Aims. Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. Methods. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers. Results. C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients. Conclusion. This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the diagnosis and treatment of OA. Cite this article: Bone Joint Res 2023;12(12):702–711

Aims. The aim of this study was to investigate the association between fracture displacement and survivorship of the native hip joint without conversion to a total hip arthroplasty (THA), and to determine predictors for conversion to THA in patients treated nonoperatively for acetabular fractures. Methods. A multicentre cross-sectional study was performed in 170 patients who were treated nonoperatively for an acetabular fracture in three level 1 trauma centres. Using the post-injury diagnostic CT scan, the maximum gap and step-off values in the weightbearing dome were digitally measured by two trauma surgeons. Native hip survival was reported using Kaplan-Meier curves. Predictors for conversion to THA were determined using Cox regression analysis. Results. Of 170 patients, 22 (13%) subsequently received a THA. Native hip survival in patients with a step-off ≤ 2 mm, > 2 to 4 mm, or > 4 mm differed at five-year follow-up (respectively: 94% vs 70% vs 74%). Native hip survival in patients with a gap ≤ 2 mm, > 2 to 4 mm, or > 4 mm differed at five-year follow-up (respectively: 100% vs 84% vs 78%). Step-off displacement > 2 mm (> 2 to 4 mm hazard ratio (HR) 4.9, > 4 mm HR 5.6) and age > 60 years (HR 2.9) were independent predictors for conversion to THA at follow-up. Conclusion. Patients with minimally displaced acetabular fractures who opt for nonoperative fracture treatment may be informed that fracture displacement (e.g. gap and step-off) up to 2 mm, as measured on CT images, results in limited risk on conversion to THA. Step-off ≥ 2 mm and age > 60 years are predictors for conversion to THA and can be helpful in the shared decision-making process. Cite this article: Bone Joint J 2023;105-B(9):1020–1029

Aims. As a proven and comprehensive molecular technique, metagenomic next-generation sequencing (mNGS) has shown its potential in the diagnosis of pathogens in patients with periprosthetic joint infection (PJI), using a single type of specimen. However, the optimal use of mNGS in the management of PJI has not been explored. In this study, we evaluated the diagnostic value of mNGS using three types of specimen with the aim of achieving a better choice of specimen for mNGS in these patients. Methods. In this prospective study, 177 specimens were collected from 59 revision arthroplasties, including periprosthetic tissues, synovial fluid, and prosthetic sonicate fluid. Each specimen was divided into two, one for mNGS and one for culture. The criteria of the Musculoskeletal Infection Society were used to define PJI (40 cases) and aseptic failure (19 cases). Results. The sensitivity and specificity of mNGS in the diagnosis of PJI were 95% and 94.7%, respectively, for all types of specimen. The sensitivity and specificity were 65% and 100%, respectively, for periprosthetic tissues, 87.5% and 94.7%, respectively, for synovial fluid, and 92.5% and 94.7%, respectively, for prosthetic sonicate fluid. The mNGS of prosthetic sonicate fluid outperformed that for other types of specimen in the rates of detection of pathogens (84.6%), sequencing reads (> ten-fold) and the rate of genome coverage (> five-fold). Conclusion. mNGS could serve as an accurate diagnostic tool in the detection of pathogens in patients with a PJI using three types of specimen. Due to its superior perfomance in identifying a pathogen, mNGS of prosthetic sonicate fluid provides the most value and may partly replace traditional tests such as bacteriological culture in these patients. Cite this article: Bone Joint J 2021;103-B(5):923–930

Chondrosarcoma is the second most common surgically treated primary bone sarcoma. Despite a large number of scientific papers in the literature, there is still significant controversy about diagnostics, treatment of the primary tumour, subtypes, and complications. Therefore, consensus on its day-to-day treatment decisions is needed. In January 2024, the Birmingham Orthopaedic Oncology Meeting (BOOM) attempted to gain global consensus from 300 delegates from over 50 countries. The meeting focused on these critical areas and aimed to generate consensus statements based on evidence amalgamation and expert opinion from diverse geographical regions. In parallel, periprosthetic joint infection (PJI) in oncological reconstructions poses unique challenges due to factors such as adjuvant treatments, large exposures, and the complexity of surgery. The meeting debated two-stage revisions, antibiotic prophylaxis, managing acute PJI in patients undergoing chemotherapy, and defining the best strategies for wound management and allograft reconstruction. The objectives of the meeting extended beyond resolving immediate controversies. It sought to foster global collaboration among specialists attending the meeting, and to encourage future research projects to address unsolved dilemmas. By highlighting areas of disagreement and promoting collaborative research endeavours, this initiative aims to enhance treatment standards and potentially improve outcomes for patients globally. This paper sets out some of the controversies and questions that were debated in the meeting. Cite this article: Bone Joint J 2024;106-B(5):425–429

