lost to follow-up, and those who had poor compliance to bracing (<16 hours a day) were excluded. The major curve Cobb angle, curve type, and location were measured on the pre-brace standing posteroanterior (PA) radiograph, supine whole spine radiograph, initial in-brace standing PA radiograph, and the post-brace weaning standing PA radiograph. Validation of the previous in-brace Cobb angle regression model was performed. The outcome of curve progression post-bracing was tested using a logistic regression model. The supine flexibility cut-off for curve progression was analyzed with receiver operating characteristic curve. Results. A total of 586 patients with mean age of 12.6 years (SD 1.2) remained for analysis after exclusion. The baseline Cobb angle was similar for thoracic major curves (31.6° (SD 3.8°)) and lumbar major curves (30.3° (SD 3.7°)). Curve progression was more common in the thoracic curves than lumbar curves with mean final Cobb angles of 40.5° (SD 12.5°) and 31.8° (SD 9.8°) respectively. This dataset matched the prediction model for in-brace Cobb angle with less mean absolute error in thoracic curves (0.61) as compared to lumbar curves (1.04). Reduced age and Risser stage, thoracic curves, increased pre-brace Cobb angle, and reduced correction and flexibility rates predicted increased likelihood of curve progression. Flexibility rate of more than 28% has likelihood of preventing curve progression with bracing. Conclusion. Supine radiographs provide satisfactory prediction for in-brace correction and post-bracing curve magnitude. The flexibility of the curve is a guide to determine the likelihood for brace success. Cite this article: Bone Joint J 2020;102-B(2):254–260

Objective. Low back pain (LBP) is a common debilitating condition with great socioeconomic impact. Identifying individuals at risk of LBP is challenging. We have shown IgG N-glycans are associated with LBP. Herewith, we used polygenic risk scores (PRS) from IgG-glycome to test predictability for LBP. Methods. Clusters of IgG-glycans were identified using weighted correlation network approach in TwinsUK (n = 4246). Genome-wide association studies were carried out for the clusters and top associated SNPs (p<5e-8) were extracted. Weighted PRS was calculated as the sum of the number of copies of effect allele from GWAS multiplied by their effect size using the UK Biobank data (n = 350000). The predictive capacity of the PRS for back pain in UK Biobank was estimated using logistic regression. Results. Multiple SNPs were found to be associated with the glycan clusters near genes known to be involved in glycosylation and the inflammatory response (e.g. ST6GAL1, B4GALT1, FUT8). A total of 175 SNPs was used to calculate weighted PRS. In UK Biobank the PRS was a statically significant, but poor, predictor of the risk of back pain (β = 0.126±0.050, p = 0.015, R. 2. = 2.6e-5). The SNPs on chromosome 14 in regulatory regions of FUT8 gene, one of the key governors of core fucosylation, were found to be significantly associated with back pain in UK Biobank (FDR-adjusted p-value < 0.05). Conclusions. These pilot data suggest that genetic component of glycosylation may be associated with the risk of LBP; however, its predictive ability is poor. Conflict of Interest: YSA is a co-owner of Maatschap PolyOmica. GL is a founder and CEO of Genos Glycoscience Research Laboratory. MBF and FMKW declare no conflict of interests. Sources of Funding: The research has been supported by the EC FP7 project PainOmics (grant agreement #602736) and conducted using the UK Biobank Resource (project # 18219)

Introduction. A subset of patients in cast awaiting fixation of ankle fractures require conversion to delayed external fixation (dEF). We aimed to evaluate the effect of delayed versus planned external fixation (pEF), then identify objective characteristics contributing to need for conversion. Method. We extracted data from our booking system to identify all ankle external fixation procedures between 2010 to 2022. Exclusions included open fractures, the skeletally immature, and pilon or talus fractures. Fractures were classified using the AO/OTA classification, then a matched cohort was identified based on fracture classification. We compared the planned, delayed and matched cohorts for demographics, posterior malleolar fragment (PMF) ratio, and degree of displacement at presentation. Results. We identified 25 pEF, 42 dEF, and 67 matched patients. Ankles with dEF had a 3.8 day longer time to ORIF from presentation than those who had pEF, and had an infection rate of 9.5%, compared to 4% in the pEF group. Two patients in the dEF group required further operative intervention. There were no infections or reoperations required in the pEF or matched groups. The dEF group were more likely to have ≥2 reductions (OR 4.13), a PMF ratio of >0.23 (OR 5.07), and have increased displacement at time of injury on lateral (32% vs 19%) and AP (62% vs 36%) radiographs. Discussion. Our retrospective study highlights the longer time to operation and increased infection rates of patients who do not get timely external fixation. We propose a series of objective parameters that predict failure of cast treatment and guide the surgeon to consider planned external fixation in some ankle

Aims. Our aim was to examine the Elixhauser and Charlson comorbidity indices, based on administrative data available before surgery, and to establish their predictive value for mortality for patients who underwent hip arthroplasty in the management of a femoral neck fracture. Patients and Methods. We analyzed data from 42 354 patients from the Swedish Hip Arthroplasty Register between 2005 and 2012. Only the first operated hip was included for patients with bilateral arthroplasty. We obtained comorbidity data by linkage from the Swedish National Patient Register, as well as death dates from the national population register. We used univariable Cox regression models to predict mortality based on the comorbidity indices, as well as multivariable regression with age and gender. Predictive power was evaluated by a concordance index, ranging from 0.5 to 1 (with the higher value being the better predictive power). A concordance index less than 0.7 was considered poor. We used bootstrapping for internal validation of the results. Results. The predictive power of mortality was poor for both the Elixhauser and Charlson comorbidity indices (concordance indices less than 0.7). The Charlson Comorbidity Index was superior to Elixhauser, and a model with age and gender was superior to both indices. Conclusion. Preoperative comorbidity from administrative data did not predict mortality for patients with a hip fracture treated by arthroplasty. This was true even if association on group level existed

