An Artificial Neural Network Stratifies the Risks of Reintervention and Mortality after Endovascular Aneurysm Repair; a Retrospective Observational study.

Background: Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques.

Plasma matrix metalloproteinase levels do not predict tissue levels in abdominal aortic aneurysms suitable for elective repair.

The role of matrix metalloproteinases (MMPs) in abdominal aortic aneurysm (AAA) pathogenesis is well described. However, a clear role for the MMPs in disease prediction has not been established. The aim of this study was to determine if circulating levels of MMPs correlated with AAA diameter and with MMP concentrations within the aneurysm wall.