Defining high-risk patients for endovascular aneurysm repair

Abstract

Background: Endovascular aneurysm repair (EVAR) is commonly used as a minimally invasive technique for repairing infrarenal aortic aneurysms. There have been recent concerns that a subset of high-risk patients experience unfavorable outcomes with this intervention. To determine whether such a high-risk cohort exists and to identify the characteristics of these patients, we analyzed the outcomes of Medicare patients treated with EVAR from 2000-2006.

Methods: We identified 66,943 patients who underwent EVAR from Inpatient Medicare database. The overall 30-day mortality was 1.6%. A risk model for perioperative mortality was developed by randomly selecting 44,630 patients; the other one third of the dataset was used to validate the model. The model was deemed reliable (Hosmer-Lemeshow statistics were P = .25 for the development, P = .24 for the validation model) and accurate (c = 0.735 and c = 0.731 for the development and the validation model, respectively).

Results: In our scoring system, where scores ranged between 1 and 7, the following were identified as significant baseline factors that predict mortality: renal failure with dialysis (score = 7); renal failure without dialysis (score = 3); clinically significant lower extremity ischemia (score = 5); patient age >or=85 years (score = 3), 75-84 years (score = 2), 70-74 years (score = 1); heart failure (score = 3); chronic liver disease (score = 3); female gender (score = 2); neurological disorders (score = 2); chronic pulmonary disease (score = 2); surgeon experience in EVAR <3 procedures (score = 1); and hospital annual volume in EVAR <7 procedures (score = 1). The majority of Medicare patients who were treated (96.6%, n = 64,651) had a score of 9 or less, which correlated with a mortality <5%. Only 3.4% of patients had a mortality >or=5% and 0.8% of patients (n = 509) had a score of 13 or higher, which correlated with a mortality >10%.

Conclusion: We conclude that there is a high-risk cohort of patients that should not be treated with EVAR because of prohibitively high mortality; however, this cohort is small. Our scoring system, which is based on patient and institutional factors, provides criteria that can be easily used by clinicians to quantify perioperative risk for EVAR candidates.

Figure 1

Relationship between observed and predicted mortality by total score. Predicted mortality was estimated based on logistic regression model of 2/3 of the cohort (development sample). Observed mortality was depicted from the rest 1/3 of the cohort (test sample). Number of observation in the test sample by score: 1 – 3229, 2 – 2497, 3 – 4051, 4 – 2573, 5 – 2135, 6 – 1555, 7 – 1104, 8 – 800, 9 – 475, 10 – 312, 11 – 186, 12 – 130, 13 – 69, 14 – 24, 15 – 31, 16 – 15, 17 – 11, 18 – 2, 19 – 0, 20 – 3.

Figure 1

Relationship between observed and predicted mortality by total score. Predicted mortality was estimated based on logistic regression model of 2/3 of the cohort (development sample). Observed mortality was depicted from the rest 1/3 of the cohort (test sample). Number of observation in the test sample by score: 1 – 3229, 2 – 2497, 3 – 4051, 4 – 2573, 5 – 2135, 6 – 1555, 7 – 1104, 8 – 800, 9 – 475, 10 – 312, 11 – 186, 12 – 130, 13 – 69, 14 – 24, 15 – 31, 16 – 15, 17 – 11, 18 – 2, 19 – 0, 20 – 3.

Figure 2

Distribution of patients by risk scores.