Objectives. Intramedullary fixation is considered the most stable treatment for pertrochanteric fractures of the proximal femur and cut-out is one of the most frequent mechanical complications. In order to determine the role of clinical variables and radiological parameters in predicting the risk of this complication, we analysed the data pertaining to a group of patients recruited over the course of six years. Methods. A total of 571 patients were included in this study, which analysed the incidence of cut-out in relation to several clinical variables: age; gender; the AO Foundation and Orthopaedic Trauma Association classification system (AO/OTA); type of nail; cervical-diaphyseal angle; surgical wait times; anti-osteoporotic medication; complete post-operative weight bearing; and radiological parameters (namely the lag-screw position with respect to the femoral head, the Cleveland system, the tip-apex distance (TAD), and the calcar-referenced tip-apex distance (CalTAD)). Results. The incidence of cut-out across the sample was 5.6%, with a higher incidence in female patients. A significantly higher risk of this complication was correlated with lag-screw tip positioning in the upper part of the femoral head in the anteroposterior radiological view, posterior in the latero-lateral radiological view, and in the Cleveland peripheral zones. The tip-apex distance and the calcar-referenced tip-apex distance were found to be highly significant predictors of the risk of cut-out at cut-offs of 30.7 mm and 37.3 mm, respectively, but the former appeared more reliable than the latter in predicting the occurrence of this complication. Conclusion. The tip-apex distance remains the most accurate predictor of cut-out, which is significantly greater above a cut-off of 30.7 mm. Cite this article: G. Caruso, M. Bonomo, G. Valpiani, G. Salvatori, A. Gildone, V. Lorusso, L. Massari. A six-year retrospective analysis of cut-out risk predictors in cephalomedullary nailing for pertrochanteric fractures: Can the tip-apex distance (TAD) still be considered the best parameter?. Bone Joint Res 2017;6:481–488. DOI: 10.1302/2046-3758.68.BJR-2016-0299.R1

Aims. The aim of this study was to assess whether it is possible to predict the mortality, and the extent and time of neurological recovery from the time of the onset of symptoms and MRI grade, in patients with the cerebral fat embolism syndrome (CFES). This has not previously been investigated. Methods. The study included 34 patients who were diagnosed with CFES following trauma between 2012 and 2018. The clinical diagnosis was confirmed and the severity graded by MRI. We investigated the rate of mortality, the time and extent of neurological recovery, the time between the injury and the onset of symptoms, the clinical severity of the condition, and the MRI grade. All patients were male with a mean age of 29.7 years (18 to 70). The mean follow-up was 4.15 years (2 to 8), with neurological recovery being assessed by the Glasgow Outcome Scale and the Mini-Mental State Examination. Results. In all, seven who had early-onset CFES (< 24 hours), and a severe Takahashi grade on MRI, died. There was a significant association between the time of onset of neurological signs and mortality (p = 0.035). Mortality was also significantly associated with a severe Takahashi grade (p < 0.001). Among the 27 surviving patients, 26 (96.3%) recovered completely. One (3.7%) had a cognitive deficit. The mean time to recovery was 4.7 weeks (2 to 13), with late recovery aftereight eight weeks being recorded in three patients. Conclusion. There was a significantly increased rate of mortality in patients with CFES who had an early onset of symptoms and a severe grade on MRI. Complete neurological recovery can be expected in most patients with CFES who survive. Cite this article: Bone Joint J 2022;104-B(1):142–149

The primary objectives of this study were to: 1) identify risk factors for subsequent surgery following initial treatment of proximal humerus fractures, stratified by initial treatment type; 2) generate risk prediction tools to predict subsequent shoulder surgery following initial treatment; and 3) internally validate the discriminative ability of each tool. We identified patients ≥ 50 years with a diagnosis of proximal humerus fracture from 2004 to 2015 using linkable health datasets in Ontario, Canada. We used procedural and fee codes within 30 days of the index fracture to classify patients into treatment groups: 1) surgical fixation; 2) shoulder replacement; and 3) conservative. We used intervention and diagnosis codes to identify all instances of complication-related subsequent shoulder surgery following initial treatment within two years post fracture. We developed logistic regression models for randomly selected two thirds of each treatment group to evaluate the association of patient, fracture, surgical, and hospital variables on the odds of subsequent shoulder surgery following initial treatment. We used regression coefficients to compute points associated with each of the variables within each category, and calculated the risk associated with each point total using the regression equation. We used the final third of each cohort to evaluate the discriminative ability of the developed risk tools (via the continuous point total and a dichotomous point cut-off value for “higher” vs. “lower” risk determined by Receiver Operating Curves) using c-statistics. We identified 20,897 patients with proximal humerus fractures that fit our inclusion criteria for analysis, 2,414 treated with fixation, 1,065 treated with replacement, and 17,418 treated conservatively. The proportions of patients who underwent subsequent shoulder surgery within two years were 13.8%, 5.1%, and 1.3%, for fixation, replacement, and conservative groups, respectively. Predictors of reoperation following fixation included the use of a bone graft, and fixation with a nail or wire vs. a plate. The only significant predictor of reoperation following replacement was poor bone quality. The only predictor of subsequent shoulder surgery following conservative treatment was more comorbidities while patients aged 70+, and those discharged home following initial presentation (vs. admitted or transferred to another facility) had lower odds of subsequent shoulder surgery. The risk tools developed were able to discriminate between patients who did or did not undergo subsequent shoulder surgery in the derivation cohorts with c-statistics of 0.75–0.88 (continuous point total), and 0.82–0.88 (dichotomous cut-off), and 0.53–0.78 (continuous point total) and 0.51–0.79 (dichotomous cut-off) in the validation cohorts. Our results present potential factors associated with subsequent shoulder surgery following initial treatment of proximal humerus fractures, stratified by treatment type. Our developed risk tools showed good to strong discriminative ability in both the derivation and validation cohorts for patients treated with fixation, and conservatively. This indicates that the tools may be useful for clinicians and researchers. Future research is required to develop risk tools that incorporate clinical variables such as functional demands

