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AimsTo develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials.MethodsThis study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration).ResultsThe developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set.ConclusionUsing high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making.Cite this article: Bone Jt Open 2023;4(3):168–181.

Background: Acromioclavicular (AC) dislocations with a concomitant fracture of the coracoid process (CP) are rare and there is ambiguity on treatment options. This systematic review was performed to address the clinically relevant question: what are the shoulder functions, union rates, and expected time until return to daily life in patients with a dislocation of the AC joint with a concomitant CP fracture after (1) nonsurgical treatment, (2) sole fixation of the AC joint, and (3) fixation of both the AC joint and the coracoid process? Methods: Studies were identified by conducting an online. Thirty records met the inclusion criteria and were suitable for data extraction. Results: A total of 37 shoulders from 37 patients were included. Surgical treatment was provided to 22 out of 37 patients, and 15 patients had nonsurgical treatment. Out of the surgically treated patients, 12 patients were treated with a fixation of both the AC joint and the CP, 9 patients with a sole fixation of the AC joint, and 1 patient with a sole fixation of the CP. Conclusion: Existing literature does not indicate that one treatment option is superior, and more data are needed to guide evidence-based decisions on this rare injury.

IntroductionThe effectiveness of rotator cuff tear repair surgery is influenced by multiple patient-related, pathology-centred and technical factors, which is thought to contribute to the reported retear rates between 17% and 94%. Adequate patient selection is thought to be essential in reaching satisfactory results. However, no clear consensus has been reached on which factors are most predictive of successful surgery. A clinical decision tool that encompassed all aspects is still to be made. Artificial intelligence (AI) and machine learning algorithms use complex self-learning models that can be used to make patient-specific decision-making tools. The aim of this study is to develop and train an algorithm that can be used as an online available clinical prediction tool, to predict the risk of retear in patients undergoing rotator cuff repair.Methods and analysisThis is a retrospective, multicentre, cohort study using pooled individual patient data from multiple studies of patients who have undergone rotator cuff repair and were evaluated by advanced imaging for healing at a minimum of 6 months after surgery. This study consists of two parts. Part one: collecting all potential factors that might influence retear risks from retrospective multicentre data, aiming to include more than 1000 patients worldwide. Part two: combining all influencing factors into a model that can clinically be used as a prediction tool using machine learning.Ethics and disseminationFor safe multicentre data exchange and analysis, our Machine Learning Consortium adheres to the WHO regulation ‘Policy on Use and Sharing of Data Collected by WHO in Member States Outside the Context of Public Health Emergencies’. The study results will be disseminated through publication in a peer-reviewed journal. Institutional Review Board approval does not apply to the current study protocol.

Background Incidental durotomy is an intraoperative complication in spine surgery that can lead to postoperative complications, increased length of stay, and higher healthcare costs. Natural language processing (NLP) is an artificial intelligence method that assists in understanding free-text notes that may be useful in the automated surveillance of adverse events in orthopaedic surgery. A previously developed NLP algorithm is highly accurate in the detection of incidental durotomy on internal validation and external validation in an independent cohort from the same country. External validation in a cohort with linguistic differences is required to assess the transportability of the developed algorithm, referred to geographical validation. Ideally, the performance of a prediction model, the NLP algorithm, is constant across geographic regions to ensure reproducibility and model validity.Question/purpose Can we geographically validate an NLP algorithm for the automated detection of incidental durotomy across three independent cohorts from two continents?Methods Patients 18 years or older undergoing a primary procedure of (thoraco)lumbar spine surgery were included. In Massachusetts, between January 2000 and June 2018, 1000 patients were included from two academic and three community medical centers. In Maryland, between July 2016 and November 2018, 1279 patients were included from one academic center, and in Australia, between January 2010 and December 2019, 944 patients were included from one academic center. The authors retrospectively studied the free-text operative notes of included patients for the primary outcome that was defined as intraoperative durotomy. Incidental durotomy occurred in 9% (93 of 1000), 8% (108 of 1279), and 6% (58 of 944) of the patients, respectively, in the Massachusetts, Maryland, and Australia cohorts. No missing reports were observed. Three datasets (Massachusetts, Australian, and combined Massachusetts and Australian) were divided into training and holdout test sets in an 80:20 ratio. An extreme gradient boosting (an efficient and flexible tree-based algorithm) NLP algorithm was individually trained on each training set, and the performance of the three NLP algorithms (respectively American, Australian, and combined) was assessed by discrimination via area under the receiver operating characteristic curves (AUC-ROC; this measures the model's ability to distinguish patients who obtained the outcomes from those who did not), calibration metrics (which plot the predicted and the observed probabilities) and Brier score (a composite of discrimination and calibration). In addition, the sensitivity (true positives, recall), specificity (true negatives), positive predictive value (also known as precision), negative predictive value, Fl-score (composite of precision and recall), positive likelihood ratio, and negative likelihood ratio were calculated.Results The combined NLP algorithm (the combined Massachusetts and Australian data) achieved excellent performance on independent testing data from Australia (AUC-ROC 0.97 [95% confidence interval 0.87 to 0.99]), Massachusetts (AUC-ROC 0.99 [95% CI 0.80 to 0.99]) and Maryland (AUC-ROC 0.95 [95% CI 0.93 to 0.97]). The NLP developed based on the Massachusetts cohort had excellent performance in the Maryland cohort (AUC-ROC 0.97 [95% CI 0.95 to 0.99]) but worse performance in the Australian cohort (AUC-ROC 0.74 [95% CI 0.70 to 0.77]).Conclusion We demonstrated the clinical utility and reproducibility of an NLP algorithm with combined datasets retaining excellent performance in individual countries relative to algorithms developed in the same country alone for detection of incidental durotomy. Further multi-institutional, international collaborations can facilitate the creation of universal NLP algorithms that improve the quality and safety of orthopaedic surgery globally. The combined NLP algorithm has been incorporated into a freely accessible web application that can be found at https://sorg-apps.shinyapps.io/nlp_incidental_durotomy/. Clinicians and researchers can use the tool to help incorporate the model in evaluating spine registries or quality and safety departments to automate detection of incidental durotomy and optimize prevention efforts.

