Automated Software Identifies Hundreds of Patients Lost to Aneurysm Follow-Up

Abdominal aortic aneurysms affect over 35 million people worldwide and represent a significant risk for fatal rupture if not monitored appropriately [1]. Current management strategies rely on regular ultrasound or computed tomography surveillance to identify when an aneurysm reaches the diameter threshold for surgical repair [2]. However, maintaining long-term follow-up remains a significant challenge in clinical practice, with high rates of patients becoming lost to the health system [3]. While small aneurysms typically carry a low risk of rupture, those that exceed 5.5 centimeters require strict adherence to monitoring guidelines to prevent catastrophic outcomes [4]. Recent advancements in machine learning and digital health interventions offer tools for improving the tracking of chronic vascular conditions [5, 6]. A recent study evaluates how automated software can be leveraged to maintain a large-scale surveillance program, ensuring high-risk patients do not slip through the cracks.