Aims. Recent improvements in surgical technique and perioperative blood management after total joint replacement (TJR) have decreased rates of transfusion. However, as many surgeons transition to outpatient TJR, obtaining routine postoperative blood tests becomes more challenging. Therefore, we sought to determine if a preoperative outpatient assessment tool that stratifies patients based on numerous medical comorbidities could predict who required postoperative haemoglobin (Hb) measurement. Methods. We performed a prospective study of consecutive unilateral primary total knee arthroplasties (TKAs) and total hip arthroplasties (THAs) performed at a single institution. Prospectively collected data included preoperative and postoperative Hb levels, need for blood transfusion, length of hospital stay, and Outpatient Arthroplasty Risk Assessment (OARA) score. Results. A total of 504 patients met inclusion criteria. Mean age at time of arthroplasty was 65.3 years (SD 10.2). Of the patients, 216 (42.9%) were THAs and 288 (57.1%) were TKAs. Six patients required a blood transfusion postoperatively (1.19%). Transfusion after surgery was associated with lower postoperative day 1 Hb (median of 8.5 (interquartile range (IQR) 7.9 to 8.6) vs 11.3 (IQR 10.4 to 12.2); p < 0.001), longer length of stay (1 day (IQR 1 to 1) vs 2 days (IQR 2 to 3); p < 0.001), higher OARA score (median of 60.0 (IQR 40 to 75) vs 5.0 (IQR 0-35); p = 0.001), and total hip arthroplasty (p < 0.001). All patients who received a transfusion had an OARA score > 34; however, this did not reach statistical significance as a screening threshold. Conclusion. Risk of blood transfusion after primary TJR was uncommon in our series, with an incidence of 1.19%. Transfusion was associated with OARA scores > 60. The OARA score, not American Society of Anesthesiologists grade, reliably identified patients at risk for postoperative blood transfusion. Selective Hb monitoring may result in substantial cost savings in the era of cost containment. Cite this article: Bone Joint J 2021;103-B(1):65–70

Aims. To devise a method to quantify and optimize tightness when inserting cortical screws, based on bone characterization and screw geometry. Methods. Cortical human cadaveric diaphyseal tibiae screw holes (n = 20) underwent destructive testing to firstly establish the relationship between cortical thickness and experimental stripping torque (T. str. ), and secondly to calibrate an equation to predict T. str. Using the equation’s predictions, 3.5 mm screws were inserted (n = 66) to targeted torques representing 40% to 100% of T. str. , with recording of compression generated during tightening. Once the target torque had been achieved, immediate pullout testing was performed. Results. Cortical thickness predicted T. str. (R. 2. = 0.862; p < 0.001) as did an equation based on tensile yield stress, bone-screw friction coefficient, and screw geometries (R. 2. = 0.894; p < 0.001). Compression increased with screw tightness up to 80% of the maximum (R. 2. = 0.495; p < 0.001). Beyond 80%, further tightening generated no increase in compression. Pullout force did not change with variations in submaximal tightness beyond 40% of T. str. (R. 2. = 0.014; p = 0.175). Conclusion. Screw tightening between 70% and 80% of the predicted maximum generated optimum compression and pullout forces. Further tightening did not considerably increase compression, made no difference to pullout, and increased the risk of the screw holes being stripped. While further work is needed for development of intraoperative methods for accurate and reliable prediction of the maximum tightness for a screw, this work justifies insertion torque being considerably below the maximum. Cite this article: Bone Joint Res 2020;9(8):493–500

Aims. 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. Patients and Methods. The technique of measuring the FEAR index on MRI was defined and its reliability validated. A retrospective study assessed three groups of 20 patients: an unstable group of ‘borderline dysplastic hips’ with lateral centre edge angle (LCEA) less than 25° treated successfully by periacetabular osteotomy; a stable group of ‘borderline dysplastic hips’ with LCEA less than 25° treated successfully by impingement surgery; and an asymptomatic control group with LCEA between 25° and 35°. The following measurements were performed on both standardized radiographs and on MRI: LCEA, acetabular index, femoral anteversion, and FEAR index. Results. The FEAR index showed excellent intraobserver and interobserver reliability on both MRI and radiographs. The FEAR index was more reliable on radiographs than on MRI. The FEAR index on MRI was lower in the stable borderline group (mean -4.2° (. sd. 9.1°)) compared with the unstable borderline group (mean 7.9° (. sd. 6.8°)). With a FEAR index cut-off value of 2°, 90% of patients were correctly identified as stable or unstable using the radiological FEAR index, compared with 82.5% using the FEAR index on MRI. The FEAR index was a better predictor of instability on plain radiographs than on MRI. Conclusion. The FEAR index measured on MRI is less reliable and less sensitive than the FEAR index measured on radiographs. The cut-off value of 2° for radiological FEAR index predicted hip stability with 90% probability. Cite this article: Bone Joint J 2019;101-B:1578–1584

