| Title: | Phenomapping aortic aneurysms via cluster analysis |
| Lead Institution: | Klinik Ottakring |
| Principal investigator: |
Application 291300
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About
Aortic aneurysm refers to an increased diameter of the main artery of the human body. The disease is commonly due to chronic degradation of the vessel wall and subsequent enlargement. However, this can also be caused by injuries to the innermost layer of the artery resulting in aortic dissections. Aortic aneurysms can affect different segments of the artery but the most common presentation are aneurysms of the aorta in the abdominal cavity - abdominal aortic aneurysms. With increasing diameters the risk of rupture and subsequent bleeding increases - a life threatening condition. Therefore, aortic aneurysms are recommend to undergo prophylactic treatment at predefined threshold. For example, in male patients abdominal aortic aneurysms are recommended to receive treatment at a diameter of 55 milimeters. Both open surgical as well as minimally invasive treatments facilitated by stentgraft implantation exist and treatment decisions are made on a case-by-case basis, as both options feature distinct benefits and disadvantages. Nevertheless, patients undergoing aneurysm treatment are at an elevated risk for adverse outcomes during and after surgery based on the procedure itself and the fact that they commonly present with other cardiovascular diseases such as hypertension, diabetes or coronary heart disease. It is therefore essential to be able to understand the associated risk of treatment for individual patients to optimize their therapeutic strategy. Additionally, understanding the disease itself, which features a complex interplay of several risk factors including comorbidities, lifestyle, or genetic predispositions, is crucial to improve patient care. Identifying patient groups that are at an elevated to risk for rapid disease progression can help to guide treatment decisions. In the present project proposal we aim to conduct a cluster analysis of aortic aneurysm patients in order to identify patterns related to the points mentioned above. This process is called phenomapping and it has been previously applied with great success in other cardiovascular diseases such as heart failure.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17490 | Unsupervised cluster analysis identifies risk profiles driving heterogeneity and survival patterns in aortic aneurysm patients | Maria Elisabeth Leinweber (+4) | 2026 | Scientific Reports |
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