Abstract
Background
Patients with congestive heart failure (CHF) are vulnerable to contrast-induced acute kidney injury (CI-AKI), but few prediction models are currently available.
Objectives
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 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% (n=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.
Figure 1
Funding Acknowledgement
Type of funding source: None
A clinical, proteomics, and artificial intelligence-driven model to predict acute kidney injury in patients undergoing coronary angiography
