Plasma endostatin may improve acute kidney injury risk prediction in critically ill patients

Background

Breakdown of renal endothelial, tubular and glomerular matrix collagen plays a major role in acute kidney injury (AKI) development. Such collagen breakdown releases endostatin into the circulation. The aim of this study was to compare the AKI predictive value of plasma endostatin with two previously suggested biomarkers of AKI, cystatin C and neutrophil gelatinase-associated lipocalin (NGAL)

Methods

We studied 93 patients without kidney disease who had a first plasma sample obtained within 48 h of ICU admission. We identified risk factors for AKI within the population and designed a predictive model. The individual ability and net contribution of endostatin, cystatin C and NGAL to predict AKI were evaluated by the area under the receiver operating characteristics curve (AUC), likelihood-ratio test, net reclassification improvement (NRI) and integrated discrimination improvement (IDI)

Results

In total, 21 (23 %) patients experienced AKI within 72 h. A three-parameter model (age, illness severity score and early oliguria) predicted AKI with an AUC of 0.759 (95 % CI 0.646–0.872). Adding endostatin to the predictive model significantly ( P  = 0.04) improved the AUC to 0.839 (95 % CI 0.752–0.925). In addition, endostatin significantly improved risk prediction using the likelihood-ratio test ( P  = 0.005), NRI analysis (0.27; P  = 0.04) and IDI analysis (0.07; P  = 0.04). In contrast, adding cystatin C or NGAL to the three-parameter model did not improve risk prediction in any of the four analyses

Conclusions

In this cohort of critically ill patients, plasma endostatin improved AKI prediction based on clinical risk factors, while cystatin C and NGAL did not.