Aims. Posterior column plating through the single anterior approach reduces the morbidity in acetabular fractures that require stabilization of both the columns. The aim of this study is to assess the effectiveness of posterior column plating through the anterior intrapelvic approach (AIP) in the management of acetabular fractures. Methods. We retrospectively reviewed the data from R G Kar Medical College, Kolkata, India, from June 2018 to April 2023. Overall, there were 34 acetabulum fractures involving both columns managed by medial buttress plating of posterior column. The posterior column of the acetabular fracture was fixed through the AIP approach with buttress plate on medial surface of posterior column. Mean follow-up was 25 months (13 to 58). Accuracy of reduction and effectiveness of this technique were measured by assessing the Merle d’Aubigné score and Matta’s radiological grading at one year and at latest follow-up. Results. Immediate postoperative radiological Matta’s reduction accuracy showed anatomical reduction (0 to 1 mm) in 23 cases (67.6%), satisfactory (2 to 3 mm) in nine (26.4%), and unsatisfactory (> 3 mm) in two (6%). Merle d’Aubigné score at the end of one year was calculated to be excellent in 18 cases (52.9%), good in 11 (32.3%), fair in three (8.8%), and poor in two (5.9%). Matta’s radiological grading at the end of one year was calculated to be excellent in 16 cases (47%), good in nine (26.4%), six in fair (17.6%), and three in poor (8.8%). Merle d’Aubigné score at latest follow-up deteriorated by one point in some cases, but the grading remained the same; Matta’s radiological grading at latest follow-up also remained unchanged. Conclusion. Stabilization of posterior column through AIP by medial surface plate along the sciatic notch gives good stability to posterior column, and at the same time can avoid morbidity of the additional lateral window. Cite this article: Bone Jt Open 2024;5(2):147–153

Aims. The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test accuracy. Methods. A total of 16,238 preoperative OSS were available in the National Joint Registry (NJR) for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey dataset (April 2012 to April 2022). Prior to CAT, the foundational item response theory (IRT) assumptions of unidimensionality, monotonicity, and local independence were established. CAT compared sequential item selection with stopping criteria set at standard error (SE) < 0.32 and SE < 0.45 (equivalent to reliability coefficients of 0.90 and 0.80) to full-length patient-reported outcome measure (PROM) precision. Results. Confirmatory factor analysis (CFA) for unidimensionality exhibited satisfactory fit with root mean square standardized residual (RSMSR) of 0.06 (cut-off ≤ 0.08) but not with comparative fit index (CFI) of 0.85 or Tucker-Lewis index (TLI) of 0.82 (cut-off > 0.90). Monotonicity, measured by H value, yielded 0.482, signifying good monotonic trends. Local independence was generally met, with Yen’s Q3 statistic > 0.2 for most items. The median item count for completing the CAT simulation with a SE of 0.32 was 3 (IQR 3 to 12), while for a SE of 0.45 it was 2 (IQR 2 to 6). This constituted only 25% and 16%, respectively, when compared to the 12-item full-length questionnaire. Conclusion. Calibrating IRT for the OSS has resulted in the development of an efficient and shortened CAT while maintaining accuracy and reliability. Through the reduction of redundant items and implementation of a standardized measurement scale, our study highlights a promising approach to alleviate time burden and potentially enhance compliance with these widely used outcome measures. Cite this article: Bone Joint Res 2024;13(8):392–400

