Urinary biomarkers predict progression and adverse outcomes of acute kidney injury in critical illness

Background Acute kidney injury (AKI) is common in hospitalized patients and is associated with high morbidity and mortality. The Dublin Acute Biomarker Group Evaluation study is a prospective cohort study of critically ill patients (n = 717). We hypothesized that novel urinary biomarkers would predict progression of AKI and associated outcomes. Methods The primary (diagnostic) analysis assessed the ability of biomarkers levels at the time of early Stage 1 or 2 AKI to predict progression to higher AKI stage, renal replacement therapy (RRT) or death within 7 days of intensive care unit admission. In the secondary (prognostic) analysis, we investigated the association between biomarker levels and RRT or death within 30 days. Results In total, 186 patients had an AKI within 7 days of admission. In the primary (diagnostic) analysis, 8 of the 14 biomarkers were independently associated with progression. The best predictors were cystatin C [adjusted odds ratio (aOR) 5.2; 95% confidence interval (CI) 1.3-23.6], interleukin-18 (IL-18; aOR 5.1; 95% CI 1.8-15.7), albumin (aOR 4.9; 95% CI 1.5-18.3) and neutrophil gelatinase-associated lipocalin (NGAL; aOR 4.6; 95% CI 1.4-17.9). Receiver-operating characteristics and net reclassification index analyses similarly demonstrated improved prediction by these biomarkers. In the secondary (prognostic) analysis of Stages 1-3 AKI cases, IL-18, NGAL, albumin and monocyte chemotactic protein-1 were also independently associated with RRT or death within 30 days. Conclusions Among 14 novel urinary biomarkers assessed, cystatin C, IL-18, albumin and NGAL were the best predictors of Stages 1-2 AKI progression. These biomarkers, after further validation, may have utility to inform diagnostic and prognostic assessment and guide management of AKI in critically ill patients.

Automated summary

This study evaluated 14 urinary biomarkers and found that cystatin C, IL-18, albumin, and NGAL were the best predictors of AKI progression. These biomarkers may be useful for diagnostic and prognostic assessment of AKI.