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

Objectives

Patient function after arthroplasty should ideally quickly improve. It is not known which peri-operative function assessments predict length of stay (LOS) and short-term functional recovery. The objective of this study was to identify peri-operative functions assessments predictive of hospital LOS and short-term function after hospital discharge in hip or knee arthroplasty patients.

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

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

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

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

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

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

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

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

Aims. This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. Methods. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate. Results. Time series clustering allowed us to divide the patients into two groups, and the predictive factors were identified including patient- and operation-related factors. The area under the receiver operating characteristic (ROC) curve (AUC) for the BMD loss prediction averaged 0.734. Virtual administration of bisphosphonate showed on average 14% efficacy in preventing BMD loss of zone 7. Additionally, stem types and preoperative triglyceride (TG), creatinine (Cr), estimated glomerular filtration rate (eGFR), and creatine kinase (CK) showed significant association with the estimated patient-specific efficacy of bisphosphonate. Conclusion. Periprosthetic BMD loss after THA is predictable based on patient- and operation-related factors, and optimal prescription of bisphosphonate based on the prediction may prevent BMD loss. Cite this article: Bone Joint Res 2024;13(4):184–192

Aims. A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. Methods. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Aims. To investigate the optimal thresholds and diagnostic efficacy of commonly used serological and synovial fluid detection indexes for diagnosing periprosthetic joint infection (PJI) in patients who have rheumatoid arthritis (RA). Methods. The data from 348 patients who had RA or osteoarthritis (OA) and had previously undergone a total knee (TKA) and/or a total hip arthroplasty (THA) (including RA-PJI: 60 cases, RA-non-PJI: 80 cases; OA-PJI: 104 cases, OA-non-PJI: 104 cases) were retrospectively analyzed. A receiver operating characteristic curve was used to determine the optimal thresholds of the CRP, ESR, synovial fluid white blood cell count (WBC), and polymorphonuclear neutrophil percentage (PMN%) for diagnosing RA-PJI and OA-PJI. The diagnostic efficacy was evaluated by comparing the area under the curve (AUC) of each index and applying the results of the combined index diagnostic test. Results. For PJI prediction, the results of serological and synovial fluid indexes were different between the RA-PJI and OA-PJI groups. The optimal cutoff value of CRP for diagnosing RA-PJI was 12.5 mg/l, ESR was 39 mm/hour, synovial fluid WBC was 3,654/μl, and PMN% was 65.9%; and those of OA-PJI were 8.2 mg/l, 31 mm/hour, 2,673/μl, and 62.0%, respectively. In the RA-PJI group, the specificity (94.4%), positive predictive value (97.1%), and AUC (0.916) of synovial fluid WBC were higher than those of the other indexes. The optimal cutoff values of synovial fluid WBC and PMN% for diagnosing RA-PJI after THA were significantly higher than those of TKA. The specificity and positive predictive value of the combined index were 100%. Conclusion. Serum inflammatory and synovial fluid indexes can be used for diagnosing RA-PJI, for which synovial fluid WBC is the best detection index. Combining multiple detection indexes can provide a reference basis for the early and accurate diagnosis of RA-PJI. Cite this article: Bone Joint Res 2023;12(9):559–570

Aims. This study aimed to explore the diagnostic value of synovial fluid neutrophil extracellular traps (SF-NETs) in periprosthetic joint infection (PJI) diagnosis, and compare it with that of microbial culture, serum ESR and CRP, synovial white blood cell (WBC) count, and polymorphonuclear neutrophil percentage (PMN%). Methods. In a single health centre, patients with suspected PJI were enrolled from January 2013 to December 2021. The inclusion criteria were: 1) patients who were suspected to have PJI; 2) patients with complete medical records; and 3) patients from whom sufficient synovial fluid was obtained for microbial culture and NET test. Patients who received revision surgeries due to aseptic failure (AF) were selected as controls. Synovial fluid was collected for microbial culture and SF-WBC, SF-PNM%, and SF-NET detection. The receiver operating characteristic curve (ROC) of synovial NET, WBC, PMN%, and area under the curve (AUC) were obtained; the diagnostic efficacies of these diagnostic indexes were calculated and compared. Results. The levels of SF-NETs in the PJI group were significantly higher than those of the AF group. The AUC of SF-NET was 0.971 (95% confidence interval (CI) 0.903 to 0.996), the sensitivity was 93.48% (95% CI 82.10% to 98.63%), the specificity was 96.43% (95% CI 81.65% to 99.91%), the accuracy was 94.60% (95% CI 86.73% to 98.50%), the positive predictive value was 97.73%, and the negative predictive value was 90%. Further analysis showed that SF-NET could improve the diagnosis of culture-negative PJI, patients with PJI who received antibiotic treatment preoperatively, and fungal PJI. Conclusion. SF-NET is a novel and ideal synovial fluid biomarker for PJI diagnosis, which could improve PJI diagnosis greatly. Cite this article: Bone Joint Res 2023;12(2):113–120