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

Aims. The modified Radiological Union Scale for Tibia (mRUST) fractures score was developed in order to assess progress to union and define a numerical assessment of fracture healing of metadiaphyseal fractures. This score has been shown to be valuable in predicting radiological union; however, there is no information on the sensitivity, specificity, and accuracy of this index for various cut-off scores. The aim of this study is to evaluate sensitivity, specificity, accuracy, and cut-off points of the mRUST score for the diagnosis of metadiaphyseal fractures healing. Methods. A cohort of 146 distal femur fractures were retrospectively identified at our institution. After excluding AO/OTA type B fractures, nonunions, follow-up less than 12 weeks, and patients aged less than 16 years, 104 sets of radiographs were included for analysis. Anteroposterior and lateral femur radiographs at six weeks, 12 weeks, 24 weeks, and final follow-up were separately scored by three surgeons using the mRUST score. The sensitivity and specificity of mean mRUST score were calculated using clinical and further radiological findings as a gold standard for ultimate fracture healing. A receiver operating characteristic curve was also performed to determine the cut-off points at each time point. Results. The mean mRUST score of ten at 24 weeks revealed a 91.9% sensitivity, 100% specificity, and 92.6% accuracy of predicting ultimate fracture healing. A cut-off point of 13 points revealed 41.9% sensitivity, 100% specificity, and 46.9% accuracy at the same time point. Conclusion. The mRUST score of ten points at 24 weeks can be used as a viable screening method with the highest sensitivity, specificity, and accuracy for healing of metadiaphyseal femur fractures. However, the cut-off point of 13 increases the specificity to 100%, but decreases sensitivity. Furthermore, the mRUST score should not be used at six weeks, as results show an inability to accurately predict eventual fracture healing at this time point. Cite this article: Bone Jt Open 2021;2(10):796–805

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. The diagnosis of periprosthetic joint infection (PJI) continues to present a significant clinical challenge. New biomarkers have been proposed to support clinical decision-making; among them, synovial fluid alpha-defensin has gained interest. Current research methodology suggests reference methods are needed to establish solid evidence for use of the test. This prospective study aims to evaluate the diagnostic accuracy of high-performance liquid chromatography coupled with the mass spectrometry (LC-MS) method to detect alpha-defensin in synovial fluid. Methods. Between October 2017 and September 2019, we collected synovial fluid samples from patients scheduled to undergo revision surgery for painful total knee arthroplasty (TKA). The International Consensus Meeting criteria were used to classify 33 PJIs and 92 aseptic joints. LC-MS assay was performed to measure alpha-defensin in synovial fluid of all included patients. Sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC) were calculated to define the test diagnostic accuracy. Results. The AUC was 0.99 (95% confidence interval (CI) 0.98 to 1.00). Receiver operating characteristic (ROC) analysis showed that the optimal cut-off value of synovial fluid alpha-defensin was 1.0 μg/l. The sensitivity of alpha-defensin was 100% (95% CI 96 to 100), the specificity was 97% (95% CI 90 to 98), the positive predictive value was 89.2% (95% CI 82 to 94), and negative predictive value was 100% (95% CI 96 to 100). ROC analysis demonstrated an AUC of 0.99 (95% CI 0.98 to 1.0). Conclusion. The present study confirms the utility of alpha-defensin in the synovial fluid in patients with painful TKA to select cases of PJI. Since LC-MS is still a time-consuming technology and is available in highly specialized laboratories, further translational research studies are needed to take this evidence into routine procedures and promote a new diagnostic approach. Cite this article: Bone Joint J 2022;104-B(9):1047–1051

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

Aims. The aim of this study was to examine the implant accuracy of custom-made partial pelvis replacements (PPRs) in revision total hip arthroplasty (rTHA). Custom-made implants offer an option to achieve a reconstruction in cases with severe acetabular bone loss. By analyzing implant deviation in CT and radiograph imaging and correlating early clinical complications, we aimed to optimize the usage of custom-made implants. Methods. A consecutive series of 45 (2014 to 2019) PPRs for Paprosky III defects at rTHA were analyzed comparing the preoperative planning CT scans used to manufacture the implants with postoperative CT scans and radiographs. The anteversion (AV), inclination (IC), deviation from the preoperatively planned implant position, and deviation of the centre of rotation (COR) were explored. Early postoperative complications were recorded, and factors for malpositioning were sought. The mean follow-up was 30 months (SD 19; 6 to 74), with four patients lost to follow-up. Results. Mean CT defined discrepancy (Δ) between planned and achieved AV and IC was 4.5° (SD 3°; 0° to 12°) and 4° (SD 3.5°; 1° to 12°), respectively. Malpositioning (Δ > 10°) occurred in five hips (10.6%). Native COR reconstruction was planned in 42 cases (93%), and the mean 3D deviation vector was 15.5 mm (SD 8.5; 4 to 35). There was no significant influence in malpositioning found for femoral stem retention, surgical approach, or fixation method. Conclusion. At short-term follow-up, we found that PPR offers a viable solution for rTHA in cases with massive acetabular bone loss, as highly accurate positioning can be accomplished with meticulous planning, achieving anatomical reconstruction. Accuracy of achieved placement contributed to reduced complications with no injury to vital structures by screw fixation. Cite this article: Bone Joint J 2022;104-B(10):1110–1117

