Aims. This systematic review aims to identify 3D predictors derived from biplanar reconstruction, and to describe current methods for improving curve prediction in patients with mild adolescent idiopathic scoliosis. Methods. A comprehensive search was conducted by three independent investigators on MEDLINE, PubMed, Web of Science, and Cochrane Library. Search terms included “adolescent idiopathic scoliosis”,“3D”, and “progression”. The inclusion and exclusion criteria were carefully defined to include clinical studies. Risk of bias was assessed with the Quality in Prognostic Studies tool (QUIPS) and Appraisal tool for Cross-Sectional Studies (AXIS), and level of evidence for each predictor was rated with the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. In all, 915 publications were identified, with 377 articles subjected to full-text screening; overall, 31 articles were included. Results. Torsion index (TI) and apical vertebral rotation (AVR) were identified as accurate predictors of curve progression in early visits. Initial TI > 3.7° and AVR > 5.8° were predictive of curve progression. Thoracic hypokyphosis was inconsistently observed in progressive curves with weak evidence. While sagittal wedging was observed in mild curves, there is insufficient evidence for its correlation with curve progression. In curves with initial Cobb angle < 25°, Cobb angle was a poor predictor for future curve progression. Prediction accuracy was improved by incorporating serial reconstructions in stepwise layers. However, a lack of post-hoc analysis was identified in studies involving geometrical models. Conclusion. For patients with mild curves, TI and AVR were identified as predictors of curve progression, with TI > 3.7° and AVR > 5.8° found to be important thresholds. Cobb angle acts as a poor predictor in mild curves, and more investigations are required to assess thoracic kyphosis and wedging as predictors. Cumulative reconstruction of radiographs improves prediction accuracy. Comprehensive analysis between progressive and non-progressive curves is recommended to extract meaningful thresholds for clinical prognostication. Cite this article: Bone Jt Open 2024;5(3):243–251

Aims. Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. Methods. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures. Results. Out of 1,160 studies initially identified, 39 were included. Most studies (85%) were published between 2020 and 2024, with 82% using publicly available datasets, primarily the Osteoarthritis Initiative. ML methods were predominantly supervised, with significant variability in the definitions of OA progression: most studies focused on structural changes (59%), while fewer addressed pain progression or both. Deep learning was used in 44% of studies, while automated ML was used in 5%. There was a lack of standardization in evaluation metrics and limited external validation. Interpretability was explored in 54% of studies, primarily using SHapley Additive exPlanations. Conclusion. Our systematic review demonstrates the feasibility of ML models in predicting OA progression, but also uncovers critical limitations that currently restrict their clinical applicability. Future priorities should include diversifying data sources, standardizing outcome measures, enforcing rigorous validation, and integrating more sophisticated algorithms. This paradigm shift from predictive modelling to actionable clinical tools has the potential to transform patient care and disease management in orthopaedic practice. Cite this article: Bone Joint J 2024;106-B(11):1216–1222

Aims. With novel promising therapies potentially limiting progression of Dupuytren’s disease (DD), better patient stratification is needed. We aimed to quantify DD development and progression after seven years in a population-based cohort, and to identify factors predictive of disease development or progression. Methods. All surviving participants from our previous prevalence study were invited to participate in the current prospective cohort study. Participants were examined for presence of DD and Iselin’s classification was applied. They were asked to complete comprehensive questionnaires. Disease progression was defined as advancement to a further Iselin stage or surgery. Potential predictive factors were assessed using multivariable regression analyses. Of 763 participants in our original study, 398 were available for further investigation seven years later. Results. We identified 143/398 (35.9%) participants with DD, of whom 56 (39.2%) were newly diagnosed. Overall, 20/93 (21.5%) previously affected participants had disease progression, while 6/93 (6.5%) patients showed disease regression. Disease progression occurred more often in patients who initially had advanced disease. Multivariable regression analyses revealed that both ectopic lesions and a positive family history of DD are independent predictors of disease progression. Previous hand injury predicts development of DD. Conclusion. Disease progression occurred in 21.5% of DD patients in our study. The higher the initial disease stage, the greater the proportion of participants who had disease progression at follow-up. Both ectopic lesions and a positive family history of DD predict disease progression. These patient-specific factors may be used to identify patients who might benefit from treatment that prevents progression. Cite this article: Bone Joint J 2021;103-B(4):704–710

