View clinical trials related to Embolism.
Filter by:The goal of this exploratory observational study is to assess the feasibility and real-world clinical impact of implementing Artificial Intelligence (AI) software for the detection of acute Pulmonary Embolism (PE) in patients who undergo Computed Tomography Pulmonary Angiogram (CTPA). The main questions that this study aims to answer are: [Question 1] What is the real-world impact of AI on the clinical outcomes and decision making by radiologists and clinicians in the management of acute PE? [Question 2] Is AI software for the detection of acute PE acceptable to use in clinical practice and do they have a favourable impact on clinical workload? [Question 3] Is it cost-effective to implement AI software for the detection of acute PE in clinical practice? Patients having a CTPA for the detection of acute PE will have their imaging analysed by AI software in combination with a human radiologist. Researchers will aim to compare the clinical and radiology specific outcomes with a retrospective cohort of patients who have had standard routine radiology reporting.
The goal of this clinical trial is to evaluate tailored duration of long-term anticoagulant treatment after a first venous thromboembolism based on individualized risk assessments of recurrent VTE and major bleeding risks. Participants will be asked to fill in a questionnaire and take a buccal swab, which are used for an individual estimation of the risks of recurrent VTE and bleeding. Based on these risks a treatment advise will be made, or randomised in a subgroup of patients.
This is a registry of the patients that are admitted to CICU and treated by the Scientific Staff of the 2nd Department of Cardiology, due to an acute cardiovascular disease (acute coronary syndrome, acute heart failure, arrhythmia, pulmonary embolism, cardiac tamponade etc) in order to investigate the clinical characteristics of the patients, their outcome, identify the factors that could predict the in-hospital mortality and compare the results with the predicted by established risk scores. Furthermore, the study will investigate the one-year mortality and also the major adverse cardiac events (MACE - acute myocardial infarction, stroke, or cardiovascular death) will be measured.
Evaluation of the Safety and Efficacy of the Symphony Thrombectomy System in the Treatment of Pulmonary Embolism
The goal of this observational study is to establish an intelligent early warning system for acute and critical complications of the respiratory system such as pulmonary embolism and respiratory failure. Based on the electronic case database of the biomedical big data research center and the clinical real-world vital signs big data collected by wearable devices, the hybrid model architecture with multi-channel gated circulation unit neural network and deep neural network as the core is adopted, Mining the time series trends of multiple vital signs and their linkage change characteristics, integrating the structural nursing observation, laboratory examination and other multimodal clinical information to establish a prediction model, so as to improve patient safety, and lay the foundation for the later establishment of a higher-level and more comprehensive artificial intelligence clinical nursing decision support system. Issues addressed in this study 1. The big data of vital signs of patients collected in real-time by wearable devices were used to explore the internal relationship between the change trend of vital signs and postoperative complications (mainly including infection complications, respiratory failure, pulmonary embolism, cardiac arrest). Supplemented with necessary nursing observation, laboratory examination and other information, and use machine learning technology to build a prediction model of postoperative complications. 2. Develop the prediction model into software to provide auxiliary decision support for clinical medical staff, and lay the foundation for the later establishment of a higher-level and more comprehensive AI clinical decision support system.
This study is a prospective, multicenter, randomized controlled trial of the FlowTriever System plus anticoagulation compared to anticoagulation alone for intermediate-risk acute PE.
The goal of this multicentric clinical trial is to compare the incidence of pulmonary thromboembolism (PTE), assessed through AngioCT, in the endovascular treatment of acute thrombosis in native and prosthetic arteriovenous fistulas (AVF). The main questions it aims to answer are: - What is the difference in the incidence of pulmonary thromboembolism (PTE) assessed by AngioCT in endovascular treatment of acute thrombosis of native and prosthetic arteriovenous fistulas using balloon thrombectomy versus thromboaspiration systems? - What is the primary patency rate of arteriovenous fistulas treated with balloon thrombectomy versus thromboaspiration systems? - What is the clinical success rate in the treatment of arteriovenous fistulas using balloon thrombectomy compared to thromboaspiration systems? - What are the costs associated with the different thrombectomy techniques in the treatment of arteriovenous fistulas? Participants will be underwent to balloon thrombectomy versus thromboaspiration systems. Researchers will compare the patients treated with balloon thrombectomy and thromboaspiration systems to see if the incidence of PE is comparable and to evaluate the primary and secondary patency rates of both thrombectomy techniques, the clinical technical success rate, and the costs associated with each technique.
Introduction: The diagnosis of pulmonary embolism (PE) is a challenge in the Emergency Department. D-dimer based diagnostic algorithms for PE have a very high sensitivity, but rely upon a vast amount of CT angiography and potentially unnecessary exposure to radiation. An accurate diagnostic algorithm that does not involve d-dimer testing might reduce this burden. An abnormal Alveolar-arterial oxygen gradient (A-a gradient) seems to increase the chance of PE. However, a normal A-a gradient on its own does not exclude the diagnosis. In this paper, the accuracy of A-a gradient testing and a combination of Years criteria with A-a gradient testing will be assessed. Methods: This is a prospective, single center, observational study. All patients that present at our emergency department from September 2022 until September 2023 with a suspicion of pulmonary embolism will be analyzed for eligibility and included in the study after informed consent. The aim is to include at least 230 patients in the study. Analysis: The primary outcome is the diagnostic accuracy of a YEARS and A-a gradient based algorithm for pulmonary embolism. The secondary outcome is the potential decrease in performed imaging in order to exclude pulmonary embolism. Valorisation An accurate A-a gradient-based algorithm for pulmonary embolism in low risk patients will be a step towards an improved clinical risk score. We aim to reduce the amount of diagnostic imaging, i.e. CT-angiography. Meaning less, potentially unnecessary, exposure to radiation for the patient. Furthermore, it could lower healthcare costs by reducing expensive diagnostic imaging.
The goal of this NIH-sponsored study is to characterize three biomarkers derived from 129Xe gas exchange MRI and to understand how they change in response to interventions.
Venous thromboembolism (VTE), clinically presenting as deep vein thrombosis or pulmonary embolism (PE) is the third most common cardiovascular disease and is associated with substantial short- and long-term morbidity and mortality and high costs of care. In addition negative physical and mental complications following VTE are common. However in terms of PE, there are no structured follow-up programs in Denmark and there is considerable variation in practice patterns of post-PE management both within and between countries. The Attend-PE project aims to develop, test and implement a structured follow-up model in a hospital setting for patients with pulmonary embolism. The Attend-PE is a pre-post intervention study and will estimate the effectiveness of implementing the structured care model on a national level.