Aims. Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. Methods. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with orthopaedic surgeons. AI-based implant identification achieved AUC 0.992 to 1, and most algorithms reported an accuracy > 90%, using 550 to 320,000 training radiographs. AI prediction of dislocation risk post-THA, determined after five-year follow-up, was satisfactory (AUC 76.67; 8,500 training radiographs). Diagnosis of hip implant loosening was good (accuracy 88.3%; 420 training radiographs) and measurement of postoperative acetabular angles was comparable to humans (mean absolute difference 1.35° to 1.39°). However, 11 of the 12 studies had several methodological limitations introducing a high risk of bias. None of the studies were externally validated. Conclusion. These studies show that AI is promising. While it already has the ability to analyze images with significant precision, there is currently insufficient high-level evidence to support its widespread clinical use. Further research to design robust studies that follow standard reporting guidelines should be encouraged to develop AI models that could be easily translated into real-world conditions. Cite this article: Bone Joint J 2022;104-B(8):929–937

Aims. The goal of the current systematic review was to assess the impact of implant placement accuracy on outcomes following total knee arthroplasty (TKA). Methods. A systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using the Ovid Medline, Embase, Cochrane Central, and Web of Science databases in order to assess the impact of the patient-reported outcomes measures (PROMs) and implant placement accuracy on outcomes following TKA. Studies assessing the impact of implant alignment, rotation, size, overhang, or condylar offset were included. Study quality was assessed, evidence was graded (one-star: no evidence, two-star: limited evidence, three-star: moderate evidence, four-star: strong evidence), and recommendations were made based on the available evidence. Results. A total of 49 studies were identified for inclusion. With respect to PROMs, there was two-star evidence in support of mechanical axis alignment (MAA), femorotibial angle (FTA), femoral coronal angle (FCA), tibial coronal angle (TCA), femoral sagittal angle (FSA), femoral rotation, tibial and combined rotation/mismatch, and implant size/overhang or offset on PROMs, and one-star evidence in support of tibial sagittal angle (TSA), impacting PROMs. With respect to survival, there was three- to four-star evidence in support FTA, FCA, TCA, and TSA, moderate evidence in support of femoral rotation, tibial and combined rotation/mismatch, and limited evidence in support of MAA, FSA, and implant size/overhang or offset impacting survival. Conclusion. Overall, there is limited evidence to suggest that PROMs are impacted by the accuracy of implant placement, and malalignment does not appear to be a significant driver of the observed high rates of patient dissatisfaction following TKA. However, FTA, FCA, TCA, TSA, and implant rotation demonstrate a moderate-strong relationship with implant survival. Efforts should be made to improve the accuracy of these parameters in order to improve TKA survival. Cite this article: Bone Joint J 2021;103-B(9):1449–1456

Abstract. Robotic-assisted total knee arthroplasty (TKA) has proven higher accuracy, fewer alignment outliers, and improved short-term clinical outcomes when compared to conventional TKA. However, evidence of cost-effectiveness and individual superiority of one system over another is the subject of further research. Despite its growing adoption rate, published results are still limited and comparative studies are scarce. This review compares characteristics and performance of five currently available systems, focusing on the information and feedback each system provides to the surgeon, what the systems allow the surgeon to modify during the operation, and how each system then aids execution of the surgical plan. Cite this article: Bone Jt Open 2023;4(1):13–18

