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. 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.Aims
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Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests.Aims
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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
Aims. Clinical management of open fractures is challenging and frequently requires complex reconstruction procedures. The Gustilo-Anderson classification lacks uniform interpretation, has poor interobserver reliability, and fails to account for injuries to musculotendinous units and bone. The Ganga Hospital Open Injury Severity Score (GHOISS) was designed to address these concerns. The major aim of this review was to ascertain the evidence available on accuracy of the GHOISS in predicting successful limb salvage in patients with mangled limbs. Methods. We searched electronic data bases including PubMed, CENTRAL, EMBASE, CINAHL, Scopus, and Web of Science to identify studies that employed the GHOISS risk tool in managing complex limb injuries published from April 2006, when the score was introduced, until April 2021. Primary outcome was the measured
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
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). 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.Aims
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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
Aims. This study aimed to answer two questions: what are the best diagnostic methods for diagnosing bacterial arthritis of a native joint?; and what are the most commonly used definitions for bacterial arthritis of a native joint?. Methods. We performed a search of PubMed, Embase, and Cochrane libraries for relevant studies published between January 1980 and April 2020. Of 3,209 identified studies, we included 27 after full screening.
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
Deep gluteal syndrome is an increasingly recognized disease entity, caused by compression of the sciatic or pudendal nerve due to non-discogenic pelvic lesions. It includes the piriformis syndrome, the gemelli-obturator internus syndrome, the ischiofemoral impingement syndrome, and the proximal hamstring syndrome. The concept of the deep gluteal syndrome extends our understanding of posterior hip pain due to nerve entrapment beyond the traditional model of the piriformis syndrome. Nevertheless, there has been terminological confusion and the deep gluteal syndrome has often been undiagnosed or mistaken for other conditions. Careful history-taking, a physical examination including provocation tests, an electrodiagnostic study, and imaging are necessary for an accurate diagnosis. After excluding spinal lesions, MRI scans of the pelvis are helpful in diagnosing deep gluteal syndrome and identifying pathological conditions entrapping the nerves. It can be conservatively treated with multidisciplinary treatment including rest, the avoidance of provoking activities, medication, injections, and physiotherapy. Endoscopic or open surgical decompression is recommended in patients with persistent or recurrent symptoms after conservative treatment or in those who may have masses compressing the sciatic nerve. Many physicians remain unfamiliar with this syndrome and there is a lack of relevant literature. This comprehensive review aims to provide the latest information about the epidemiology, aetiology, pathology, clinical features, diagnosis, and treatment. Cite this article:
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. 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.Aims
Methods
Aims. To assess the diagnostic value of C-reactive protein (CRP), leucocyte count (LC), and erythrocyte sedimentation rate (ESR) in late fracture-related infection (FRI). Materials and Methods. PubMed, Embase, and Cochrane databases were searched focusing on the diagnostic value of CRP, LC, and ESR in late FRI.
Aims. The aim of this review was to evaluate the available literature
and to calculate the pooled