• Alexander Lukasz, Jan Beneke, Jan Menne, Frank Vetter, Bernhard M W Schmidt, Mario Schiffer, Hermann Haller, Philipp Kümpers, and Jan T Kielstein.
• Alexander Lukasz, MD, Department of Medicine D, Division of General Internal Medicine, Nephrology, and Rheumatology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany, Tel.: +49 251 8347516, Fax: +49 251 8346979, E-mail: alexander-henrik.lukasz@ukmuenster.de.
• Thromb Haemostasis. 2014 Feb 1;111(2):365-72.

AbstractNeutrophil gelatinase-associated lipocalin (NGAL) is an increasingly used biomarker for acute kidney injury (AKI). Its utility in adult patients with AKI caused by Shiga toxin producing Escherichia coli infection (STEC)-associated haemolytic-uraemic syndrome (HUS), remains unknown. We aimed to evaluate the prognostic value of serum NGAL admission levels for the need of renal replacement therapy (RRT) in STEC-HUS patients. Baseline serum NGAL was determined by ELISA in 39 patients with STEC O104:H4 infection cared for at Hannover Medical School during the outbreak in Germany through May-July 2011. Patients with HUS had significant higher NGAL levels than healthy controls (379 [248 - 540] vs 39.0 [37.5-45] ng/ml, p < 0.0001). During clinical course, 24 patients required RRT at a median of five days after admission. NGAL admission levels were higher in patients requiring RRT (476 (344-639) ng/ml) compared to patients not requiring RRT (257 (196-426) ng/ml; p < 0.001). Unadjusted and adjusted logistic regression analyses identified NGAL as an independent predictor for need of RRT. In a combined model, a joint NGAL/AKIN classification approach improved the predictive accuracy for need of RRT over either marker alone. The combined categorical cut-off point defined by NGAL ≥ 330 ng/ml and presence of AKI (AKIN ≥ I) on admission correctly identified 20 of 24 patients requiring RRT (odds ratio 20, sensitivity 83%, specificity 80%, negative predictive value 75%, positive predictive value 87%). NGAL may serve as an adjunctive tool to improve risk prediction in patients with STEC-HUS.

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