Aims. The risk factors for recurrent instability (RI) following a primary traumatic anterior shoulder dislocation (PTASD) remain unclear. In this study, we aimed to determine the rate of RI in a large cohort of patients managed nonoperatively after PTASD and to develop a clinical prediction model. Methods. A total of 1,293 patients with PTASD managed nonoperatively were identified from a trauma database (mean age 23.3 years (15 to 35); 14.3% female). We assessed the prevalence of RI, and used multivariate regression modelling to evaluate which demographic- and injury-related factors were independently predictive for its occurrence. Results. The overall rate of RI at a mean follow-up of 34.4 months (SD 47.0) was 62.8% (n = 812), with 81.0% (n = 658) experiencing their first recurrence within two years of PTASD. The median time for recurrence was 9.8 months (IQR 3.9 to 19.4). Independent predictors increasing risk of RI included male sex (p < 0.001), younger age at PTASD (p < 0.001), participation in contact sport (p < 0.001), and the presence of a bony Bankart (BB) lesion (p = 0.028). Greater tuberosity fracture (GTF) was protective (p < 0.001). However, the discriminative ability of the resulting predictive model for two-year risk of RI was poor (area under the curve (AUC) 0.672). A subset analysis excluding identifiable radiological predictors of BB and GTF worsened the predictive ability (AUC 0.646). Conclusion. This study clarifies the prevalence and risk factors for RI following PTASD in a large, unselected patient cohort. Although these data permitted the development of a predictive tool for RI, its discriminative ability was poor. Predicting RI remains challenging, and as-yet-undetermined risk factors may be important in determining the risk. Cite this article: Bone Joint J 2024;106-B(10):1111–1117

Aims

To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports.

Acute bone and joint infections in children are serious, and misdiagnosis can threaten limb and life. Most young children who present acutely with pain, limping, and/or loss of function have transient synovitis, which will resolve spontaneously within a few days. A minority will have a bone or joint infection. Clinicians are faced with a diagnostic challenge: children with transient synovitis can safely be sent home, but children with bone and joint infection require urgent treatment to avoid complications. Clinicians often respond to this challenge by using a series of rudimentary decision support tools, based on clinical, haematological, and biochemical parameters, to differentiate childhood osteoarticular infection from other diagnoses. However, these tools were developed without methodological expertise in diagnostic accuracy and do not consider the importance of imaging (ultrasound scan and MRI). There is wide variation in clinical practice with regard to the indications, choice, sequence, and timing of imaging. This variation is most likely due to the lack of evidence concerning the role of imaging in acute bone and joint infection in children. We describe the first steps of a large UK multicentre study, funded by the National Institute for Health Research, which seeks to integrate definitively the role of imaging into a decision support tool, developed with the assistance of individuals with expertise in the development of clinical prediction tools. Cite this article: Bone Joint J 2023;105-B(3):227–229

Aims

The aim of this study was to describe the introduction of a virtual pathway for the management of patients with a suspected fracture of the scaphoid, and to report patient-reported outcome measures (PROMs) and satisfaction following treatment using this service.

Aims. To develop and internally validate a preoperative clinical prediction model for acute adjacent vertebral fracture (AVF) after vertebral augmentation to support preoperative decision-making, named the after vertebral augmentation (AVA) score. Methods. In this prognostic study, a multicentre, retrospective single-level vertebral augmentation cohort of 377 patients from six Japanese hospitals was used to derive an AVF prediction model. Backward stepwise selection (p < 0.05) was used to select preoperative clinical and imaging predictors for acute AVF after vertebral augmentation for up to one month, from 14 predictors. We assigned a score to each selected variable based on the regression coefficient and developed the AVA scoring system. We evaluated sensitivity and specificity for each cut-off, area under the curve (AUC), and calibration as diagnostic performance. Internal validation was conducted using bootstrapping to correct the optimism. Results. Of the 377 patients used for model derivation, 58 (15%) had an acute AVF postoperatively. The following preoperative measures on multivariable analysis were summarized in the five-point AVA score: intravertebral instability (≥ 5 mm), focal kyphosis (≥ 10°), duration of symptoms (≥ 30 days), intravertebral cleft, and previous history of vertebral fracture. Internal validation showed a mean optimism of 0.019 with a corrected AUC of 0.77. A cut-off of ≤ one point was chosen to classify a low risk of AVF, for which only four of 137 patients (3%) had AVF with 92.5% sensitivity and 45.6% specificity. A cut-off of ≥ four points was chosen to classify a high risk of AVF, for which 22 of 38 (58%) had AVF with 41.5% sensitivity and 94.5% specificity. Conclusion. In this study, the AVA score was found to be a simple preoperative method for the identification of patients at low and high risk of postoperative acute AVF. This model could be applied to individual patients and could aid in the decision-making before vertebral augmentation. Cite this article: Bone Joint J 2022;104-B(1):97–102

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines.

Cite this article: Bone Joint J 2021;103-B(12):1754–1758.

Aims

The aim of this study was to evaluate the diagnostic value of preoperative serum CRP, white blood cell count (WBC), percentage of neutrophils (%N), and neutrophil to lymphocyte ratio (NLR) when using the fracture-related infection (FRI) consensus definition.

Aims

To investigate whether pre-operative functional mobility is a determinant of delayed inpatient recovery of activities (IRoA) after total knee arthroplasty (TKA) in three periods that coincided with changes in the clinical pathway.

