Aims. The aims of this study were to determine the success of a reconstruction algorithm used in major acetabular bone loss, and to further define the indications for custom-made implants in major acetabular bone loss. Methods. We reviewed a consecutive series of Paprosky type III acetabular defects treated according to a reconstruction algorithm. IIIA defects were planned to use a superior augment and hemispherical acetabular component. IIIB defects were planned to receive either a hemispherical acetabular component plus augments, a cup-cage reconstruction, or a custom-made implant. We used national digital health records and registry reports to identify any reoperation or re-revision procedure and Oxford Hip Score (OHS) for patient-reported outcomes. Implant survival was determined via Kaplan-Meier analysis. Results. A total of 105 procedures were carried out in 100 patients (five bilateral) with a mean age of 73 years (42 to 94). In the IIIA defects treated, 72.0% (36 of 50) required a porous metal augment; the remaining 14 patients were treated with a hemispherical acetabular component alone. In the IIIB defects, 63.6% (35 of 55) underwent reconstruction as planned with 20 patients who actually required a hemispherical acetabular component alone. At mean follow-up of 7.6 years, survival was 94.3% (95% confidence interval 97.4 to 88.1) for all-cause revision and the overall dislocation rate was 3.8% (4 of 105). There was no difference observed in survival between type IIIA and type IIIB defects and whether a hemispherical implant alone was used for the reconstruction or not. The mean gain in OHS was 16 points. Custom-made implants were only used in six cases, in patients with either a mega-defect in which the anteroposterior diameter > 80 mm, complex pelvic discontinuity, and massive bone loss in a small pelvis. Conclusion. Our findings suggest that a reconstruction algorithm can provide a successful approach to reconstruction in major acetabular bone loss. The use of custom implants has been defined in this series and accounts for < 5% of cases. Cite this article: Bone Joint J 2024;106-B(5 Supple B):47–53

In March 2012, an algorithm for the treatment of intertrochanteric fractures of the hip was introduced in our academic department of Orthopaedic Surgery. It included the use of specified implants for particular patterns of fracture. In this cohort study, 102 consecutive patients presenting with an intertrochanteric fracture were followed prospectively (post-algorithm group). Another 117 consecutive patients who had been treated immediately prior to the implementation of the algorithm were identified retrospectively as a control group (pre-algorithm group). The total cost of the implants prior to implementation of the algorithm was $357 457 (mean: $3055 (1947 to 4133)); compared with $255 120 (mean: $2501 (1052 to 4133)) after its implementation. There was a trend toward fewer complications in patients who were treated using the algorithm (33% pre- versus 22.5% post-algorithm; p = 0.088). Application of the algorithm to the pre-algorithm group revealed a potential overall cost saving of $70 295. The implementation of an evidence-based algorithm for the treatment of intertrochanteric fractures reduced costs while maintaining quality of care with a lower rate of complications and re-admissions. Cite this article: Bone Joint J 2014;96-B:1192–7

Aims. To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. Methods. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration). Results. The developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set. Conclusion. Using high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making. Cite this article: Bone Jt Open 2023;4(3):168–181

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

Aims. There remains a lack of consensus regarding the management of chronic anterior sternoclavicular joint (SCJ) instability. This study aimed to assess whether a standardized treatment algorithm (incorporating physiotherapy and surgery and based on the presence of trauma) could successfully guide management and reduce the number needing surgery. Methods. Patients with chronic anterior SCJ instability managed between April 2007 and April 2019 with a standardized treatment algorithm were divided into non-traumatic (offered physiotherapy) and traumatic (offered surgery) groups and evaluated at discharge. Subsequently, midterm outcomes were assessed via a postal questionnaire with a subjective SCJ stability score, Oxford Shoulder Instability Score (OSIS, adapted for the SCJ), and pain visual analogue scale (VAS), with analysis on an intention-to-treat basis. Results. A total of 47 patients (50 SCJs, three bilateral) responded for 75% return rate. Of these, 31 SCJs were treated with physiotherapy and 19 with surgery. Overall, 96% (48/50) achieved a stable SCJ, with 60% (30/50) achieving unrestricted function. In terms of outcomes, 82% (41/50) recorded good-to-excellent OSIS scores (84% (26/31) physiotherapy, 79% (15/19) surgery), and 76% (38/50) reported low pain VAS scores at final follow-up. Complications of the total surgical cohort included a 19% (5/27) revision rate, 11% (3/27) frozen shoulder, and 4% (1/27) scar sensitivity. Conclusion. This is the largest midterm series reporting chronic anterior SCJ instability outcomes when managed according to a standardized treatment algorithm that emphasizes the importance of appropriate patient selection for either physiotherapy or surgery, based on a history of trauma. All but two patients achieved a stable SCJ, with stability maintained at a median of 70 months (11 to 116) for the physiotherapy group and 87 months (6 to 144) for the surgery group. Cite this article: Bone Jt Open 2022;3(10):815–825

