Aims. The early diagnosis of cauda equina syndrome (CES) is crucial for a favourable outcome. Several studies have reported the use of an ultrasound scan of the bladder as an adjunct to assess the minimum post-void residual volume of urine (mPVR). However, variable mPVR values have been proposed as a threshold without consensus on a value for predicting CES among patients with relevant symptoms and signs. The aim of this study was to perform a meta-analysis and systematic review of the published evidence to identify a threshold mPVR value which would provide the highest diagnostic accuracy in patients in whom the diagnosis of CES is suspected. Methods. The search strategy used electronic databases (PubMed, Medline, EMBASE, and AMED) for publications between January 1996 and November 2021. All studies that reported mPVR in patients in whom the diagnosis of CES was suspected, followed by MRI, were included. Results. A total of 2,115 studies were retrieved from the search. Seven fulfilled the inclusion criteria. These included 1,083 patients, with data available from 734 being available for meta-analysis. In 125 patients, CES was confirmed by MRI. The threshold value of mPVR reported in each study varied and could be categorized into 100 ml, 200 ml, 300 ml, and 500 ml. From the meta-analysis, 200 ml had the highest diagnostic accuracy, with 82% sensitivity (95% confidence interval (CI) 0.72 to 0.90) and 65% specificity (95% CI 0.70 to 0.90). When compared using summative receiver operating characteristic curves, mPVR of 200 ml was superior to other values in predicting the radiological confirmation of CES. Conclusion. mPVR is a useful tool when assessing patients in whom the diagnosis of CES is suspected. Compared with other values a mPVR of 200 ml had superior sensitivity, specificity, and positive and negative predictive values. In a patient with a suggestive history and clinical findings, a mPVR of > 200 ml should further raise the suspicion of CES. Caution is recommended when considering the mPVR in isolation and using it as an ‘exclusion tool’, and it should only be used as an adjunct to a full clinical assessment. Cite this article: Bone Joint J 2023;105-B(5):487–495

Aims

Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.

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.