The February 2023 Spine Roundup. 360. looks at: S2AI screws: At what cost?; Just how good is spinal deformity surgery?; Is 80 years of age too late in the day for spine surgery?; Factors affecting the accuracy of pedicle screw placement in robot-assisted surgery; Factors causing delay in discharge in patients eligible for ambulatory lumbar fusion surgery; Anterior cervical discectomy or fusion and selective laminoplasty for cervical spondylotic myelopathy; Surgery for cervical radiculopathy: what is the complication burden?; Hypercholesterolemia and neck pain; Return to work after surgery for cervical radiculopathy: a nationwide registry-based observational study

Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193

Aims. The aims of this systematic review were to assess the learning curve of semi-active robotic arm-assisted total hip arthroplasty (rTHA), and to compare the accuracy, patient-reported functional outcomes, complications, and survivorship between rTHA and manual total hip arthroplasty (mTHA). Methods. Searches of PubMed, Medline, and Google Scholar were performed in April 2020 in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “robotic”, “hip”, and “arthroplasty”. The criteria for inclusion were published clinical research articles reporting the learning curve for rTHA (robotic arm-assisted only) and those comparing the implantation accuracy, functional outcomes, survivorship, or complications with mTHA. Results. There were 501 articles initially identified from databases and references. Following full text screening, 17 articles that satisfied the inclusion criteria were included. Four studies reported the learning curve of rTHA, 13 studies reported on implant positioning, five on functional outcomes, ten on complications, and four on survivorship. The meta-analysis showed a significantly greater number of cases of acetabular component placement in the safe zone compared with the mTHA group (95% confidence interval (CI) 4.10 to 7.94; p < 0.001) and that rTHA resulted in a significantly better Harris Hip Score compared to mTHA in the short- to mid-term follow-up (95% CI 0.46 to 5.64; p = 0.020). However, there was no difference in infection rates, dislocation rates, overall complication rates, and survival rates at short-term follow-up. Conclusion. The learning curve of rTHA was between 12 and 35 cases, which was dependent on the assessment goal, such as operating time, accuracy, and team working. Robotic arm-assisted total hip arthroplasty was associated with improved accuracy of component positioning and functional outcome, however no difference in complication rates or survival were observed at short- to mid-term follow-up. Overall, there remains an absence of high-quality level I evidence and cost analysis comparing rTHA and mTHA. Cite this article: Bone Joint J 2021;103-B(6):1009–1020

Aims. Ultrasound (US)-guided injections are widely used in patients with conditions of the shoulder in order to improve their accuracy. However, the clinical efficacy of US-guided injections compared with blind injections remains controversial. The aim of this study was to compare the accuracy and efficacy of US-guided compared with blind corticosteroid injections into the glenohumeral joint in patients with primary frozen shoulder (FS). Methods. Intra-articular corticosteroid injections were administered to 90 patients primary FS, who were randomly assigned to either an US-guided (n = 45) or a blind technique (n = 45), by a shoulder specialist. Immediately after injection, fluoroscopic images were obtained to assess the accuracy of the injection. The outcome was assessed using a visual analogue scale (VAS) for pain, the American Shoulder and Elbow Surgeons (ASES) score, the subjective shoulder value (SSV) and range of movement (ROM) for all patients at the time of presentation and at three, six, and 12 weeks after injection. Results. The accuracy of injection in the US and blind groups was 100% (45/45) and 71.1% (32/45), respectively; this difference was significant (p < 0.001). Both groups had significant improvements in VAS pain score, ASES score, SSV, forward flexion, abduction, external rotation, and internal rotation throughout follow-up until 12 weeks after injection (all p < 0.001). There were no significant differences between the VAS pain scores, the ASES score, the SSV and all ROMs between the two groups at the time points assessed (all p > 0.05). No injection-related adverse effects were noted in either group. Conclusion. We found no significant differences in pain and functional outcomes between the two groups, although an US-guided injection was associated with greater accuracy. Considering that it is both costly and time-consuming, an US-guided intra-articular injection of corticosteroid seems not always to be necessary in the treatment of FS as it gives similar outcomes as a blind injection. Cite this article: Bone Joint J 2021;103-B(2):353–359

