Atrial Fibrillation and Stroke risk

Every year, 15 million people suffer a stroke globally, with 5 million losing their lives and another 5 million left permanently disabled (WHO). Cardioembolic stroke, the most severe subtype of ischemic stroke, accounts for approximately 22% of stroke incidence worldwide, and data indicates that, in developed countries, the proportion of cardioembolic stroke reaches over 50%. One explanation might be that atrial fibrillation (AF), one of the most discussed risk factors of cardioembolic stroke, has a higher prevalence in developed countries.

The most significant risk factor of cardioembolic stroke, AF, has a general prevalence of about 1,9-2,9% in the European population and the prevalence increases with age, approaching 17% in the population aged 80 or above. The high prevalence coupled with the fact that AF causes a 4-5 times increase in the risk of stroke.

Clinically the risk of stroke in a patient with AF, independent of type, is today estimated with a clinical scoring instrument like CHA₂DS₂-VASc. However, these instruments have been shown to predict high-risk individuals only modestly, indicating an important need for further improvement in the risk stratification of AF patients. Innovations for precise, data-driven insights towards personalized care in stroke prevention and atrial fibrillation. Ensuring the right treatment reaches the right patient at the right time, reducing unnecessary risks and improving outcomes.

Valve surgery – patient prosthesis mismatch

In an adjacent field, valvular heart disease affects over 41 million people worldwide and is increasingly prevalent in developing countries. Valve replacement remains a cornerstone of treatment for severe conditions such as aortic stenosis and mitral regurgitation. Yet, the success of these procedures can be compromised by suboptimal prosthesis sizing and placement, leading to patient-prosthesis mismatch (PPM). PPM is common (20–70% of aortic valve replacements) and has been shown to be associated with worse outcome and lower survival.

Despite access to high-quality imaging, today’s surgical planning lacks the ability to predict or quantify the optimal position and hemodynamic performance of the valve preoperatively. True functional assessment is only possible after full implantation and weaning from cardiopulmonary bypass—when it’s too late to adjust.

There is a clear and growing need for advanced preoperative tools that can simulate, compare, and optimize valve performance before surgery. Solutions that offer patient-specific prediction of hemodynamic outcomes will be essential to improving clinical results and reducing surgical risks—unlocking significant value for patients, providers, and health systems worldwide.