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

Aims. The management of mid-shaft clavicle fractures (MSCFs) has evolved over the last three decades. Controversy exists over which specific fracture patterns to treat and when. This review aims to synthesize the literature in order to formulate an appropriate management algorithm for these injuries in both adolescents and adults. Methods. This is a systematic review of clinical studies comparing the outcomes of operative and nonoperative treatments for MSCFs in the past 15 years. The literature was searched using, PubMed, Google scholar, OVID Medline, and Embase. All databases were searched with identical search terms: mid-shaft clavicle fractures (± fixation) (± nonoperative). Results. Using the search criteria identified, 247 studies were deemed eligible. Following initial screening, 220 studies were excluded on the basis that they were duplicates and/or irrelevant to the research question being posed. A total of 27 full-text articles remained and were included in the final review. The majority of the meta-analyses draw the same conclusions, which are that operatively treated fractures have lower nonunion and malunion rates but that, in those fractures which unite (either operative or nonoperative), the functional outcomes are the same at six months. Conclusion. With regard to the adolescent population, the existing body of evidence is insufficient to support the use of routine operative management. Regarding adult fractures, the key to identifying patients who benefit from operative management lies in the identification of risk factors for nonunion. We present an algorithm that can be used to guide both the patient and the surgeon in a joint decision-making process, in order to optimize patient satisfaction and outcomes. Cite this article: Bone Jt Open 2022;3(11):850–858

Aims. The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance. Methods. A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset. Results. The convolutional neural network we built performed well when detecting loosening from radiographs alone. The first model built de novo with only the radiological image as input had an accuracy of 70%. The final model, which was built by fine-tuning a publicly available model named DenseNet, combining the AP and lateral radiographs, and incorporating information from the patient’s history, had an accuracy, sensitivity, and specificity of 88.3%, 70.2%, and 95.6% on the independent test dataset. It performed better for cases of revision THA with an accuracy of 90.1%, than for cases of revision TKA with an accuracy of 85.8%. Conclusion. This study showed that machine learning can detect prosthetic loosening from radiographs. Its accuracy is enhanced when using highly trained public algorithms, and when adding clinical data to the algorithm. While this algorithm may not be sufficient in its present state of development as a standalone metric of loosening, it is currently a useful augment for clinical decision making. Cite this article: Bone Joint J 2020;102-B(6 Supple A):101–106

Aims. Once knee arthritis and deformity have occurred, it is currently not known how to determine a patient’s constitutional (pre-arthritic) limb alignment. The purpose of this study was to describe and validate the arithmetic hip-knee-ankle (aHKA) algorithm as a straightforward method for preoperative planning and intraoperative restoration of the constitutional limb alignment in total knee arthroplasty (TKA). Methods. A comparative cross-sectional, radiological study was undertaken of 500 normal knees and 500 arthritic knees undergoing TKA. By definition, the aHKA algorithm subtracts the lateral distal femoral angle (LDFA) from the medial proximal tibial angle (MPTA). The mechanical HKA (mHKA) of the normal group was compared to the mHKA of the arthritic group to examine the difference, specifically related to deformity in the latter. The mHKA and aHKA were then compared in the normal group to assess for differences related to joint line convergence. Lastly, the aHKA of both the normal and arthritic groups were compared to test the hypothesis that the aHKA can estimate the constitutional alignment of the limb by sharing a similar centrality and distribution with the normal population. Results. There was a significant difference in means and distributions of the mHKA of the normal group compared to the arthritic group (mean -1.33° (SD 2.34°) vs mean -2.88° (SD 7.39°) respectively; p < 0.001). However, there was no significant difference between normal and arthritic groups using the aHKA (mean -0.87° (SD 2.54°) vs mean -0.77° (SD 2.84°) respectively; p = 0.550). There was no significant difference in the MPTA and LDFA between the normal and arthritic groups. Conclusion. The arithmetic HKA effectively estimated the constitutional alignment of the lower limb after the onset of arthritis in this cross-sectional population-based analysis. This finding is of significant importance to surgeons aiming to restore the constitutional alignment of the lower limb during TKA. Cite this article: Bone Jt Open 2021;2(5):351–358

