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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.

Background: fracture-related infection (FRI) remains a serious complication in orthopedic trauma. To standardize daily clinical practice, a consensus definition was established, based on confirmatory and suggestive criteria. In the presence of clinical confirmatory criteria, the diagnosis of an FRI is evident, and treatment can be started. However, if these criteria are absent, the decision to surgically collect deep tissue cultures can only be based on suggestive criteria. The primary study aim was to characterize the subpopulation of FRI patients presenting without clinical confirmatory criteria (fistula, sinus, wound breakdown, purulent wound drainage or presence of pus during surgery). The secondary aims were to describe the prevalence of the diagnostic criteria for FRI and present the microbiological characteristics, both for the entire FRI population. Methods: a multicenter, retrospective cohort study was performed, reporting the demographic, clinical and microbiological characteristics of 609 patients (with 613 fractures) who were treated for FRI based on the recommendations of a multidisciplinary team. Patients were divided in three groups, including the total population and two subgroups of patients presenting with or without clinical confirmatory criteria. Results: clinical and microbiological confirmatory criteria were present in 77g and 87g of the included fractures, respectively. Of patients, 23g presented without clinical confirmatory criteria, and they mostly displayed one (31g) or two (23g) suggestive clinical criteria (redness, swelling, warmth, pain, fever, new-onset joint effusion, persisting/increasing/new-onset wound drainage). The prevalence of any suggestive clinical, radiological or laboratory criteria in this subgroup was 85g, 55g and 97g, respectively. Most infections were monomicrobial (64g) and caused by Staphylococcus aureus. Conclusion: clinical confirmatory criteria were absent in 23g of the FRIs. In these cases, the decision to ope

Purpose: Convolutional neural networks (CNNs) are increasingly being developed for automated fracture detection in orthopaedic trauma surgery. Studies to date, however, are limited to providing classification based on the entire image—and only produce heatmaps for approximate fracture localization instead of delineating exact fracture morphology. Therefore, we aimed to answer (1) what is the performance of a CNN that detects, classifies, localizes, and segments an ankle fracture, and (2) would this be externally valid? Methods: The training set included 326 isolated fibula fractures and 423 non-fracture radiographs. The Detectron2 implementation of the Mask R-CNN was trained with labelled and annotated radiographs. The internal validation (or ‘test set’) and external validation sets consisted of 300 and 334 radiographs, respectively. Consensus agreement between three experienced fellowship-trained trauma surgeons was defined as the ground truth label. Diagnostic accuracy and area under the receiver operator characteristic curve (AUC) were used to assess classification performance. The Intersection over Union (IoU) was used to quantify accuracy of the segmentation predictions by the CNN, where a value of 0.5 is generally considered an adequate segmentation. Results: The final CNN was able to classify fibula fractures according to four classes (Danis-Weber A, B, C and No Fracture) with AUC values ranging from 0.93 to 0.99. Diagnostic accuracy was 89% on the test set with average sensitivity of 89% and specificity of 96%. External validity was 89–90% accurate on a set of radiographs from a different hospital. Accuracies/AUCs observed were 100/0.99 for the ‘No Fracture’ class, 92/0.99 for ‘Weber B’, 88/0.93 for ‘Weber C’, and 76/0.97 for ‘Weber A’. For the fracture bounding box prediction by the CNN, a mean IoU of 0.65 (SD ± 0.16) was observed. The fracture segmentation predictions by the CNN resulted in a mean IoU of 0.47 (SD ± 0.17). Conclusions: This study present