Background Dorsal intercalated segment instability (DISI) in scaphoid nonunions is frequently attributed to fracture location relative to ligamentous attachments onto the scaphoid apex. We hypothesize scaphoid length loss to have a stronger correlation with DISI deformity than fracture location in patients with scaphoid nonunion. Questions/Purposes To investigate the correlation between (1) scaphoid length loss, (2) fracture location relative to the scaphoid apex, and (3) type of nonunion (Herbert classification) and DISI deformity in skeletally mature patients with scaphoid nonunion. Patients and Methods Twenty-seven cases of computed tomography (CT)–confirmed scaphoid nonunion (>6 months) were retrospectively included. Our primary outcome was the degree of DISI as measured by the radiolunate (RL) angle on CT. Scaphoid length loss was expressed as height-to-length (H/L) ratio. Fracture location was classified as proximal or distal to the scaphoid apex. Nonunions were classified as fibrous unions (type D1) or pseudoarthrosis (type D2). The correlation between RL angle, H/L ratio, fracture location, and nonunion type was evaluated. Results H/L ratio was the only factor associated with the degree of DISI as measured by RL angle. As scaphoid length loss increased (increasing H/L ratio), the RL angle increased. There was no significant difference in RL angle between fractures located proximal (30 degrees) or distal (28 degrees) to the scaphoid apex, or type D1 (31 degrees) versus type D2 (28 degrees) nonunions. There was no correlation between patient age, sex, or wrist side affected and RL angle. Conclusions Scaphoid length loss, rather than fracture location, is correlated to the degree of DISI deformity in patients with scaphoid nonunion. This highlights the importance of restoring scaphoid height when planning scaphoid nonunion reconstruction. Level of Evidence Level III, diagnostic study.

Background: Unstable fractures of the distal radius fractures (DRFs) may result in malunion, usually consisting of subsequent shortening and angular deviations. Ulnar shortening osteotomy (USO) is assumed to be a simpler procedure than radial correction osteotomy, resulting in fewer complications and comparable outcomes. The aim of this study was to identify the best surgical technique to perform USO to restore distal radioulnar joint congruency after DRF malunion. Methods: A systematic review of the literature is performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines in February 2022 to identify studies reporting outcomes and surgical technique for isolated USO. The primary outcome was complication rates. Secondary outcomes included functional, radiologic, and patient-rated outcomes. The methodological index for nonrandomized studies criteria were used to assess the quality of evidence. Results: Included were 12 cohorts (185 participants). Due to substantial heterogeneity, a meta-analysis could not be performed. The overall complication rate was 33% (95% confidence interval, 16% to 51%). The most reported complication was implant irritation (22%), often requiring removal of the implant (13%). Only 3% nonunions were mentioned. Functional and patient-rated outcomes improved in most patients after USO. Quality of evidence of the papers was low to very low. Common methodological flaws were related to retrospective research. Conclusion: No evident differences in complication rates and functional outcomes between the surgical techniques were observed. Based on this literature, most complications are related to implant irritation. Nonunion and infection rates were rare. Therefore, a surgical technique with a buried implant might be preferred. This hypothesis requires further investigation.

Purpose This study aims to investigate the symmetry of the left and right tibial plateau in young healthy individuals to determine whether left–right mirroring can be reliably used to optimize preoperative 3D virtual planning for patients with tibial plateau fractures. Methods One hundred healthy subjects, without previous knee surgery, severe knee trauma, or signs of osteoarthritis were included for a previous dynamic imaging study of the knee. The subjects underwent a CT scan, scanning the left and right knee with a slice thickness of 0.8 mm. 3D surface models of the femur, patella, and tibia were created using a convolutional neural network. The 3D models of the left and right tibias were exported to MATLAB © and the tibias were mirrored. The mirrored tibias were superimposed on the contralateral tibia using a coherent point drift surface matching algorithm. Correspondence points on both surfaces were established, the mean root squared distance was calculated and visualized in a boxplot and heatmaps. Results The overall mean difference between correspondence points on the left and right tibial plateau is 0.6276 ± 0.0343 mm. The greatest differences between correspondence points were seen around two specific surfaces on the outside of the tibial plateau; where the distal tibia was cut 15 mm below the tibial plateau and around the tibiofibular joint. Conclusions The differences between the left and right tibial plateau are small and therefore, we can be confident that the mirrored contralateral, unfractured, tibial plateau can be used as a template for 3D virtual preoperative planning for young patients without previous damage to the knee.

This study aimed to answer the following questions: do 3D-printed models lead to a more accurate recognition of the pattern of complex fractures of the elbow?; do 3D-printed models lead to a more reliable recognition of the pattern of these injuries?; and do junior surgeons benefit more from 3D-printed models than senior surgeons?A total of 15 orthopaedic trauma surgeons (seven juniors, eight seniors) evaluated 20 complex elbow fractures for their overall pattern (i.e. varus posterior medial rotational injury, terrible triad injury, radial head fracture with posterolateral dislocation, anterior (trans-)olecranon fracture-dislocation, posterior (trans-)olecranon fracture-dislocation) and their specific characteristics. First, fractures were assessed based on radiographs and 2D and 3D CT scans; and in a subsequent round, one month later, with additional 3D-printed models. Diagnostic accuracy (acc) and inter-surgeon reliability (κ) were determined for each assessment.Accuracy significantly improved with 3D-printed models for the whole group on pattern recognition (accThe use of 3D-printed models significantly improved the accuracy and reliability of recognizing the pattern of complex fractures of the elbow. However, the current long printing time and non-reusable materials could limit the usefulness of 3D-printed models in clinical practice. They could be suitable as a reusable tool for teaching residents.Cite this article

BACKGROUND: Femoral 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/PURPOSE: What 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?METHODS: We 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 conversion from those who did not; expressed with the area under the receiver operating characteristic [AUC]), (2) calibration (the plotted estimated versus the observed probabilities; expressed with the calibration curve intercept and slope), and (3) the overall model performance (Brier score: a composite of discrimination and calibration).RESULTS: None of the five ML algorithms performed well in predicting conversion to arthroplasty in the training set and the test set; AUCs of the algorithms in the training set ranged from 0.57 to 0.64, slopes of calibration plots ranged from 0.53 to 0.82, calibration intercepts ranged from --0.04 to 0.05, and Brier scores ranged from 0.14 to 0.15. The algorithms were further evaluated in the test set; AUCs ranged from 0.49 to 0.73, calibration slopes ranged from 0.17 to 1.29, calibration intercepts ranged from -1.28 to 0.34, and Brier scores ranged from 0.13 to 0.15.CONCLUSION: The predictive performance of the trained algorithms was poor, despite the use of one of the best datasets available worldwide on this subject. If the current dataset consisted of different variables or more patients, the performance may have been better. Also, various reasons for conversion to arthroplasty were pooled in this study, but the separate prediction of underlying pathology (such as, avascular necrosis or nonunion) may be more precise. Finally, it may be possible that it is inherently difficult to predict conversion to arthroplasty based on preoperative variables alone. Therefore, future studies should aim to include more variables and to differentiate between the various reasons for arthroplasty.LEVEL OF EVIDENCE: Level III, prognostic study.