To examine whether Natural Language Processing (NLP) using a state-of-the-art clinically based Large Language Model (LLM) could predict patient selection for Total Hip Arthroplasty (THA), across a range of routinely available clinical text sources. Data pre-processing and analyses were conducted according to the Ai to Revolutionise the patient Care pathway in Hip and Knee arthroplasty (ARCHERY) project protocol (. https://www.researchprotocols.org/2022/5/e37092/. ). Three types of deidentified Scottish regional clinical free text data were assessed: Referral letters, radiology reports and clinic letters. NLP algorithms were based on the GatorTron model, a Bidirectional Encoder Representations from Transformers (BERT) based LLM trained on 82 billion words of de-identified clinical text. Three specific inference tasks were performed: assessment of the base GatorTron model, assessment after model-fine tuning, and external validation. There were 3911, 1621 and 1503 patient text documents included from the sources of referral letters, radiology reports and clinic letters respectively. All letter sources displayed significant class imbalance, with only 15.8%, 24.9%, and 5.9% of patients linked to the respective text source documentation having undergone surgery. Untrained model performance was poor, with F1 scores (harmonic mean of precision and recall) of 0.02, 0.38 and 0.09 respectively. This did however improve with model training, with mean scores (range) of 0.39 (0.31–0.47), 0.57 (0.48–0.63) and 0.32 (0.28–0.39) across the 5 folds of cross-validation. Performance deteriorated on external validation across all three groups but remained highest for the radiology report cohort. Even with further training on a large cohort of routinely collected free-text data a clinical LLM fails to adequately perform clinical inference in NLP tasks regarding identification of those selected to undergo THA. This likely relates to the complexity and heterogeneity of free-text information and the way that patients are determined to be surgical candidates

Objectives. In this prospective cohort study, we investigated whether patient-specific finite element (FE) models can identify patients at risk of a pathological femoral fracture resulting from metastatic bone disease, and compared these FE predictions with clinical assessments by experienced clinicians. Methods. A total of 39 patients with non-fractured femoral metastatic lesions who were irradiated for pain were included from three radiotherapy institutes. During follow-up, nine pathological fractures occurred in seven patients. Quantitative CT-based FE models were generated for all patients. Femoral failure load was calculated and compared between the fractured and non-fractured femurs. Due to inter-scanner differences, patients were analyzed separately for the three institutes. In addition, the FE-based predictions were compared with fracture risk assessments by experienced clinicians. Results. In institute 1, median failure load was significantly lower for patients who sustained a fracture than for patients with no fractures. In institutes 2 and 3, the number of patients with a fracture was too low to make a clear distinction. Fracture locations were well predicted by the FE model when compared with post-fracture radiographs. The FE model was more accurate in identifying patients with a high fracture risk compared with experienced clinicians, with a sensitivity of 89% versus 0% to 33% for clinical assessments. Specificity was 79% for the FE models versus 84% to 95% for clinical assessments. Conclusion. FE models can be a valuable tool to improve clinical fracture risk predictions in metastatic bone disease. Future work in a larger patient population should confirm the higher predictive power of FE models compared with current clinical guidelines. Cite this article: F. Eggermont, L. C. Derikx, N. Verdonschot, I. C. M. van der Geest, M. A. A. de Jong, A. Snyers, Y. M. van der Linden, E. Tanck. Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians? Towards computational modelling in daily clinical practice. Bone Joint Res 2018;7:430–439. DOI: 10.1302/2046-3758.76.BJR-2017-0325.R2

Aims. The best marker for assessing glycaemic control prior to total knee arthroplasty (TKA) remains unknown. The purpose of this study was to assess the utility of fructosamine compared with glycated haemoglobin (HbA1c) in predicting early complications following TKA, and to determine the threshold above which the risk of complications increased markedly. Patients and Methods. This prospective multi-institutional study evaluated primary TKA patients from four academic institutions. Patients (both diabetics and non-diabetics) were assessed using fructosamine and HbA1c levels within 30 days of surgery. Complications were assessed for 12 weeks from surgery and included prosthetic joint infection (PJI), wound complication, re-admission, re-operation, and death. The Youden’s index was used to determine the cut-off for fructosamine and HbA1c associated with complications. Two additional cut-offs for HbA1c were examined: 7% and 7.5% and compared with fructosamine as a predictor for complications. Results. Overall, 1119 patients (441 men, 678 women) were included in the study. Fructosamine level of 293 µmol/l was identified as the optimal cut-off associated with complications. Patients with high fructosamine (> 293 µmol/l) were 11.2 times more likely to develop PJI compared with patients with low fructosamine (p = 0.001). Re-admission and re-operation rates were 4.2 and 4.5 times higher in patients with fructosamine above the threshold (p = 0.005 and p = 0.019, respectively). One patient (1.7%) from the elevated fructosamine group died compared with one patient (0.1%) in the normal fructosamine group (p = 0.10). These complications remained statistically significant in multiple regression analysis. Unlike fructosamine, all three cut-offs for HbA1c failed to show a significant association with complications. Conclusion. Fructosamine is a valid and an excellent predictor of complications following TKA. It better reflects the glycaemic control, has greater predictive power for adverse events, and responds quicker to treatment compared with HbA1c. These findings support the screening of all patients undergoing TKA using fructosamine and in those with a level above 293 µmol/l, the risk of surgery should be carefully weighed against its benefit. Cite this article: Bone Joint J 2019;101-B(7 Supple C):3–9