BackgroundFemoral neck fractures are common and are frequently treated with internal fixation. A major disadvantage of internal fixation is the substantially high number of conversions to arthroplasty because of nonunion, malunion, avascular necrosis, or implant failure. A clinical prediction model identifying patients at high risk of conversion to arthroplasty may help clinicians in selecting patients who could have benefited from arthroplasty initially.Question/purposeWhat is the predictive performance of a machine-learning (ML) algorithm to predict conversion to arthroplasty within 24 months after internal fixation in patients with femoral neck fractures?MethodsWe included 875 patients from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial. The FAITH trial consisted of patients with low-energy femoral neck fractures who were randomly assigned to receive a sliding hip screw or cancellous screws for internal fixation. Of these patients, 18% (155 of 875) underwent conversion to THA or hemiarthroplasty within the first 24 months. All patients were randomly divided into a training set (80%) and test set (20%). First, we identified 27 potential patient and fracture characteristics that may have been associated with our primary outcome, based on biomechanical rationale and previous studies. Then, random forest algorithms (an ML learning, decision tree-based algorithm that selects variables) identified 10 predictors of conversion: BMI, cardiac disease, Garden classification, use of cardiac medication, use of pulmonary medication, age, lung disease, osteoarthritis, sex, and the level of the fracture line. Based on these variables, five different ML algorithms were trained to identify patterns related to conversion. The predictive performance of these trained ML algorithms was assessed on the training and test sets based on the following performance measures: (1) discrimination (the model's ability to distinguish patients who had c

Background: The recently developed fracture-related infection (FRI) consensus definition, which is based on specific diagnostic criteria, has not been fully validated in clinical studies. We aimed to determine the diagnostic performance of the criteria of the FRI consensus definition and evaluated the effect of the combination of certain suggestive and confirmatory criteria on the diagnostic performance. Methods: A multicenter, multi-national, retrospective cohort study was performed. Patients were subdivided into an FRI or a control group, according to the treatment they received and the recommendations from a multidisciplinary team (‘intention to treat’). Exclusion criteria were patients with an FRI diagnosed outside the study period, patients younger than 18 years of age, patients with pathological fractures or patients with fractures of the skull, cervical, thoracic and lumbar spine. Minimum follow up for all patients was 18 months. Results: Overall, 637 patients underwent revision surgery for suspicion of FRI. Of these, 480 patients were diagnosed with FRI, treated accordingly, and included in the FRI group. The other 157 patients were included in the control group. The presence of at least one confirmatory sign was associated with a sensitivity of 97.5%, a specificity of 100% and a high discriminatory value (AUROC 0.99, p < 0.001). The presence of a clinical confirmatory criterion or, if not present, at least one positive culture was associated with the highest diagnostic performance (sensitivity: 98.6%, specificity: 100%, AUROC: 0.99 (p < 0.001)). In the subgroup of patients without clinical confirmatory signs at presentation, specificities of at least 95% were found for the clinical suggestive signs of fever, wound drainage, local warmth and redness. Conclusions: The presence of at least one confirmatory criterion identifies the vast majority of patients with an FRI and was associated with an excellent diagnostic discriminatory value. Therefore, our

Purpose: To evaluate the effect of three-dimensional virtual pre-operative planning (3DVP) on the incidence of dorsal screw penetration after volar plating of distal radius fractures. Methods: A cross-sectional diagnostic imaging study was performed. Twenty out of 50 patients were randomly selected from our index prospective cohort (IPC): a prior study evaluating dorsal tangential views (DTVs) in reducing dorsal screw penetration in internal fixation of intra-articular distal radius fractures using post-operative CT scans to quantify screw protrusion. Pre-operative CTs from this cohort were now used for 3DVP by three experienced orthopaedic trauma surgeons (supplementary video). 3DVP was compared with the corresponding post-operative CT for assessing screw lengths and incidence of dorsal penetration. The Wilcoxon Signed Ranks test was used to compare screw lengths and the Fishers’ exact for incidence of penetration. Results: Three surgeons performed 3DVP for 20 distal radius fractures and virtually applied 60 volar plates and 273 screws. Median screw length was shorter in the 3DVP when compared to IPC: 18 mm (range, 12–22) versus 20 mm (range, 14–26) (p < 0.001). The number of penetrating screws was 5% (13/273 screws) in the 3DVP group compared to 11% (10/91 screws) in the IPC (p = 0.047). Corresponding to a reduction in incidence of at least one dorsally penetrating screw in 40% of patients in the IPC group, to 18% in the 3DVP group (p = 0.069). Conclusion: Three-Dimensional Virtual Pre-Operative Planning (3DVP) may reduce the incidence of dorsally penetrating screws in patients treated with volar plating for intra-articular distal radius fractures. Level of evidence: II, diagnostic imaging study.