Literature DB >> 21031541

Neutrophil gelatinase--associated lipocalin predicts acute kidney injury in patients undergoing liver transplantation.

Andrew J Portal1, Mark J W McPhail, Matthew Bruce, Iona Coltart, Andrew Slack, Roy Sherwood, Nigel D Heaton, Debbie Shawcross, Julia A Wendon, Michael A Heneghan.   

Abstract

Postoperative acute kidney injury (AKI) increases morbidity and mortality after liver transplantation (LT). Novel methods of assessing AKI including cystatin C (CyC) and neutrophil gelatinase-associated lipocalin (NGAL) have been identified as potential markers of AKI. We compare the ability of standard renal markers (serum creatinine [sCr], estimated glomerular filtration rate [eGFR] and intensive therapy unit organ failure scores with CyC and NGAL to predict AKI within the first 48 hours after LT. 95 patients (median age 50 [interquartile range = 41-59], 60% male) underwent LT (25% with acute liver failure). AKI was defined according to the Acute Kidney Injury Network criteria. Severe AKI was classified as ≥stage 2. NGAL (urine [u] and plasma [p]) and CyC concentrations taken immediately after transplantation on admission to the Liver Intensive Care Unit were compared with standard markers of renal function. Predictive ability was assessed using the area under the curve generated by receiver operator characteristic analysis (AUROC) and logistic regression. Day 0 sCr, uNGAL, pNGAL, CyC, and eGFR predicted AKI as did SOFA (Sequential Organ Failure Assessment) and APACHE II (Acute Physiology and Chronic Health Evaluation II) scores. APACHE II and pNGAL were the most powerful predictors of severe AKI (APACHE II AUROC = 0.87 [0.77-0.97], P < 0.001; pNGAL AUROC = 0.87 [0.77-0.92], P < 0.001). Using multivariate logistic regression, APACHE II (odds ratio 1.64/point [95% confidence interval = 1.22-2.21, P = 0.001] and pNGAL [odds ratio = 1.01/ng/mL [95% confidence interval = 1.00-1.02], P = 0.002) retained independent significance. A "renal risk score" using APACHE II > 13 and pNGAL > 258 ng/mL was calculated with a score of ≥1 having a 100% sensitivity and 76% specificity for severe AKI. In conclusion, a combination of NGAL and APACHE II predicts AKI with high sensitivity and specificity after LT.
© 2010 AASLD.

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Year:  2010        PMID: 21031541     DOI: 10.1002/lt.22158

Source DB:  PubMed          Journal:  Liver Transpl        ISSN: 1527-6465            Impact factor:   5.799


  27 in total

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Review 2.  Difficulties in diagnosing acute kidney injury post liver transplantation using serum creatinine based diagnostic criteria.

Authors:  Banwari Agarwal; Andrew Davenport
Journal:  World J Hepatol       Date:  2014-10-27

3.  Urinary biomarkers and progression of AKI in patients with cirrhosis.

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Journal:  Clin J Am Soc Nephrol       Date:  2014-09-02       Impact factor: 8.237

4.  Incidence and risk factors for early renal dysfunction after liver transplantation.

Authors:  Patricia Wiesen; Paul B Massion; Jean Joris; Olivier Detry; Pierre Damas
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5.  Difficulties in assessing renal function in patients with cirrhosis: potential impact on patient treatment.

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Review 6.  The multifaceted roles of neutrophil gelatinase associated lipocalin (NGAL) in inflammation and cancer.

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Journal:  Biochim Biophys Acta       Date:  2012-03-31

7.  Is neutrophil gelatinase associated lipocalin useful in hepatitis C virus infection?

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Journal:  World J Hepatol       Date:  2016-07-08

8.  Neutrophil gelatinase-associated lipocalin and liver-type fatty acid-binding protein as biomarkers for acute kidney injury after organ transplantation.

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Journal:  J Anesth       Date:  2014-09-10       Impact factor: 2.078

9.  Discovery and Validation of a Biomarker Model (PRESERVE) Predictive of Renal Outcomes After Liver Transplantation.

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Journal:  Hepatology       Date:  2020-01-28       Impact factor: 17.425

10.  Urinary neutrophil gelatinase-associated lipocalin predicts mortality and identifies acute kidney injury in cirrhosis.

Authors:  Elizabeth C Verna; Robert S Brown; Erica Farrand; Elsa M Pichardo; Catherine S Forster; David A Sola-Del Valle; Sarah H Adkins; Meghan E Sise; Juan A Oliver; Jai Radhakrishnan; Jonathan M Barasch; Thomas L Nickolas
Journal:  Dig Dis Sci       Date:  2012-05-06       Impact factor: 3.199

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