Aims. The aim of this study was to estimate time to arthroplasty among patients with hip and knee osteoarthritis (OA), and to identify factors at enrolment to first-line intervention that are prognostic for progression to surgery. Methods. In this longitudinal register-based observational study, we identified 72,069 patients with hip and knee OA in the Better Management of Patients with Osteoarthritis Register (BOA), who were referred for first-line OA intervention, between May 2008 and December 2016. Patients were followed until the first primary arthroplasty surgery before 31 December 2016, stratified into a hip and a knee OA cohort. Data were analyzed with Kaplan-Meier and multivariable-adjusted Cox regression. Results. At five years, Kaplan-Meier estimates showed that 46% (95% confidence interval (CI) 44.6 to 46.9) of those with hip OA, and 20% (95% CI 19.7 to 21.0) of those with knee OA, had progressed to arthroplasty. The strongest prognostic factors were desire for surgery (hazard ratio (HR) hip 3.12 (95% CI 2.95 to 3.31), HR knee 2.72 (95% CI 2.55 to 2.90)), walking difficulties (HR hip 2.20 (95% CI 1.97 to 2.46), HR knee 1.95 (95% CI 1.73 to 2.20)), and frequent pain (HR hip 1.56 (95% CI 1.40 to 1.73), HR knee 1.77 (95% CI 1.58 to 2.00)). In hip OA, the probability of progression to surgery was lower among those with comorbidities (e.g. ≥ four conditions; HR 0.64 (95% CI 0.59 to 0.69)), with no detectable effects in the knee OA cohort. Instead, being overweight or obese increased the probability of OA progress in the knee cohort (HR 1.25 (95% CI 1.15 to 1.37)), but not among those with hip OA. Conclusion. Patients with hip OA progressed faster and to a greater extent to arthroplasty than patients with knee OA. Progression was strongly influenced by patients’ desire for surgery and by factors related to severity of OA symptoms, but factors not directly related to OA symptoms are also of importance. However, a large proportion of patients with OA do not seem to require surgery within five years, especially among those with knee OA. Cite this article: Bone Joint J 2022;104-B(7):792–800

Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA). Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. To create a reliable and interpretable precision health tool that predicts rapid knee OA progression over a 2-year period from baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising disease progression into pain and/or radiographic progression) and binary predictions. Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics. Interpretability analyses were carried out to identify important predictors of progression. Our final models yielded higher accuracy scores for multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856-0.860) compared to binary predictions (AUC-ROC: 0.717, 95% CI: 0.712-0.722). Important predictors of rapid disease progression included WOMAC scores and MRI features. Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression. Our models provide accurate predictions and, importantly, allow specific predictors of rapid disease progression to be identified. Furthermore, the transparency and explainability of our methods may facilitate their acceptance by clinicians and patients, enabling effective translation to clinical practice

Abstract. Introduction. Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA), a degenerative joint disease affecting over 300 million people worldwide. Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. Objectives. This study aims to create a trustworthy and interpretable precision health tool that predicts rapid knee OA progression based on baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. Methods. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising patients into non-progressors, pain-only progressors, radiographic-only progressors, and both pain and radiographic progressors) and binary predictions (categorising patients into non-progressors and progressors). Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics, such as AUC-ROC, AUC-PRC, F1-score, precision, and recall. Additionally, interpretability analyses were carried out to identify important predictors of rapid disease progression. Results. Our final models yielded high accuracy scores for both multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856–0.860; AUC-PRC: 0.675, 95% CI: 0.671–0.679; F1-score: 0.560, 95% CI: 0.554–0.566) and binary predictions (AUC-ROC: 0.717, 95% CI: 0.712–0.722; AUC-PRC: 0.620, 95% CI: 0.616–0.624; F1-score: 0.676, 95% CI: 0.673–0679). Important predictors of rapid disease progression included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and MRI features. Our models were further successfully validated using a hold-out dataset, which was previously omitted from model development and training (AUC-ROC: 0.877 for multi-class predictions; AUC-ROC: 0.746 for binary predictions). Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger (AUC-ROC: 0.862, 95% CI: 0.861–0.863 for multi-class predictions; AUC-ROC: 0.736, 95% CI: 0.734–0.738 for binary predictions). Conclusions. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression using “Autoprognosis 2.0”. Our models provide accurate predictions and offer insights into important predictors of rapid disease progression. Furthermore, the transparency and interpretability of our methods may facilitate their acceptance by clinicians and patients, enabling effective utilisation in clinical practice. Future work should focus on refining these models by increasing the sample size, integrating additional features, and using independent datasets for external validation. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

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

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

Aim. The primary endpoint of this study is to characterize the progression of bone defects at the femoral and tibial side in patients who sustained PJI of the knee that underwent two-stage revision with spacer implantation. In addition, we want to analyze the differences between functional moulded and hand-made spacers. Methods. A retrospective analysis of patients that underwent two-stage revision due to PJI of the knee between January 2014 and December 2021 at our institution. Diagnosis of infection was based on the criteria of the Muscoloskeletal Infection Society. The bone defect evaluation was performed intraoperatively based on the AORI classification. The basal evaluation was performed at the time the resection arthroplasty and spacer implantation surgery. The final evaluation was performed at the second-stage surgery, at the time of spacer removal and revision implant positioning. The differences between groups were characterized by using T-test student for continuous variables, and by using chi-square for categorical variables. A p-value < 0.05 was defined as significant. Results. Complete data of 37 two-stage TKAs revision were included in the study. An articulating moulded functional spacer was used in 14 (35.9%) cases, while a hand-made spacer was used in 23 (58.9%) cases. The average length of interval period (excluding the time for patients that retained the spacer) was 146.6 days. A bone defects progression based on the AORI classification was documented in 24 cases at the femoral side (61.6%), a bone defect progression was documented in 17 cases at the tibial side (43.6%), and a bone defect at both sides was documented in 13 cases (33.3%). A statistically significant greater bone defect progression at the tibial side was observed when hand-made spacers were used. A complication during the interval period was reported in five cases (12.8%) and postoperative complication was reported in 9 cases (23.1%). Conclusions. When comparing patients in which a functional articulating spacer was used, with patients in which static spacer was used, we reported a statistically significant reduced bone defect progression during the interval period at the femoral side only when moulded spacers were used. We observed a higher incidence of bone defect progression also at the tibial and both sides when hand-made spacers were used. This is the first study that documented the bone defect progression during two-stage revision of the knee, the results observed in this study are very encouraging

Aims. cAMP response element binding protein (CREB1) is involved in the progression of osteoarthritis (OA). However, available findings about the role of CREB1 in OA are inconsistent. 666-15 is a potent and selective CREB1 inhibitor, but its role in OA is unclear. This study aimed to investigate the precise role of CREB1 in OA, and whether 666-15 exerts an anti-OA effect. Methods. CREB1 activity and expression of a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) in cells and tissues were measured by immunoblotting and immunohistochemical (IHC) staining. The effect of 666-15 on chondrocyte viability and apoptosis was examined by cell counting kit-8 (CCK-8) assay, JC-10, and terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling (TUNEL) staining. The effect of 666-15 on the microstructure of subchondral bone, and the synthesis and catabolism of cartilage, in anterior cruciate ligament transection mice were detected by micro-CT, safranin O and fast green (S/F), immunohistochemical staining, and enzyme-linked immunosorbent assay (ELISA). Results. CREB1 was hyperactive in osteoarthritic articular cartilage, interleukin (IL)-1β-treated cartilage explants, and IL-1β- or carbonyl cyanide 3-chlorophenylhydrazone (CCCP)-treated chondrocytes. 666-15 enhanced cell viability of OA-like chondrocytes and alleviated IL-1β- or CCCP-induced chondrocyte injury through inhibition of mitochondrial dysfunction-associated apoptosis. Moreover, inhibition of CREB1 by 666-15 suppressed expression of ADAMTS4. Additionally, 666-15 alleviated joint degeneration in an ACLT mouse model. Conclusion. Hyperactive CREB1 played a critical role in OA development, and 666-15 exerted anti-IL-1β or anti-CCCP effects in vitro as well as joint-protective effects in vivo. 666-15 may therefore be used as a promising anti-OA drug. Cite this article: Bone Joint Res 2024;13(1):4–18

