Objectives. The monitoring of fracture healing is a complex process. Typically, successive radiographs are performed and an emerging calcification of the fracture area is evaluated. The aim of this study was to investigate whether different bone healing patterns can be distinguished using a telemetric instrumented femoral internal plate fixator. Materials and Methods. An electronic telemetric system was developed to assess bone healing mechanically. The system consists of a telemetry module which is applied to an internal locking plate fixator, an external reader device, a sensor for measuring externally applied load and a laptop computer with processing software. By correlation between externally applied load and load measured in the implant, the elasticity of the osteosynthesis is calculated. The elasticity decreases with ongoing consolidation of a fracture or nonunion and is an appropriate parameter for the course of bone healing. At our centre, clinical application has been performed in 56 patients suffering nonunion or fracture of the femur. Results. A total of 39 cases of clinical application were reviewed for this study. In total, four different types of healing curves were observed: fast healing; slow healing; plateau followed by healing; and non-healing. Conclusion. The electronically instrumented internal fixator proved to be valuable for the assessment of bone healing in difficult healing situations. Cost-effective manufacturing is possible because the used electronic components are derived from large-scale production. The incorporation of microelectronics into orthopaedic implants will be an important innovation in future clinical care. Cite this article: B. Kienast, B. Kowald, K. Seide, M. Aljudaibi, M. Faschingbauer, C. Juergens, J. Gille. An electronically instrumented internal fixator for the assessment of bone healing. Bone Joint Res 2016;5:191–197. DOI: 10.1302/2046-3758.55.2000611

Aims. Several previously identified patient-, injury-, and treatment-related factors are associated with the development of nonunion in distal femur fractures. However, the predictive value of these factors is not well defined. We aimed to assess the predictive ability of previously identified risk factors in the development of nonunion leading to secondary surgery in distal femur fractures. Methods. We conducted a retrospective cohort study of adult patients with traumatic distal femur fracture treated with lateral locking plate between 2009 and 2018. The patients who underwent secondary surgery due to fracture healing problem or plate failure were considered having nonunion. Background knowledge of risk factors of distal femur fracture nonunion based on previous literature was used to form an initial set of variables. A logistic regression model was used with previously identified patient- and injury-related variables (age, sex, BMI, diabetes, smoking, periprosthetic fracture, open fracture, trauma energy, fracture zone length, fracture comminution, medial side comminution) in the first analysis and with treatment-related variables (different surgeon-controlled factors, e.g. plate length, screw placement, and proximal fixation) in the second analysis to predict the nonunion leading to secondary surgery in distal femur fractures. Results. We were able to include 299 fractures in 291 patients. Altogether, 31/299 fractures (10%) developed nonunion. In the first analysis, pseudo-R. 2. was 0.27 and area under the receiver operating characteristic curve (AUC) was 0.81. BMI was the most important variable in the prediction. In the second analysis, pseudo-R. 2. was 0.06 and AUC was 0.67. Plate length was the most important variable in the prediction. Conclusion. The model including patient- and injury-related factors had moderate fit and predictive ability in the prediction of distal femur fracture nonunion leading to secondary surgery. BMI was the most important variable in prediction of nonunion. Surgeon-controlled factors had a minor role in prediction of nonunion. Cite this article: Bone Jt Open 2023;4(8):584–593

Objectives. A successful outcome following treatment of nonunion requires the correct identification of all of the underlying cause(s) and addressing them appropriately. The aim of this study was to assess the distribution and frequency of causative factors in a consecutive cohort of nonunion patients in order to optimise the management strategy for individual patients presenting with nonunion. Methods. Causes of the nonunion were divided into four categories: mechanical; infection; dead bone with a gap; and host. Prospective and retrospective data of 100 consecutive patients who had undergone surgery for long bone fracture nonunion were analysed. Results. A total of 31% of patients had a single attributable cause, 55% had two causes, 14% had three causes and 1% had all four. Of those (31%) with only a single attributable cause, half were due to a mechanical factor and a quarter had dead bone with a gap. Mechanical causation was found in 59% of all patients, dead bone and a gap was present in 47%, host factors in 43% and infection was a causative factor in 38% of patients. In all, three of 58 patients (5%) thought to be aseptic and two of nine (22%) suspected of possible infection were found to be infected. A total of 100% of previously treated patients no longer considered to have ongoing infection, had multiple positive microbiology results. Conclusion. Two thirds of patients had multiple contributing factors for their nonunion and 5% had entirely unexpected infection. This study highlights the importance of identifying all of the aetiological factors and routinely testing tissue for infection in treating nonunion. It raises key points regarding the inadequacy of a purely radiographic nonunion classification system and the variety of different definitions for atrophic nonunion in the current mainstream classifications used for nonunion. Cite this article: L. Mills, J. Tsang, G. Hopper, G. Keenan, A. H. R. W. Simpson. The multifactorial aetiology of fracture nonunion and the importance of searching for latent infection. Bone Joint Res 2016;5:512–519. DOI: 10.1302/2046-3758.510.BJR-2016-0138