ESC Geoffrey Rose Lecture on Population Sciences: Prof. Renate B. Schnabel
Digitalisation and the atrial fibrillation pandemic in cardiology
25 Aug 2023
The presenter of this year’s ESC Geoffrey Rose Lecture in Population Sciences is Professor Renate B. Schnabel (University Heart & Vascular Center Hamburg - Hamburg, Germany), whose research has contributed enormously to raising awareness of atrial fibrillation (AF) and continues to change perceptions of appropriate management approaches.
What first made you interested in cardiology?
I became interested in cardiology in medical school. Initially drawn by a fascination with the mechanics of the cardiovascular system, my interest continued to grow when I realised that rapidly made clinical decisions, for example performing cardiopulmonary resuscitation or a percutaneous coronary intervention, can have an immediate life-saving effect. Another attraction is the fast-moving nature of cardiology research. Even in the time that I’ve been in the field, we have seen many innovations that have become integrated into practice. And cardiology is really leading the way in digitalisation in medicine, a rapidly evolving area that will revolutionise patient care. Finally, cardiology tends to produce really sound evidence in large-scale studies and that is crucial for my research. Despite being an interventional cardiologist, my research focus is on population sciences and epidemiology, and for more than 10 years, I have been looking at AF.
What are the key themes of your lecture?
One of the themes is the dynamic epidemiology of AF. Prior to 2006 and the work I conducted with my mentor, Professor Emilia Benjamin, on five decades worth of data from the Framingham Heart Study, AF had not been considered seriously at the population level. We have come a long way since then. However, AF remains a huge problem for a number of reasons, including ageing populations, increased survival of patients with cardiac conditions and predisposing risk factors, and the rise of implantable devices and risk monitoring that facilitate early detection.
The next challenge is to more accurately define risk factors for AF. The lecture provides insights into refined risk prediction using cutting-edge methods to provide a better understanding of an individual’s susceptibility to AF. We have been working to improve and personalise a basic risk-prediction algorithm developed from the Framingham Heart Study data. Refinements include the incorporation of genetic data from genome-wide studies and information on natriuretic peptides, and the use of machine-learning algorithms to integrate multiomics, clinical variables and subclinical changes, for example, ECGs in sinus rhythm.
The lecture also discusses current data on effective screening methods, including the use of implantable devices and wearables and their potential in clinical practice. And, in fact, my team is currently working in worldwide consortia to try to define the optimal screening strategy for AF.
What are the current challenges in your field?
We need to consider the definition of AF in different settings in relation to its outcome and its treatment. And we still do not understand the mechanisms behind this very heterogeneous disease. For example, we do not know the pathophysiological differences between valvular and non-valvular AF, even though there are distinct differences in treatment at the clinical level. Also, while there are effective means to avoid stroke in patients with AF, the risk of heart failure is still high and is a major cause of death.
When to treat is another unanswered question. It is recognised that in younger individuals with a family history, AF may occur early but may have little thromboembolic risk. The same is true of very infrequent episodes detected by implantable devices, wearables and hand-held devices. So we need to define what level of AF requires therapeutic intervention.
Where is research in your field heading in the future?
I think further innovation of currently available methods will guide us in the near future. For instance, important pathophysiological information may come from atrial tissue and blood omics along with refined functional imaging, particularly of the left atrium, using high-resolution techniques and advanced AI-driven modelling to describe atrial haemodynamics. The rapid expansion of smartphones and wearables able to capture AF will drive earlier reporting of AF and in larger numbers. However, we will need to understand how to deal with what will be an enormous amount of data and to ensure that patients with the greatest need for treatment do not get overlooked. That said, I am certain that with the energy of researchers and continued rapid technological advancements we will, in line with the ESC’s goal of reducing the burden of CVD, improve AF-related morbidity and mortality.