Aims. The aim of this study was to systematically review the literature for evidence of the effect of a high-fat diet (HFD) on the onset or progression of osteoarthritis (OA) in mice. Methods. A literature search was performed in PubMed, Embase, Web of Science, and Scopus to find all studies on mice investigating the effects of HFD or Western-type diet on OA when compared with a control diet (CD). The primary outcome was the determination of cartilage loss and alteration. Secondary outcomes regarding local and systemic levels of proteins involved in inflammatory processes or cartilage metabolism were also examined when reported. Results. In total, 14 publications met our inclusion criteria and were included in our review. Our meta-analysis showed that, when measured by the modified Mankin Histological-Histochemical Grading System, there was a significantly higher rate of OA in mice fed a HFD than in mice on a CD (standardized mean difference (SMD) 1.27, 95% confidence interval (CI) 0.63 to 1.91). Using the Osteoarthritis Research Society International (OARSI) score, there was a trend towards HFD causing OA (SMD 0.78, 95% CI -0.04 to 1.61). In terms of OA progression, a HFD consistently worsened the progression of surgically induced OA when compared with a CD. Finally, numerous inflammatory cytokines such as tumour necrosis factor alpha (TNF-α), interleukin (IL)-1β, and leptin, among others, were found to be altered by a HFD. Conclusion. A HFD seems to induce or exacerbate the progression of OA in mice. The metabolic changes and systemic inflammation brought about by a HFD appear to be key players in the onset and progression of OA. Cite this article: Bone Joint Res 2019;8:582–592

The aim of this research was to determine biomechanical markers which differentiate medial knee osteoarthritis (OA) patients who do and do not show structural progression over a 2-year period. A cohort of 36 subjects was selected from a longitudinal study (Meireles et al 2017) using Kellgren-Lawrence (KL) scores at baseline and 2-year follow-up. The cohort consisted of 10 healthy controls (HC) (KL=0 at both time points), 15 medial knee OA non-progressors (NPKOA) (KL≥1 at baseline and no change over 2 years), and 11 medial knee OA progressors (PKOA) (KL≥1 at baseline and increase of ≥1 over 2 years). 3D integrated motion capture data from three walking trials were processed through a musculoskeletal modelling framework (Smith et al 2016) to estimate knee joint loading parameters (i.e., magnitude of mean contact pressure, and centre of pressure (COP)). Parameters at first and second peak were extracted and compared between groups using Kruskal-Wallis and Mann-Whitney tests. Higher magnitudes were observed in PKOA vs NPKOA, and PKOA vs HC groups at both time points. Additionally, a posterior (1st and 2nd peak), and lateral (2nd peak) shift in medial compartment COP was shown between PKOA and NPKOA, and PKOA and HC subjects. Interestingly, in the studied parameters, no differences were observed between NPKOA and HC groups. Significantly higher magnitude, and a more posterior and lateral COP was observed between PKOA and NPKOA patients. These differences, combined with an absence of difference between NPKOA and HC suggest structural OA progression is driven by a combination of altered loading magnitude and location. These results may serve as guidelines for targeted gait retraining rehabilitation to slow or stop knee OA progression whereby shifting COP anterior and medial and reducing magnitude by ~22% may shift patients from a PKOA to a NPKOA trajectory

Nuclear factor erythroid 2–related factor 2 (Nrf2) is a crucial transcription factor to maintain cellular redox homeostasis, but is also affecting bone metabolism. As the association between Nrf2 and osteoporosis in elderly females is not fully elucidated, our aim was to shed light on the potential contribution of Nrf2 to the development of age-dependent osteoporosis using a mouse model. Female wild-type (WT, n=18) and Nrf2-knockout (KO, n=12) mice were sacrificed at different ages (12 weeks=young mature adult, and 90 weeks=old), morphological cortical and trabecular properties of femoral bone analyzed by micro-computed tomography (µCT), and compared to histochemistry. Mechanical properties were derived from quasi-static compression tests and digital image correlation (DIC) used to analyze full-field strain distribution. Bone resorbing cells and aromatase expression by osteocytes were evaluated immunohistochemically and empty osteocyte lacunae counted in cortical bone. Wilcoxon rank sum test was used for data comparison and differences considered statistically significant at p<0.05. When compared to old WT mice, old Nrf2-KO mice revealed a significantly reduced trabecular bone mineral density (BMD), cortical thickness (Ct.Th), cortical area (Ct.Ar), and cortical bone fraction (Ct.Ar/Tt.Ar). Surprisingly, these parameters were not different in skeletally mature young adult mice. Metaphyseal trabeculae were thin but present in all old WT mice, while no trabecular bone was detectable in 60% of old KO mice. Occurrence of empty osteocyte lacunae did not differ between both groups, but a significantly higher number of osteoclast-like cells and fewer aromatase-positive osteocytes were found in old KO mice. Furthermore, female Nrf2-KO mice showed an age-dependently reduced fracture resilience when compared to age-matched WT mice. Our results confirmed lower bone quantity and quality as well as an increased number of bone resorbing cells in old female Nrf2-KO mice. Additionally, aromatase expression in osteocytes of old Nrf2-KO mice was compromised, which may indicate a chronic lack of estrogen in bones of old Nrf2-deficient mice. Thus, chronic Nrf2 loss seems to contribute to age-dependent progression of female osteoporosis

Aims. To analyze the potential role of synovial fluid peptidase activity as a measure of disease burden and predictive biomarker of progression in knee osteoarthritis (KOA). Methods. A cross-sectional study of 39 patients (women 71.8%, men 28.2%; mean age of 72.03 years (SD 1.15) with advanced KOA (Ahlbäck grade ≥ 3 and clinical indications for arthrocentesis) recruited through the (Orthopaedic Department at the Complejo Asistencial Universitario de León, Spain (CAULE)), measuring synovial fluid levels of puromycin-sensitive aminopeptidase (PSA), neutral aminopeptidase (NAP), aminopeptidase B (APB), prolyl endopeptidase (PEP), aspartate aminopeptidase (ASP), glutamyl aminopeptidase (GLU) and pyroglutamyl aminopeptidase (PGAP). Results. Synovial fluid peptidase activity varied significantly as a function of clinical signs, with differences in levels of PEP (p = 0.020), ASP (p < 0.001), and PGAP (p = 0. 003) associated with knee locking, PEP (p = 0.006), ASP (p = 0.001), GLU (p = 0.037), and PGAP (p = 0.000) with knee failure, and PEP (p = 0.006), ASP (p = 0.001), GLU (p = 0.037), and PGAP (p < 0.001) with knee effusion. Further, patients with the greatest functional impairment had significantly higher levels of APB (p = 0.005), PEP (p = 0.005), ASP (p = 0.006), GLU (p = 0.020), and PGAP (p < 0.001) activity, though not of NAP or PSA, indicating local alterations in the renin-angiotensin system. A binary logistic regression model showed that PSA was protective (p = 0.005; Exp (B) 0.949), whereas PEP (p = 0.005) and GLU were risk factors (p = 0.012). Conclusion. These results suggest synovial fluid peptidase activity could play a role as a measure of disease burden and predictive biomarker of progression in KOA. Cite this article: Bone Joint Res 2020;9(11):789–797

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

Introduction and Objective. Osteoarthristis (OA) has been associated with many genes and yet the genetic basis for this disease has never formally been established. Recent realization that epigenetic changes could be the underlying pathological mechanisms has helped to explain many complex multifactorial diseases with no clear genetic cause. We therefore asked whether epigenetics could also play a role in OA. We have previously shown that the DNA epigenetic modification, specifically the hydroxymethylation on cytosine (5hmC), undergoes a fivefold increase on OA-associated genes which are activated at OA onset. In this study, we further uncovered a set of 5hmC-mediated gene targets and their mechanistic link to OA progression. Materials and Methods. We surgically induced OA on 4 to 6 months old Tet1−/− mice (Tet1tm1.1Jae, the Jackson laboratory) and wild-type littermates by performing destabilization of the medial meniscus (DMM) surgery. Joints were collected for histological assessment through blinded grading with the OARSI scoring system. Human articular chondrocytes were harvested from OA cartilage samples obtained during total knee arthroplasty or from grossly normal cartilage pieces obtained during notchplasty or debridement from patients undergoing anterior cruciate ligament (ACL) reconstruction with no history of OA symptoms, under approved Human subjects Institutional Review Board protocols. Bioinformatic analyses of RNA-sequencing and CCGG sequencing (reduced representation 5hmC profiling) were performed to identify TET1 target genes associated with OA progression. Several measurements were used to assess the effect of TET1 ablation on the phenotype of mouse cartilage tissue and human chondrocytes including, histological evaluation, and quantitative bone assessment by micro-CT imaging and multiplex cytokine analyses in the serum of mice in vivo (mouse 39-plex assay) and in the supernatant of human chondrocyte cultures (human 62-plex assay). Results. We used a mouse model with surgically induced OA and found that OA onset was accompanied by a gain of ∼40,000 differentially hydroxymethylated sites prior the notable histological onset of the disease. We additionally revealed that these changes are mediated by the ten-eleven-translocation enzyme 1 (TET1), since Tet1−/− mice lost 98% of 5hmC sites upon OA induction. Remarkably, Tet1−/− mice were protected from OA development including degeneration of the cartilage surface and osteophyte formation. Silencing of TET1 expression in human OA chondrocytes reduced the expression in a set of genes, which may represent the pathological gene targets that exacerbate OA including MMP3 and MMP13 and several inflammatory cytokines. Therefore, our study reveals the unexpected beneficial role of TET1 inhibition in blocking OA progression. In fact, intra-articular injections of a dioxygenases’ inhibitor, 2 hydroxyglutarate, on mice after surgical induction of OA stalled disease progression. Furthermore, treatment of human OA chondrocytes with the same inhibitor also phenocopied TET1 loss, implicating a therapeutic potential of TET inhibition in OA patients. Conclusions. Collectively, our study not only demonstrate the role of TET1 in OA; the 5hmC-mediated gene targets acting on multiple OA pathways were identified and can be modulated as therapeutic intervention to treat OA

To design osteoarthritis (OA) care based on prognosis, we need to identify individuals who are most likely of disease progression. We estimated survival time of the native hip and knee joint and evaluated what patient-related and OA disease-related factors associated with progression to joint replacement surgery. We included 72,069 patients referred to first-line OA intervention (patient education and exercise) during 2008 and 2016 and registered in the Swedish quality register Better Management of Patients with Osteoarthritis (BOA). Kaplan–Meier survival analyses were used to estimate joint survival time. Hazard ratios (HR) with 95% confidence interval [CI] were calculated using multiple Cox regression. The 5-year survival time of the native joint was 56% for hip OA and 80% for knee OA. Disease-related factors were more strongly associated with progression to joint replacement (e.g. willingness for surgery HR; hip 2.9 [95% CI, 2.7–3.1], knee 2.7 [2.6–2.9] and walking difficulties (HR; hip 2.2 [2.0–2.5], knee 1.9 [1.7–2.2]), than patient-related factors such socioeconomic factors (e.g. highest income quartile HR; hip 1.3 [1.2–1.3], knee 1.3 [1.2–1.4]) and comorbidities (e.g. ≥6 conditions HR; hip: 0.7 [0.6–0.7], knee; 1.1 [1.0–1.2]). Patients with hip OA were more likely to undergo surgery and at an earlier time compared with those with knee OA. Progression was strongly influenced by factors associated with the OA disease, but other patient-related factors are important. However, a large proportion of patients with OA do not seem to require surgery, especially among those with knee OA

Aims. To investigate the risk factors for progression of articular cartilage damage after anatomical anterior cruciate ligament (ACL) reconstruction. Patients and Methods. A total of 174 patients who underwent second-look arthroscopic evaluation after anatomical ACL reconstruction were enrolled in this study. The graded condition of the articular cartilage at the time of ACL reconstruction was compared with that at second-look arthroscopy. Age, gender, body mass index (BMI), ACL reconstruction technique, meniscal conditions, and other variables were assessed by regression analysis as risk factors for progression of damage to the articular cartilage. Results. In the medial compartment, multivariable logistic regression analysis indicated that partial medial meniscectomy (odds ratio (OR) 6.82, 95% confidence interval (CI) 2.11 to 22.04, p = 0.001), pivot-shift test grade at the final follow-up (OR 3.53, CI 1.39 to 8.96, p = 0.008), BMI (OR 1.15, CI 1.03 to 1.28, p = 0.015) and medial meniscal repair (OR 3.19, CI 1.24 to 8.21, p = 0.016) were significant risk factors for progression of cartilage damage. In the lateral compartment, partial lateral meniscectomy (OR 10.94, CI 4.14 to 28.92, p < 0.001) and side-to-side differences in anterior knee laxity at follow-up (OR 0.63, p = 0.001) were significant risk factors. Conclusion. Partial meniscectomy was found to be strongly associated with the progression of articular cartilage damage despite r anatomical ACL reconstruction. Cite this article: Bone Joint J 2018;100-B:285–93

Developmental dysplasia of the hip can cause pain and premature osteoarthritis. However, the risk factors and timing for disease progression in young adults are not fully defined. This study identified the incidence and risk factors for contralateral hip pain and surgery after periacetabular osteotomy (PAO) on an index dysplastic hip. Patients followed for 2+ years after unilateral PAO were grouped by eventual contralateral pain or no-pain, based on modified Harris Hip Score, and surgery or no-surgery. Univariate analysis tested group differences in demographics, radiographic measures, and range-of-motion. Kaplan-Meier survival analysis assessed pain development and contralateral hip surgery over time. Multivariate regression identified pain and surgery risk factors. Pain and surgery predictors were further analyzed in Dysplastic, Borderline, and Non-dysplastic subcategories, and in five-degree increments of lateral center edge angle (LCEA) and acetabular inclination (AI). 184 patients were followed for 4.6±1.6 years, during which 51% (93/184) reported hip pain and 33% (60/184) underwent contralateral surgery. Kaplan-Meier analysis predicted 5-year survivorship of 49% for pain development and 66% for contralateral surgery. Painful hips exhibited more severe dysplasia than no-pain hips (LCEA 16.5º vs 20.3º, p<0.001; AI 13.2º vs 10.0º p<0.001). AI was the sole predictor of pain, with every 1° AI increase raising the risk by 11%. Surgical hips also had more severe dysplasia (LCEA 14.9º vs 20.0º, p<0.001; AI 14.7º vs 10.2º p<0.001) and were younger (21.6 vs 24.1 years, p=0.022). AI and a maximum alpha angle ≥55° predicted contralateral surgery. 5 years after index hip PAO, 51% of contralateral hips experience pain and 34% percent are expected to need surgery. More severe dysplasia, based on LCEA and AI, increases the risk of contralateral hip pain and surgery, with AI being a predictor of both outcomes. Knowing these risks can inform patient counseling and treatment planning

Although the association between femoroacetabular impingement and osteoarthritis is established, it is not yet clear which hips have the greatest likelihood to progress rapidly to end-stage disease. We investigated the effect of several radiological parameters, each indicative of a structural aspect of the hip joint, on the progression of osteoarthritis. Pairs of plain anteroposterior pelvic radiographs, taken at least ten years apart, of 43 patients (43 hips) with a pistol-grip deformity of the femur and mild (Tönnis grade 1) or moderate (Tönnis grade 2) osteoarthritis were reviewed. Of the 43 hips, 28 showed evidence of progression of osteoarthritis. There was no significant difference in the prevalence of progression between hips with initial Tönnis grade 1 or grade 2 osteoarthritis (p = 0.31). Comparison of the hips with and without progression of arthritis revealed a significant difference in the mean medial proximal femoral angle (81° vs 87°, p = 0.004) and the presence of the posterior wall sign (39% vs 7%, p = 0.02) only. A logistic regression model was constructed to predict the influence of these two variables in the development of osteoarthritis. Mild to moderate osteoarthritis in hips with a pistol-grip deformity will not progress rapidly in all patients. In one-third, progression will take more than ten years to manifest, if ever. The individual geometry of the proximal femur and acetabulum partly influences this phenomenon. A hip with cam impingement is not always destined for end-stage arthritic degeneration