Abstract

IntroductionTranscatheter aortic valve replacement (TAVR) has been established as a standard of care for patients with severe aortic stenosis. We aim to study the predictors of acute kidney injury (AKI) after TAVR from a contemporary analysis using the National Inpatient Sample (NIS) database.MethodsWe performed a national analysis using the NIS database to evaluate predictors of acute kidney injury (AKI) after TAVR. Our study period was from 2015 to 2018, and we identified TAVR patients in all procedure fields. Patients aged less than 18 years were excluded from the study.ResultsWe report data of 173,760 TAVR patients, of which 20,045 (11.5%) had AKI and 153,715 (88.4%) did not. There were three principal findings of our study. First, mortality was higher in patients with AKI compared to patients who did not have AKI (8% vs. 0.8%; p<0.01). Second, patients with chronic kidney disease, weight loss, liver disease, congestive heart failure, cerebrovascular disease, chronic obstructive pulmonary disease, metastatic cancer, and peripheral vascular disease had higher adjusted odds of AKI. Third, length of stay and cost of stay were significantly higher in patients who had AKI during the index admission. ConclusionPatients with AKI had higher in-hospital mortality. We also report that at baseline, chronic kidney disease, weight loss, liver disease, congestive heart failure, cerebrovascular disease, chronic obstructive pulmonary disease, metastatic cancer, and peripheral vascular disease were important predictors of AKI in patients after TAVR. Length of stay and cost of stay were higher with AKI, which result in higher burden on the health care system due to increased resource utilization.

Highlights

  • Transcatheter aortic valve replacement (TAVR) has been established as a standard of care for patients with severe aortic stenosis

  • We aim to study the predictors of acute kidney injury (AKI) after TAVR from a contemporary analysis using the National Inpatient Sample (NIS) database

  • We developed a binary logistic model using entry method including demographic factors such as age, sex, race, median income, hospital location, baseline co-morbidities, obesity, weight loss, metastatic cancer, lymphoma, solid organ tumor, alcohol use, coagulopathy, hypothyroidism, chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CVA), congestive heart failure (CHF), coronary artery disease (CAD), diabetes mellitus, hypertension, liver disease, chronic kidney disease (CKD), and peripheral vascular disease (PVD)

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Summary

Objectives

We aim to study the predictors of acute kidney injury (AKI) after TAVR from a contemporary analysis using the National Inpatient Sample (NIS) database. The aim of this study was to identify important predictors of AKI, mortality rate, and resource utilization after TAVR from a U.S national database

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