Sex-specific machine learning classification models improve outcome prediction for abdominal aortic aneurysms.

ABSTRACT:

Background

Abdominal aortic aneurysm (AAA) is an abnormal dilation of the abdominal aorta that carries up to a 90% mortality rate when ruptured. Although male patients experience AAA at a higher rate than females, female patients experience AAA rupture at a rate three- to four-fold higher that of their male counterparts. The current standard clinicians use for determining when to surgically intervene is maximum transverse diameter of the AAA perpendicular to the axis of flow. However, some aneurysms below these diameter thresholds rupture. Machine learning (ML) classification models have been previously shown to predict patient outcomes with more discriminability than the diameter criterion. However, these models do not consider sex-based differences. In this proof-of-concept study

SUBMITTER: Kerr KE 

PROVIDER: S-EPMC12607067 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature