View clinical trials related to Bone Fracture.
Filter by:Prospective observational clinical, molecular, translational and basic study aimed at identifying the main determinants and predictive factors of risk of bone damage in acromegaly patients
Osteoporosis is a chronic skeletal disease which leads to a decrease in bone strength which increases the risk of fractures. Clinically overt hypercortisolism leads to hypertension, central obesity, diabetes and osteoporosis. More recently, even the condition of mild and asymptomatic hypercortisolism has been associated with increased prevalence of chronic complications of cortisol excess and mortality. In patients with osteoporosis this form of hypercortisolism may remain occult (hidden hypercortisolism, HidHyCo). Although asymptomatic, however, this subtle cortisol excess is associated with an increased risk of osteoporosis and fragility fractures. Moreover, HidHyCo prevalence seems to be increased in osteoporotic patients. The HidHyCo case finding is of utmost importance. However, given the high prevalence of bone fragility and the relatively low diagnostic accuracy of the currently available tests for the HidHyCo detection, a mass screening for HidHyCo is considered unthinkable. As now, no guidelines are available for addressing the HidHyCo screening in osteoporosis. Therefore, the aims of the present study are the following: i) to assess the HidHyCo prevalence in a sample of osteoporotic patients; ii) to compare the clinical characteristics between osteoporotic/osteopenic patients with HidHyCo and those without HidHyCo in order to determine the clinical characteristics more frequently associated with the HidHyCo presence and to identify those osteoporotic patients worthy of HidHyCo screening; iii) to further investigate bone quality and turnover in HidHyCo patients, to characterize HidHyco patients from a molecular and genetic point of view and to evaluate the pathogenetic mechanisms explaining the negative effects of endogenous cortisol excess on bone health in these patients and the potential role of the genetic background and of the gut microbiome. The HidHyCo could be present in a not negligible percentage of osteopenic/osteoporotic patients. In these patients, osteoporosis and, if present, other comorbidities can improve by the surgical resection of the adrenal or pituitary adenoma if feasible, or by the use of drugs able to modulate cortisol secretion or glucocorticoid sensitivity. Moreover, the case-finding could be reserved in those patients at higher risk of having HidHyCo, therefore, reducing the costs of a scarcely specific mass screening.
The purpose of this study is to demonstrate the effect of bioceramic implants on the repair of human bone defects, and to explore the application of bioceramic materials in bone defects, bone implantation, and bone fusion. The surface microstructure of β-tricalcium phosphate bioceramic implants can be effectively controlled to guide the regeneration of bones, promote the restoration of bones, accelerate the speed of recovery, and improve bone quality, which is of great clinical and social significance.
This study has been added as a sub study to the Simulation Training for Emergency Department Imaging 2 study (ClinicalTrials.gov ID NCT05427838). This work aims to evaluate the impact of an Artificial Intelligence (AI)-enhanced algorithm called Boneview on the diagnostic accuracy of clinicians in the detection of fractures on plain XR (X-Ray). The study will create a dataset of 500 plain X-Rays involving standard images of all bones other than the skull and cervical spine, with 50% normal cases and 50% containing fractures. A reference 'ground truth' for each image to confirm the presence or absence of a fracture will be established by a senior radiologist panel. This dataset will then be inferenced by the Gleamer Boneview algorithm to identify fractures. Performance of the algorithm will be compared against the reference standard. The study will then undertake a Multiple-Reader Multiple-Case study in which clinicians interpret all images without AI and then subsequently with access to the output of the AI algorithm. 18 clinicians will be recruited as readers with 3 from each of six distinct clinical groups: Emergency Medicine, Trauma and Orthopedic Surgery, Emergency Nurse Practitioners, Physiotherapy, Radiology and Radiographers, with three levels of seniority in each group. Changes in reporting accuracy (sensitivity, specificity), confidence, and speed of readers in two sessions will be compared. The results will be analyzed in a pooled analysis for all readers as well as for the following subgroups: Clinical role, Level of seniority, Pathological finding, Difficulty of image. The study will demonstrate the impact of an AI interpretation as compared with interpretation by clinicians, and as compared with clinicians using the AI as an adjunct to their interpretation. The study will represent a range of professional backgrounds and levels of experience among the clinical element. The study will use plain film x-rays that will represent a range of anatomical views and pathological presentations, however x-rays will present equal numbers of pathological and non-pathological x-rays, giving equal weight to assessment of specificity and sensitivity. Ethics approval has already been granted, and the study will be disseminated through publication in peer-reviewed journals and presentation at relevant conferences.
