A Simple Nomogram to Predict Contrast-Induced Acute Kidney Injury in Patients with Congestive Heart Failure Undergoing Coronary Angiography

Abstract

Background. Patients with congestive heart failure (CHF) are vulnerable to contrast-induced kidney injury (CI-AKI), but few prediction models are currently available. Therefore, we aimed to establish a simple nomogram for CI-AKI risk assessment for patients with CHF undergoing coronary angiography. Methods. A total of 1876 consecutive patients with CHF (defined as New York Heart Association functional class II-IV or Killip class II-IV) were enrolled and randomly (2:1) assigned to a development cohort and a validation cohort. The endpoint was CI-AKI defined as serum creatinine elevation of ≥0.3 mg/dL or 50% from baseline within the first 48–72 hours following the procedure. Predictors for the simple nomogram were selected by multivariable logistic regression with a stepwise approach. The discriminative power was assessed using the area under the receiver operating characteristic (ROC) curve and was compared with the classic Mehran score in the validation cohort. Calibration was assessed using the Hosmer–Lemeshow test and 1000 bootstrap samples. Results. The incidence of CI-AKI was 9.06% (170) in the total sample, 8.64% (n = 109) in the development cohort, and 9.92% (n = 61) in the validation cohort ( P = 0.367 ). The simple nomogram including four predictors (age, intra-aortic balloon pump, acute myocardial infarction, and chronic kidney disease) demonstrated a similar predictive power as the Mehran score (area under the curve: 0.80 vs. 0.75, P = 0.061 ), as well as a well-fitted calibration curve. Conclusions. The present simple nomogram including four predictors is a simple and reliable tool to identify CHF patients at risk of CI-AKI, whereas further external validations are needed.

Age-Related Effect of Uric Acid on Contrast-Induced Acute Kidney Injury of Patients Undergoing Coronary Angiography

“…Multinomial multiple logistic regression analyses were performed to examine between the UA and CI-AKI adjusted for age, gender,intra-aortic balloon pump (IABP), congestive heart failure (CHF), anemia, DM, pre-SCr, contrast medium volume, AMI and PCI, which were based on the classic Mehran CIN risk score 4 and relevant literature. 11,12 Furthermore, restricted cubic spline (RCS) was used to investigate the linear tendency of the association between UA value and the risk of CI-AKI. In this method, we selected four SUA values as knots based on UA percentiles, tested the linear and non-linear associations between knots using a cubic function, and presented the smoothly integrated graph.…”

Predicting pre- and post-operative acute kidney injury in elderly patients with coronary artery disease

“…In the present research, the baseline characteristics such as age, co-existing conditions, drug combinations, routine blood tests, liver and kidney function, BNP, cardiac enzyme, and D-value were significantly different between patients with and without AKI. Previous studies have revealed consistent predictors of AKI in patients with heart disease, such as age [ 5 , 10 ], IABP [ 7 , 11 , 26 ], diuretic [ 7 , 11 ], white blood cells [ 7 , 10 ], biomarkers of cardiac damage [ 27 ], and hemoglobin [ 5 , 10 , 11 , 26 ].…”

“…The pathophysiological processes underlying contrast-associated AKI are complicated and not yet entirely elucidated. Several risk factors have been identified as contributing to the higher likelihood of AKI, including advanced age, lower baseline creatinine clearance, diabetes mellitus, advanced congestive heart failure, liver disease, pre-existing chronic kidney disease, length of the procedure, large contrast volume, and use of intra-aortic balloon pump (IABP) [ [6] , [7] , [8] , [9] , [10] , [11] , [12] ]. Certain investigations have revealed some biomarkers associated with AKI, such as serum creatinine, cystatin C, neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, and interleukin-18 [ 13 , 14 ].…”

“…Certain investigations have revealed some biomarkers associated with AKI, such as serum creatinine, cystatin C, neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, and interleukin-18 [ 13 , 14 ]. Furthermore, studies have developed various prediction models for AKI [ 7 , 10 , 11 , [15] , [16] , [17] ] and have been focusing on AKI among elderly patients undergoing CAG [ 18 ]. However, the clinical baseline characteristics reflecting AKI are not thoroughly established in the above research.…”