Risk Calculator Tool for In-hospital Adverse Events following Endovascular Aortic Aneurysm Repair
Besma J Nejim1, Devin Zarkowsky2, Caitlin W. Hicks1, Mohammad Fateeh1, James Hamilton Black, III1, Mahmoud B. Malas1
1Johns Hopkins University School of Medicine, Baltimore, MD;2University of California San Francisco, Baltimore, MD
INTRODUCTION: Perioperative complications following endovascular repair of abdominal aortic aneurysms contribute to longer hospitalization and significant morbidity and mortality. EVAR-related mortality has been exhaustively studied but little is known about the determinants of in-hospital morbidities following EVAR. The aim of this study was to identify the predictors of in-hospital events following elective EVAR.
METHODS: The Vascular Quality Initiative EVAR database (2003-2016) was explored. Patients who had non-elective repair, intraoperative death or were converted to open repair were excluded. In-hospital events (IHE) were defined as any in-hospital myocardial infarction, stroke, pneumonia, respiratory failure, renal failure, lower extremity ischemia, bowel ischemia, or reoperation. Standard summary statistics were used to describe the patient’s characteristics. Stepwise backward selection based on the Akaike information criterion statistic was implemented to select the predictors of IHE from the multivariable logistic regression (MLR) model. Receiver Operating Curves (ROC) were used to assess the final models. A graphical risk probability calculator (nomogram) was constructed as a post-estimation of the MLR model.
RESULTS: A total of 24,550 patients undergoing EVAR were included, of which an IHE occurred in 1,628 (6.6%). Patients who had IHE were slightly older [mean age (±SD): 75.6(±8.2) vs.73.4 (±8.5); P<.001] and more frequently female (26.7%vs.18.0%; P<.001). Comorbid conditions were more prevalent in patients who developed IHE such as diabetes, hypertension, CKD, COPD, and CHF (All P<.05). The selected predictors of in-hospital events based on MLR are depicted in Figure 1, and included GFR<60 (strongest predictor), CHF, COPD, blood transfusion, contrast volume, female gender, increasing age, diabetes, increasing aneurysm diameter, and HTN (weakest predictor). GFR<60 was associated with 89% higher risk for IHE [adjusted odds ratio (95%CI): 1.89(1.69-2.11); P<.001]. Moderate-to-severe CHF increased the risk of IHE by 88% [aOR(95%CI): 1.88(1.38-2.56); P<.001]. Female gender was associated with 28% higher odds to develop IHE [aOR (95%CI): 1.28(1.13-1.46); <.001]. Each one centimeter increase in aneurysm diameter increased IHE risk by 15% [aOR(95%CI): 1.15(1.10-1.22); P<.001]. Area under the curve was 72.5%. Based on the MLR, a nomogram was constructed demonstrating a score for each predictor of IHE. A summation of the predictor scores is the total patient score (range: 1.7-30.2); for example, a patient with a score of 3 will have a 1% probability of IHE, whereas a patient with a score of 9 will have a 30% probability of IHE (Figure 2).
CONCLUSIONS: This study provides insights about the potential risk factors for postoperative complications following EVAR. We have introduced a risk calculator tool to assist surgeons in determining individual patients’ risk of developing IHE. The risks and benefits of intervention need to be discussed and weighed beforehand for patients at higher risk for IHE post-EVAR.
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