Aims. This study aimed to assess the risk of acute kidney injury (AKI) associated with combined intravenous (IV) and topical antibiotic therapy in patients undergoing treatment for periprosthetic joint infections (PJIs) following total knee arthroplasty (TKA), utilizing the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for classification. Methods. We conducted a retrospective analysis of 162 knees (162 patients) that received treatment for PJI post-TKA with combined IV and topical antibiotic infusions at a single academic hospital from 1 January 2010 to 31 December 2022. The incidence of AKI was evaluated using the KDIGO criteria, focussing on the identification of significant predictors and the temporal pattern of AKI development. Results. AKI was identified in 9.26% (15/162) of the cohort, predominantly presenting as stage 1 AKI, which was transient in nature and resolved prior to discharge. The analysis highlighted moderate anaemia and lower baseline serum creatinine levels as significant predictors for the development of AKI. Notably, the study found no instances of severe complications such as wound dehiscence, skin erosion, or the need for haemodialysis following treatment. Conclusion. The findings suggest that the combined use of IV and topical antibiotic therapy in the management of PJIs post-TKA is associated with a low incidence of primarily transient stage 1 AKI. This indicates a potentially favourable renal safety profile, advocating for further research to confirm these outcomes and potentially influence treatment protocols in PJI management. Cite this article: Bone Joint Res 2024;13(10):525–534

Aims. The presence of facet tropism has been correlated with an elevated susceptibility to lumbar disc pathology. Our objective was to evaluate the impact of facet tropism on chronic lumbosacral discogenic pain through the analysis of clinical data and finite element modelling (FEM). Methods. Retrospective analysis was conducted on clinical data, with a specific focus on the spinal units displaying facet tropism, utilizing FEM analysis for motion simulation. We studied 318 intervertebral levels in 156 patients who had undergone provocation discography. Significant predictors of clinical findings were identified by univariate and multivariate analyses. Loading conditions were applied in FEM simulations to mimic biomechanical effects on intervertebral discs, focusing on maximal displacement and intradiscal pressures, gauged through alterations in disc morphology and physical stress. Results. A total of 144 discs were categorized as ‘positive’ and 174 discs as ‘negative’ by the results of provocation discography. The presence of defined facet tropism (OR 3.451, 95% CI 1.944 to 6.126) and higher Adams classification (OR 2.172, 95% CI 1.523 to 3.097) were important predictive parameters for discography-‘positive’ discs. FEM simulations showcased uneven stress distribution and significant disc displacement in tropism-affected discs, where loading exacerbated stress on facets with greater angles. During varied positions, notably increased stress and displacement were observed in discs with tropism compared to those with normal facet structure. Conclusion. Our findings indicate that facet tropism can contribute to disc herniation and changes in intradiscal pressure, potentially exacerbating disc degeneration due to altered force distribution and increased mechanical stress. Cite this article: Bone Joint Res 2024;13(9):452–461

Aims. The association of auraptene (AUR), a 7-geranyloxycoumarin, on osteoporosis and its potential pathway was predicted by network pharmacology and confirmed in experimental osteoporotic mice. Methods. The network of AUR was constructed and a potential pathway predicted by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) terms enrichment. Female ovariectomized (OVX) Institute of Cancer Research mice were intraperitoneally injected with 0.01, 0.1, and 1 mM AUR for four weeks. The bone mineral density (BMD) level was measured by dual-energy X-ray absorptiometry. The bone microstructure was determined by histomorphological changes in the femora. In addition, biochemical analysis of the serum and assessment of the messenger RNA (mRNA) levels of osteoclastic markers were performed. Results. In total, 65.93% of the genes of the AUR network matched with osteoporosis-related genes. Osteoclast differentiation was predicted to be a potential pathway of AUR in osteoporosis. Based on the network pharmacology, the BMD and bone mineral content levels were significantly (p < 0.05) increased in the whole body, femur, tibia, and lumbar spine by AUR. AUR normalized the bone microstructure and the serum alkaline phosphatase (ALP), bone-specific alkaline phosphatase (bALP), osteocalcin, and calcium in comparison with the OVX group. In addition, AUR treatment reduced TRAP-positive osteoclasts and receptor activator of nuclear factor kappa-B ligand (RANKL). +. nuclear factor of activated T cells 1 (NFATc1). +. expression in the femoral body. Moreover, the expressions of initiators for osteoclastic resorption and bone matrix degradation were significantly (p < 0.05) regulated by AUR in the lumbar spine of the osteoporotic mice. Conclusion. AUR ameliorated bone loss by downregulating the RANKL/NFATc1 pathway, resulting in improvement of osteoporosis. In conclusion, AUR might be an ameliorative cure that alleviates bone loss in osteoporosis via inhibition of osteoclastic activity. Cite this article: Bone Joint Res 2022;11(5):304–316

