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Urinary Neutrophil Gelatinase-Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study.

Publication ,  Journal Article
Katz-Greenberg, G; Malinchoc, M; Broyles, DL; Oxman, D; Hamrahian, SM; Maarouf, OH
Published in: Kidney360
September 29, 2022

BACKGROUND: Acute kidney injury (AKI) is most commonly caused by tubular injury and is associated with a wide variety of critical illnesses. It is well known that urinary biomarkers can lead to the early identification of AKI. However, the ability of urinary biomarkers to distinguish between different types of critical illness has been less studied. METHODS: In this prospective cohort study, urinary neutrophil gelatinase-associated lipocalin (uNGAL) was measured in 107 patients consecutively admitted to the ICUs in our tertiary medical center. uNGAL samples were collected within 3-6 hours of admission to an ICU and measured by ELISA. All data were analyzed using R statistical software, and univariate analysis was used to determine the correlations of uNGAL levels with AKI stage, admission diagnoses, and ICU course. RESULTS: uNGAL level increased by a mean of 24-fold (SD 10-59) in ICU patients with AKI and demonstrated a significant correlation with the different AKI stages. uNGAL predicted the need for RRT, with values increased by more than 15-fold (P<0.05) in patients needing RRT, and remained a useful tool to predict AKI in ICU patients with a urinary tract infection. uNGAL level was correlated with certain ICU admitting diagnoses whereby uNGAL levels were lower in ICU patients with cardiogenic shock compared with other admission diagnoses (β=-1.92, P<0.05). CONCLUSIONS: uNGAL can be used as an early predictor of AKI and its severity in patients admitted to the ICU, including the need for RRT. uNGAL may also help in distinguishing patients with cardiogenic shock from those with other critical illnesses and identifying those at risk for poor outcomes irrespective of the presence of AKI.

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Published In

Kidney360

DOI

EISSN

2641-7650

Publication Date

September 29, 2022

Volume

3

Issue

9

Start / End Page

1502 / 1510

Location

United States

Related Subject Headings

  • Shock, Cardiogenic
  • Proto-Oncogene Proteins
  • Prospective Studies
  • Lipocalins
  • Lipocalin-2
  • Intensive Care Units
  • Humans
  • Critical Illness
  • Biomarkers
  • Acute-Phase Proteins
 

Citation

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MLA
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Katz-Greenberg, G., Malinchoc, M., Broyles, D. L., Oxman, D., Hamrahian, S. M., & Maarouf, O. H. (2022). Urinary Neutrophil Gelatinase-Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study. Kidney360, 3(9), 1502–1510. https://doi.org/10.34067/KID.0001492022
Katz-Greenberg, Goni, Michael Malinchoc, Dennis L. Broyles, David Oxman, Seyed M. Hamrahian, and Omar H. Maarouf. “Urinary Neutrophil Gelatinase-Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study.Kidney360 3, no. 9 (September 29, 2022): 1502–10. https://doi.org/10.34067/KID.0001492022.
Katz-Greenberg G, Malinchoc M, Broyles DL, Oxman D, Hamrahian SM, Maarouf OH. Urinary Neutrophil Gelatinase-Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study. Kidney360. 2022 Sep 29;3(9):1502–10.
Katz-Greenberg, Goni, et al. “Urinary Neutrophil Gelatinase-Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study.Kidney360, vol. 3, no. 9, Sept. 2022, pp. 1502–10. Pubmed, doi:10.34067/KID.0001492022.
Katz-Greenberg G, Malinchoc M, Broyles DL, Oxman D, Hamrahian SM, Maarouf OH. Urinary Neutrophil Gelatinase-Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study. Kidney360. 2022 Sep 29;3(9):1502–1510.

Published In

Kidney360

DOI

EISSN

2641-7650

Publication Date

September 29, 2022

Volume

3

Issue

9

Start / End Page

1502 / 1510

Location

United States

Related Subject Headings

  • Shock, Cardiogenic
  • Proto-Oncogene Proteins
  • Prospective Studies
  • Lipocalins
  • Lipocalin-2
  • Intensive Care Units
  • Humans
  • Critical Illness
  • Biomarkers
  • Acute-Phase Proteins