This paper has been temporarily removed by the publisher, Wolters-Kluwer, as it may have been published in error. We regret any confusion this may have caused.

Background: The Boileau classification distinguishes three surgical neck fracture patterns: types A, B, and C. However, the reproducibility of this classification on plain radiographs is unclear. Therefore, we questioned what the interobserver agreement and accuracy of displaced surgical neck fracture patterns is categorized according to the modified Boileau classification. Does the reliability to recognize these fracture patterns differ between orthopedic residents and attending surgeons?Methods: This interobserver study consisted of a randomly retrieved series of 30 plain radiographs representing clinical practice in a level 1 and a level 2 trauma center. Radiographs were included from patients (≥18 years) who sustained an isolated displaced surgical neck fracture if they were taken ≤1 week after initial injury. A ground truth was established by consensus among three senior orthopedic surgeons. All images were assessed by 17 orthopedic residents and 17 attending orthopedic trauma surgeons.Results: Agreement for the modified Boileau classification was fair (κ=0.37; 95% confidence interval [CI], 0.36–0.38) with an accuracy of 62% (95% CI, 57%–66%). Comparison of interobserver variability between residents and attending surgeons revealed a significant but clinically irrelevant difference in favor of attending surgeons (0.34 vs. 0.39, respectively, Δ κ=0.05, 95% CI, 0.02–0.07).Conclusions: The modified Boileau classification yields a low interobserver agreement with an unsatisfactory accuracy in a panel of orthopedic residents and attending surgeons. This supports the hypothesis that surgical neck fractures are challenging to categorize and that this classification should not be used to determine prognosis if only plain radiographs are available.

IntroductionShoulder instability is a common injury, with a reported incidence of 23.9 per 100 000 person-years. There is still an ongoing debate on the most effective treatment strategy. Non-operative treatment has recurrence rates of up to 60%, whereas operative treatments such as the Bankart repair and bone block procedures show lower recurrence rates (16% and 2%, respectively) but higher complication rates (Methods and analysisThis is a multicentre retrospective cohort study. Patients with traumatic anterior shoulder dislocations that were treated with an arthroscopic Bankart repair without remplissage will be included. This study includes two parts. Part 1, collecting all potential factors influencing the recurrence rate following an arthroscopic Bankart repair in patients using multicentre data, aiming to include data from >1000 patients worldwide. Part 2, the multicentre data will be re-evaluated (and where applicable complemented) using machine learning algorithms to predict outcomes. Recurrence will be the primary outcome measure.Ethics and disseminationFor safe multicentre data exchange and analysis, our Machine Learning Consortium adhered to the WHO regulation ‘Policy on Use and Sharing of Data Collected by WHO in Member States Outside the Context of Public Health Emergencies’. The study results will be disseminated through publication in a peer-reviewed journal. No Institutional Review Board is required for this study.

Background Reliably recognizing the overall pattern and specific characteristics of proximal humerus fractures may aid in surgical decision-making. With conventional onscreen imaging modalities, there is considerable and undesired interobserver variability, even when observers receive training in the application of the classification systems used. It is unclear whether three-dimensional (3D) models, which now can be fabricated with desktop printers at relatively little cost, can decrease interobserver variability in fracture classification. Questions/purposes Do 3D-printed handheld models of proximal humerus fractures improve agreement among residents and attending surgeons regarding (1) specific fracture characteristics and (2) patterns according to the Neer and Hertel classification systems? Methods Plain radiographs, as well as two-dimensional (2D) and 3D CT images, were collected from 20 patients (aged 18 years or older) who sustained a three-part or four-part proximal humerus fracture treated at a Level I trauma center between 2015 and 2019. The included images were chosen to comprise images from patients whose fractures were considered as difficult-to-classify, displaced fractures. Consequently, the images were assessed for eight fracture characteristics and categorized according to the Neer and Hertel classifications by four orthopaedic residents and four attending orthopaedic surgeons during two separate sessions. In the first session, the assessment was performed with conventional onscreen imaging (radiographs and 2D and 3D CT images). In the second session, 3D-printed handheld models were used for assessment, while onscreen imaging was also available. Although proximal humerus classifications such as the Neer classification have, in the past, been shown to have low interobserver reliability, we theorized that by receiving direct tactile and visual feedback from 3D-printed handheld fracture models, clinicians would be able to recognize the complex 3D aspects of classification systems reliably. Interobserver agreement was determined with the multirater Fleiss kappa and scored according to the categorical rating by Landis and Koch. To determine whether there was a difference between the two sessions, we calculated the delta (difference in the) kappa value with 95% confidence intervals and a two-tailed p value. Post hoc power analysis revealed that with the current sample size, a delta kappa value of 0.40 could be detected with 80% power at alpha = 0.05. Results Using 3D-printed models in addition to conventional imaging did not improve interobserver agreement of the following fracture characteristics: more than 2 mm medial hinge displacement, more than 8 mm metaphyseal extension, surgical neck fracture, anatomic neck fracture, displacement of the humeral head, more than 10 mm lesser tuberosity displacement, and more than 10 mm greater tuberosity displacement. Agreement regarding the presence of a humeral head-splitting fracture was improved but only to a level that was insufficient for clinical or scientific use (fair to substantial, delta kappa = 0.33 [95% CI 0.02 to 0.64]). Assessing 3D-printed handheld models adjunct to onscreen conventional imaging did not improve the interobserver agreement for pattern recognition according to Neer (delta kappa = 0.02 [95% CI -0.11 to 0.07]) and Hertel (delta kappa = 0.01 [95% CI -0.11 to 0.08]). There were no differences between residents and attending surgeons in terms of whether 3D models helped them classify the fractures, but there were few differences to identify fracture characteristics. However, none of the identified differences improved to almost perfect agreement (kappa value above 0.80), so even those few differences are unlikely to be clinically useful. Conclusion Using 3D-printed handheld fracture models in addition to conventional onscreen imaging of three-part and four-part proximal humerus fractures does not improve agreement among residents and attending surgeons on specific fracture characteristics and patterns. Therefore, we do not recommend that clinicians expend the time and costs needed to create these models if the goal is to classify or describe patients' fracture characteristics or pattern, since doing so is unlikely to improve clinicians' abilities to select treatment or estimate prognosis. Level of evidence Level III, diagnostic study.