Background. Structural bone allografts are an established treatment method for long-bone structural defects arising from such conditions as trauma, sarcoma, and osteolysis following total joint replacement. However, the quality of structural bone allografts is difficult to non-destructively assess prior to use. The functional lifetime of structural allografts depend on their ability to resist cyclic loading, which can lead to fracture even at stress levels well below the yield strength. Because allograft bone has limited capacity for remodeling, optimizing allograft selection for bone quality could decrease long-term fracture risk. Raman spectroscopy biomarkers can non-destructively assess the three primary components of bone (collagen, mineral, and water), and may predict the resistance of donor bone allografts to fracture from cyclic loads. The purpose of this study was to prospectively assess the ability of Raman biomarkers to predict number of cycles to fracture (“cyclic fatigue life”) of human allograft cortical bone. Methods. Twenty-one cortical bone specimens were from the mid-diaphysis of human donor bone tissue (bilateral femurs from 4 donors: 63M, 61M, 51F, 48F) obtained from the Musculoskeletal Transplant Foundation. Six Raman biomarkers were analyzed: collagen disorganization, type B carbonate substitution (a surrogate for mineral maturation), matrix mineralization, and 3 water compartments. Specimens underwent cyclic fatigue testing under fully reversed conditions at 35 and 45MPa (physiologically relevant stress levels for structural allografts). Specimens were tested to fracture or to 30 million cycles (“run-out”), simulating 15 years of moderate activity (i.e., 6000 steps per day). Multivariate regression analysis was performed using a tobit model (censored linear regression) for prediction of cyclic fatigue life. Specimens were right-censored at 30 million cycles. Results. All of the 6 biomarkers that were evaluated were independently associated with cyclic fatigue life (p < 0.05). The multivariate model explained 70% of the variance in cyclic fatigue life (R2=0.695, p<0.001,). Increasing disordered collagen (p<0.001) and loosely collagen-bound water compartments (p<0.001) were associated with decreased cyclic fatigue life. Increasing type B carbonate substitution (p<0.001), matrix mineralization (p<0.001), tightly collagen-bound water (p<0.001), and mineral-bound water (p=0.002) were associated with increased cyclic fatigue life. In the predictive model, 42% of variance in cyclic fatigue life was attributable to degree of collagen disorder, all bound water compartments accounted for 6%, and age and sex accounted for 17%. Conclusions. Raman biomarkers of three bone components (collagen, mineral, and water) predict cyclic fatigue life of human cortical bone. Increased baseline collagen disorder was associated with decreased cyclic fatigue life, and was the strongest determinant of cyclic fatigue life. Increased matrix mineralization and mineral maturation were associated with increased cyclic fatigue life. Bound-water compartments of bone contributed minimally to cyclic fatigue life. These results are complementary with prior Raman studies of monotonic testing of bone that reported decreased toughness and strength with increased collagen disorder and increased stiffness with increased bone mineralization and mineral maturation. This model should be prospectively validated. Raman analysis is a promising tool for the non-destructive evaluation of structural bone allograft quality and may be useful as a screening tool for selection of allograft bone. Acknowledgements. Supported by a grant from the Musculoskeletal Transplant Foundation. The Dudley P. Allen Fellowship (JYD), Wilbert J. Austin Professor of Engineering Chair (CMR) and the Leonard Case Jr. Professor of Engineering Chair (OA) are gratefully acknowledged

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. Our aim was to develop and validate nomograms that would predict the cumulative incidence of sarcoma-specific death (CISSD) and disease progression (CIDP) in patients with localized high-grade primary central and dedifferentiated chondrosarcoma. Methods. The study population consisted of 391 patients from two international sarcoma centres (development cohort) who had undergone definitive surgery for a localized high-grade (histological grade II or III) conventional primary central chondrosarcoma or dedifferentiated chondrosarcoma. Disease progression captured the first event of either metastasis or local recurrence. An independent cohort of 221 patients from three additional hospitals was used for external validation. Two nomograms were internally and externally validated for discrimination (c-index) and calibration plot. Results. In the development cohort, the CISSD at ten years was 32.9% (95% confidence interval (CI) 19.8% to 38.4%). Age at diagnosis, grade, and surgical margin were found to have significant effects on CISSD and CIDP in multivariate analyses. Maximum tumour diameter was also significantly associated with CISSD. In the development cohort, the c-indices for CISSD and CIDP at five years were 0.743 (95% CI 0.700 to 0.819) and 0.761 (95% CI 0.713 to 0.800), respectively. When applied to the validation cohort, the c-indices for CISSD and CIDP at five years were 0.839 (95% CI 0.763 to 0.916) and 0.749 (95% CI 0.672 to 0.825), respectively. The calibration plots for these two nomograms demonstrated good fit. Conclusion. Our nomograms performed well on internal and external validation and can be used to predict CISSD and CIDP after resection of localized high-grade conventional primary central and dedifferentiated chondrosarcomas. They provide a new tool with which clinicians can assess and advise individual patients about their prognosis. Cite this article: Bone Joint J 2020;102-B(12):1752–1759

Aims. Fixation of osteoporotic proximal humerus fractures remains challenging even with state-of-the-art locking plates. Despite the demonstrated biomechanical benefit of screw tip augmentation with bone cement, the clinical findings have remained unclear, potentially as the optimal augmentation combinations are unknown. The aim of this study was to systematically evaluate the biomechanical benefits of the augmentation options in a humeral locking plate using finite element analysis (FEA). Methods. A total of 64 cement augmentation configurations were analyzed using six screws of a locking plate to virtually fix unstable three-part fractures in 24 low-density proximal humerus models under three physiological loading cases (4,608 simulations). The biomechanical benefit of augmentation was evaluated through an established FEA methodology using the average peri-screw bone strain as a validated predictor of cyclic cut-out failure. Results. The biomechanical benefit was already significant with a single cemented screw and increased with the number of augmented screws, but the configuration was highly influential. The best two-screw (mean 23%, SD 3% reduction) and the worst four-screw (mean 22%, SD 5%) combinations performed similarly. The largest benefits were achieved with augmenting screws purchasing into the calcar and having posteriorly located tips. Local bone mineral density was not directly related to the improvement. Conclusion. The number and configuration of cemented screws strongly determined how augmentation can alleviate the predicted risk of cut-out failure. Screws purchasing in the calcar and posterior humeral head regions may be prioritized. Although requiring clinical corroborations, these findings may explain the controversial results of previous clinical studies not controlling the choices of screw augmentation

