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Radboud universitair medisch centrum, Cardiologie

Radboud universitair medisch centrum, Cardiologie

3 Projects, page 1 of 1
  • Funder: Netherlands Organisation for Scientific Research (NWO) Project Code: P23.002

    Heart failure poses a large burden on patients and healthcare, largely because heart failure patients have low fitness and require frequent hospitalisation for close monitoring. In CardiacCare@Home, researchers work together with patients, doctors, industry, and others to develop technology for home-based monitoring of cardiac function and rehabilitation. This approach facilitates early detection of worsening of cardiac function, which allows doctors to rapidly alter treatment and prevent hospitalisation. Moreover, home-based rehabilitation will improve patients’ fitness levels. Technological innovations will facilitate a new care path that improves patients’ quality of life and lower socio-economic costs, and lower burden for hospital staff.

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  • Funder: Netherlands Organisation for Scientific Research (NWO) Project Code: KIEM.K23.01.119

    Within the KIEM project "Wavy Zone - stress reduction for better recovery for cardiac patients", research is being conducted on the effectiveness of stress management and reduction using the Blue Zone interventions in combination with biofeedback in cardiac patients during hospitalization and rehabilitation in their own living environment. The goal is to increase the quality of care in cardiac patients, reducing stress, anxiety and symptoms. The project contributes to the KIA of Health and Care, including mission II & III. The consortium is new and consists of Radboudumc, two innovative SMEs and two foundations.

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  • Funder: Netherlands Organisation for Scientific Research (NWO) Project Code: 175.2023.003

    CardioResource will be the first national registry for patients with Heritable cardiac conditions. By bringing together the resources of all seven largest Dutch University Medical Centers, it will enable breakthrough research into these diseases by combining cutting edge (AI-based) analysis in genetics, imaging and the integration of clinical data. This will lead to more accurate diagnosis and improved understanding of the risk of developing disease and severe cardiac complications for patients and their families. It will also facilitate the development of novel therapies for more effective and targeted treatment of these life-threatening conditions.

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