Purpose The decision to continue immobilization of a nondisplaced scaphoid waist fracture is often based on radiographic appearance (despite evidence that radiographs are unreliable and inaccurate for diagnosing scaphoid union 6–12 weeks after fracture) and fracture tenderness (even though it is influenced by cognitive biases on pain). This may result in unhelpful additional immobilization. We studied nondisplaced scaphoid waist fractures to determine the factors associated with (1) the surgeon’s decision to continue cast or splint immobilization at the first visit when cast removal was being considered; (2) greater pain on examination; and (3) the surgeon’s concern about radiographic consolidation. Methods We prospectively included 46 patients with a nondisplaced scaphoid waist fracture treated nonoperatively. At the first visit when cast removal was considered – after an average of 6 weeks of immobilization – patients rated pain during 4 examination maneuvers. The treating surgeon assessed union on radiographs and decided whether to continue or discontinue immobilization. Patients completed measures of the following: (1) the degree to which pain limits activities (Patient-Reported Outcome Measure Interactive System [PROMIS] Pain Interference Computer Adaptive Test [CAT], Pain Self-Efficacy Questionnaire-2); (2) symptoms of depression (PROMIS Depression CAT); and (3) upper extremity function (PROMIS Upper Extremity Function CAT). We used multivariable regression analysis to investigate the factors associated with each outcome. Results Perceived inadequate radiographic healing and greater symptoms of depression were independently associated with continued immobilization. Pain during the examination was not associated with continued immobilization. Patient age was associated with pain on examination. Shorter immobilization duration was the only factor associated with the surgeon’s perception of inadequate radiographic consolidation. Conclusions Inadequate radiographic healing and greater symptoms of depression are associated with a surgeon’s decision to continue cast or splint immobilization of a nondisplaced scaphoid waist fracture. Clinical relevance Overreliance on radiographs and inadequate accounting for psychological distress may hinder the adoption of shorter immobilization times for nondisplaced waist fractures.

Supplemental Digital Content is Available in the Text., Objectives: To assess the effectiveness of suprapatellar (SP)-nailing versus infrapatellar (IP)-nailing of tibia fractures in anterior knee pain, complications (retropatellar chondropathy, infection, and malalignment) and physical functioning and quality of life. A clinical question-driven and thorough systematic review of current literature is provided. Data source: PubMed and Embase databases were searched for studies published between 2010 and 2020 relating to SP and IP-nailing of tibia fractures. The study is performed in concordance with PRISMA-guidelines. Study selection: Studies eligible for inclusion were randomized controlled trials, prospective and retrospective observational studies reporting on outcomes of interest. Data extraction: Data extraction was performed independently by 2 assessors. Methodological quality and risk of bias was assessed according to the guidelines of the McMaster Critical Appraisal. Data synthesis: Continuous variables are presented as means with SD and dichotomous variables as frequency and percentages. The weighted mean, standardized weighted mean differences, and 95% confidence interval were calculated. A pooled analysis could not be performed because of differences in outcome measures, time-points, and heterogeneity. Results: Fourteen studies with 1447 patients were analyzed. The weighted incidence of anterior knee pain was 29% after SP-nailing and 39% after IP-nailing, without reported significance. There was a significant lower rate of malalignment after the SP-approach (4% vs. 26%) with small absolute differences in all planes. No substantial differences were observed in retropatellar chondropathy, infection, physical functioning, and quality of life. Conclusions: This systematic review does not reveal superiority of either technique in any of the respective outcomes of interest. Definitive choice should depend on the surgeon's experience and available resources. Level of Evidence: Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.

The three-dimensional (3D) microstructure of the cortical and trabecular bone of the proximal ulna has not yet been described by means of high-resolution 3D imaging. An improved characterization can provide a better understanding of their relative contribution to resist impact load. The aim of this study is to describe the proximal ulna bone microstructure using micro-computed tomography (micro-CT) and relate it to gross morphology and function. Five dry cadaveric human ulnae were scanned by micro-CT (17 μm/voxel, isotropic). Both qualitative and quantitative assessments were performed on sagittal image stacks. The cortical thickness of the trochlear notch and the trabecular bone microstructure were measured in the olecranon, bare area and coronoid. Groups of trabecular struts starting in the bare area, spanning towards the anterior and posterior side of the proximal ulna, were observed; within the coronoid, the trabeculae were orthogonal to the joint surface. Consistently among the ulnae, the coronoid showed the highest cortical thickness (1.66 ± 0.59 mm, p = 0.04) and the olecranon the lowest (0.33 ± 0.06 mm, p = 0.04). The bare area exhibited the highest bone volume fraction (BV/TV = 43.7 ± 22.4%), trabecular thickness (Tb.Th = 0.40 ± 0.09 mm) and lowest structure model index (SMI = – 0.28 ± 2.20, indicating plate-like structure), compared to the other regions (p = 0.04). Our microstructural results suggest that the bare area is the region where most of the loading of the proximal ulna is concentrated, whereas the coronoid, together with its anteromedial facet, is the most important bony stabilizer of the elbow joint. Studying the proximal ulna bone microstructure helps understanding its possible everyday mechanical loading conditions and potential fractures. N.A.

Background Lesser tuberosity fractures are relatively rare, with an incidence of 0.46 per 100,000 persons per year. This systematic review was performed to address patient-reported outcomes (PROMs), shoulder function, and complications after lesser tuberosity fractures in pediatric and adult patients, as well as patients with an associated posterior shoulder dislocation. Within these groups, identical outcomes were evaluated for nonoperative, surgical, acute and delayed treatment. Method A comprehensive search was carried out in multiple databases. Articles were included if patients sustained a lesser tuberosity fracture without a concomitant proximal humerus fracture. There were no restrictions on age, type of treatment, fragment displacement, time to presentation, or associated injuries. Results One thousand six hundred forty-four records were screened for eligibility of which 71 studies were included (n = 172). Surgical treatment was provided to 50 of 62 (81%) pediatric patients, 49 of 66 (74%) adults, and 34 of 44 (77%) patients with an associated posterior shoulder dislocation. In the pediatric group, the mean of PROMs was 94 (range 70-100) and among adults 89 (range 85-100). In the posterior shoulder dislocation group, 89% did not regain full range of motion and the complication rate was 17%. In pediatric patients, surgery was associated with fewer complications (P = .021) compared to nonoperative treatment. Conclusion Pediatric patients have excellent outcomes after lesser tuberosity fractures and respond well to surgical treatment. Adults have acceptable outcomes but patients with an associated posterior shoulder dislocation have impaired range of shoulder movement and are more likely to develop complications.

Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A common criticism of CNNs is their opaque learning and reasoning process, making it difficult to trust machine diagnosis and the subsequent adoption of such algorithms in clinical setting. This is especially true when the CNN is trained with limited amount of medical data, which is a common issue as curating sufficiently large amount of annotated medical imaging data is a long and costly process. While interest has been devoted to explaining CNN learnt knowledge by visualizing network attention, the utilization of the visualized attention to improve network learning has been rarely investigated. This paper explores the effectiveness of regularizing CNN network with human-provided attention guidance on where in the image the network should look for answering clues. On two orthopedics radiographic fracture classification datasets, through extensive experiments we demonstrate that explicit human-guided attention indeed can direct correct network attention and consequently significantly improve classification performance. The development code for the proposed attention guidance is publicly available on GitHub., 12 pages, Published in IEEE Journal of Biomedical and Health Informatics

Purpose The aim of this systematic review was to provide an overview of current applications of 3D technologies in surgical management of tibial plateau fractures and to assess whether 3D-assisted surgery results in improved clinical outcome as compared to surgery based on conventional imaging modalities. Methods A literature search was performed in Pubmed and Embase for articles reporting on the use of 3D techniques in operative management of tibial plateau fractures. This systematic review was performed in concordance with the PRISMA-guidelines. Methodological quality and risk of bias was assessed according to the guidelines of the McMaster Critical Appraisal. Differences in terms of operation time, blood loss, fluoroscopy frequency, intra-operative revision rates and patient-reported outcomes between 3D-assisted and conventional surgery were assessed. Data were pooled using the inverse variance weighting method in RevMan. Results Twenty articles evaluating 948 patients treated with 3D-assisted surgery and 126 patients with conventional surgery were included. Five different concepts of 3D-assisted surgery were identified: ‘3D virtual visualization’, ‘3D printed hand-held fracture models’, ‘Pre-contouring of osteosynthesis plates’, ‘3D printed surgical guides’, and ‘Intra-operative 3D imaging’. 3D-assisted surgery resulted in reduced operation time (104.7 vs. 126.4 min; P P P P = 0.23). Conclusions Five concepts of 3D-assisted surgical management of tibial plateau fractures emerged over the last decade. These include 3D virtual fracture visualization, 3D-printed hand-held fracture models for surgical planning, 3D-printed models for pre-contouring of osteosynthesis plates, 3D-printed surgical guides, and intra-operative 3D imaging. 3D-assisted surgery may have a positive effect on operation time, blood loss, and fluoroscopy frequency.

Aims This study evaluated variation in the surgical treatment of stable (A1) and unstable (A2) trochanteric hip fractures among an international group of orthopaedic surgeons, and determined the influence of patient, fracture, and surgeon characteristics on choice of implant (intramedullary nailing (IMN) versus sliding hip screw (SHS)). Methods A total of 128 orthopaedic surgeons in the Science of Variation Group evaluated radiographs of 30 patients with Type A1 and A2 trochanteric hip fractures and indicated their preferred treatment: IMN or SHS. The management of Type A3 (reverse obliquity) trochanteric fractures was not evaluated. Agreement between surgeons was calculated using multirater kappa. Multivariate logistic regression models were used to assess whether patient, fracture, and surgeon characteristics were independently associated with choice of implant. Results The overall agreement between surgeons on implant choice was fair (kappa = 0.27 (95% confidence interval (CI) 0.25 to 0.28)). Factors associated with preference for IMN included USA compared to Europe or the UK (Europe odds ratio (OR) 0.56 (95% CI 0.47 to 0.67); UK OR 0.16 (95% CI 0.12 to 0.22); p < 0.001); exposure to IMN only during training compared to surgeons that were exposed to both (only IMN during training OR 2.6 (95% CI 2.0 to 3.4); p < 0.001); and A2 compared to A1 fractures (Type A2 OR 10 (95% CI 8.4 to 12); p < 0.001). Conclusion In an international cohort of orthopaedic surgeons, there was a large variation in implant preference for patients with A1 and A2 trochanteric fractures. This is due to surgeon bias (country of practice and aspects of training). The observation that surgeons favoured the more expensive implant (IMN) in the absence of convincing evidence of its superiority suggests that surgeon de-biasing strategies may be a useful focus for optimizing patient outcomes and promoting value-based healthcare. Cite this article: Bone Joint J 2021;103-B(4):775–781.

Background and purposeHumeral shaft fractures are often associated with radial nerve palsy (RNP) (8–16%). The primary aim of this systematic review was to assess the incidence of primary and secondary RNP in closed humeral shaft fractures. The secondary aim was to compare the recovery rate of primary RNP and the incidence of secondary RNP between operative and non-operative treatment.MethodsA systematic literature search was performed in ‘Trip Database’, ‘Embase’ and ‘PubMed’ to identify original studies reporting on RNP in closed humeral shaft fractures. The Coleman Methodology Score was used to grade the quality of the studies. The incidence and recovery of RNP, fracture characteristics and treatment characteristics were extracted. Chi-square and Fisher exact tests were used to compare operative versus non-operative treatment.ResultsForty studies reporting on 1758 patients with closed humeral shaft fractures were included. The incidence of primary RNP was 10%. There was no difference in the recovery rate of primary RNP when comparing operative treatment with radial nerve exploration (98%) versus non-operative treatment (91%) (p = 0.29). The incidence of secondary RNP after operative and non-operative treatment was 4% and 0.4%, respectively (p InterpretationOne-in-ten patients with a closed humeral shaft fracture has an associated primary RNP, of which > 90% recovers without the need of (re-)intervention. No beneficial effect of early exploration on the recovery of primary RNP could be demonstrated when comparing patients managed non-operatively with those explored early. Patients managed operatively for closed humeral shaft fractures have a higher risk of developing secondary RNP.Level of evidenceLevel IV; Systematic Review.

