10:15pm Sunday 13 October 2019

Yale experts say ‘guilt by association’ approach helps detect silent aneurysms

Yale researchers outlined a new, more aggressive strategy for detecting silent but deadly aortic aneurysms in an article published April 24 by Open Heart, a publication by the British Medical Journal and British Cardiovascular Society.

Aneurysms are areas of enlargement in arteries caused by a weakened artery wall. More than 15,000 people in the United States die from aneurysm disease each year — a number that exceeds deaths by HIV/AIDS. Aneurysms that develop in the chest, known as thoracic aortic aneurysms, typically cause no symptoms but are the most life threatening.

To help identify patients at risk for thoracic aortic aneurysms, Dr. John A. Elefteriades, the William W.L. Glenn Professor of Surgery at Yale School of Medicine, and his co-authors at the Aortic Institute at Yale-New Haven conducted a review of medical conditions and other indicators that often occur in patients with these aneurysms.

In their paper, the research team pinpointed a number of conditions, or associations, that could help providers better predict thoracic aortic aneurysms. Their list of “guilt by association” indicators include: aneurysms in other parts of the body; variants in the anatomy of the aorta; certain autoimmune disorders; renal cysts; and a family history of aneurysm.

Another notable association is a connective tissue disease that can be detected with a simple “thumb-palm” test. If a patient can readily extend the thumb across the palm and beyond the edge of the palm, there’s a good chance the patient is at heightened risk for thoracic aortic aneurysm.

Patients with any of the signs or conditions that accompany thoracic aortic aneurysm should undergo testing for the presence of such an aneurysm, said the researchers. “By applying the ‘guilt by association’ paradigm, and searching diligently for thoracic aortic aneurysm via cardiac ECHO or CT scan in patients with the associated conditions, many silent aneurysms can be identified in the general population before they threaten or shorten lives,” Elefteriades explained.


Ziba Kashef


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