Fracture-related infections (FRIs) are a major concern for patients and healthcare systems, yet their impact on mental health has been largely overlooked. This study aimed to assess the longitudinal impact of FRI on patients’ quality of life. A prospective study was conducted at a level 1 trauma centre between January 2020 and December 2022. In total, 56 patients participated, with quality of life assessed at five timepoints: one week preoperatively, and one, three, six, and 12 months postoperatively. Statistical analysis was performed using repeated measures analysis of variance (ANOVA) with adjusted post-hoc analysis.Aims
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To develop a multidisciplinary health research agenda (HRA) utilizing expertise from various disciplines to identify and prioritize evidence uncertainties in orthopaedics, thereby reducing research waste. We employed a novel, structured framework to develop a HRA. We started by systematically collecting all evidence uncertainties from stakeholders with an interest in orthopaedic care, categorizing them into 13 sub-themes defined by the Dutch Orthopaedic Association (NOV). Subsequently, a modified two-phased Delphi study (two rounds per phase), adhering to the Conducting and REporting DElphi Studies (CREDES) guideline, was conducted. In Phase 1, board members assessed the collected evidence uncertainties on a three-point Likert scale to confirm knowledge gaps. In Phase 2, diverse stakeholders, including orthopaedic surgeons, rated the confirmed knowledge gaps on a seven-point Likert scale. Panel members rated one self-selected sub-theme and two randomly assigned sub-themes. The results from Phase 2 were ranked based on the overall average score for each uncertainty. Finally, a focus group discussion with patient associations’ representatives identified their top-ranked uncertainty from a predefined consensus process, leading to the final HRA. An advisory board, the Federation of Medical Specialists, and the NOV research coordinator oversaw the process.Aims
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Valgus subsidence of uncemented tibial components following medial unicompartmental knee arthroplasty (UKA) poses a challenge in the early postoperative phase, necessitating a comprehensive understanding of its prevalence, risk factors, and impact on patient outcomes. This prospective multicentre study analyzed 97 knees from 90 patients undergoing UKA across four participating hospitals. A standardized surgical technique was employed uniformly by all participating surgeons. Postoperative evaluations were conducted preoperatively, and one day, four weeks, three months, and one year postoperative, encompassing weightbearing radiographs, bone mineral density assessments, and clinical outcome reports using the Forgotten Joint Score and Oxford Knee Score. Statistical analyses, including non-parametric correlation analysis using the Kendall correlation coefficient and Mann-Whitney U test, were performed to explore associations between subsidence and various patient-related or radiological parameters.Aims
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Unicompartmental knee arthroplasty (UKA) is associated with an accelerated recovery, improved functional outcomes, and retention of anatomical knee kinematics when compared to manual total knee arthroplasty (mTKA). UKA is not universally employed by all surgeons as there is a higher revision risk when compared to mTKA. Robotic arm-assisted (ra) UKA enables the surgeon to position the prosthesis more accurately when compared to manual UKA, and is associated with improved functional outcomes and a lower early revision risk. Non-randomized data suggests that, when compared to mTKA, raUKA has a clinically meaningful greater functional benefit. This protocol describes a randomized controlled trial that aims to evaluate the clinical and cost-effectiveness of raUKA compared to mTKA for individuals with isolated medial compartment osteoarthritis (OA). The total versus robotic-assisted unicompartmental knee arthroplasty (TRAKER) trial is a patient- and assessor-blinded, pragmatic parallel two-arm randomized superiority trial of adults undergoing elective primary knee arthroplasty for primary medial compartment OA at a single NHS hospital (ClinicalTrials.gov NCT05290818). Participants will be randomly allocated on a 1:2 basis to either raUKA or mTKA, respectively. The primary analysis will compare the Oxford Knee Score (OKS) six months after surgery. Secondary outcomes measured at three, six, and 12 months include the OKS, Forgotten Joint Score, patient expectations, EuroQol five-dimension questionnaire (EQ-5D), and EQ-visual analogue scale (EQ-VAS), patient satisfaction, range of motion, postoperative complications, need for further surgery, resource use, and financial costs. Cost-effectiveness will be measured over a ten-year time span. A total of 159 patients will be randomized (n = 53 raUKA vs n = 106 mTKA) to obtain 80% power to detect a five-point difference in OKS between the groups six months after surgery.Aims
