Development of model to predict end-stage renal disease after coronary artery bypass grafting: The ACHE score

Abstract

Because 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.