Abstract

We aimed to compare the ability of preoperative estimated glomerular filtration rate (eGFR), calculated using five different equations, to predict adverse renal outcomes after cardiovascular surgery. Cohorts of 4,125 adult patients undergoing elective cardiovascular surgery were evaluated. Preoperative eGFR was calculated using the Cockcroft-Gault, Modification of Diet in Renal Disease (MDRD) II, re-expressed MDRD II, Chronic Kidney Disease Epidemiology Collaboration, and Mayo quadratic (Mayo) equations. The primary outcome was postoperative acute kidney injury (AKI), defined by Kidney Disease: Improving Global Outcomes Definition and Staging criteria based on changes in serum creatinine concentrations within 7 days. The MDRD II and Cockcroft-Gault equations yielded the highest (88.1 ± 26.7 ml/min/1.73 m2) and lowest (79.6 ± 25.5 ml/min/1.73 m2) mean eGFR values, respectively. Multivariable analysis showed that a preoperative decrease in renal function according to all five equations was independently associated with an increased risk of postoperative AKI. The area under the receiver operating characteristics curve for predicting postoperative AKI was highest for the Mayo equation (0.713). Net improvements in reclassification and integrated discrimination were higher for the Mayo equation than for the other equations. The Mayo equation was the most accurate in predicting postoperative AKI in patients undergoing cardiovascular surgery.

Details

Title
Comparison of five glomerular filtration rate estimating equations as predictors of acute kidney injury after cardiovascular surgery
Author
Jun-Young, Jo 1 ; Seung Ah Ryu 2 ; Jong-Il, Kim 1 ; Eun-Ho, Lee 1   VIAFID ORCID Logo  ; Choi, In-Cheol 1 

 Department of Anaesthesiology and Pain Medicine, Laboratory for Perioperative Outcomes Analysis and Research, Asan Medical Centre, University of Ulsan College of Medicine, Seoul, Korea 
 Department of Anaesthesiology and Pain Medicine, Seoul Medical Centre, Seoul, Korea 
Pages
1-9
Publication year
2019
Publication date
Jul 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2266992820
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.