Predictive Models of Complications after Endovascular Aortic Aneurysm Repair.

Background: The risk of long-term complications after endovascular aneurysm repair (EVAR) is still higher than open surgery and is a critical issue. This study aims to make available reliable statistical predictive models of complications after EVAR.

Methods: Two hundred and thirteen patients who underwent EVAR between 2002 and 2012 were included in this study. The preoperative computed tomography scans were analyzed with a dedicated workstation to provide spatially correct 3-dimensional data. Age, gender, operation-related factors, and 21 morphologic variables were measured and included in the analyses. Five postoperative outcomes were studied. After an initial selection of predictors based on univariate analysis, binomial logistic regression models were proposed for each outcome. The ability to predict each outcome was assessed with receiver operating characteristic curves considering that an area under the curve (AUC) > 0.70 is generally considered sufficiently accurate.

Results: The mean age was 74.8 ± 8.6 years with a mean follow-up of 43.8 ± 22.1 months. Respectively, rates and risk factors of each outcome were 25.3% (n = 51) for abdominal aortic aneurysm (AAA) enlargement (age, number of patent sac branches, iliac calcifications and tortuosity, aneurysmal thrombus), 7% (n = 15) for type IA endoleak (neck calcification and AAA diameter), 3.7% (n = 8) for type IB endoleak (iliac tortuosity, AAA diameter, neck thrombus), 19.8% (n = 40) for type II endoleak (female, number of patent sac branches), and 25.9% (n = 55) for reintervention from any cause (neck calcification). The risk associated to each outcome can be calculated with a combination of these different preoperative variables. AUC for each outcome were 79.6% for AAA enlargement, 70.4% for reintervention, 81.3% for type IA endoleak, 92.3% for type IB endoleak, 70.6% for type II endoleak.

Conclusions: This study shows that an exhaustive description of the preoperative anatomy before EVAR is a powerful and reliable tool to predict the risk of developing the most common complications after EVAR.