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 aim of this study was to determine the diagnostic accuracy of α defensin (AD) lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) tests for periprosthetic joint infection (PJI) in comparison to conventional synovial white blood cell (WBC) count and polymorphonuclear neutrophil percentage (PMN%) analysis. Methods. Patients undergoing joint aspiration for evaluation of pain after total knee arthroplasty (TKA) or total hip arthroplasty (THA) were considered for inclusion. Synovial fluids from 99 patients (25 THA and 74 TKA) were analyzed by WBC count and PMN% analysis, AD LFA, and AD ELISA. WBC and PMN% cutoffs of ≥ 1,700 cells/mm. 3. and ≥ 65% for TKA and ≥ 3,000 cells/mm. 3. and ≥ 80% for THA were used, respectively. A panel of three physicians, all with expertise in orthopaedic infections and who were blinded to the results of AD tests, independently reviewed patient data to diagnose subjects as with or without PJI. Consensus PJI classification was used as the reference standard to evaluate test performances. Results were compared using McNemar’s test and area under the receiver operating characteristic curve (AUC) analysis. Results. Expert consensus classified 18 arthroplasies as having failed due to PJI and 81 due to aseptic failure. Using these classifications, the calculated sensitivity and specificity of AD LFA was 83.3% (95% confidence interval (CI) 58.6 to 96.4) and 93.8% (95% CI 86.2 to 98.0), respectively. Sensitivity and specificity of AD ELISA was 83.3% (95% CI 58.6 to 96.4) and 96.3% (95% CI 89.6 to 99.2), respectively. There was no statistically significant difference between sensitivity (p = 1.000) or specificity (p = 0.157) of the two AD assays. AUC for AD LFA was 0.891. In comparison, AUC for synovial WBC count, PMN%, and the combination of the two values was 0.821 (sensitivity p = 1.000, specificity p < 0.001), 0.886 (sensitivity p = 0.317, specificity p = 0.011), and 0.926 (sensitivity p = 0.317, specificity p = 0.317), respectively. Conclusion. The diagnostic accuracy of synovial AD for PJI diagnosis is comparable and not statistically superior to that of synovial WBC count plus PMN% combined. Cite this article: Bone Joint J 2021;103-B(6):1119–1126

Aims. The diagnosis of periprosthetic joint infection (PJI) can be difficult. All current diagnostic tests have problems with accuracy and interpretation of results. Many new tests have been proposed, but there is no consensus on the place of many of these in the diagnostic pathway. Previous attempts to develop a definition of PJI have not been universally accepted and there remains no reference standard definition. Methods. This paper reports the outcome of a project developed by the European Bone and Joint Infection Society (EBJIS), and supported by the Musculoskeletal Infection Society (MSIS) and the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Implant-Associated Infections (ESGIAI). It comprised a comprehensive review of the literature, open discussion with Society members and conference delegates, and an expert panel assessment of the results to produce the final guidance. Results. This process evolved a three-level approach to the diagnostic continuum, resulting in a definition set and guidance, which has been fully endorsed by EBJIS, MSIS, and ESGIAI. Conclusion. The definition presents a novel three-level approach to diagnosis, based on the most robust evidence, which will be useful to clinicians in daily practice. Cite this article: Bone Joint J 2021;103-B(1):18–25

There has been a marked increase in the number of hip arthroscopies performed over the past 16 years, primarily in the management of femoroacetabular impingement (FAI). Insights into the pathoanatomy of FAI, and high-level evidence supporting the clinical effectiveness of arthroscopy in the management of FAI, have fuelled this trend. Arthroscopic management of labral tears with repair may have superior results compared with debridement, and there is now emerging evidence to support reconstructive options where repair is not possible. In situations where an interportal capsulotomy is performed to facilitate access, data now support closure of the capsule in selective cases where there is an increased risk of postoperative instability. Preoperative planning is an integral component of bony corrective surgery in FAI, and this has evolved to include computer-planned resection. However, the benefit of this remains controversial. Hip instability is now widely accepted, and diagnostic criteria and treatment are becoming increasingly refined. Instability can also be present with FAI or develop as a result of FAI treatment. In this annotation, we outline major current controversies relating to decision-making in hip arthroscopy for FAI. Cite this article: Bone Joint J 2022;104-B(5):532–540

