In absence of available quantitative measures, the assessment of fracture healing based on clinical examination and X-rays remains a subjective matter. Lacking reliable information on the state of healing, rehabilitation is hardly individualized and mostly follows non evidence-based protocols building on common guidelines and personal experience. Measurement of fracture stiffness has been demonstrated as a valid outcome measure for the maturity of the repair tissue but so far has not found its way to clinical application outside the research space. However, with the recent technological advancements and trends towards digital health care, this seems about to change with new generations of instrumented implants – often unfortunately termed “smart implants” – being developed as medical devices. The AO Fracture Monitor is a novel, active, implantable sensor system designed to provide an objective measure for the assessment of fracture healing progression (1). It consists of an implantable sensor that is attached to conventional locking plates and continuously measures implant load during physiological weight bearing. Data is recorded and processed in real-time on the implant, from where it is wirelessly transmitted to a cloud application via the patient's smartphone. Thus, the system allows for timely, remote and X-ray free provision of feedback upon the mechanical competence of the repair tissue to support therapeutic decision making and individualized aftercare. The device has been developed according to medical device standards and underwent extensive verification and validation, including an in-vivo study in an ovine tibial osteotomy model, that confirmed the device's capability to depict the course of fracture healing as well as its long-term technical performance. Currently a multi-center clinical investigation is underway to demonstrate clinical safety of the novel implant system. Rendering the progression of bone fracture healing assessable, the AO Fracture Monitor carries potential to enhance today's postoperative care of fracture patients.
Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS. Cite this article:
