Literature DB >> 35368827

Kidney Biomarkers and Major Adverse Kidney Events in Critically Ill Patients.

Alexander H Flannery1, Katherine Bosler2,3, Victor M Ortiz-Soriano4, Fabiola Gianella3, Victor Prado3, Joshua Lambert5, Robert D Toto6, Orson W Moe3,6, Javier A Neyra3,4.   

Abstract

Background: Several biomarkers of AKI have been examined for their ability to predict AKI before serum creatinine. Few studies have focused on using kidney biomarkers to better predict major adverse kidney events (MAKE), an increasingly used composite outcome in critical care nephrology research.
Methods: Single-center prospective study collecting blood and urine samples from critically ill patients with AKI Kidney Disease Improving Global Outcomes stage 2 or above, and matched controls from a single, tertiary care intensive care unit (ICU). Samples were collected at 24-48 hours after AKI diagnosis (patients) or ICU admission (controls), 5-7 days later, and 4-6 weeks after discharge for patients with AKI. The primary outcome of interest was MAKE at hospital discharge (MAKE-DC), consisting of the composite end point of death, RRT dependence, or a decrease in estimated glomerular filtration to <75% of baseline.
Results: Serum/urinary neutrophil gelatinase-associated lipocalin (NGAL), serum/urinary cystatin C, and urinary kidney injury molecule-1 early in the AKI or ICU course were all significantly higher in patients with MAKE-DC compared with those not experiencing MAKE-DC. Additionally, serum/urinary NGAL and serum cystatin C measurements at the first time point remained significantly associated with MAKE events at 3, 6, and 12 months. Serum cystatin C, and to a lesser extent serum NGAL, significantly improved upon a logistic regression clinical prediction model of MAKE-DC (AUROC 0.94 and 0.87 versus 0.83; P=0.001 and P=0.02, respectively). Patients without MAKE-DC experienced a greater decline in serum NGAL from first to second measurement than those patients experiencing MAKE-DC. Conclusions: Early measures of kidney biomarkers in patients who are critically ill are associated with MAKE-DC. This relationship appears to be greatest with serum NGAL and cystatin C, which display additive utility to a clinical prediction model. Trending serum NGAL may also have utility in predicting MAKE-DC.
Copyright © 2021 by the American Society of Nephrology.

Entities:  

Keywords:  acute kidney injury; acute kidney injury and ICU nephrology; biomarker; critical care; critical illness; intensive care; major adverse kidney event; outcome

Mesh:

Substances:

Year:  2020        PMID: 35368827      PMCID: PMC8785730          DOI: 10.34067/KID.0003552020

Source DB:  PubMed          Journal:  Kidney360        ISSN: 2641-7650


  17 in total

1.  Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery.

Authors:  Chirag R Parikh; Steven G Coca; Heather Thiessen-Philbrook; Michael G Shlipak; Jay L Koyner; Zhu Wang; Charles L Edelstein; Prasad Devarajan; Uptal D Patel; Michael Zappitelli; Catherine D Krawczeski; Cary S Passik; Madhav Swaminathan; Amit X Garg
Journal:  J Am Soc Nephrol       Date:  2011-08-11       Impact factor: 10.121

Review 2.  Clinical trial endpoints in acute kidney injury.

Authors:  Frederic T Billings; Andrew D Shaw
Journal:  Nephron Clin Pract       Date:  2014-09-24

3.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

Authors:  M E Charlson; P Pompei; K L Ales; C R MacKenzie
Journal:  J Chronic Dis       Date:  1987

4.  Combining functional and tubular damage biomarkers improves diagnostic precision for acute kidney injury after cardiac surgery.

Authors:  Rajit K Basu; Hector R Wong; Catherine D Krawczeski; Derek S Wheeler; Peter B Manning; Lakhmir S Chawla; Prasad Devarajan; Stuart L Goldstein
Journal:  J Am Coll Cardiol       Date:  2014-12-30       Impact factor: 24.094

5.  Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

Authors:  Andrew C McKown; Li Wang; Jonathan P Wanderer; Jesse Ehrenfeld; Todd W Rice; Gordon R Bernard; Matthew W Semler
Journal:  J Med Syst       Date:  2017-08-31       Impact factor: 4.460

6.  A new equation to estimate glomerular filtration rate.

Authors:  Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh
Journal:  Ann Intern Med       Date:  2009-05-05       Impact factor: 25.391

7.  Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery.

Authors:  John M Arthur; Elizabeth G Hill; Joseph L Alge; Evelyn C Lewis; Benjamin A Neely; Michael G Janech; James A Tumlin; Lakhmir S Chawla; Andrew D Shaw
Journal:  Kidney Int       Date:  2013-09-04       Impact factor: 10.612

8.  Acute kidney injury subphenotypes based on creatinine trajectory identifies patients at increased risk of death.

Authors:  Pavan K Bhatraju; Paramita Mukherjee; Cassianne Robinson-Cohen; Grant E O'Keefe; Angela J Frank; Jason D Christie; Nuala J Meyer; Kathleen D Liu; Michael A Matthay; Carolyn S Calfee; David C Christiani; Jonathan Himmelfarb; Mark M Wurfel
Journal:  Crit Care       Date:  2016-11-17       Impact factor: 9.097

9.  Kidney Tubular Damage and Functional Biomarkers in Acute Kidney Injury Following Cardiac Surgery.

Authors:  Javier A Neyra; Ming-Chang Hu; Abu Minhajuddin; Geoffrey E Nelson; Syed A Ahsan; Robert D Toto; Michael E Jessen; Orson W Moe; Amanda A Fox
Journal:  Kidney Int Rep       Date:  2019-05-18

10.  Development of biomarker combinations for postoperative acute kidney injury via Bayesian model selection in a multicenter cohort study.

Authors:  Allison Meisner; Kathleen F Kerr; Heather Thiessen-Philbrook; Francis Perry Wilson; Amit X Garg; Michael G Shlipak; Peter Kavsak; Richard P Whitlock; Steven G Coca; Chirag R Parikh
Journal:  Biomark Res       Date:  2018-01-12
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