Aims. The preoperative diagnosis of periprosthetic joint infection (PJI) remains a challenge due to a lack of biomarkers that are both sensitive and specific. We investigated the performance characteristics of polymerase chain reaction (PCR), interleukin-6 (IL6), and calprotectin of synovial fluid in the diagnosis of PJI. Methods. We performed systematic search of PubMed, Embase, The Cochrane Library, Web of Science, and Science Direct from the date of inception of each database through to 31 May 2021. Studies which described the diagnostic accuracy of synovial fluid PCR, IL6, and calprotectin using the Musculoskeletal Infection Society criteria as the reference standard were identified. Results. Overall, 31 studies were identified: 20 described PCR, six described IL6, and five calprotectin. The sensitivity and specificity were 0.78 (95% confidence interval (CI) 0.67 to 0.86) and 0.97 (95% CI 0.94 to 0.99), respectively, for synovial PCR;, 0.86 (95% CI 0.74 to 0.92), and 0.94 (95% CI 0.90 to 0.96), respectively, for synovial IL6; and 0.94 (95% CI 0.82 to 0.98) and 0.93 (95% CI 0.85 to 0.97), respectively, for synovial calprotectin. Likelihood ratio scattergram analyses recommended clinical utility of synovial fluid PCR and IL6 as a confirmatory test only. Synovial calprotectin had utility in the exclusion and confirmation of PJI. Conclusion. Synovial fluid PCR and IL6 had low sensitivity and high specificity in the diagnosis of PJI, and is recommended to be used as confirmatory test. In contrast, synovial fluid calprotectin had both high sensitivity and specificity with utility in both the exclusion and confirmation of PJI. We recommend use of synovial fluid calprotectin studies in the preoperative workup of PJI. Cite this article: Bone Joint J 2022;104-B(3):311–320

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 further evaluate the accuracy of ten promising synovial biomarkers (bactericidal/permeability-increasing protein (BPI), lactoferrin (LTF), neutrophil gelatinase-associated lipocalin (NGAL), neutrophil elastase 2 (ELA-2), α-defensin, cathelicidin LL-37 (LL-37), human β-defensin (HBD-2), human β-defensin 3 (HBD-3), D-dimer, and procalcitonin (PCT)) for the diagnosis of periprosthetic joint infection (PJI), and to investigate whether inflammatory joint disease (IJD) activity affects their concentration in synovial fluid. Methods. We included 50 synovial fluid samples from patients with (n = 25) and without (n = 25) confirmed PJI from an institutional tissue bank collected between May 2015 and December 2016. We also included 22 synovial fluid samples aspirated from patients with active IJD presenting to Department of Rheumatology, the first Medical Centre, Chinese PLA General Hospital. Concentrations of the ten candidate biomarkers were measured in the synovial fluid samples using standard enzyme-linked immunosorbent assays (ELISA). The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves. Results. BPI, LTF, NGAL, ELA-2, and α-defensin were well-performing biomarkers for detecting PJI, with areas under the curve (AUCs) of 1.000 (95% confidence interval, 1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), and 0.998 (0.994 to 1.000), respectively. The other markers (LL-37, HBD-2, D-dimer, PCT, and HBD-3) had limited diagnostic value. For the five well-performing biomarkers, elevated concentrations were observed in patients with active IJD. The original best thresholds determined by the Youden index, which discriminated PJI cases from non-PJI cases could not discriminate PJI cases from active IJD cases, while elevated thresholds resulted in good performance. Conclusion. BPI, LTF, NGAL, ELA-2, and α-defensin demonstrated excellent performance for diagnosing PJI. However, all five markers showed elevated concentrations in patients with IJD activity. For patients with IJD, elevated thresholds should be considered to accurately diagnose PJI. Cite this article: Bone Joint J 2021;103-B(1):32–38

Injuries to the quadriceps muscle group are common in athletes performing high-speed running and kicking sports. The complex anatomy of the rectus femoris puts it at greatest risk of injury. There is variability in prognosis in the literature, with reinjury rates as high as 67% in the severe graded proximal tear. Studies have highlighted that athletes can reinjure after nonoperative management, and some benefit may be derived from surgical repair to restore function and return to sport (RTS). This injury is potentially career-threatening in the elite-level athlete, and we aim to highlight the key recent literature on interventions to restore strength and function to allow early RTS while reducing the risk of injury recurrence. This article reviews the optimal diagnostic strategies and classification of quadriceps injuries. We highlight the unique anatomy of each injury on MRI and the outcomes of both nonoperative and operative treatment, providing an evidence-based management framework for athletes. Cite this article: Bone Joint J 2023;105-B(12):1244–1251