The October 2023 Oncology Roundup. 360. looks at: Are pathological fractures in patients with osteosarcoma associated with worse survival outcomes?; Spotting the difference: how secondary osteosarcoma manifests in retinoblastoma survivors versus conventional cases; Accuracy of MRI scans in predicting intra-articular joint involvement in high-grade sarcomas around the knee; Endoprosthetic reconstruction for lower extremity soft-tissue sarcomas with bone involvement; Local relapse of soft-tissue sarcoma of the extremities or trunk wall operated on with wide margins without radiation therapy; 3D-printed, custom-made prostheses in patients who had resection of tumours of the hand and foot; Long-term follow-up for low-grade chondrosarcoma; Evaluation of local recurrence and diagnostic discordance in chondrosarcoma patients undergoing preoperative biopsy; Radiological scoring and resection grade for intraosseous chondrosarcoma

Aims. To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Methods. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology. Results. Overall, 152 patients without and 58 with a history of surgical revision following surgery for ASD were observed; the mean age was 68.9 years (SD 8.7) and 66.9 years (SD 6.6), respectively. On implementing a random forest model, the classification of URO events resulted in a balanced accuracy of 86.8%. Among machine learning-extracted risk factors, URO, proximal junction failure (PJF), and postoperative distance from the posterosuperior corner of C7 and the vertical axis from the centroid of C2 (SVA) were significant upon Kaplan-Meier survival analysis. Conclusion. The major risk factors for URO following surgery for ASD, i.e. postoperative SVA and PJF, and their interactions were identified using a machine learning algorithm and game theory. Clinical benefits will depend on patient risk profiles. Cite this article: Bone Joint Res 2023;12(4):245–255

Aims. The sensitivity and specificity of electrodiagnostic parameters in diagnosing carpal tunnel syndrome (CTS) have been reported differently, and this study aims to address this gap. Methods. This case-control study was conducted on 57 cases with CTS and 58 controls without complaints, such as pain or paresthesia on the median nerve. The main assessed electrodiagnostic parameters were terminal latency index (TLI), residual latency (RL), median ulnar F-wave latency difference (FdifMU), and median sensory latency-ulnar motor latency difference (MSUMLD). Results. The mean age in cases and controls were 50.7 years (SD 9.9) and 47.9 years (SD 12.1), respectively. The CTS severity was mild in 20 patients (34.4%), moderate in 19 patients (32.8%), and severe in 19 patients (32.8%). The sensitivity and specificity of the electrodiagnostic parameters in diagnosing CTS were as follows: TLI 75.4% and 87.8%; RL 85.9% and 82.5%; FdifMU 87.9% and 82.9%; and MSUMLD 94.8% and 60.0%, respectively. Conclusion. Our findings indicated that electrodiagnostic parameters are significantly associated with the clinical manifestation of CTS, and are associated with high diagnostic accuracy in CTS diagnosis. However, further studies are required to highlight the role of electrodiagnostic parameters and their combination in CTS detection. Cite this article: Bone Jt Open 2024;5(10):898–903

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. Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. Methods. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp). Results. NIRS scans on both the inner (trabecular) surface or outer (cortical) surface accurately identified variations in bone collagen, water, mineral, and fat content, which then accurately predicted bone volume fraction (BV/TV, inner R. 2. = 0.91, outer R. 2. = 0.83), thickness (Tb.Th, inner R. 2. = 0.9, outer R. 2. = 0.79), and cortical thickness (Ct.Th, inner and outer both R. 2. = 0.90). NIRS scans also had 100% classification accuracy in grading the quartile of bone thickness and quality. Conclusion. We believe this is a fundamental step forward in creating an instrument capable of intraoperative real-time use. Cite this article: Bone Jt Open 2023;4(4):250–261