Austin Health

Title
Neutrophil Gelatinase-Associated Lipocalin Measured on Clinical Laboratory Platforms for the Prediction of Acute Kidney Injury and the Associated Need for Dialysis Therapy: A Systematic Review and Meta-analysis.
Publication Date
2020-07-15
Author(s)
Albert, Christian
Zapf, Antonia
Haase, Michael
Röver, Christian
Pickering, John W
Albert, Annemarie
Bellomo, Rinaldo
Breidthardt, Tobias
Camou, Fabrice
Chen, Zhongquing
Chocron, Sidney
Cruz, Dinna
de Geus, Hilde Rh
Devarajan, Prasad
Di Somma, Salvatore
Doi, Kent
Endre, Zoltan H
Garcia-Alvarez, Mercedes
Hjortrup, Peter B
Hur, Mina
Karaolanis, Georgios
Kavalci, Cemil
Kim, Hanah
Lentini, Paolo
Liebetrau, Christoph
Lipcsey, Miklós
Mårtensson, Johan
Müller, Christian
Nanas, Serafim
Nickolas, Thomas L
Pipili, Chrysoula
Ronco, Claudio
Rosa-Diez, Guillermo J
Ralib, Azrina
Soto, Karina
Braun-Dullaeus, Rüdiger C
Heinz, Judith
Haase-Fielitz, Anja
Subject
NGAL
acute kidney injury
cut-off value
meta-analysis
neutrophil gelatinase-associated lipocalin
plasma NGAL
renal replacement therapy
renal risk assessment
urine NGAL
Type of document
Journal Article
DOI
10.1053/j.ajkd.2020.05.015
Abstract
The usefulness of measures of neutrophil gelatinase-associated lipocalin in urine or plasma (u/pNGAL) obtained on clinical laboratory platforms for predicting acute kidney injury (AKI) and severe AKI requiring kidney dialysis (AKI-D) has not been fully evaluated. We sought to quantitatively summarize published data to evaluate the value of urinary and plasma NGAL for prediction. Literature-based meta-analysis and individual-study-data meta-analysis of diagnostic studies following PRISMA-IPD guidelines. Studies of adults investigating AKI, severe AKI, and AKI-D in the setting of cardiac surgery, intensive care, or emergency department care using either urine or plasma NGAL measured on clinical laboratory platforms. PubMed, Web of Science, Cochrane Library, Scopus and congress abstracts ever published through February 2020 reporting diagnostic test studies of NGAL measured on clinical laboratory platforms to predict AKI. Individual-study-data meta-analysis was accomplished by providing authors data specifications tailored to their studies and requesting standardized patient-level data analysis. Individual-study-data meta-analysis utilized a bivariate time-to-event model for interval-censored data from which discriminative ability (area under the receiver operating characteristic curve (AUC)) was characterized. NGAL cutoff concentrations at 95% sensitivity, 95% specificity, as well as optimal sensitivity and specificity were also estimated. Models incorporated as confounders clinical setting and use versus non-use of urine output as a criterion for AKI. A literature-based meta-analysis was also performed for all published studies including those studies for which the authors were unable to provide individual study data analyses. We included 52 observational studies involving 13,040 patients. We analyzed 30 datasets for the individual-study-data meta-analysis with 837 AKI events, 304 severe AKI events, and 103 severe AKI-D events for analyses of urine NGAL and 705 AKI events, 271 severe AKI events, and 178 AKI-D events for analyses of plasma NGAL. Discriminative performance was similar in individual-study-data meta-analysis and literature-based meta-analysis. Individual-study-data meta-analysis AUCs for uNGAL were 0.75 (95% CI 0.73-0.76) and 0.80 (0.79-0.81) for severe AKI and AKI-D, respectively; for pNGAL, the corresponding values were 0.80 (0.79-0.81) and 0.86 (0.84-0.86). Cut-off-concentrations at 95% specificity for uNGAL were >580 ng/mL with 27% sensitivity for severe AKI and >589 ng/mL with 24% sensitivity for AKI-D. Corresponding cut-offs for pNGAL were >364 ng/mL with 44% sensitivity and >546 ng/mL with 26% sensitivity, respectively. Practice variability on initiation of acute dialysis. Imperfect harmonization of data across studies. Urinary and plasma NGAL concentrations may identify patients at high risk for AKI in clinical research and practice. The reported cut-off concentrations in this study require prospective evaluation.
Link
Citation
American Journal of Kidney Diseases 2020; online first: 15 July
Jornal Title
American Journal of Kidney Diseases

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