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Falls in senior home residents are common. Individual preventive training can lower the fall risk. To detect the need for training, a systematic assessment of the individual fall risk is needed. The aim of this study was thus to assess whether a fall risk score based on free field insole measurements can distinguish between an at-risk group of senior home residents and a healthy young control group. A published fall risk score was used in senior home residents over the age of 75 and a young (< 40 years) control group to determine the individual fall risk. In addition, the fall events over 12 months were assessed. Statistical analysis including ROC analysis was performed to determine the ability of the score to detect participants at heightened fall risk. In total, 18 nursing home residents and 9 young control participants were included. Of the nursing home residents, 15 had at least one fall, with a total of 37 falls recorded over 12 months. In the control group, no falls were recorded. The fall risk score was significantly different between nursing home residents and the control group (9.2 + 3.2 vs. 5.7 ± 2.2). Furthermore, the score significantly differentiated fallers from non-fallers (10.3 ± 1.8 vs. 5.2 ± 2.5), with a cut-off > 7.5 (AUC: 0.95) and a sensitivity of 86.7% (specificity 83.3%). The fall risk score is able to detect the difference between senior nursing home residents and young, healthy controls, as well as between fallers and non-fallers. Its main proof of concept is demonstrated, as based on movement data outside special gait labs, and it can simplify the risk of fall determination in geriatric nursing home residents and can now be used in further, prospective studies., Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

The diagnosis and treatment of non-unions still represents an interdisciplinary challenge. Therefore, prevention, early detection and specific treatment are of great importance. Non-unions of the upper extremities, although less common than that of the lower extremities, requires special attention for successful treatment due to the central role of the shoulder girdle and arm in day to day activities. Successful treatment of non-unions requires a comprehensive evaluation of the patient's medical history, a thorough clinical examination and in particular radiological imaging. In order to effectively treat the pseudarthrosis it is crucial to distinguish between pseudarthroses that are suspected to be due to infections and those that are not. This article presents a treatment algorithm for managing both pseudarthrosis due to infection and pseudarthrosis without infection in the upper extremities., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Introduction: The overall frequency of proximal femoral fractures means that we are repeatedly confronted with failed healing and implant failure, despite a relatively low nonunion rate especially in intertrochanteric fractures (< 5%). The aim of this paper is to present our approach to treating these nonunions of the proximal femur and discuss the treatment results., Material and Methods: Between 2009 and 2023, patients with nonunion of the proximal femur were retrospectively identified and analyzed. Age, gender, time to revision, the Weber-Cech classification of pseudarthrosis and radiographic imaging before and after revision were analyzed., Results: A total of 66 patients were analyzed. The mean age was 58 years (range 25-88 years). The overall healing rate was 88% with a mean consolidation time of 8 months (range 2-29 months). The main osteosynthesis procedures were plate osteosynthesis (n = 45, of which 44 were blade plates), and nail replacement (n = 12). Other procedures included augmentative plate osteosyntheses (n = 4), isolated cancellous bone graft (n = 2), nail dynamization (n = 2), and the use of a dynamic hip screw (n = 1)., Discussion: The analysis of our treatment data as well as the current literature, revealed a trend towards intramedullary revision procedures. Implants that can be used to correct the CCD angle, such as the blade plate, remain a predictable option to achieve correction, especially in nonunions with an increased degree of varus. Particularly in the subtrochanteric region, fractures can also be treated in a targeted manner by a combination of mechanical and biological methods with a reamed nail change to a larger caliber implant., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Background: The mechanical boundary conditions of the non-union and osteosynthetic construct are a key determinant of fracture healing after revision surgery. Aim of this study was to introduce a movement analysis and simulation workflow to determine the mechanical conditions during non-union healing in vivo., Material and Methods: On an individual case basis after non-union revision surgery we performed an accelerometry-based movement analysis. The results were then used as input for a musculoskeletal simulation of the non-union, osteosynthetic construct as well as adjacent joints mechanical boundary conditions., Results: A total of 13 patients were analyzed with our new workflow. The introduced protocol allows an in vivo determination of the mechanical boundary conditions. On clinical follow-up all patients showed radiographic consolidation of the non-union., Conclusion: The introduced workflow allows a clinically applicable determination of the mechanical boundary conditions of fracture and non-union healing. Further studies can now determine the effect of the introduced technique for mechanically optimized postoperative aftercare regimes as well as biomechanically adapted surgical treatment., (© 2022. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Methods of artificial intelligence (AI) have found applications in many fields of medicine within the last few years. Some disciplines already use these methods regularly within their clinical routine. However, the fields of application are wide and there are still many opportunities to apply these new AI concepts. This review article gives an insight into the history of AI and defines the special terms and fields, such as machine learning (ML), neural networks and deep learning. The classical steps in developing AI models are demonstrated here, as well as the iteration of data rectification and preparation, the training of a model and subsequent validation before transfer into a clinical setting are explained. Currently, musculoskeletal disciplines implement methods of ML and also neural networks, e.g. for identification of fractures or for classifications. Also, predictive models based on risk factor analysis for prevention of complications are being initiated. As non-union in bone is a rare but very complex disease with dramatic socioeconomic impact for the healthcare system, many open questions arise which could be better understood by using methods of AI in the future. New fields of research applying AI models range from predictive models and cost analysis to personalized treatment strategies., (© 2022. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Cilostazol, a selective phosphodiesterase-3 inhibitor, is known to control cyclic adenosine monophosphate (c-AMP) and to stimulate angiogenesis through upregulation of pro-angiogenic factors. There is no information, however, whether cilostazol affects fracture healing. We, therefore, studied the effect of cilostazol on callus formation and biomechanics during fracture repair. Bone healing was analyzed in a murine femur fracture stabilized with an intramedullary screw. Radiological, biomechanical, histomorphometric, histochemical, and protein biochemical analyses were performed at 2 and 5 weeks after fracture. Twenty-five mice received 30 mg/kg body weight cilostazol p.o. daily. Controls (n=24) received equivalent amounts of vehicle. In cilostazol-treated animals radiological analysis at 2 weeks showed an improved healing with an accelerated osseous bridging compared to controls. This was associated with a significantly higher amount of bony tissue and a smaller amount of cartilage tissue within the callus. Western blot analysis showed a higher expression of cysteine-rich protein 61 (CYR61), bone morphogenetic protein (BMP)-4, and receptor activator of NF-kappaB ligand (RANKL). At 5 weeks, improved fracture healing after cilostazol treatment was indicated by biomechanical analyses, demonstrating a significant higher bending stiffness compared to controls. Thus, cilostazol improves fracture healing by accelerating both bone formation and callus remodeling., (© 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.)

Study Objective: To document mortality rate and predictors of mortality in elderly patients with complex pelvic fractures., Methods: We reviewed a total of 84 subjects whose ages were above 70 years with complex pelvic fractures, admitted to our hospital from January 2001 to December 2012. A multivariate linear regression model was used to determine the predictors of mortality in the study population. The median age of the patients was 80.4 years (range 70-94 years). 65 of 84 (77%) patients were females. There were 72 Tile Type B fractures (86%) and 12 Type C fractures (14%). The most common associated injuries were thoracic, extremity and head injuries, with incidence of 13 (15%), 11 (13%), and 9 (11%), respectively., Results: The mortality rate was 10% in our study population. The initial haemoglobin on admission (p<0.01), the presence of blood vessel injuries (p<0.01) and the number of PRBCs transfused within the first six hours after admission (p<0.01) independently predicted mortality in elderly patients with complex pelvic fractures., Conclusion: Although there is a downward trend in mortality in elderly patients with complex pelvic fractures, haemodynamic instability still has a significant impact on survival of those patients., (Copyright © 2015 Elsevier Ltd. All rights reserved.)