Abstract
OBJECTIVES: The impact of risk factors upon perioperative mortality might differ for patients undergoing open vs endovascular repair (EVAR) of abdominal aortic aneurysms (AAA). In order to investigate this, we developed a differential predictive model of perioperative mortality after AAA repair. METHODS: A total of 45,660 propensity score matched Medicare beneficiaries undergoing elective open or endovascular AAA repair from 2001 to 2004 were studied. Using half the dataset we developed a multiple logistic regression model for a matched cohort of open and EVAR patients and used this to derive an easily evaluable risk prediction score. The remainder of the dataset formed a validation cohort used to confirm results. RESULTS: The derivation cohort included 11,415 open and 11,415 endovascular repairs. Perioperative mortality was 5.3% and 1.8%, respectively. Independent predictors of mortality (relative risk [RR], 95% confidence interval [CI]) were open repair (3.2, 2.7-3.8); age (71-75 years 1.2, 0.9-1.6; 76-80 years 1.9, 1.4-2.5; >80 years 3.1, 2.4-4.2); female gender (1.5, 1.3-1.8); dialysis (2.6, 1.5-4.6); chronic renal insufficiency (2.0, 1.6-2.6); congestive heart failure (1.7, 1.5-2.1); and vascular disease (1.3, 1.2-1.6). There were no differential predictors of mortality across the two procedures. A simple scoring system was developed from a logistic regression model fit to both endovascular and open patients (area under the receiver operator curve [ROC] curve of 72.6) from which low, medium, and high risk groups were developed. The absolute predicted mortality ranged from 0.7% for an EVAR patient 80 with all the comorbidities considered. Although relative risk was similar among age groups, the absolute difference was greater for older patients (with higher baseline risk). CONCLUSION: Mortality after AAA repair is predicted by comorbidities, gender, and age, and these predictors have similar effects for both methods of AAA repair. This simple scoring system can predict repair mortality for both treatment options and thus may help guide clinical decisions.