Aims. In 2013, we introduced a specialized, centralized, and interdisciplinary team in our institution that applied a standardized diagnostic and treatment algorithm for the management of prosthetic joint infections (PJIs). The hypothesis for this study was that the outcome of treatment would be improved using this approach. Patients and Methods. In a retrospective analysis with a standard postoperative follow-up, 95 patients with a PJI of the hip and knee who were treated with a two-stage exchange between 2013 and 2017 formed the study group. A historical cohort of 86 patients treated between 2009 and 2011 not according to the standardized protocol served as a control group. The success of treatment was defined according to the Delphi criteria in a two-year follow-up. Results. Patients in the study group had a significantly higher Charlson Comorbidity Index (3.9 vs 3.1; p = 0.009) and rate of previous revisions for infection (52.6% vs 36%; p = 0.025), and tended to be older (69.0 vs 66.2 years; p = 0.075) with a broader polymicrobial spectrum (47.3% vs 33.7%; p = 0.062). The rate of recurrent infection (3.1% vs 10.4%; p = 0.048) and the mean time interval between the two stages of the procedure (66.6 vs 80.7 days; p < 0.001) were reduced significantly in the study group compared with the control group. Conclusion. We were able to show that the outcome following the treatment of PJIs of the hip and knee is better when managed in a separate department with an interdisciplinary team using a standard algorithm

Aims. We aimed to assess the reliability and validity of OpenPose, a posture estimation algorithm, for measurement of knee range of motion after total knee arthroplasty (TKA), in comparison to radiography and goniometry. Methods. In this prospective observational study, we analyzed 35 primary TKAs (24 patients) for knee osteoarthritis. We measured the knee angles in flexion and extension using OpenPose, radiography, and goniometry. We assessed the test-retest reliability of each method using intraclass correlation coefficient (1,1). We evaluated the ability to estimate other measurement values from the OpenPose value using linear regression analysis. We used intraclass correlation coefficients (2,1) and Bland–Altman analyses to evaluate the agreement and error between radiography and the other measurements. Results. OpenPose had excellent test-retest reliability (intraclass correlation coefficient (1,1) = 1.000). The R. 2. of all regression models indicated large correlations (0.747 to 0.927). In the flexion position, the intraclass correlation coefficients (2,1) of OpenPose indicated excellent agreement (0.953) with radiography. In the extension position, the intraclass correlation coefficients (2,1) indicated good agreement of OpenPose and radiography (0.815) and moderate agreement of goniometry with radiography (0.593). OpenPose had no systematic error in the flexion position, and a 2.3° fixed error in the extension position, compared to radiography. Conclusion. OpenPose is a reliable and valid tool for measuring flexion and extension positions after TKA. It has better accuracy than goniometry, especially in the extension position. Accurate measurement values can be obtained with low error, high reproducibility, and no contact, independent of the examiner’s skills. Cite this article: Bone Joint Res 2023;12(5):313–320

Aims. The Oswestry-Bristol Classification (OBC) is an MRI-specific assessment tool to grade trochlear dysplasia. The aim of this study is to validate clinically the OBC by demonstrating its use in selecting treatments that are safe and effective. Methods. The OBC and the patellotrochlear index were used as part of the Oswestry Patellotrochlear Algorithm (OPTA) to guide the surgical treatment of patients with patellar instability. Patients were assigned to one of four treatment groups: medial patellofemoral ligament reconstruction (MPFLr); MPFLr + tibial tubercle distalization (TTD); trochleoplasty; or trochleoplasty + TTD. A prospective analysis of a longitudinal patellofemoral database was performed. Between 2012 and 2018, 202 patients (233 knees) with a mean age of 24.2 years (SD 8.1), with recurrent patellar instability were treated by two fellowship-trained consultant sports/knee surgeons at The Robert Jones and Agnes Hunt Orthopaedic Hospital. Clinical efficacy of each treatment group was assessed by Kujala, International Knee Documentation Committee (IKDC), and EuroQol five-dimension questionnaire (EQ-5D) scores at baseline, and up to 60 months postoperatively. Their safety was assessed by complication rate and requirement for further surgery. The pattern of clinical outcome over time was analyzed using mixed regression modelling. Results. In all, 135 knees (mean age 24.9 years (SD 9.4)) were treated using a MPFLr. Ten knees (7.4%) required additional surgery. A total of 50 knees (mean age 24.4 years (SD 6.3)) were treated using MPFLr + TTD. Ten (20%) required additional surgery. A total of 20 knees (mean age 19.5 years (SD 3.0)) were treated using trochleoplasty + TTD. Three patients (15%) required additional surgery. In each treatment group, there was a significant improvement in Kujala, IKDC, and EQ-5D at one year postoperatively (p < 0.001) with a recognized level of overall complication rate. Conclusion. The OBC is a valid assessment tool to grade patients with trochlear dysplasia and, when used as part of the OPTA, helps to determine treatments that are safe and effective. This fulfils the requirements for its application in mainstream clinical practice. Cite this article: Bone Joint J 2021;103-B(10):1586–1594