Background Evidence suggests that there is substantial and unexplained surgeon-to-surgeon variation in recommendation of operative treatment for fractures of the distal radius. We studied (1) what factors are associated with recommendation for operative treatment of a fracture of the distal radius and (2) which factors are rated as the most influential on recommendation of operative treatment. Methods One-hundred thirty-one upper extremity and fracture surgeons evaluated 20 fictitious patient scenarios with randomly assigned factors (e.g., personal, clinical, and radiologic factors) for patients with a fracture of the distal radius. They addressed the following questions: (1) Do you recommend operative treatment for this patient (yes/no)? We determined the influence of each factor on this recommendation using random forest algorithms. Also, participants rated the influence of each factor—excluding age and sex— on a scale from 0 (not at all important) to 10 (extremely important). Results Random forest algorithms determined that age and angulation were having the most influence on recommendation for operative treatment of a fracture of the distal radius. Angulation on the lateral radiograph and presence or absence of lunate subluxation were rated as having the greatest influence and smoking status and stress levels the lowest influence on advice to patients. Conclusions The observation that—other than age—personal factors have limited influence on surgeon recommendations for surgery may reflect how surgeon cognitive biases, personal preferences, different perspectives, and incentives may contribute to variations in care. Future research can determine whether decision aids—those that use patient-specific probabilities based on predictive analytics in particular—might help match patient treatment choices to what matters most to them, in part by helping to neutralize the influence of common misconceptions as well as surgeon bias and incentives. Level of Evidence There is no level of evidence for the study.

Background and purpose — There is ongoing debate as to whether commercial funding influences reporting of medical studies. We asked: Is there a difference in reported tones between abstracts, introductions, and discussions of orthopedic journal studies that were commercially funded and those that were not commercially funded? Methods — We conducted a systematic PubMed search to identify commercially funded studies published in 20 orthopedic journals between January 1, 2000 and December 1, 2019. We identified commercial funding of studies by including in our search the names of 10 medical device companies with the largest revenue in 2019. Commercial funding was designated when either the study or 1 or more of the authors received funding from a medical device company directly related to the content of the study. We matched 138 commercially funded articles 1 to 1 with 138 non-commercially funded articles with the same study design, published in the same journal, within a time range of 5 years. The IBM Watson Tone Analyzer was used to determine emotional tones (anger, fear, joy, and sadness) and language style (analytical, confident, and tentative). Results — For abstract and introduction sections, we found no differences in reported tones between commercially funded and non-commercially funded studies. Fear tones (non-commercially funded studies 5.1%, commercially funded studies 0.7%, p = 0.04), and analytical tones (non-commercially funded studies 95%, commercially funded studies 88%, p = 0.03) were more common in discussions of studies that were not commercially funded. Interpretation — Commercially funded studies have comparable tones to non-commercially funded studies in the abstract and introduction. In contrast, the discussion of non-commercially funded studies demonstrated more fear and analytical tones, suggesting them to be more tentative, accepting of uncertainty, and dispassionate. As text analysis tools become more sophisticated and mainstream, it might help to discern commercial bias in scientific reports.

Background Treatment for distal diaphyseal or metaphyseal tibia fractures is challenging and the optimal surgical strategy remains a matter of debate. The purpose of this study was to compare plate fixation with nailing in terms of operation time, non-union, time-to-union, mal-union, infection, subsequent re-interventions and functional outcomes (quality of life scores, knee- and ankle scores). Methods A search was performed in PubMed/Embase/CINAHL/CENTRAL for all study designs comparing plate fixation with intramedullary nailing (IMN). Data were pooled using RevMan and presented as odds ratios (OR), risk difference (RD), weighted mean difference (WMD) or weighted standardized mean difference (WSMD) with a 95% confidence interval (95%CI). All analyzes were stratified for study design. Results A total of 15 studies with 1332 patients were analyzed, including ten RCTs (n = 873) and five observational studies (n = 459). IMN leads to a shorter time-to-union (WMD: 0.4 months, 95%CI 0.1 – 0.7), shorter time-to-full-weightbearing (WMD: 0.6 months, 95%CI 0.4 – 0.8) and shorter operation duration (WMD: 15.5 min, 95%CI 9.3 – 21.7). Plating leads to a lower risk for mal-union (RD: -10%, OR: 0.4, 95%CI 0.3 – 0.6), but higher risk for infection (RD: 8%, OR: 2.4, 95%CI 1.5 – 3.8). No differences were detected with regard to non-union (RD: 1%, OR: 0.7, 95%CI 0.3 – 1.7), subsequent re-interventions (RD: 4%, OR: 1.3, 95%CI 0.8 – 1.9) and functional outcomes (WSMD: -0.4, 95%CI -0.9 – 0.1). The effect estimates of RCTs and observational studies were equal for all outcomes except for time to union and mal-union. Conclusion Satisfactory results can be obtained with both plate fixation and nailing for distal extra-articular tibia fractures. However, nailing is associated with higher rates of mal-union and anterior knee pain while plate fixation results in an increased risk of infection. This study provides a guideline towards a personalized approach and facilitates shared decision-making in surgical treatment of distal extra-articular tibia fractures. The definitive treatment should be case-based and aligned to patient-specific needs in order to minimize the risk of complications.

