Ann Lab Med.  2020 Mar;40(2):131-141. 10.3343/alm.2020.40.2.131.

Urinary Biomarkers may Complement the Cleveland Score for Prediction of Adverse Kidney Events After Cardiac Surgery: A Pilot Study

Affiliations
  • 1Faculty of Medicine, Otto-von-Guericke University Magdeburg, Magdeburg, Germany. Christian.Albert@Diaverum.com
  • 2Diaverum Renal Services, MVZ Potsdam, Potsdam, Germany.
  • 3Department of Nephrology and Endocrinology, Klinikum Ernst von Bergmann, Potsdam, Germany.
  • 4Institute for Biometrics and Medical Informatics, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
  • 5School of Medicine, University of Melbourne, Melbourne, Australia.
  • 6Institute of Laboratory Medicine, Hospital Dessau, Dessau, Germany.
  • 7Intrinsic LifeSciences, La Jolla, CA, USA.
  • 8Department of Internal Medicine, University Clinic for Cardiology and Angiology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
  • 9Department of Cardiology, Immanuel Diakonie Bernau, Heart Center Brandenburg, Brandenburg Medical School Theodor Fontane (MHB), Germany. Anja.Haase-Fielitz@med.ovgu.de
  • 10Institute of Social Medicine and Health Economics, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.

Abstract

BACKGROUND
The ability of urinary biomarkers to complement established clinical risk prediction models for postoperative adverse kidney events is unclear. We assessed the effect of urinary biomarkers linked to suspected pathogenesis of cardiac surgery-induced acute kidney injury (AKI) on the performance of the Cleveland Score, a risk assessment model for postoperative adverse kidney events.
METHODS
This pilot study included 100 patients who underwent open-heart surgery. We determined improvements to the Cleveland Score when adding urinary biomarkers measured using clinical laboratory platforms (neutrophil gelatinase-associated lipocalin [NGAL], interleukin-6) and those in the preclinical stage (hepcidin-25, midkine, alpha-1 microglobulin), all sampled immediately post-surgery. The primary endpoint was major adverse kidney events (MAKE), and the secondary endpoint was AKI. We performed ROC curve analysis, assessed baseline model performance (odds ratios [OR], 95% CI), and carried out statistical reclassification analyses to assess model improvement.
RESULTS
NGAL (OR [95% CI] per 20 concentration-units wherever applicable): (1.07 [1.01-1.14]), Interleukin-6 (1.51 [1.01-2.26]), midkine (1.01 [1.00-1.02]), 1-hepcidin-25 (1.08 [1.00-1.17]), and NGAL/hepcidin-ratio (2.91 [1.30-6.49]) were independent predictors of MAKE and AKI (1.38 [1.03-1.85], 1.08 [1.01-1.15], 1.01 [1.00-1.02], 1.09 [1.01-1.18], and 3.45 [1.54-7.72]). Category-free net reclassification improvement identified interleukin-6 as a model-improving biomarker for MAKE and NGAL for AKI. However, only NGAL/hepcidin-25 improved model performance for event- and event-free patients for MAKE and AKI.
CONCLUSIONS
NGAL and interleukin-6 measured immediately post cardiac surgery may complement the Cleveland Score. The combination of biomarkers with hepcidin-25 may further improve diagnostic discrimination.

Keyword

Acute kidney injury; Cleveland Score; Major adverse kidney events; Cardiac surgery; Hepcidin; Interleukin-6; Midkine; Neutrophil gelatinase-associated lipocalin; Reclassification analysis

MeSH Terms

Acute Kidney Injury
Biomarkers*
Complement System Proteins*
Discrimination (Psychology)
Hepcidins
Humans
Interleukin-6
Kidney*
Lipocalins
Pilot Projects*
Risk Assessment
ROC Curve
Thoracic Surgery*
Biomarkers
Complement System Proteins
Interleukin-6
Lipocalins
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