Prediction of cardiac surgery-associated acute kidney injury using Cleveland and Mehta scores

Abstract

Objective To detect the clinical accuracy of two models for the prediction of cardiac surgery-associated acute kidney injury (AKI) and severe AKI that need renal replacement therapy according to Cleveland and Mehta scores and using Kidney Disease Improving Global Outcomes (KDIGO) definitions for AKI. Patients and methods In total, 742 patients who underwent cardiac surgery in the Department of Cardiac Surgery NHI of Egypt, between January 2016 and December 2018, were enrolled in this research. We evaluate the prediction for cardiac surgery-associated AKI using Cleveland and Mehta scores. We also evaluate the effect of hemofiltration during cardiopulmonary bypass as a preventive measure for postoperative AKI in cardiac surgery. Results Depending on KDIGO AKI definition, the incidence of AKI and renal replacement therapy was 35.7% (265/742) and 1.1% (8/742), respectively. The mortality of AKI and renal replacement therapy was 6.4% (17/265) and 62.5% (6/8), respectively, while the total mortality was 3.1% (23/742). For the prediction of renal replacement therapy–AKI, the detection power of Cleveland and Mehta scores was not good. The use of hemofiltration decreases the incidence of developing postoperative acute renal failure requiring replacement therapy as predicted by Cleveland and Mehta scores from 1.7 to 1.3% and 1.4 to 1.2%, respectively. Conclusion In a single-center study, depending upon valve surgery dominant and according to KDIGO AKI definition, the predictive power of the two models, Cleveland score and Mehta score, was not accurate enough. The use of hemofiltration decreases the incidence of developing severe renal failure after cardiac surgery.

Keywords

• acute kidney injury
• cardiac surgery
• mehta score