Predicting outcomes following open abdominal aortic aneurysm repair using machine learning.

ABSTRACT: Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post-operative complications. However, there are no widely used tools to predict surgical risk in this population. We used machine learning (ML) techniques to develop automated algorithms that predict 30-day outcomes following open AAA repair. The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent elective, non-ruptured open AAA repair between 2011 and 2021. Input features included 35 pre-operative demographic/clinical variables. The primary outcome was 30-day major adverse cardiovascular event (MACE; composite of myocardial infarction, stroke, or death). We split our data into training (70%) and test (30%) sets. Using 10-fold cro

SUBMITTER: Li B 

PROVIDER: S-EPMC12022244 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature