Urine biomarkers predict acute kidney injury in newborns

Abstract

Objective: To identify urine biomarkers predictive of acute kidney injury (AKI) in infants admitted to level 2 and 3 neonatal intensive care units with birth weight >2000 g and 5-minute Apgar score ≤ 7.

Study design: A nested case-control study was performed comparing 8 candidate urine AKI biomarkers in infants with AKI (defined as a rise in serum creatinine of at least 0.3 mg/dL or a serum creatinine elevation ≥ 1.7 mg/dL persisting for 3 days) and 24 infants from the described cohort without AKI. Urine was analyzed for neutrophil gelatinase-associated lipocalin, osteopontin, cystatin C, albumin, β(2) microglobulin, epithelial growth factor, uromodulin (UMOD), and kidney injury molecule 1.

Results: Compared with the infants without AKI, those with AKI had higher levels of urine cystatin C (1123 pg/mL [95% CI, 272-4635 pg/mL] vs 90 pg/mL [95% CI, 39-205 pg/mL]; P < .004; area under the receiver operating characteristic curve [AUC] = 0.82), lower levels of UMOD (11.0 pg/mL [95% CI, 5.7-21.4 pg/mL] vs 26.2 pg/mL [95% CI, 17.4-39.4 pg/mL]; P < .03; AUC = 0.77), and lower levels of epithelial growth factor (6.7 pg/mL [95% CI, 4.0-11.3 pg/mL] vs 17.4 pg/mL [95% CI, 12.7-23.8 pg/mL; P = .003; AUC = 0.82). Although the differences were not statistically significant, levels of urine neutrophil-associated gelatinase lipocalin, kidney injury molecule 1, and osteopontin trended higher in infants with AKI.

Conclusion: Urinary biomarkers can predict AKI in neonates admitted to level 2 and 3 neonatal intensive care units.

Figure 1

Flow diagram depicting the patients consenting for the study, those excluded because of findings of congenital renal anomaly, those with AKI, and those without AKI.

Figure 2

Urine values of NGAL, UMOD, KIM-1, Cys C, OPN, B2mG, EGF, and albumin in infants with AKI (gray bars) and infants without AKI (white bars) during the first 3 days of life.

Figure 3

Biomarkers with an AUC value of 0.5 are no better than a coin flip in predicting the disease of interest. Those with an AUC value close to 1 have excellent positive predictive ability, whereas those with an AUC value close to 0 have excellent negative predictive ability. The reciprocal of a value will change a negative predictive value to a positive predictive value. This Figure shows the AUCs for Cys C, EGF, UMOD, and a combination of these 3 biomarkers. The model using all 3 biomarkers was not significantly different (AUC = 0.81) from the model with Cys C alone.