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Control of acute pain following knee arthroplasty (KA) with a perioperative peripheral nerve block (PNB) may improve functional outcomes and reduce the risk of chronic postoperative knee pain (CPKP). The aims of this study were to assess whether a PNB influences patient-reported outcomes and risk of CPKP at one year following KA. A retrospective study was conducted over a two-year period and included 3,338 patients who underwent KA, of whom 1,434 (43.0%) had a lower limb PNB. A total of 2,588 patients (77.6%) completed and returned their one-year follow-up questionnaire. The Oxford Knee Score (OKS) and pain component (OKS-PS), EuroQol five-dimension questionnaire (EQ-5D), and EQ-visual analogue scale (VAS) were collected preoperatively and at one year postoperatively. Patient satisfaction was also recorded at one year. The OKS-PS was used to define CPKP at one year.Aims
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In our previous research, we have found that melatonin (MEL) affects the osteoporotic process. By balancing bone remoulding, autophagy is involved in age-related bone loss. However, as a regulator of autophagy, whether MEL influences senile osteoporosis via regulating autophagy remains unclear. Cellular, radiological, and histopathological evaluations were performed on 36 16-month-old male C57BL6/L mice or aged bone marrow-derived mesenchymal stem cells. A MEL-gelatin methacrylamide system was constructed to aid osteoporotic fracture healing.Aims
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Aims. Machine learning (ML) holds significant promise in optimizing various aspects of total shoulder arthroplasty (TSA), potentially improving patient outcomes and enhancing surgical decision-making. The aim of this systematic review was to identify ML algorithms and evaluate their effectiveness, including those for predicting clinical outcomes and those used in image analysis. Methods. We searched the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases for studies applying ML algorithms in TSA. The analysis focused on dataset characteristics, relevant subspecialties, specific ML algorithms used, and their performance outcomes. Results. Following the final screening process, 25 articles satisfied the eligibility criteria for our review. Of these, 60% focused on tabular data while the remaining 40% analyzed image data. Among them, 16 studies were dedicated to developing new models and nine used transfer learning to leverage existing pretrained models. Additionally, three of these models underwent external validation to confirm their reliability and effectiveness. Conclusion. ML algorithms used in TSA demonstrated fair to good performance, as evidenced by the reported metrics. Integrating these models into daily
The February 2025 Sports Roundup360 looks at: Long-term outcomes of focal cartilage lesions of the knee; Comparison of early and delayed multiligament knee reconstruction; Platelet-rich plasma does not improve recovery after partial meniscectomy; Patient height and sex predict semitendinosus autograft diameter.
The aim of the study was to apply 3D measurements for fracture displacement in minimally to moderately displaced acetabular fractures treated nonoperatively, and to evaluate whether this measurement can be used to estimate the likelihood of conversion to total hip arthroplasty (THA) at follow-up. A multicentre, cross-sectional study was performed on 144 patients who were treated nonoperatively for an acetabular fracture in four level 1 trauma centres between January 2000 and December 2020. For each patient, fracture displacement was measured on CT-based 3D models. The 3D gap area represents fracture displacement (mm2) between all fracture fragments. A receiver operating characteristic curve was generated to determine a 3D gap area threshold representing the optimal sensitivity and specificity to predict conversion to THA. Native hip survival was reported using Kaplan-Meier curves. Predictors of conversion to THA were determined using Cox regression analysis.Aims
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The February 2025 Knee Roundup360 looks at: Once-weekly semaglutide in patients with obesity and knee osteoarthritis; How many patients should have a unicompartmental knee arthroplasty?; Staged revision of the infected knee arthroplasty and endoprosthesis; The metal allergy argument and knee arthroplasty; Is kinematic alignment all it’s cracked up to be?; Is bone-patella-bone the gold standard for revision?; Blood flow restriction and the dissatisfied knee arthroplasty.
Complex elbow fracture-dislocations often result in suboptimal outcomes and necessitate a thorough understanding of injury patterns to guide effective management and reduce adverse sequelae. The Wrightington Classification System (WCS) offers a comprehensive approach and considers both bony and soft-tissue disruption, providing clearer guidance for treatment. This is the first external study to assess the reliability of the WCS for elbow fracture-dislocations. A blinded study of patients with elbow fracture-dislocations at a single institution between December 2014 and December 2022 was conducted. Five assessors with a range of experience, including orthopaedic surgeons and radiologists, independently classified injuries using the WCS across three image methods: plain radiograph, 2D CT, and 2D and 3D CT reconstruction images, on two occasions with an eight-week interval. Interobserver and intraobserver reliability were evaluated using kappa statistics and the Landis and Koch criteria.Aims
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Aims. The Birmingham Orthopaedic Oncology Meeting (BOOM), held in January 2024, convened 309 delegates from 53 countries to discuss and refine 21 consensus statements on the optimal management of chondrosarcoma. Methods. With representation from Europe (43%; n = 133), North America (17%; n = 53), South America (16%; n = 49), Asia (13%; n = 40), Australasia (5%; n = 16), the Middle East (4%; n = 12), and Africa (2%; n = 6), the combined experience of treating bone sarcomas among attendees totalled approximately 30,000 cases annually, equivalent to 66 years of experience in the UK alone. The meeting’s process began with the formation of a local organizing committee, regional leads, and a scientific committee comprising representatives from 150 specialist units across 47 countries. Supported by major orthopaedic oncology organizations, the meeting used a modified Delphi process to develop consensus statements through online questionnaires, thematic groupings, narrative reviews, and anonymous pre-meeting polling. Results. Strong (> 80%) consensus was achieved on 19 out of 21 statements, reflecting agreement among delegates. Key areas of consensus included the role of radiology in diagnosis and surveillance, the management of locally recurrent disease, and the treatment of dedifferentiated chondrosarcoma. Notably, there was agreement that routine chemotherapy has no role in chondrosarcoma treatment, and radiological surveillance is safe for intraosseous chondrosarcomas. Despite the overall consensus, areas of controversy remain, particularly regarding the treatment of atypical cartilage tumours and surgical margins. These unresolved issues underscore the need for further research and collaboration within the orthopaedic oncology community. Conclusion. BOOM represents the largest global consensus meeting in orthopaedic oncology, providing valuable guidance for clinicians managing chondrosarcoma worldwide. The consensus statements offer a reference for
The aim of this study was to evaluate the suitability, against an accepted international standard, of a linked hip fracture registry and routinely collected administrative dataset in England to embed and deliver randomized controlled trials (RCTs). First, a bespoke cohort of individuals sustaining hip fractures between 2011 and 2016 was generated from the National Hip Fracture Database (NHFD) and linked to individual Hospital Episode Statistics (HES) records and mortality data. Second, in order to explore the availability and distribution of outcomes available in linked HES-Office of National Statistics (ONS) data, a more contemporary cohort with incident hip fracture was identified within HES between January 2014 and December 2018. Distributions of the outcomes within the HES-ONS dataset were reported using standard statistical summaries; descriptive characteristics of the NHFD and linked HES-ONS dataset were reported in line with the Clinical Trials Transformation Initiative recommendations for registry-enabled trials.Aims
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The aims of this study, using a porcine model of multiple trauma, were to investigate the expression of microRNAs at the fracture site, in the fracture haematoma (fxH) and in the fractured bone, compared with a remote unfractured long bone, to characterize the patterns of expression of circulating microRNAs in plasma, and identify and validate messenger RNA (mRNA) targets of the microRNAs. Two multiple trauma treatment strategies were compared: early total care (ETC) and damage control orthopaedics (DCO). For this study, fxH, fractured bone, unfractured control bone, plasma, lung, and liver samples were harvested. MicroRNAs were analyzed using quantitative real-time polymerase chain reaction arrays, and the identified mRNA targets were validated in vivo in the bone, fxH, lung, and liver tissue.Aims
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The February 2025 Oncology Roundup360 looks at:The role of bone grafting versus bone cement in the treatment of giant cell tumour of bone: a systematic review and meta-analysis on the risk of recurrence in 1,454 patients; Tumour necrosis drives prognosis in osteosarcoma; Correlation between post-chemotherapy MRI and histopathology of malignant bone tumours treated with extra-articular resection; Real-world referral pattern of unplanned excision in patients with soft-tissue sarcoma; Assessment of artificial intelligence chatbot responses to common patient questions on bone sarcoma; Chondrosarcoma of the pelvis and limbs at ten years; Chest wall resection and reconstruction for primary chest wall sarcomas: analysis of survival, predictors of outcome, and long-term functional status; Ewing’s sarcoma in the paediatric population: predictors of survival within the USA; Pulmonary metastasectomy for sarcoma: insights from a referral centre cohort.