Objectives. Preservation of posterior condylar offset (PCO) has been shown to correlate with improved functional results after primary total knee arthroplasty (TKA). Whether this is also the case for revision TKA, remains unknown. The aim of this study was to assess the independent effect of PCO on early functional outcome after revision TKA. Methods. A total of 107 consecutive aseptic revision TKAs were performed by a single surgeon during an eight-year period. The mean age was 69.4 years (39 to 85) and there were 59 female patients and 48 male patients. The Oxford Knee Score (OKS) and Short-form (SF)-12 score were assessed pre-operatively and one year post-operatively. Patient satisfaction was also assessed at one year. Joint line and PCO were assessed radiographically at one year. Results. There was a significant improvement in the OKS (10.6 points, 95% confidence interval (CI) 8.8 to 12.3) and the SF-12 physical component score (5.9, 95% CI 4.1 to 7.8). PCO directly correlated with change in OKS (p < 0.001). Linear regression analysis confirmed the independent effect of PCO on the OKS (p < 0.001) and the SF-12 physical score (p = 0.02). The overall rate of satisfaction was 85% and on logistic regression analysis improvement in the OKS (p = 0.002) was a significant predictor of patient satisfaction, which is related to PCO; although this was not independently associated with satisfaction. Conclusion. Preservation of PCO should be a major consideration when undertaking revision TKA. The option of increasing PCO to balance the flexion gap while maintaining the joint line should be assessed intra-operatively. Cite this article: N. D. Clement, D. J. MacDonald, D. F. Hamilton, R. Burnett. Posterior condylar offset is an independent predictor of functional outcome after revision total knee arthroplasty. Bone Joint Res 2017;6:172–178. DOI: 10.1302/2046-3758.63.BJR-2015-0021.R1

Introduction. The use of bone cement as a fixation agent has ensured the long-term functionality of THA implants . 1. However, some studies have shown the undesirable effect of wear of stem-cement interface, due to the release of metals and polymeric debris lead to implant failure . 2,3. Debris is generated by the micromotion together with a severely corrosive medium present in the crevice of stem-cement interface . 3,4. FEA studies showed that micromotion can affect osseointegration and fretting wear . 5,6. The aim of this research is to investigate if the micromotions measures from in silico analysis of the stem-cement correlate with the fretting-corrosion damage observed on in vitro testing. Methods. The in vitro fretting-corrosion testing was made with positioning and loading based on ISO 7206-4 and ISO 7206-6. It was used Exeter stems embedded in bone cement (PMMA) and immersed in a saline solution (9.0 g/L of NaCl). A fatigue testing system (Instron 8872, USA) was used to conduct the test, applying a sinusoidal cyclic load at 5.0 Hz. The tests were finished after 10 million cycles and images of stem surfaces were taken with a photographic camera (Canon EOS Rebel T6i, Japan) and a stereoscope (Leica M165C, Germany). For the computational analysis, the same testing configurations were modeled on software ANSYS. The analysis was performed using linear isotropic elasticity for both stem (E=193GPa; ⱱ=0.27; σ. y. =400MPa) and PMMA cement (E=2.7GPa; ⱱ=0.35; σ. u. =76MPa). 7,8. . A second-order tetrahedral element was used to mesh all components with a size of 0.5 mm in the stem-cement contact area, increasing until 1.0 mm outside from them. A frictional contact (µ=0.25) with an augmented Lagrange formulation was used. The third cycle of loading was evaluated and a variation of sliding distance less than 10% was set as convergence criteria. The micromotion was measured as the sliding distance on the stem-cement interface. Results and Discussion. The in silico analysis showed the presence of areas almost without micromotion in the proximal lateral and distal medial regions. In these regions, there is no evidence of fretting-corrosion after the in vitro testing. The lack of micromotion is caused by the debonding due to testing configurations and implant design. The absence of contact doesn't allow wear by abrasion or third body, avoiding the fretting-corrosion damage. For the regions distal lateral and proximal medial, it is possible to observe fretting-corrosion due to micromotions, which is supported by the in silico analysis results. The region proximal medial had the highest micromotion on computational analysis and the fretting-corrosion was more severe on laboratory testing, reinforcing the relevance of micromotion in the fretting-corrosion damage on the stem-cement interface. Conclusion. The results indicate a correlation of micromotion calculated by in silico analysis and fretting-corrosion damage observed on in vitro testing. The developed FEA model may be a useful tool to predict the fretting-corrosion damage on the THA implants on pre-clinical testing. Additional efforts are needed to apply this tool on bone-implant systems to predict fretting-corrosion damage observed in vivo. For any figures or tables, please contact authors directly

Acetabular dysplasia (AD) can cause hip pain and early osteoarthritis. Lateral Centre Edge Angle (LCEA) and sourcil angle (AI) are plain radiographic measures of acetabular morphology, however there is little agreement as to what constitutes mild, moderate or severe dysplasia. This study aims to establish the correlation, if any, between two-dimensional (XR) and three-dimensional (CT) measurements of acetabular morphology and to establish the level of femoral head cover (CTFHC) for different levels of dysplasia. Methods. Governance board approved retrospective study. 353 PAOs performed by the senior author between January 2014 and December 2017 were included. Exclusion criteria were inadequate pre-operative CT imaging and/or plain radiographs, previous pelvic/hip surgery, acetabular retroversion, or femoral head asphericity. Of the remainder, 84 had 3D analysis by clinical graphics giving measurements for CTFHC, LCEA at 1100, 1200, 1300 and sourcil angle (AI). XRLCEA, AI, posterior wall index (PWI), and anterior wall index (AWI), were measured from supine AP pelvis radiographs. Pearson correlation coefficient, and mean CTFHC for stratified LCEAs were calculated. A linear regression model to predict CTFHC from XRLCEA was validated against these. Results. XRLCEA correlated very strongly with total femoral head coverage (Pearson=0.917, p<0.001). Mean CTFHC with XRLCEA between 15°-19.9° was 55% (range 51–59%). At 25° −29.9° mean CTFHC was 61%. There was a linear relation of CTFHC with XR LCEA such that CTFHC = 41.5 + 0.78(XRLCEA). This linear regression model predicted CTFHC 55% (95%CI 54–56%) for XRLCEA of 17.5°, and CTFHC 63% (95%CI 62–64%) for XRLCEA 27.5°. Conclusions. Currently an XRLCEA greater than 25° is considered normal. Previously reported normal values for CTFHC are 71–75%. This study demonstrates that those with acetabular parameters considered normal, may have low CTFHC and AD should be considered as a cause for their hip pain

