A simple risk score model for predicting contrast-induced nephropathy after coronary angiography in patients with diabetes

Background Contrast-induced nephropathy (CIN) is a common complication in patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI) and associated with poor outcome. Some previous studies have already set up models to predict CIN, but there is no model for patients with diabetes mellitus (DM) especially. Therefore, we aim to develop and validate a simple risk score for predicting the risk of CIN in patients with DM undergoing CAG/PCI. Methods A total of 1157 consecutive patients with DM undergoing CAG/PCI were randomly assigned to a development cohort ( n = 771) and a validation cohort ( n = 386). The primary endpoint was CIN, which was defined as an absolute increase in serum creatinine (SCr) by 0.5 mg/dL from the baseline within 48–72 h after contrast exposure. The independent predictors for CIN were identified by multivariate logistic regression, and the discrimination and calibration of the risk score were assessed by ROC curve and Hosmer–Lemeshow test, respectively. Results The overall incidence of CIN was 45 (3.9%). The new simple risk score (Chen score), which included four independent variables (age > 75 years, acute myocardial infarction, SCr > 1.5 mg/dL, the use of intra-aortic balloon pump), exhibited a similar discrimination and predictive ability on CIN (AUC 0.813, 0.843, 0.796, P > 0.05, respectively), mortality (AUC 0.735, 0.771, 0.826, respectively) and MACEs when being compared with the classical Mehran or ACEF risk score. Conclusion Our data suggest that the new simple risk score might be a good tool for predicting CIN in patients with DM undergoing CAG/PCI.