Aims. Total hip arthroplasty (THA) in patients with post-polio residual paralysis (PPRP) is challenging. Despite relief in pain after THA, pre-existing muscle imbalance and altered gait may cause persistence of difficulty in walking. The associated soft tissue contractures not only imbalances the pelvis, but also poses the risk of dislocation, accelerated polyethylene liner wear, and early loosening. Methods. In all, ten hips in ten patients with PPRP with fixed pelvic obliquity who underwent THA as per an algorithmic approach in two centres from January 2014 to March 2018 were followed-up for a minimum of two years (2 to 6). All patients required one or more additional soft tissue procedures in a pre-determined sequence to correct the pelvic obliquity. All were invited for the latest clinical and radiological assessment. Results. The mean Harris Hip Score at the latest follow-up was 79.2 (68 to 90). There was significant improvement in the coronal pelvic obliquity from 16.6. o. (SD 7.9. o. ) to 1.8. o. (SD 2.4. o. ; p < 0.001). Radiographs of all ten hips showed stable prostheses with no signs of loosening or migration, regardless of whether paralytic or non-paralytic hip was replaced. No complications, including dislocation or infection related to the surgery, were observed in any patient. The subtrochanteric shortening osteotomy done in two patients had united by nine months. Conclusion. Simultaneous correction of soft tissue contractures is necessary for obtaining a stable hip with balanced pelvis while treating hip arthritis by THA in patients with PPRP and fixed pelvic obliquity. Cite this article: Bone Jt Open 2021;2(9):696–704

Aims. Fungal periprosthetic joint infections (fPJIs) are rare complications, constituting only 1% of all PJIs. Neither a uniform definition for fPJI has been established, nor a standardized treatment regimen. Compared to bacterial PJI, there is little evidence for fPJI in the literature with divergent results. Hence, we implemented a novel treatment algorithm based on three-stage revision arthroplasty, with local and systemic antifungal therapy to optimize treatment for fPJI. Methods. From 2015 to 2018, a total of 18 patients with fPJI were included in a prospective, single-centre study (DKRS-ID 00020409). The diagnosis of PJI is based on the European Bone and Joint Infection Society definition of periprosthetic joint infections. The baseline parameters (age, sex, and BMI) and additional data (previous surgeries, pathogen spectrum, and Charlson Comorbidity Index) were recorded. A therapy protocol with three-stage revision, including a scheduled spacer exchange, was implemented. Systemic antifungal medication was administered throughout the entire treatment period and continued for six months after reimplantation. A minimum follow-up of 24 months was defined. Results. Eradication of infection was achieved in 16 out of 18 patients (88.8%), with a mean follow-up of 35 months (25 to 54). Mixed bacterial and fungal infections were present in seven cases (39%). The interval period, defined as the period of time from explantation to reimplantation, was 119 days (55 to 202). In five patients, a salvage procedure was performed (three cementless modular knee arthrodesis, and two Girdlestone procedures). Conclusion. Therapy for fPJI is complex, with low cure rates according to the literature. No uniform treatment recommendations presently exist for fPJI. Three-stage revision arthroplasty with prolonged systemic antifungal therapy showed promising results. Cite this article: Bone Jt Open 2021;2(8):671–678

The use of plate-and-cable constructs to treat periprosthetic fractures around a well-fixed femoral component in total hip replacements has been reported to have high rates of failure. Our aim was to evaluate the results of a surgical treatment algorithm to use these lateral constructs reliably in Vancouver type-B1 and type-C fractures. The joint was dislocated and the stability of the femoral component was meticulously evaluated in 45 type-B1 fractures. This led to the identification of nine (20%) unstable components. The fracture was considered to be suitable for single plate-and-cable fixation by a direct reduction technique if the integrity of the medial cortex could be restored. Union was achieved in 29 of 30 fractures (97%) at a mean of 6.4 months (3 to 30) in 29 type-B1 and five type-C fractures. Three patients developed an infection and one construct failed. Using this algorithm plate-and-cable constructs can be used safely, but indirect reduction with minimal soft-tissue damage could lead to shorter times to union and lower rates of complications

