Performance of Prediction Models for Contrast-Induced Acute Kidney Injury after Transcutaneous Aortic Valve Replacement

Abstract

Background: Acute kidney injury (AKI) has shown to adversely affect outcomes in patients undergoing transcutaneous aortic valve replacement (TAVR), and its correct risk estimation may interfere in procedural planning and strategies. The aim of the study was to test and compare 6 scores in predicting AKI after TAVR.

Methods: We tested 6 scores (the contrast material limit score, volume-to-creatinine clearance ratio, ACEF, CR4EATME3AD3, Mehran model A, and Mehran model B) in a total of 559 consecutive patients included in the Brazilian TAVR registry.

Results: All scores had a poor accuracy and calibration to predict the occurrence of AKI grade 1 or 2. All scores improved the accuracy of AKI risk prediction when stratified for AKI grade 2/3 and AKI grade 3 for all scores. The CR4EATME3AD3 was the best predictor of AKI stage 2/3 (AUC: 0.62; OR: 1.12; 95% CI 1.01-1.26; p = 0.04) and AKI stage 3 (AUC: 0.64; OR: 1.16; 95% CI 1.02-1.32; p = 0.02). Mehran models A and B were both good models for AKI stage 3 (AUC: 0.63; OR: 1.10; 95% CI 1.01-1.22; p = 0.05; and AUC: 0.62; OR: 1.10; 95% CI 1.00-1.21; p = 0.05, respectively).

Conclusions: None of the current models demonstrated validity in detecting AKI when its lower grades were evaluated. CR4EATME3AD3 was the best score in predicting moderate to severe AKI after TAVR. These findings suggest that contrast-induced AKI may not be the only factor related to kidney injury after TAVR.