Biomarkers predict progression of acute kidney injury after cardiac surgery

Abstract

Being able to predict whether AKI will progress could improve monitoring and care, guide patient counseling, and assist with enrollment into trials of AKI treatment. Using samples from the Translational Research Investigating Biomarker Endpoints in AKI study (TRIBE-AKI), we evaluated whether kidney injury biomarkers measured at the time of first clinical diagnosis of early AKI after cardiac surgery can forecast AKI severity. Biomarkers included urinary IL-18, urinary albumin to creatinine ratio (ACR), and urinary and plasma neutrophil gelatinase-associated lipocalin (NGAL); each measurement was on the day of AKI diagnosis in 380 patients who developed at least AKI Network (AKIN) stage 1 AKI. The primary end point (progression of AKI defined by worsening AKIN stage) occurred in 45 (11.8%) patients. Using multivariable logistic regression, we determined the risk of AKI progression. After adjustment for clinical predictors, compared with biomarker values in the lowest two quintiles, the highest quintiles of three biomarkers remained associated with AKI progression: IL-18 (odds ratio=3.0, 95% confidence interval=1.3-7.3), ACR (odds ratio=3.4, 95% confidence interval=1.3-9.1), and plasma NGAL (odds ratio=7.7, 95% confidence interval=2.6-22.5). Each biomarker improved risk classification compared with the clinical model alone, with plasma NGAL performing the best (category-free net reclassification improvement of 0.69, P<0.0001). In conclusion, biomarkers measured on the day of AKI diagnosis improve risk stratification and identify patients at higher risk for progression of AKI and worse patient outcomes.

Trial registration: ClinicalTrials.gov NCT00774137.

Figures

Figure 1.

Timing of AKI after cardiac surgery. The graph displays when those patients with and without AKI progression were first diagnosed with AKI after cardiac surgery; 66% of patients developed AKI within the first 2 postoperative days.

Figure 2.

Improvements in predicted risk with the inclusion of biomarkers in the clinical model. The plots display the changes in risk stratification for (left) progressors and (right) nonprogressors with the addition of individual biomarkers urinary ACR (UACR), urine NGAL, urine IL-18, and plasma NGAL to the clinical model. The x axis for all plots is the predicted risk according to the clinical model alone, and the y axis is the clinical model plus the given biomarker. The diagonal line indicates the line of identity; for the points above this line, the predicted risk is higher in the new model, and for points below this line, the predicted risk is lower. The individual plots display the number of patients who were at increased and decreased risk of progressive AKI after the addition of a biomarker to the model. As an example, inclusion of plasma NGAL in the model led to increased predicted risk in 28 of 45 progressors (62%) and decreased predicted risk in 216 of 335 nonprogressors (66.4%). The clinical model contains age, sex, white race, CPB time>120 minutes, nonelective surgery, preoperative estimated GFR, diabetes, hypertension, intraoperative intra-aortic balloon pump, repeat cardiac surgery during the hospitalization, and percent change in postoperative serum creatinine.