Aims. The aim of this study was to report the meaningful values of the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) and EuroQol visual analogue scale (EQ-VAS) in patients undergoing primary knee arthroplasty (KA). Methods. This is a retrospective study of patients undergoing primary KA for osteoarthritis in a university teaching hospital (Royal Infirmary of Edinburgh) (1 January 2013 to 31 December 2019). Pre- and postoperative (one-year) data were prospectively collected for 3,181 patients (median age 69.9 years (interquartile range (IQR) 64.2 to 76.1); females, n = 1,745 (54.9%); median BMI 30.1 kg/m. 2. (IQR 26.6 to 34.2)). The reliability of the EQ-5D-3L was measured using Cronbach’s alpha. Responsiveness was determined by calculating the anchor-based minimal clinically important difference (MCID), the minimal important change (MIC) (cohort and individual), the patient-acceptable symptom state (PASS) predictive of satisfaction, and the minimal detectable change at 90% confidence intervals (MDC-90). Results. The EQ-5D-3L demonstrated good internal consistency with an overall Cronbach alpha of 0.75 (preoperative) and 0.88 (postoperative), respectively. The MCID for the Index score was 0.085 (95% confidence interval (CI) 0.042 to 0.127) and EQ-VAS was 6.41 (95% CI 3.497 to 9.323). The MIC. COHORT. was 0.289 for the EQ-5D and 5.27 for the EQ-VAS. However, the MIC. INDIVIDUAL. for both the EQ-5D-3L Index (0.105) and EQ-VAS (-1) demonstrated poor-to-acceptable reliability. The MDC-90 was 0.023 for the EQ-5D-3L Index and 1.0 for the EQ-VAS. The PASS for the postoperative EQ-5D-3L Index and EQ-VAS scores predictive of patient satisfaction were 0.708 and 77.0, respectively. Conclusion. The meaningful values of the EQ-5D-3L Index and EQ-VAS scores can be used to measure clinically relevant changes in health-related quality of life in patients undergoing primary KA. Cite this article: Bone Joint Res 2022;11(9):619–628

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article: Bone Joint Res 2023;12(7):447–454

Aims. Better prediction of outcome after total hip arthroplasty (THA) is warranted. Systemic inflammation and central neuroinflammation are possibly involved in progression of osteoarthritis and pain. We explored whether inflammatory biomarkers in blood and cerebrospinal fluid (CSF) were associated with clinical outcome, and baseline pain or disability, 12 months after THA. Methods. A total of 50 patients from the Danish Pain Research Biobank (DANPAIN-Biobank) between January and June 2018 were included. Postoperative outcome was assessed as change in Oxford Hip Score (OHS) from baseline to 12 months after THA, pain was assessed on a numerical rating scale, and disability using the Pain Disability Index. Multiple regression models for each clinical outcome were included for biomarkers in blood and CSF, respectively, including age, sex, BMI, and Kellgren-Lawrence score. Results. Change in OHS was associated with blood concentrations of tumour necrosis factor (TNF), interleukin-8 (IL-8), interleukin-6 receptor (IL-6R), glycoprotein 130 (gp130), and IL-1β (R. 2. = 0.28, p = 0.006), but not with CSF biomarkers. Baseline pain was associated with blood concentrations of lymphotoxin alpha (LTα), TNFR1, TNFR2, and IL-6R (R. 2. = 0.37, p < 0.001) and CSF concentrations of TNFR1, TNFR2, IL-6, IL-6R, and IL-1Ra (R. 2. = 0.40, p = 0.001). Baseline disability was associated with blood concentrations of TNF, LTα, IL-8, IL-6, and IL-1α (R. 2. = 0.53, p < 0.001) and CSF concentrations of gp130, TNF, and IL-1β (R. 2. = 0.26, p = 0.002). Thus, preoperative systemic low-grade inflammation predicted 12-month postoperative outcome after THA, and was associated with preoperative pain and disability. Conclusion. This study highlights the importance of systemic inflammation in osteoarthritis, and presents a possible path for better patient selection for THA in the future. Preoperative central neuroinflammation was associated with preoperative pain and disability, but not change in OHS after THA. Cite this article: Bone Joint Res 2024;13(12):741–749