Pre-operative 3D glenoid planning improves component placement in terms of version, inclination, offset and orientation. Version and inclination measurements require the position of the inferior angle. As a consequence, current planning tools require a 3D model of the full scapula to accurately determine the glenoid parameters. Statistical shape models (SSMs) can be used to reconstruct the missing anatomy of bones. Therefore, the objective of this study is to develop and validate an SSM for the reconstruction of the inferior scapula, hereby reducing the irradiation exposure for patients. The training dataset for the statistical shape consisted of 110 CT images from patients without observable scapulae pathologies as judged by an experienced shoulder surgeon. 3D scapulae models were constructed from the segmented images. An open-source non-rigid B-spline-based registration algorithm was used to obtain point-to-point correspondences between the models. A statistical shape model was then constructed from the dataset using principal component analysis. Leave-one-out cross-validation was performed to evaluate the accuracy of the predicted glenoid parameters from virtual partial scans. Five types of virtual partial scans were created on each of the training set models, where an increasing amount of scapular body was removed to mimic a partial CT scan. The statistical shape model was reconstructed using the leave-one-out method, so the corresponding training set model is no longer incorporated in the shape model. Reconstruction was performed using a Monte Carlo Markov chain algorithm, random walk proposals included both shape and pose parameters, the closest fitting proposal was selected for the virtual reconstruction. Automatic 3D measurements were performed on both the training and reconstructed 3D models, including glenoid version, inclination, glenoid centre point position and glenoid offset. In terms of inclination and version we found a mean absolute difference between the complete model and the different virtual partial scan models of 0.5° (SD 0.4°). The maximum difference between models was 3° for inclination and 2° for version. For offset and centre point position the mean absolute difference was 0 mm with an absolute maximum of 1 mm. The magnitude of the mean and maximum differences for all anatomic measurements between the partial scan and complete models is smaller than the current surgical accuracy. Considering these findings, we believe a SSM based reconstruction technique can be used to accurately reconstruct the glenoid parameters from partial CT scans

Aims

The aims of this study were to identify means to quantify coronal plane displacement associated with distal radius fractures (DRFs), and to understand their relationship to radial inclination (RI).

Aims. The primary aim of this study was to quantify the improvement in patient-reported outcome measures (PROMs) following total hip arthroplasty (THA), as well as the extent of any deterioration through the seven-year follow-up. The secondary aim was to identify predictors of PROM improvement and deterioration. Patients and Methods. A total of 976 patients were enrolled into a prospective, international, multicentre study. Patients completed a battery of PROMs prior to THA, at three months post-THA, and at one, three, five, and seven-years post-THA. The Harris Hip Score (HHS), the 36-Item Short-Form Health Survey (SF-36) Physical Component Summary (PCS), the SF-36 Mental Component Summary (MCS), and the EuroQol five-dimension three-level (EQ-5D) index were the primary outcomes. Longitudinal changes in each PROM were investigated by piece-wise linear mixed effects models. Clinically significant deterioration was defined for each patient as a decrease of one half of a standard deviation (group baseline). Results. Improvements were noted in each PROM between the preoperative and one-year visits, with one-year values exceeding age-matched population norms. Patients with difficulty in self-care experienced less improvement in HHS (odds ratio (OR) 2.2; p = 0.003). Those with anxiety/depression experienced less improvement in PCS (OR -3.3; p = 0.002) and EQ-5D (OR -0.07; p = 0.005). Between one and seven years, obesity was associated with deterioration in HHS (1.5 points/year; p = 0.006), PCS (0.8 points/year; p < 0.001), and EQ-5D (0.02 points/year; p < 0.001). Preoperative difficulty in self-care was associated with deterioration in HHS (2.2 points/year; p < 0.001). Preoperative pain from other joints was associated with deterioration in MCS (0.8 points/year; p < 0.001). All aforementioned factors were associated with clinically significant deterioration in PROMs (p < 0.035), except anxiety/depression with regard to PCS (p = 0.060). Conclusion. The present study finds that patient factors affect the improvement and deterioration in PROMs over the medium term following THA. Special attention should be given to patients with risk factors for decreased PROMs, both preoperatively and during follow-up. Cite this article: Bone Joint J 2019;101-B:768–778

Aims. The aim of the study was to develop a quantitative scoring system to predict whether a large-to-massive rotator cuff tear was arthroscopically reparable prior to surgery. Patients and Methods. We conducted a retrospective review of the pre-operative MR imaging and surgical records of 87 patients (87 shoulders) who underwent arthroscopic repair of a large-to-massive rotator cuff tear. Patients were divided into two groups, based on the surgical outcome of the repair. Of the 87 patients, 53 underwent complete repair (Group I) and 34 an incomplete repair (Group II). Pre-operative MR images were reviewed to quantify several variables. Between-group differences were evaluated and multiple logistic regression analysis was used to calculate the predictive value of significant variables. The reparability index (RI) was constructed using the odds ratios of significant variables and a receiver operating characteristic curve analysis performed to identify the optimal RI cutoff to differentiate between the two groups. Results. The following variables were identified as independent predictors of arthroscopic reparability: the size of the defect with medial-lateral diameter (cutoff, 4.2 cm) and anterior-posterior diameter (cutoff, 3.7cm); Patte’s grade of muscle atrophy (cutoff, grade 3) and Goutallier grade of fatty degeneration (cutoff, grade 3). An RI cutoff value of 2.5 provided the highest differentiation between groups I and II, with an area under the curve of 0.964, and a sensitivity of 73.5% and specificity of 96.2%. Conclusion. The RI developed in our study may prove to be an efficient clinical scoring system to predict whether a large-to-massive rotator cuff tear is arthroscopically reparable. Cite this article: Bone Joint J 2016;98-B:1656–61

