ArticleBMC cardiovascular disorders2025
The association of albumin-corrected anion gap and acute kidney injury in heart failure patients: a competing risk model analysis.
Article in BMC cardiovascular disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Associations Between Albumin-Corrected Anion Gap and Mortality in Heart Failure Patients with Chronic Obstructive Pulmonary Disease: A Retrospective Cohort Study.International journal of chronic obstructive pulmonary disease · 2026Article
- Association Between Albumin-Corrected Anion Gap and Mortality in ICU Patients With Acute Heart Failure: A MIMIC-IV Cohort Study.Cardiovascular therapeutics · 2026Article
- Albumin-corrected anion gap and risk of mortality among US adults.Archives of public health = Archives belges de sante publique · 2025Article
- Association of albumin-corrected anion gap with mortality in ICU patients with heart failure and acute kidney injury: analysis of the MIMIC-IV database.European journal of medical research · 2025Article
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsData 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.
resultsThe 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).
conclusionHigh ACAG was associated with the risk of AKI in HF patients. Clinicians can risk-stratify HF patients by combining ACAG levels.
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