Previously, we showed that case-specific non-linear finite element (FE) models are better at predicting the load to failure of metastatic femora than experienced clinicians. In this study we improved our FE modelling and increased the number of femora and characteristics of the lesions. We retested the robustness of the FE predictions and assessed why clinicians have difficulty in estimating the load to failure of metastatic femora. A total of 20 femora with and without artificial metastases were mechanically loaded until failure. These experiments were simulated using case-specific FE models. Six clinicians ranked the femora on load to failure and reported their ranking strategies. The experimental load to failure for intact and metastatic femora was well predicted by the FE models (R² = 0.90 and R² = 0.93, respectively). Ranking metastatic femora on load to failure was well performed by the FE models (τ = 0.87), but not by the clinicians (0.11 < τ < 0.42). Both the FE models and the clinicians allowed for the characteristics of the lesions, but only the FE models incorporated the initial bone strength, which is essential for accurately predicting the risk of fracture. Accurate prediction of the risk of fracture should be made possible for clinicians by further developing FE models.

A prospective study was performed to develop a clinical prediction rule that incorporated demographic and clinical factors predictive of a fracture of the scaphoid. Of 260 consecutive patients with a clinically suspected or radiologically confirmed scaphoid fracture, 223 returned for evaluation two weeks after injury and formed the basis of our analysis. Patients were evaluated within 72 hours of injury and at approximately two and six weeks after injury using clinical assessment and standard radiographs. Demographic data and the results of seven specific tests in the clinical examination were recorded. There were 116 (52%) men and their mean age was 33 years (13 to 95; . sd. 17.9). In 62 patients (28%) a scaphoid fracture was confirmed. A logistic regression model identified male gender (p = 0.002), sports injury (p = 0.004), anatomical snuff box pain on ulnar deviation of the wrist within 72 hours of injury (p < 0.001), and scaphoid tubercle tenderness at two weeks (p < 0.001) as independent predictors of fracture. All patients with no pain at the anatomical snuff box on ulnar deviation of the wrist within 72 hours of injury did not have a fracture (n = 72, 32%). With four independently significant factors positive, the risk of fracture was 91%. Our study has demonstrated that clinical prediction rules have a considerable influence on the probability of a suspected scaphoid fracture. This will help improve the use of supplementary investigations where the diagnosis remains in doubt

Clinical prediction algorithms are used to differentiate transient synovitis from septic arthritis. These algorithms typically include the erythrocyte sedimentation rate (ESR), although in clinical practice measurement of the C-reactive protein (CRP) has largely replaced the ESR. We evaluated the use of CRP in a predictive algorithm. The records of 311 children with an effusion of the hip, which was confirmed on ultrasound, were reviewed (mean age 5.3 years (0.2 to 15.1)). Of these, 269 resolved without intervention and without long-term sequelae and were considered to have had transient synovitis. The remaining 42 underwent arthrotomy because of suspicion of septic arthritis. Infection was confirmed in 29 (18 had micro-organisms isolated and 11 had a high synovial fluid white cell count). In the remaining 13 no evidence of infection was found and they were also considered to have had transient synovitis. In total 29 hips were categorised as septic arthritis and 282 as transient synovitis. The temperature, weight-bearing status, peripheral white blood cell count and CRP was reviewed in each patient. A CRP > 20 mg/l was the strongest independent risk factor for septic arthritis (odds ratio 81.9, p < 0.001). A multivariable prediction model revealed that only two determinants (weight-bearing status and CRP > 20 mg/l) were independent in differentiating septic arthritis from transient synovitis. Individuals with neither predictor had a < 1% probability of septic arthritis, but those with both had a 74% probability of septic arthritis. A two-variable algorithm can therefore quantify the risk of septic arthritis, and is an excellent negative predictor.

A suspected fracture of the scaphoid remains difficult to manage despite advances in knowledge and imaging methods. Immobilisation and restriction of activities in a young and active patient must be balanced against the risks of nonunion associated with an undiagnosed and undertreated fracture of the scaphoid. The assessment of diagnostic tests for a suspected fracture of the scaphoid must take into account two important factors. First, the prevalence of true fractures among suspected fractures is low, which greatly reduces the probability that a positive test will correspond with a true fracture, as false positives are nearly as common as true positives. This situation is accounted for by Bayesian statistics. Secondly, there is no agreed reference standard for a true fracture, which necessitates the need for an alternative method of calculating diagnostic performance characteristics, based upon a statistical method which identifies clinical factors tending to associate (latent classes) in patients with a high probability of fracture. The most successful diagnostic test to date is MRI, but in low-prevalence situations the positive predictive value of MRI is only 88%, and new data have documented the potential for false positive scans. The best strategy for improving the diagnosis of true fractures among suspected fractures of the scaphoid may well be to develop a clinical prediction rule incorporating a set of demographic and clinical factors which together increase the pre-test probability of a fracture of the scaphoid, in addition to developing increasingly sophisticated radiological tests

The crucial differentiation between septic arthritis and transient synovitis of the hip in children can be difficult. In 1999, Kocher et al introduced four clinical predictors which were highly predictive (99.6%) of septic arthritis. These included fever (temperature ≥ 38.5°C), inability to bear weight, white blood-cell count > 12.0 × 10⁹ cells/L and ESR ≥ 40 mm/hr; CRP ≥ 20 mg/L was later added as a fifth predictor. We retrospectively evaluated these predictors to differentiate septic arthritis from transient synovitis of the hip in children over a four-year period in a primary referral general hospital. When all five were positive, the predicted probability of septic arthritis in this study was only 59.9%, with fever being the best predictor. When applied to low-prevalence diseases, even highly specific tests yield a high number of false positives and the predictive value is thereby diminished.

Clinical predictors should be applied with caution when assessing a child with an irritable hip, and a high index of suspicion, and close observation of patients at risk should be maintained.