The February 2025 Shoulder & Elbow Roundup360 looks at: Reverse shoulder arthroplasty is superior to plate fixation for displaced proximal humeral fractures in the elderly; Long-term outcomes of reverse total shoulder arthroplasty for complex proximal humerus fractures; The RAND/UCLA algorithm does streamline the clinical decision-making process; Smoking negatively impacts long-term outcomes and survival after anatomical total shoulder arthroplasty; Evaluating subscapularis tears: special tests lack sensitivity to tear severity and pain; Rotator cuff tear progression: insights into rates, risk factors, and the need for standardized reporting; Outcomes and complications of revision reverse shoulder arthroplasty: a systematic review; Prevalence and risk factors of glenohumeral chondral damage in shoulder instability: implications for early surgical stabilization.
The aim of this study was to develop and evaluate a deep learning-based model for classification of hip fractures to enhance diagnostic accuracy. A retrospective study used 5,168 hip anteroposterior radiographs, with 4,493 radiographs from two institutes (internal dataset) for training and 675 radiographs from another institute for validation. A convolutional neural network (CNN)-based classification model was trained on four types of hip fractures (Displaced, Valgus-impacted, Stable, and Unstable), using DAMO-YOLO for data processing and augmentation. The model’s accuracy, sensitivity, specificity, Intersection over Union (IoU), and Dice coefficient were evaluated. Orthopaedic surgeons’ diagnoses served as the reference standard, with comparisons made before and after artificial intelligence assistance.Aims
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Radiostereometric analysis (RSA) is considered the gold standard for in vivo migration analysis, but CT-based alternatives show comparable results in the shoulder and hip. We have previously validated a CT-based migration analysis method (CTMA) in a knee phantom compared to RSA. In this study, we validated the method in patients undergoing total knee arthroplasty (TKA). Our primary outcome measure was the difference in maximum total point motion (MTPM) between the differing methods. A total of 31 patients were prospectively studied having undergone an uncemented medial pivot knee TKA. Migrations were measured up to 12 months with marker-based and model-based RSA, and CT-RSA.Aims
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Aims. While cementless fixation offers potential advantages over cemented fixation, such as a shorter operating time, concerns linger over its higher cost and increased risk of periprosthetic fractures. If the risk of fracture can be forecasted, it would aid the shared decision-making process related to cementless stems. Our study aimed to develop and validate predictive models of periprosthetic femoral fracture (PPFF) necessitating revision and reoperation after elective total hip arthroplasty (THA). Methods. We included 154,519 primary elective THAs from the Swedish Arthroplasty Register (SAR), encompassing 21 patient-, surgical-, and implant-specific features, for model derivation and validation in predicting 30-day, 60-day, 90-day, and one-year revision and reoperation due to PPFF. Model performance was tested using the area under the curve (AUC), and feature importance was identified in the best-performing algorithm. Results. The Lasso regression excelled in predicting 30-day revisions (area under the receiver operating characteristic curve (AUC) = 0.85), while the Gradient Boosting Machine (GBM) model outperformed other models by a slight margin for all remaining endpoints (AUC range: 0.79 to 0.86). Predictive factors for revision and reoperation were identified, with patient features such as increasing age, higher American Society of Anesthesiologists grade (> III), and World Health Organization obesity classes II to III associated with elevated risks. A preoperative diagnosis of idiopathic necrosis increased revision risk. Concerning implant design, factors such as cementless femoral fixation, reverse-hybrid fixation, hip resurfacing, and small (< 35 mm) or large (> 52 mm) femoral heads increased both revision and reoperation risks. Conclusion. This is the first study to develop machine-learning models to forecast the risk of PPFF necessitating secondary surgery. Future studies are required to externally validate our algorithm and assess its applicability in
