ASCVD management: will the future look smarter?: Thomas F. Lüscher, Zürich, Switzerland
The rise of cardiometabolic disease as global health threat: towards the UN 2030 goals
Thomas Lüscher is Director of Research, Education & Development and Consulting Cardiologist at the Royal Brompton & Harefield Hospital Trust, and Professor of Cardiology at the National Heart and Lung Institute of Imperial College and at Kings College in London, UK. He studied medicine at the University of Zurich, and trained in cardiovascular research and in cardiology at the Mayo Clinic in Rochester, USA before he was appointed Professor of Pharmacotherapy, University of Base. He subsequently trained in interventional cardiology and was Professor of Cardiology at the University of Berne, before being appointed as Professor and Chairman of Cardiology and Director of the University Heart Center, University Hospital Zurich and Director of the Center for Molecular Cardiology at the University of Zurich, Switzerland. His research is translational focusing on vascular disease, specifically the role of the endothelium in the regulation of vascular tone and structure, platelet-vessel wall interactions, inflammation and coagulation. More recently, his research team has studied inflammatory pathways in acute coronary syndromes. He was Editor-in-Chief of the European Heart Journal and Chairman of the ESC Publications Committee from 2009-2020.
With the ongoing evolution of information technology, the concept of smart healthcare is now entering clinical reality. The inherent strengths of big data, cloud computing, and artificial intelligence offer the possibility of transforming conventional medicine so that healthcare becomes more efficient and more personalized. This is especially the case for atherosclerotic cardiovascular disease (ASCVD) management, as artificial intelligence offers possibilities for deep phenotyping, combining biologic and genomic data to better understand the risk profile of the individual, so that treatment can be appropriately targeted. The application of smart healthcare is likely to result in more effective health care delivery with the potential for significant cost savings.
Imaging is one example which has already adapted to smart intelligence-based approaches. With the availability and use of large datasets, artificial intelligence has the potential to improve patient care at every stage of the imaging chain. The use of machine learning algorithms allow for complex pattern recognition and iterative learning. Such strategies do not replace the role of the cardiologist but instead improve clinical focus. Data mining the electronic health history of the patient for relevant information will allow clinicians to better characterize disease and personalize therapy.
Despite rapid growth in the availability and affordability of technology, however, there are still some issues. While further research and development are needed, the use of smart healthcare will undoubtedly lead to a paradigm shift toward precision cardiovascular medicine in the 21st century.
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Lüscher TF. A revolution in diabetes care: novel drugs and new recommendations. Eur Heart J 2020;41:195-8.