The purpose of this study was to evaluate treatment results following arthroscopic triangular fibrocartilage complex (TFCC) debridement for recalcitrant ulnar wrist pain. According to the treatment algorithm, 66 patients (36 men and 30 women with a mean age of 38.1 years (15 to 67)) with recalcitrant ulnar wrist pain were allocated to undergo ulnar shortening osteotomy (USO; n = 24), arthroscopic TFCC repair (n = 15), arthroscopic TFCC debridement (n = 14) or prolonged conservative treatment (n = 13). The mean follow-up was 36.0 months (15 to 54). Significant differences in Hand20 score at 18 months were evident between the USO group and TFCC debridement group (p = 0.003), and between the TFCC repair group and TFCC debridement group (p = 0.029). Within-group comparisons showed that Hand20 score at five months or later and pain score at two months or later were significantly decreased in the USO/TFCC repair groups. In contrast, scores in the TFCC debridement/conservative groups did not decrease significantly. Grip strength at 18 months was significantly improved in the USO/TFCC repair groups, but not in the TFCC debridement/conservative groups. TFCC debridement shows little benefit on the clinical course of recalcitrant ulnar wrist pain even after excluding patients with ulnocarpal abutment or TFCC detachment from the fovea from the indications for arthroscopic TFCC debridement. Cite this article: Bone Joint J 2013;95-B:1687–96

Cite this article: Bone Joint Res 2023;12(9):598–600.

We investigated the incidence of anomalies in the vertebral arteries and Circle of Willis with three-dimensional CT angiography in 55 consecutive patients who had undergone an instrumented posterior fusion of the cervical spine.

We recorded any peri-operative and post-operative complications. The frequency of congenital anomalies was 30.9%, abnormal vertebral artery blood flow was 58.2% and vertebral artery dominance 40%.

The posterior communicating artery was occluded on one side in 41.8% of patients and bilaterally in 38.2%. Variations in the vertebral arteries and Circle of Willis were not significantly related to the presence or absence of posterior communicating arteries. Importantly, 18.2% of patients showed characteristic variations in the Circle of Willis with unilateral vertebral artery stenosis or a dominant vertebral artery, indicating that injury may cause lethal complications. One patient had post-operative cerebellar symptoms due to intra-operative injury of the vertebral artery, and one underwent a different surgical procedure because of insufficient collateral circulation.

Pre-operative assessment of the vertebral arteries and Circle of Willis is essential if a posterior spinal fusion with instrumentation is to be carried out safely.

Cite this article: Bone Joint J 2014;96-B:535–40.

Aims. An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. Methods. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data. Results. The patient-specific approach with engineered features achieved the highest in-clinic performance for differentiating physiotherapy exercise from non-exercise activity (area under the receiver operating characteristic (AUROC) = 0.924). Including non-exercise data in algorithm training further improved classifier performance (random forest, AUROC = 0.985). The highest accuracy achieved for classifying individual in-clinic exercises was 0.903, using a patient-specific method with deep neural network model extracted features. Grouping exercises by motion type improved exercise classification. For at-home data, OOD detection yielded similar performance with the non-exercise data in the algorithm training (fully convolutional network AUROC = 0.919). Conclusion. Including non-exercise data in algorithm training improves detection of exercises. A patient-specific approach leveraging data from earlier patient-supervised sessions should be considered but is highly dependent on per-patient data quality. Cite this article: Bone Joint Res 2023;12(3):165–177

Aims. The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales. Methods. We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID). Results. The CAT algorithms accurately estimated 12-item questionnaire scores from between four and nine items. Scores followed a very similar distribution between CAT and full-length assessments, with the mean score difference ranging from 0.03 to 0.26 out of 48 points. Pearson’s correlation coefficient and ICC were 0.98 for each 12-item scale and 0.95 or higher for the OES subscales. In over 95% of cases, a patient’s CAT score was within five points of the full-length questionnaire score for each 12-item questionnaire. Conclusion. Oxford Hip Score, Oxford Knee Score, Oxford Shoulder Score, and Oxford Elbow Score (including separate subscale scores) CATs all markedly reduce the burden of items to be completed without sacrificing score accuracy. Cite this article: Bone Jt Open 2022;3(10):786–794