Background: Medial patellofemoral complex (MPFC) reconstruction plays an important role in the surgical treatment of patellar instability. Anatomic reconstruction is critical in re-creating the native function of the ligament, which includes minimizing length changes that occur in early flexion. Anatomic risk factors for patellar instability such as trochlear dysplasia, patella alta, and increased tibial tuberosity to trochlear groove (TT-TG) distance have been shown to influence the function of the MPFC graft in cadaveric studies, but the native length change patterns of the MPFC fibers in knees with anatomic risk factors have not been described. Purpose: To describe the in vivo length changes of the MPFC fibers in knees with anatomic risk factors for patellar instability and identify the optimal attachment sites for MPFC reconstruction. Study Design: Controlled laboratory study. Methods: Dynamic computed tomography imaging was performed on the asymptomatic knee in patients with contralateral patellar instability. Three-dimensional digital knee models were created to assess knees between 0° and 50° of flexion in 10° increments. MPFC fiber lengths were calculated at each flexion angle between known anatomic attachment points on the extensor mechanism (quadriceps tendon, MPFC midpoint [M], and patella) and femur (1, 2, and 3, representing the proximal to distal femoral footprint). Changes in MPFC fiber length were compared for each condition and assessed for their relationships to morphologic risk factors (trochlear depth, Caton Deschamps Index [CDI], and TT-TG distance). Results: In 22 knees, native MPFC fibers were found to be longer at 0° than at 20° to 50° of flexion. Length changes observed between 0° and 50° increased with the number of risk factors present. In the central fibers of the MPFC (M-2), 1.7% ± 3.1% length change was noted in knees with no anatomic risk factors, which increased to 5.6% ± 4.6%, 17.0% ± 6.4%, and 26.7% ± 6.8% in the setting of 1, 2, and 3 risk factors, respectively. Nonanatomic patella-based attachments were more likely to demonstrate unfavorable length change patterns, in which length was greater at 50° than 0°. In patellar attachments, an independent relationship was found between increasing length changes and TT-TG distance, while in quadriceps tendon attachments, a trend toward a negative relationship between length changes and CDI was noted. All configurations demonstrated a strong relationship between percentage change in length and number of morphologic risk factors present, with the greatest influence found in patella-based attachments. Conclusion: The MPFC fibers demonstrated increased length changes in knees when a greater number of morphological risk factors for patellar instability were present, which worsened in the setting of nonanatomic configurations. This suggests that the function of the intact MPFC in patients with anatomic risk factors may not reflect previously described findings in anatomically normal knees. Further studies are needed to understand the pathoanatomy related to these changes, as well as the implications for graft placement and assessment of length changes during MPFC reconstruction techniques. Clinical Relevance: MPFC length change patterns vary based on the number of morphologic risk factors for patellar instability present and should be considered during reconstructive procedures.

Purpose: Effects of clockwise torque rotation onto proximal femoral fracture fixation have been subject of ongoing debate: fixated right-sided trochanteric fractures seem more rotationally stable than left-sided fractures in the biomechanical setting, but this theoretical advantage has not been demonstrated in the clinical setting to date. The purpose of this study was to identify a difference in early reoperation rate between patients undergoing surgery for left- versus right-sided proximal femur fractures using cephalomedullary nailing (CMN). Materials and methods: The American College of Surgeons National Surgical Quality Improvement Program was queried from 2016-2019 to identify patients aged 50 years and older undergoing CMN for a proximal femoral fracture. The primary outcome was any unplanned reoperation within 30 days following surgery. The difference was calculated using a Chi-square test, and observed power calculated using post-hoc power analysis. Results: In total, of 20,122 patients undergoing CMN for proximal femoral fracture management, 1.8% (n=371) had to undergo an unplanned reoperation within 30 days after surgery. Overall, 208 (2.0%) were left-sided and 163 (1.7%) right-sided fractures (p=0.052, risk ratio [RR] 1.22, 95% confidence interval [CI] 1.00–1.50), odds ratio [OR] 1.23 (95%CI 1.00–1.51), power 49.2% (α=0.05). Conclusion: This study shows a higher risk of reoperation for left-sided compared to right-sided proximal femur fractures after CMN in a large sample size. Although results may be underpowered and statistically insignificant, this finding might substantiate the hypothesis that clockwise rotation during implant insertion and (postoperative) weightbearing may lead to higher reoperation rates. Level of evidence: Therapeutic level II.

BackgroundThe femoral nerve block (FNB) may be used for analgesia in hip fracture surgery. The pericapsular nerve group (PENG) block is a novel regional technique and may provide better pain reduction while preserving motor function, but these blocks have not been directly compared.MethodsIn a single-center double-blinded randomized comparative trial, patients presenting for hip fracture surgery received analgesia with either FNB or PENG block. The primary outcome measure was pain scores (Numeric Rating Scale (NRS) 0 to 10). Secondary outcomes were postoperative quadriceps strength, opiate use, complications, length of hospital stay, and patient-reported outcomes.ResultsSixty patients were randomized and equally allocated between groups. Baseline demographics were similar. Postoperatively in recovery (day 0), the PENG group experienced less pain compared with the FNB group. (In the PENG group, 63% experienced no pain, 27% mild pain, and 10% moderate to severe pain. In comparison, 30% of the FNB group reported no pain, 27% mild pain, and 36% moderate to severe pain; p=0.04). This was assessed using an 11-point Likert NRS. Quadriceps strength was better preserved in the PENG group in the recovery unit (assessed using Oxford muscle strength grading, 60% intact in the PENG group vs none intact in the FNB group; pConclusionsPatients receiving a PENG block for intraoperative and postoperative analgesia during hip fracture surgery experience less postoperative pain in the recovery room with no difference detected by postoperative day 1. Quadriceps strength was better preserved with the PENG block. Despite the short-term analgesic benefit and improved quadriceps strength, there were no differences detected in the quality of recovery.

Introduction The reported rate of subsequent surgery after intramedullary nailing (IMN) of tibial shaft fractures (TSFs) is as high as 21%. However, most studies have not included the removal of symptomatic implant in these rates. The purpose of this study was to evaluate the subsequent surgery rate after IMN of TSFs, including the removal of symptomatic implants. Secondly, this study aimed to assess what factors are associated with subsequent surgery (1) to promote fracture and wound healing and (2) for the removal of symptomatic implants. Methods One-hundred and ninety-one patients treated with IMN for TSFs were retrospectively included. The rate of subsequent surgery was determined. Bi- and multivariable analysis was used to identify variables associated with subsequent surgery. Results Approximately half of patients (46%) underwent at least one subsequent surgical procedure. Forty-eight (25%) underwent a subsequent surgical procedure to promote fracture or wound healing. Age (P P P P P Conclusions Patients treated with IMN for TSFs should be consented that about one-in-two patients will undergo an additional surgical procedure. Half of these procedures are required to promote wound or fracture healing; the other half are for symptomatic implant removal. Level of evidence Therapeutic level-IV.

