Literature DB >> 31175848

Urinary neutrophil gelatinase-associated lipocalin as a biomarker of acute kidney injury in sepsis patients in the emergency department.

Hee Su Park1, Jong Won Kim2, Kyeong Ryong Lee1, Dae Young Hong1, Sang O Park1, Sin Young Kim1, Jin Young Kim3, Sang Kuk Han4.   

Abstract

BACKGROUND: Plasma neutrophil gelatinase-associated lipocalin (NGAL) is a useful biomarker for predicting acute kidney injury (AKI). The purpose of this study was to evaluate the diagnostic performance of urinary NGAL in predicting AKI in sepsis patients in the emergency department.
METHODS: A total of 140 patients were enrolled. We compared serum procalcitonin and urinary NGAL concentrations between patients with local infection, sepsis, and septic shock, and between patients who did and did not develop AKI with sepsis. Receiver-operating characteristic curve analysis was used to evaluate the ability to predict AKI in sepsis patients.
RESULTS: Both serum procalcitonin and urinary NGAL concentrations were significantly higher in the sepsis and septic shock groups than in the local infection group (both p < 0.001). In sepsis patients, serum procalcitonin and urinary NGAL concentrations were higher in AKI patients than in those without AKI (p = 0.006, p < 0.001, respectively). The area under the curve for predicting of AKI was higher for a urinary NGAL of 0.820 (95% confidence interval (CI) 0.721-0.895) than for a serum procalcitonin concentration of 0.76 (95% CI 0.597-0.800).
CONCLUSION: Urinary NGAL concentration may predict AKI in patients with sepsis in the emergency department.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Neutrophil gelatinase-associated lipocalin; Procalcitonin, acute kidney injury; Sepsis

Mesh:

Substances:

Year:  2019        PMID: 31175848     DOI: 10.1016/j.cca.2019.06.005

Source DB:  PubMed          Journal:  Clin Chim Acta        ISSN: 0009-8981            Impact factor:   3.786


  6 in total

1.  Machine learning for the prediction of acute kidney injury in patients with sepsis.

Authors:  Suru Yue; Shasha Li; Xueying Huang; Jie Liu; Xuefei Hou; Yumei Zhao; Dongdong Niu; Yufeng Wang; Wenkai Tan; Jiayuan Wu
Journal:  J Transl Med       Date:  2022-05-13       Impact factor: 8.440

2.  Meta-analysis of procalcitonin as a predictor for acute kidney injury.

Authors:  Yunxia Feng; Haiyan He; Chao Jia; Zhihua Xu; Yuan Li; Dan Liao
Journal:  Medicine (Baltimore)       Date:  2021-03-12       Impact factor: 1.817

3.  The prognostic value of neutrophil gelatinase-associated lipocalin in sepsis-associated acute kidney injury: A prospective observational study.

Authors:  Radhey Shyam; Munna Lal Patel; Dhananjay Kumar; Rekha Sachan; Shyam Chand Chaudhary; K K Gupta
Journal:  Int J Crit Illn Inj Sci       Date:  2020-09-16

4.  Endothelial progenitor cells-derived exosomal microRNA-21-5p alleviates sepsis-induced acute kidney injury by inhibiting RUNX1 expression.

Authors:  Yue Zhang; Hongdong Huang; Wenhu Liu; Sha Liu; Xue Yan Wang; Zong Li Diao; Ai Hua Zhang; Wang Guo; Xue Han; Xiaoqun Dong; Oleksandr Katilov
Journal:  Cell Death Dis       Date:  2021-03-30       Impact factor: 8.469

Review 5.  Predictive Ability of Procalcitonin for Acute Kidney Injury: A Narrative Review Focusing on the Interference of Infection.

Authors:  Wei-Chih Kan; Ya-Ting Huang; Vin-Cent Wu; Chih-Chung Shiao
Journal:  Int J Mol Sci       Date:  2021-06-27       Impact factor: 5.923

6.  Analysis of the diagnostic capabilities of urinary neutrophil gelatinase-associated lipocalin and serum procalcitonin for acute kidney injury at the early stage of critical care intensive care unit admission.

Authors:  Yuji Imoto; Ayano Wakasaki; Kumiko Izumida; Hiroshi Shimada; Kumiko Ohkubo; Yasumasa Kawano; Hiroyasu Ishikura; Akira Matsunaga
Journal:  J Clin Lab Anal       Date:  2021-06-08       Impact factor: 2.352

  6 in total

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