Aims. Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes. Methods. A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines using the MEDLINE, Embase, PubMed, and Cochrane databases. Studies included were case series, case control series, and cohort studies looking specifically at HSF. Results. The primary analysis, which pooled the results from 17 published studies and four meeting abstracts, identified over 200 metabolites. Seven of these studies (six published studies, one meeting abstract) had asymptomatic control groups and collectively suggested 26 putative biomarkers in osteoarthritis, inflammatory arthropathies, and trauma. These can broadly be categorized into amino acids plus related metabolites, fatty acids, ketones, and sugars. Conclusion. The role of metabolic profiling in orthopaedics is fast evolving with many metabolites already identified in a variety of pathologies. However, these results need to be interpreted with caution due to the presence of multiple confounding factors in many of the studies. Future research should include largescale epidemiological metabolic profiling studies incorporating various confounding factors with appropriate statistical analysis to account for multiple testing of the data. Cite this article:Bone Joint Res. 2020;9(3):108–119

Aims. The diagnosis of periprosthetic joint infection (PJI) has always been challenging. Recently, D-dimer has become a promising biomarker in diagnosing PJI. However, there is controversy regarding its diagnostic value. We aim to investigate the diagnostic value of D-dimer in comparison to ESR and CRP. Methods. PubMed, Embase, and the Cochrane Library were searched in February 2020 to identify articles reporting on the diagnostic value of D-dimer on PJI. Pooled analysis was conducted to investigate the diagnostic value of D-dimer, CRP, and ESR. Results. Six studies with 1,255 cases were included (374 PJI cases and 881 non-PJI cases). Overall D-dimer showed sensitivity of 0.80 (95% confidence interval (CI) 0.69 to 0.87) and specificity of 0.76 (95% CI 0.63 to 0.86). Sub-group analysis by excluding patients with thrombosis and hyper-coagulation disorders showed sensitivity of 0.82 (95% CI 0.70 to 0.90) and specificity of 0.80 (95% CI 0.70 to 0.88). Serum D-dimer showed sensitivity of 0.85 (95% CI 0.76 to 0.92), specificity of 0.83 (95% CI 0.74 to 0.90). Plasma D-dimer showed sensitivity of 0.67 (95% CI 0.60 to 0.73), specificity of 0.58 (95% CI 0.45 to 0.72). CRP showed sensitivity of 0.78 (95% CI 0.72 to 0.83), specificity of 0.81 (95% CI 0.72 to 0.87). ESR showed sensitivity of 0.68 (95% CI 0.63 to 0.73), specificity of 0.83 (95% CI 0.78 to 0.87). Conclusion. In patients without thrombosis or a hyper-coagulation disorder, D-dimer has a higher diagnostic value compared to CRP and ESR. In patients with the aforementioned conditions, D-dimer has higher sensitivity but lower specificity compared to ESR and CRP. We do not recommend the use of serum D-dimer in patients with thrombosis and hyper-coagulation disorders for diagnosing PJI. Serum D-dimer may perform better than plasma D-dimer. Further studies are needed to compare serum D-dimer and plasma D-dimer in arthroplasty patients. Cite this article: Bone Joint Res 2020;9(10):701–708

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

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.

Osteoarthritis (OA), one of the most common motor system disorders, is a degenerative disease involving progressive joint destruction caused by a variety of factors. At present, OA has become the fourth most common cause of disability in the world. However, the pathogenesis of OA is complex and has not yet been clarified. Long non-coding RNA (lncRNA) refers to a group of RNAs more than 200 nucleotides in length with limited protein-coding potential, which have a wide range of biological functions including regulating transcriptional patterns and protein activity, as well as binding to form endogenous small interference RNAs (siRNAs) and natural microRNA (miRNA) molecular sponges. In recent years, a large number of lncRNAs have been found to be differentially expressed in a variety of pathological processes of OA, including extracellular matrix (ECM) degradation, synovial inflammation, chondrocyte apoptosis, and angiogenesis. Obviously, lncRNAs play important roles in regulating gene expression, maintaining the phenotype of cartilage and synovial cells, and the stability of the intra-articular environment. This article reviews the results of the latest research into the role of lncRNAs in a variety of pathological processes of OA, in order to provide a new direction for the study of OA pathogenesis and a new target for prevention and treatment.

Cite this article: Bone Joint Res 2021;10(2):122–133.

Aims

Patients with metabolic syndrome (MetS) are known to be at increased risk of postoperative complications, but it is unclear whether MetS is also associated with complications after total hip arthroplasty (THA) or total knee arthroplasty (TKA). Here, we perform a systematic review and meta-analysis linking MetS to postoperative complications in THA and TKA.

Aims

The aim of this review was to evaluate the available literature and to calculate the pooled sensitivity and specificity for the different alpha-defensin test systems that may be used to diagnose prosthetic joint infection (PJI).