Background For fracture care, radiographs and two-dimensional (2-D) and three-dimensional (3-D) CT are primarily used for preoperative planning and postoperative evaluation. Intraarticular distal radius fractures are technically challenging to treat, and meticulous preoperative planning is paramount to improve the patient's outcome. Three-dimensionally printed handheld models might improve the surgeon's interpretation of specific fracture characteristics and patterns preoperatively and could therefore be clinically valuable; however, the additional value of 3-D printed handheld models for fractures of the distal radius, a high-volume and commonly complex fracture due to its intraarticular configuration, has yet to be determined. Questions/purposes (1) Does the reliability of assessing specific fracture characteristics that guide surgical decision-making for distal radius fractures improve with 3-D printed handheld models? (2) Does surgeon agreement on the overall fracture classification improve with 3-D printed handheld models? (3) Does the surgeon's confidence improve when assessing the overall fracture configuration with an additional 3-D model? Methods We consecutively included 20 intraarticular distal radius fractures treated at a Level 1 trauma center between May 2018 and November 2018. Ten surgeons evaluated the presence or absence of specific fracture characteristics (volar rim fracture, die punch, volar lunate facet, dorsal comminution, step-off > 2 mm, and gap > 2 mm), fracture classification according to the AO/Orthopaedic Trauma Association (OTA) classification scheme, and their confidence in assessing the overall fracture according to the classification scheme, rated on a scale from 0 to 10 (0 = not at all confident to 10 = very confident). Of 10 participants regularly treating distal radius fractures, seven were orthopaedic trauma surgeons and three upper limb surgeons with experience levels ranging from 1 to 25 years after completion of residency training. Fractures were assessed twice, with 1 month between each assessment. Initially, fractures were assessed using radiographs and 2-D and 3-D CT images (conventional assessment); the second time, the evaluation was based on radiographs and 2-D and 3-D CT images with an additional 3-D handheld model (3-D printed handheld model assessment). On both occasions, fracture characteristics were evaluated upon a surgeon's own interpretation, without specific instruction before assessment. We provided a sheet demonstrating the AO/OTA classification scheme before evaluation on each session. Multi-rater Fleiss's kappa was used to determine intersurgeon reliability for assessing fracture characteristics and classification. Confidence regarding assessment of the overall fracture classification was assessed using a paired t-test. Results We found that 3-D printed models of intraarticular distal radius fractures led to no change in kappa values for the reliability of all characteristics: volar rim (conventional kappa 0.19 [95% CI 0.06 to 0.32], kappa for 3-D handheld model 0.23 [95% CI 0.11 to 0.36], difference of kappas 0.04 [95% CI -0.14 to 0.22]; p = 0.66), die punch (conventional kappa 0.38 [95% CI 0.15 to 0.61], kappa for 3-D handheld model 0.50 [95% CI 0.23 to 0.78], difference of kappas 0.12 [95% CI -0.23 to 0.47]; p = 0.52), volar lunate facet (conventional kappa 0.31 [95% CI 0.14 to 0.49], kappa for 3-D handheld model 0.48 [95% CI 0.23 to 0.72], difference of kappas 0.17 [95% CI -0.12 to 0.46]; p = 0.26), dorsal comminution (conventional kappa 0.36 [95% CI 0.13 to 0.58], kappa for 3-D handheld model 0.31 [95% CI 0.11 to 0.51], difference of kappas -0.05 [95% CI -0.34 to 0.24]; p = 0.74), step-off > 2 mm (conventional kappa 0.55 [95% CI 0.29 to 0.82], kappa for 3-D handheld model 0.58 [95% CI 0.31 to 0.85], difference of kappas 0.03 [95% CI -0.34 to 0.40]; p = 0.87), gap > 2 mm (conventional kappa 0.59 [95% CI 0.39 to 0.79], kappa for 3-D handheld model 0.69 [95% CI 0.50 to 0.89], difference of kappas 0.10 [95% CI -0.17 to 0.37]; p = 0.48). Although there appeared to be categorical improvement in kappa values for some fracture characteristics, overlapping CIs indicated no change. Fracture classification did not improve (conventional diagnostics: kappa 0.27 [95% CI 0.14 to 0.39], conventional diagnostics with an additional 3-D handheld model: kappa 0.25 [95% CI 0.15 to 0.35], difference of kappas: -0.02 [95% CI -0.18 to 0.14]; p = 0.81). There was no improvement in self-assessed confidence in terms of assessment of overall fracture configuration when a 3-D model was added to the evaluation process (conventional diagnostics 7.8 [SD 0.79 {95% CI 7.2 to 8.3}], 3-D handheld model 8.5 [SD 0.71 {95% CI 8.0 to 9.0}], difference of score: 0.7 [95% CI -1.69 to 0.16], p = 0.09). Conclusions Intersurgeon reliability for evaluating the characteristics of and classifying intraarticular distal radius fractures did not improve with an additional 3-D model. Further studies should evaluate the added value of 3-D printed handheld models for teaching surgical residents and medical trainees to define the future role of 3-D printing in caring for fractures of the distal radius. Level of evidence Level II, diagnostic study.

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?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.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).This study presents a look into the 'black box' of CNNs and represents the first automated delineation (segmentation) of fracture lines on (ankle) radiographs. The AUC values presented in this paper indicate good discriminatory capability of the CNN and substantiate further study of CNNs in detecting and classifying ankle fractures.II, Diagnostic imaging study.

The use of computed tomography (CT) in fractures is time consuming, challenging and suffers from poor inter-surgeon reliability. Convolutional neural networks (CNNs), a subset of artificial intelligence (AI), may overcome shortcomings and reduce clinical burdens to detect and classify fractures. The aim of this review was to summarize literature on CNNs for the detection and classification of fractures on CT scans, focusing on its accuracy and to evaluate the beneficial role in daily practice.Literature search was performed according to the PRISMA statement, and Embase, Medline ALL, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and Google Scholar databases were searched. Studies were eligible when the use of AI for the detection of fractures on CT scans was described. Quality assessment was done with a modified version of the methodologic index for nonrandomized studies (MINORS), with a seven-item checklist. Performance of AI was defined as accuracy, F1-score and area under the curve (AUC).Of the 1140 identified studies, 17 were included. Accuracy ranged from 69 to 99%, the F1-score ranged from 0.35 to 0.94 and the AUC, ranging from 0.77 to 0.95. Based on ten studies, CNN showed a similar or improved diagnostic accuracy in addition to clinical evaluation only.CNNs are applicable for the detection and classification fractures on CT scans. This can improve automated and clinician-aided diagnostics. Further research should focus on the additional value of CNN used for CT scans in daily clinics.