Clinical trials

The goal of this clinical randomised controlled trial is to compare two treatment strategies - antiplatelet treatment strategy versus anticoagulation treatment strategy - in patients with acute, ischemic Cervical Artery Dissection (CAD). The study population includes patients presenting with any (clinical or imaging) signs of cerebral ischemia due to CAD. The trial aims to estimate the net effect of antiplatelet versus anticoagulation treatment strategies on the composite primary outcome including recurrent ischemic stroke, major bleeding, or vascular death at 90 days (±2 weeks) after randomization. Participants will: * be randomly allocated to antiplatelet treatment strategy or anticoagulation treatment strategy * receive treatment according to assigned strategy for the study period of 90 days * be followed up for 90 days (±2 weeks) after randomization * undergo clinical assessments to monitor for stroke recurrence, bleeding events, and vascular death Participant reported outcomes will be assessed both at 90 days (±2 weeks) and 12 months (± 4 weeks) after enrolment and will also expand to measures of quality of life and mental health outcomes.

Musculoskeletal aging is one of the major responsibilities and challenges for public health. In particular, sarcopenia correlates with an increased risk of falls and increased morbidity and mortality. With regard to screening for sarcopenia, the guidelines of the European Working Group on Sarcopenia in Older People (EWGSOP2) refer to algorithmic case finding, diagnosis, and quantification of the severity of sarcopenia in clinical. While functional measurements are more difficult to standardize and associated with higher variability, Dual-energy X-ray absorptiometry (DXA) is considered a highly accurate method, even referred to as the "gold standard" to determine muscle mass in the scientific literature. Nevertheless, DXA, which is routinely used, shows inconsistent correlation with functional decline in muscle strength. Another method of muscle quantification is bioelectrical impedance analysis (BIA), a simple, portable instrument that is more readily available and applicable due to its lower cost. However, it tends to overestimate muscle mass and is also more susceptible to a person's hydration status. Because of these difficulties, recent research has focused on the potential of using shear wave elastography. This method indirectly serves to quantify the rapid type II muscle fibers in order to make statements about the muscle quality because an age-related decrease in type II muscle fibers is associated with a more frequent fall frequency. First, the investigators will define three different categories according to the EWGSOP 2 guidelines based on the muscle strength (grip strength, assessed by pneumatic hand dynamometer) and muscle mass (Appendicular skeletal muscle mass, assessed by BIA): "No Sarcopenia", "Probable Sarcopenia" and "Confirmed Sarcopenia". Within these categories, the Investigators would like to establish a multivariate data analysis of different functional measurements with quantitative imaging results. This exploratory trial design is intended to improve understanding within the three categories and to test proxy measurements of different patients who are ruled out for common routine measurements due to, for example, cognitive impairment or pre-existing rheumatic disease. This is essential to consider the heterogeneity of the aging society proportionally.

This study focuses on researching sarcopenia and bone loss (osteoporosis), aiming to develop early and effective methods for diagnosis and treatment. These health issues significantly contribute to falls, fractures, and loss of independence and quality of life in old age, particularly affecting individuals impairments. To address these challenges, the study employs innovative imaging techniques based on artificial intelligence (AI) to accurately assess age-related muscle atrophy. A central approach is to analyze existing computed tomography (CT) images of older adults, using retrospective data to evaluate muscle quality. This method aims to efficiently assess muscle quality without additional resources. AI algorithms analyze fine details of muscle tissue, such as muscle adiposity and density. The algorithm can detect fat content within muscles, which negatively impacts muscle health and functionality, and identify irregularities or abnormalities in muscle fibers. This non-invasive approach is crucial for early detection of muscle atrophy and monitoring treatment success. Integrating AI technologies advances beyond conventional imaging techniques, allowing precise analysis of muscle quality. This method not only offers efficient diagnosis and monitoring of sarcopenia but also opens new avenues for personalized therapeutic approaches and improved patient care. Almost every elderly person has at least one existing CT scan, a common and excellent method of medical imaging for significant health issues. These images can be retrospectively analyzed for muscle health. In addition to imaging techniques, the study includes functional tests such as hand strength and walking speed measurements to assess muscle health and condition. These tests establish objective quality characteristics of muscles and assess the effectiveness of prevention and treatment measures. This research aims to provide early diagnosis and effective treatment strategies for sarcopenia and osteoporosis, ultimately improving the quality of life for the elderly. By leveraging AI and existing medical imaging data, the study promotes efficient, sustainable, and precise healthcare solutions for age-related muscle and bone deterioration.