The aim of this study was to compare the efficacy of ibuprofen and dexketoprofen, two common analgesic drugs used in pain control in patients with long bone fractures.
As part of the management of a patient with suspected bone fractures, emergency physicians are required to make treatment decisions before obtaining the imaging reading report from the radiologist, who is generally not available only a few hours after the patient's admission, or even the following day. This situation of the emergency doctor, alone interpreting the radiological image, in a context of limited time due to the large flow of patients to be treated, leads to a significant risk of interpretation error. Unrecognized fractures represent one of the main causes of diagnostic errors in emergency departments. This comparative study consists of two cohorts of patients referred to the emergency department for suspected bone fracture. The first will be of interest to patients whose radiological images will be interpreted by the reading of the emergency doctor systematically doubled by the reading of the artificial intelligence. The other will interest a group of patients cared for by the simple reading of the emergency doctor. All of the images from both groups of patients will be re-read by the establishment's group of radiologists no later than 24 hours following the patient's treatment. A centralized review will be provided by two expert radiologists. Also, patients in both groups will be systematically recalled in the event of detection of an unknown fracture for hospitalization.
The purpose of this study is to assess the ability of long-duration low-intensity therapeutic ultrasound (LITUS) to alleviate bone-fracture related pain over a 12-week period. The primary objective of this study is to evaluate the analgesic effect of LITUS in subjects suffering from bone-fracture pain. Secondary objectives are to assess the ability of LITUS to improve patients return to work time.
The study evaluates, in 3 emergency departments (ED) and on randomized alternate periods, the use of SmartUrgences®, Augmented Intelligence (AI) software to help the interpretation of bone standard X-rays prescibed by the ED.
Diseases of bone associated with ageing, including osteoporosis (OP) and osteoarthritis (OA), reduce bone mass, bone strength and joint integrity. Current non-surgical approaches are limited to pharmaceutical agents that are not disease modifying and have poor patient tolerability due to side effect profiles. Developing a fundamental understanding of cellular bone homeostasis, including how key cell types affect tissue health, and offering novel therapeutic targets for prevention of bone disease is therefore essential. This is the focus of OSTEOMICS. A number of factors have been linked to increased risk of bone disease, including genetic predisposition, diet, smoking, ageing, autoimmune disorders and endocrine disorders. In our study, we will recruit patients undergoing elective and non-elective orthopaedic surgery and obtain surgical bone waste for analysis. This will capture a cohort of patients with bone disorders like OP and OA, in addition to patients without overt clinical bone disease. We will study the relationship between the molecular biology of bone cells, bone structure, genetics (DNA) and environmental factors with the aim of identifying and validating novel therapeutic targets. We will leverage modern single cell technologies to understand the diversity of cell types found in bone. These technologies have now led to the characterisation of virtually every tissue in the body, however bone and bone-adjacent tissues are massively underrepresented due to the anatomical location and underlying technical challenges. Early protocols to demineralise bone and perform single cell profiling have now been developed. We will systematically scale up these efforts to observe how genetic variation at the population level leads to alterations in bone structure and quality. Over the next 10 years, we will generate data to comprehensively characterise bone across health and disease, use machine learning to drive analysis, and experimentally validate hypotheses - which will ultimately contribute to developing the next generation of therapeutic agents.
Relative Energy Deficiency in Sport (RED-S) characterizes a range of negative health and performance outcomes that result from chronically low energy availability. RED-S concerns high performance junior and senior athletes across Canada and has a prevalence rate of 3-60%. Our ability to assess and diagnose RED-S remains poor. Accordingly, we aim to create the best parameters to diagnose and manage RED-S; along with information of the prevalence and severity across Canada and globally. These outcomes are expected to have a significant positive impact on the health and performance of Canadian athletes in preparation for the Olympic Games in 2022 and beyond.