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

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. 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)

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. Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential. Cite this article: Bone Jt Open 2024;5(8):671–680

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 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

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

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

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

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.

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

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

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

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

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

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

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. 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

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. 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. 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. 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

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

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 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

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

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

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

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. 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

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