Background and Aims: Cardiovascular disease (CVD) impacts significantly health and social care systems as well as society through premature mortality and disability, with patients requiring care from relatives. Previous pan-European estimates of the economic burden of CVD are now outdated. This study aims to provide novel, up-to-date evidence on the economic burden across the 27 European Union (EU) countries in 2021. Methods: Aggregate country-specific resource use data on morbidity, mortality, and health, social and informal care were obtained from international sources, such as the Statistical Office of the European Communities, enhanced by data from the European Society of Cardiology Atlas programme and patient-level data from the Survey of Health, Ageing and Retirement in Europe. Country-specific unit costs were used, with cost estimates reported on a per capita basis, after adjustment for price differentials. Results: CVD is estimated to cost the EU €282 billion annually, with health and long-term care accounting for €155 billion (55%), equalling 11% of EU-health expenditure. Productivity losses accounted for 17% (€48 billion), whereas informal care costs were €79 billion (28%). CVD represented a cost of €630 per person, ranging from €381 in Cyprus to €903 in Germany. Coronary heart disease accounted for 27% (€77 billion) and cerebrovascular diseases for 27% (€76 billion) of CVD costs. Conclusions: This study provides contemporary estimates of the wide-ranging impact of CVD on all aspects of the economy. The data help inform evidence-based policies to reduce the impact of CVD, promoting care access and better health outcomes and economic sustainability.

The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular researcher and healthcare professional are challenged to understand the opportunities as well as the limitations of the AI-based predictions. In this article, we present 12 critical questions for cardiovascular health professionals to ask when confronted with an AI-based prediction model. We aim to support medical professionals to distinguish the AI-based prediction models that can add value to patient care from the AI that does not.

The European Union's Artificial Intelligence Act (AI Act), published in July 2024, is a pioneering horizontal regulatory framework aimed at ensuring the ethical and safe integration of AI technologies across sectors, including healthcare. While it offers the potential to improve patient care and drive innovation, it also presents challenges for healthcare providers, such as identifying high-risk applications, ensuring transparency in algorithms, and mitigating data bias. However, there are several challenges in its implementation. These include unclear guidance for certain technologies, the need to ensure fairness for diverse patient populations, effective monitoring of AI performance after deployment, and clarifying responsibility in cases of errors. Additionally, varying levels of resources among EU countries may lead to inconsistent implementation of the regulations. This article explores the core elements of the AI Act and its relevance to cardiology and identifies key gaps and unanswered questions that need to be addressed to effectively advance AI-driven medical practices.

The ESC-EHRA Atlas on Heart Rhythm Disorders was developed to comprehensively map arrhythmia care across the European Society of Cardiology (ESC) member countries. A survey of National Cardiac Societies, Working Groups, and other EHRA partners in ESC member countries was conducted to gather data from 2023 or the most recently available year on arrhythmia care organization and delivery. In total, 51 ESC member countries actively participated in the study, with a survey completeness rate of 91%. The median number of hospitals performing EP or CIED procedures was 3.3 per million people. The annual median numbers of ablation procedures for heart rhythm disorders, atrial fibrillation, and supraventricular tachycardia per million people were 432, 151, and 136, respectively. The annual median numbers of pacemakers, implantable cardioverter-defibrillators (ICD), and cardiac resynchronization therapy cardioverter-defibrillator (CRT-D) implantations per million people were 739, 195, and 54, respectively. The median number of hospitals performing remote monitoring of CIEDs per million people was 0.5, though this service was unavailable in 15 countries. Two main universal issues emerged among the obstacles to guideline implementation: a lack of heart rhythm allied professionals and general dissatisfaction with the country’s reimbursement system. The first edition of the ESC-EHRA Atlas presents up-to-date information on arrhythmia care organization and delivery among ESC member countries and highlights significant discrepancies in patients’ access to ESC-guideline-recommended therapies.

This article presents some of the most important developments in the field of digital medicine that have appeared over the last 12 months and are related to cardiovascular medicine. The article consists of three main sections, as follows: (i) artificial intelligence-enabled cardiovascular diagnostic tools, techniques, and methodologies, (ii) big data and prognostic models for cardiovascular risk protection, and (iii) wearable devices in cardiovascular risk assessment, cardiovascular disease prevention, diagnosis, and management. To conclude the article, the authors present a brief further prospective on this new domain, highlighting existing gaps that are specifically related to artificial intelligence technologies, such as explainability, cost-effectiveness, and, of course, the importance of proper regulatory oversight for each clinical implementation.