Predictors of in-hospital adverse events after endovascular aortic aneurysm repair

Abstract

BackgroundEndovascular aneurysm repair (EVAR) offered outstanding survival benefit but at the expense of cost, periodic radiographic monitoring, and higher reinterventions rates. Perioperative complications, although rare, can occur after EVAR, contributing to longer hospitalization, higher cost, and significant comorbidity and mortality. Therefore, the aim of this study was to identify the predictors of in-hospital events (IHEs) after elective EVAR. MethodsThe Vascular Quality Initiative database was explored from 2003 to 2017. Patients who had converted to open repair were excluded. IHEs were defined as any in-hospital myocardial infarction, dysrhythmia, congestive heart failure (CHF), stroke, pneumonia, respiratory failure, renal failure, lower extremity ischemia, bowel ischemia, or reoperation. Stepwise backward selection based on the Akaike information criterion statistic was implemented to select the predictors of IHE from the multivariable logistic regression models. Bootstrapping was performed with 1000 replications to internally validate the model and to obtain bias-corrected estimates. Receiver operating characteristic curves (area under the curve [AUC]) and Hosmer-Lemeshow tests were used to assess the discrimination and calibration of the models. ResultsA total of 28,240 patients with full information about IHEs were included. Any IHE took place in 2365 (8.4%) patients. Patients who had an IHE were slightly older (mean age ± standard deviation, 75.6 ± 8.1 years vs 73.3 ± 8.5 years; P < .001]. A higher proportion of women had an IHE (25.6% vs 17.9%; P < .001). Comorbid conditions were more prevalent in patients who developed an IHE (chronic kidney disease, 49.1% vs 33.2%; coronary artery disease, 34.3% vs 29.0%; moderate to severe CHF, 3.9% vs 1.4%; chronic obstructive pulmonary disease, 42.5% vs 31.9%; hypertension, 87.0% vs 83.1%; and diabetes, 18.0% vs 16.1%; all P ≤ .015). An IHE was associated with high in-hospital (5.6% vs 0.03%) and 30-day mortality (6.3% vs 0.3%; both P < .001) and worse 3-year survival beyond the perioperative period (81.1% [79.3%-82.9%] vs 91.1% [90.7%-91.5%]; P < .001). Two models were constructed, one from preoperative factors and the second from preoperative and intraoperative factors. The selected predictors of IHEs were female sex, moderate or severe CHF, chronic kidney disease, coronary artery disease, chronic obstructive pulmonary disease, hypertension, and aneurysm diameter. Intraoperative factors were contrast material volume, operative time, and packed red blood cell transfusion. Nomograms were constructed from the final models. AUC significantly improved after adding intraoperative factors (AUC [95% confidence interval], 0.71 [0.70-0.73] vs 0.65 [0.64-0.66]; P < .001]. ConclusionsIn-hospital adverse events can complicate the perioperative course of EVAR and increase the risk of operative and long-term mortality. Predicting IHEs and identifying their risk factors can potentially mitigate their development in patients at high risk. Predicting IHE risk can have tremendous prognostic value and help disposition planning. This study introduces an internally validated tool to enable vascular surgeons to identify patients' chance of having an IHE.