Aims. The aim of this study was to inform the epidemiology and treatment of slipped capital femoral epiphysis (SCFE). Methods. This was an anonymized comprehensive cohort study, with a nested consented cohort, following the the Idea, Development, Exploration, Assessment, Long-term study (IDEAL) framework. A total of 143 of 144 hospitals treating SCFE in Great Britain participated over an 18-month period. Patients were cross-checked against national administrative data and potential missing patients were identified. Clinician-reported outcomes were collected until two years. Patient-reported outcome measures (PROMs) were collected for a subset of participants. Results. A total of 486 children (513 hips) were newly affected, with a median of two patients (interquartile range 0 to 4) per hospital. The annual incidence was 3.34 (95% confidence interval (CI) 3.01 to 3.67) per 100,000 six- to 18-year-olds. Time to diagnosis in stable disease was increased in severe deformity. There was considerable variation in surgical strategy among those unable to walk at diagnosis (66 urgent surgery vs 43 surgery after interval delay), those with severe radiological deformity (34 fixation with deformity correction vs 36 without correction) and those with unaffected opposite hips (120 prophylactic fixation vs 286 no fixation). Independent risk factors for avascular necrosis (AVN) were the inability of the child to walk at presentation to hospital (adjusted odds ratio (aOR) 4.4 (95% CI 1.7 to 11.4)) and surgical technique of open reduction and internal fixation (aOR 7.5 (95% CI 2.4 to 23.2)). Overall, 33 unaffected untreated opposite hips (11.5%) were treated for SCFE by two-year follow-up. Age was the only independent risk factor for contralateral SCFE, with age under 12.5 years the optimal cut-off to define ‘at risk’. Of hips treated with prophylactic fixation, none had SCFE, though complications included femoral fracture, AVN, and revision surgery. PROMs demonstrated the marked impact on quality of life on the child because of SCFE. Conclusion. The experience of individual hospitals is limited and mechanisms to consolidate learning may enhance care. Diagnostic delays were common and radiological severity worsened with increasing time to diagnosis. There was unexplained variation in treatment, some of which exposes children to significant risks that should be evaluated through randomized controlled trials. Cite this article: Bone Joint J 2022;104-B(4):519–528

Aims. Use of molecular sequencing methods in periprosthetic joint infection (PJI) diagnosis and organism identification have gained popularity. Next-generation sequencing (NGS) is a potentially powerful tool that is now commercially available. The purpose of this study was to compare the diagnostic accuracy of NGS, polymerase chain reaction (PCR), conventional culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al in the diagnosis of PJI. Methods. In this retrospective study, aspirates or tissue samples were collected in 30 revision and 86 primary arthroplasties for routine diagnostic investigation for PJI and sent to the laboratory for NGS and PCR. Concordance along with statistical differences between diagnostic studies were calculated. Results. Using the MSIS criteria to diagnose PJI as the reference standard, the sensitivity and specificity of NGS were 60.9% and 89.9%, respectively, while culture resulted in sensitivity of 76.9% and specificity of 95.3%. PCR had a low sensitivity of 18.4%. There was no significant difference based on sample collection method (tissue swab or synovial fluid) (p = 0.760). There were 11 samples that were culture-positive and NGS-negative, of which eight met MSIS criteria for diagnosing infection. Conclusion. In our series, NGS did not provide superior sensitivity or specificity results compared to culture. PCR has little utility as a standalone test for PJI diagnosis with a sensitivity of only 18.4%. Currently, several laboratory tests for PJI diagnosis should be obtained along with the overall clinical picture to help guide decision-making for PJI treatment. Cite this article: Bone Joint J 2021;103-B(1):26–31

Aims. The aim of this study was to analyze the prevalence of culture-negative periprosthetic joint infections (PJIs) when adequate methods of culture are used, and to evaluate the outcome in patients who were treated with antibiotics for a culture-negative PJI compared with those in whom antibiotics were withheld. Methods. A multicentre observational study was undertaken: 1,553 acute and 1,556 chronic PJIs, diagnosed between 2013 and 2018, were retrospectively analyzed. Culture-negative PJIs were diagnosed according to the Muskuloskeletal Infection Society (MSIS), International Consensus Meeting (ICM), and European Bone and Joint Society (EBJIS) definitions. The primary outcome was recurrent infection, and the secondary outcome was removal of the prosthetic components for any indication, both during a follow-up period of two years. Results. None of the acute PJIs and 70 of the chronic PJIs (4.7%) were culture-negative; a total of 36 culture-negative PJIs (51%) were treated with antibiotics, particularly those with histological signs of infection. After two years of follow-up, no recurrent infections occurred in patients in whom antibiotics were withheld. The requirement for removal of the components for any indication during follow-up was not significantly different in those who received antibiotics compared with those in whom antibiotics were withheld (7.1% vs 2.9%; p = 0.431). Conclusion. When adequate methods of culture are used, the incidence of culture-negative PJIs is low. In patients with culture-negative PJI, antibiotic treatment can probably be withheld if there are no histological signs of infection. In all other patients, diagnostic efforts should be made to identify the causative microorganism by means of serology or molecular techniques. Cite this article: Bone Joint J 2022;104-B(1):183–188

Aims. The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Methods. Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA. Results. PLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model. Conclusion. SF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy trials and monitor the efficacy of such interventions. Cite this article: Bone Joint Res 2020;9(9):623–632