The association of albumin-corrected anion gap and acute kidney injury in heart failure patients: a competing risk model analysis.

Background: The combination of heart failure (HF) and acute kidney injury (AKI) increases the mortality of patients. It is critical to identify HF patients who may have a high risk for AKI. Albumin-corrected anion gap (ACAG) is a new indicator, but there are no studies on ACAG and the risk of AKI in HF patients.

Methods: Data for HF patients was obtained from the MIMIC-IV database. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were employed to evaluate the clinical value of ACAG in predicting AKI risk. Logistic regression analysis and restricted cubic spline (RCS) curve were conducted to explore the relationship between ACAG and AKI. A competing risk model was developed to further investigate the relationship between ACAG on AKI.

Results: The study analyzed 5,972 HF patients, with 49.82% (2886/5972) suffering from AKI. The prediction performance of ACAG on AKI was good (AUC:0.656). Continuous ACAG was associated with AKI after adjusting for various significant variables (Model 1: OR = 1.094, 95%CI: 1.078-1.110; Model 2: OR = 1.150, 95%CI: 1.133-1.166; Model 3: OR = 1.035, 95%CI. 1.017-1.054). All High ACAG groups showed a higher risk of AKI (all P < 0.001). ACAG was also linked to in-hospital mortality (P < 0.001). The competing risks model revealed that high ACAG was still a risk factor for AKI when in-hospital mortality served as a competing risk event (P < 0.001).

Conclusion: High ACAG was associated with the risk of AKI in HF patients. Clinicians can risk-stratify HF patients by combining ACAG levels.