Urinary Neutrophil Gelatinase-Associated Lipocalin Measured on Admission to the Intensive Care Unit Accurately Discriminates between Sustained and Transient Acute Kidney Injury in Adult Critically ill Patients

Hilde R H de Geus*, Jessica G Woo, Yu Wang, Prasad Devarajan, Michiel G Betjes, Jos L M L le Noble, Jan Bakker

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

BACKGROUND: First we aimed to evaluate the ability of neutrophil gelatinase-associated lipocalin (NGAL) and cystatin-C (CyC) in plasma and urine to discriminate between sustained, transient and absent acute kidney injury (AKI), and second to evaluate their predictive performance for sustained AKI in adult intensive care unit (ICU) patients.

METHODS: A prospective cohort study of 700 patients was studied. Sample collection was performed over 8 time points starting on admission.

RESULTS: After exclusion 510 patients remained for the analysis. All biomarkers showed significant differentiation between sustained and no AKI at all time points (p ≤ 0.0002) except for urine CyC (uCyC) on admission (p = 0.06). Urine NGAL (uNGAL) was the only biomarker significantly differentiating sustained from transient AKI on ICU admission (p = 0.02). Individually, uNGAL performed better than the other biomarkers (area under the curves, AUC = 0.80, 95% confidence interval, CI = 0.72-0.88) for the prediction of sustained AKI. The combination with plasma NGAL (pNGAL) showed a nonsignificant improvement (AUC = 0.83, 95% CI = 0.75-0.91). The combination of individual markers with a model of clinical characteristics (MDRD eGFR, HCO3- and sepsis) did not improve its performance significantly. However, the integrated discrimination improvement showed significant improvement when uNGAL was added (p = 0.04).

CONCLUSIONS: uNGAL measured on ICU admission differentiates patients with sustained AKI from transient or no-AKI patients. Combining biomarkers such as pNGAL, uNGAL and plasma CyC with clinical characteristics adds some value to the predictive model.

Original languageEnglish
Pages (from-to)9-23
Number of pages15
JournalNephron Extra
Volume1
Issue number1
DOIs
Publication statusPublished - Jan 2011

Bibliographical note

© 2011 S. Karger AG, Basel

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