Introduction. Fretting corrosion at the taper interface of modular connections can be studied using Finite Element (FE) analyses. However, the loading conditions in FE studies are often simplified, or based on generic activity patterns. Using musculoskeletal modeling, subject-specific muscle and joint forces can be calculated, which can then be applied to a FE model for wear predictions. The objective of the current study was to investigate the effect of incorporating more detailed activity patterns on fretting simulations of modular connections. Methods. Using a six-camera motion capture system, synchronized force plates, and 45 optical markers placed on 6 different subjects, data was recorded for three different activities: walking at a comfortable speed, chair rise, and stair climbing. Musculoskeletal models, using the Twente Lower Extremity Model 2.0 implemented in the AnyBody modeling System™ (AnyBody Technology A/S, Aalborg, Denmark; figure1), were used to determine the hip joint forces. Hip forces for the subject with the lowest and highest peak force, as well as averaged hip forces were then applied to an FE model of a modular taper connection (Biomet Type-1 taper with a Ti6Al4V Magnum +9 mm adaptor; Figure 2). During the FE simulations, the taper geometry was updated iteratively to account for material removal due to wear. The wear depth was calculated based on Archard's Law, using contact pressures, micromotions, and a wear factor, which was determined from accelerated fretting experiments. Results. The forces for the comfortable walking speed had the highest peak forces for the maximum peak subject, with a maximum peak force of 3644 N, followed by walking up stairs, with a similar maximum peak force of 3626 N. The chair rise had a lower maximum peak force of 2240 N (−38.5%). The simulated volumetric wear followed the trends seen in the peaks of the predicted hip joint forces, with the largest wear volumes predicted for a comfortable walking speed, followed by the stairs up activity and the chair rise (Figure 3). The subjects with the highest peak forces produced the most volumetric wear in all cases. However, the lowest peak subject had a higher volumetric wear for the stairs up case than the average subject. Discussion. This study explored the effect of subject-specific variations in hip joint loads on taper fretting. The results indicate that taper wear was predominantly affected by the magnitudes of the peak forces, rather than by the orientation of the force. A more comprehensive study, capturing the full spectrum of patient variability, can help identifying parameters that accelerate fretting corrosion. Such a study should also incorporate other sources of variability, including surgical factors such as implant orientation, sizing, and offset. These factors also affect hip joint forces, and can be evaluated in musculoskeletal models such as presented here

Aims

In-hospital length of stay (LOS) and discharge dispositions following arthroplasty could act as surrogate measures for improvement in patient pathways, and have major cost saving implications for healthcare providers. With the ever-growing adoption of robotic technology in arthroplasty, it is imperative to evaluate its impact on LOS. The objectives of this study were to compare LOS and discharge dispositions following robotic arm-assisted total knee arthroplasty (RO TKA) and unicompartmental arthroplasty (RO UKA) versus conventional technique (CO TKA and UKA).

The requirement for release of collateral ligaments to achieve a stable, balanced total knee replacement has been reported to arise in about 50% to 100% of procedures. This wide range reflects a lack of standardised quantitative indicators to determine the necessity for a release. Using recent advances in computerised navigation, we describe two navigational predictors which provide quantitative measures that can be used to identify the need for release. The first was the ability to restore the mechanical axis before any bone resection was performed and the second was the discrepancy in the measured medial and lateral joint spaces after the tibial osteotomy, but before any femoral resection. These predictors showed a significant association with the need for collateral ligament release (p < 0.001). The first predictor using the knee stress test in extension showed a sensitivity of 100% and a specificity of 98% and the second, the difference between medial and lateral gaps in millimetres, a sensitivity of 83% and a specificity of 95%. The use of the two navigational predictors meant that only ten of the 93 patients required collateral ligament release to achieve a stable, neutral knee

Background. The overall goal of total knee arthroplasty (TKA) is to facilitate the restoration of native function following late stage osteoarthritis and for this reason it is important to develop a thorough understanding of the mechanics of a normal healthy knee. While there are several methods for assessing TKA mechanics, these methods have limitations that make them prohibitive to both replicating physiological systems and evaluating non-implanted knees. These limitations can be circumvented through the development of mathematical models that use anatomical and physiological inputs to computationally simulate joint mechanics. This can be done in an inverse or forward manner to solve for either joint forces or motions respectively. The purpose of this study is to evaluate one such forward model and determine the accuracy of the predicted motions using fluoroscopy. Methods. In vivo kinematics were determined during flexion from full extension to 120 degrees for ten normal, healthy, subjects using fluoroscopy and a 3D-to-2D registration method. All ten subjects had previously undergone CT scans allowing for the digital reconstruction of native femur and tibia geometries. These geometries were then input into a ridged body forward model based on Kane's system of dynamics. The resulting kinematics determined through fluoroscopy and the mathematical model were compared for all of the ten subjects. Results. The three kinematic parameters evaluated for this study were the initial positioning and translation of the medial and lateral condylar contact point in addition to the axial position and rotation of the femur with respect to the tibia. The model simulations demonstrated an average of −2.16mm of medial condyle translation, −14.03mm of lateral condyle translation, and 20.09°of axial rotation. Through fluoroscopy, subjects demonstrated an average of −3.63mm of medial condyle translation, −16.02mm of lateral condyle translation, and 15.65°of axial rotation. Comparing these two methods the model predicted on average an additional 1.47mm of medial condyle translation, 1.98mm of lateral condyle translation, and 4.44° less axial rotation compared to the fluoroscopic analysis of the same ten subjects. Conclusion. In comparing the simulation kinematics to the that of the fluoroscopic assessment, the results are comparably similar demonstrating a forward model can be a viable assessment of knee kinematics in the future. By validating mathematical simulation as a feasible means of mechanical assessment, it becomes possible to evaluate mechanics using inputs to reflect extraordinary and theoretical instances such as trauma patients and congenital deformities unable to be assessed by other methods. The nature of the model also allows for a seamless transition to assess TKA mechanics, creating a more efficient means of evaluating both device design and surgical technique