• Yeonhee Lee, Jiwon Park, Myoung-Jin Jang, Hong Ran Moon, Dong Ki Kim, Kook-Hwan Oh, Kwon Wook Joo, Chun Soo Lim, Yon Su Kim, Ki Young Na, and Seung Seok Han.
• Department of Internal Medicine, Seoul National University College of Medicine.
• Medicine (Baltimore). 2019 May 1; 98 (21): e15789e15789.

AbstractBecause end-stage renal disease (ESRD) increases the risks of morbidity and mortality, early detection and prevention of ESRD is a critical issue in clinical practice. However, no ESRD-prediction models have been developed or validated in patients undergoing coronary artery bypass grafting (CABG).This is a retrospective multicenter cohort study, recruited between January 2004 and December 2015. A cohort of 3089 patients undergoing CABG in two tertiary referral centers was analyzed to derive a risk-prediction model. The model was developed using Cox proportional hazard analyses, and its performance was assessed using C-statistics. The model was externally validated in an independent cohort of 279 patients.During the median follow-up of 6 years (maximum 13 years), ESRD occurred in 60 patients (2.0%). Through stepwise selection multivariate analyses, the following three variables were finally included in the ESRD-prediction model: postoperative Acute kidney injury, underlying Chronic kidney disease, and the number of antiHypertensive drugs (ACHE score). This model showed good performance in predicting ESRD with the following C-statistics: 0.89 (95% confidence interval [CI] 0.84-0.94) in the development cohort and 0.82 (95% CI 0.60-1.00) in the external validation cohort.The present ESRD-prediction model may be applicable to patients undergoing CABG, with the advantage of simplicity and preciseness.

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