title: Acute kidney injury prediction in cardiac surgery patients by a urinary peptide pattern: a case-control validation study.
abstract: BACKGROUND
  Acute kidney injury (AKI) is a prominent problem in hospitalized patients and associated with increased morbidity and mortality. Clinical medicine is currently hampered by the lack of accurate and early biomarkers for diagnosis of AKI and the evaluation of the severity of the disease. In 2010, we established a multivariate peptide marker pattern consisting of 20 naturally occurring urinary peptides to screen patients for early signs of renal failure. The current study now aims to evaluate if, in a different study population and potentially various AKI causes, AKI can be detected early and accurately by proteome analysis.
  
  
  METHODS
  Urine samples from 60 patients who developed AKI after cardiac surgery were analyzed by capillary electrophoresis-mass spectrometry (CE-MS). The obtained peptide profiles were screened by the AKI peptide marker panel for early signs of AKI. Accuracy of the proteomic model in this patient collective was compared to that based on urinary neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) ELISA levels. Sixty patients who did not develop AKI served as negative controls.
  
  
  RESULTS
  From the 120 patients, 110 were successfully analyzed by CE-MS (59 with AKI, 51 controls). Application of the AKI panel demonstrated an AUC in receiver operating characteristics (ROC) analysis of 0.81 (95 % confidence interval: 0.72-0.88). Compared to the proteomic model, ROC analysis revealed poorer classification accuracy of NGAL and KIM-1 with the respective AUC values being outside the statistical significant range (0.63 for NGAL and 0.57 for KIM-1).
  
  
  CONCLUSIONS
  This study gives further proof for the general applicability of our proteomic multimarker model for early and accurate prediction of AKI irrespective of its underlying disease cause.
authors.affiliation: Mosaiques Diagnostics GmbH, Hannover, Germany. metzger@mosaiques-diagnostics.com.
authors.forename: Jochen
authors.initials: J
authors.lastname: Metzger
authors.affiliation: Institute of Cardiovascular and Medical Sciences, Glasgow, UK.
authors.forename: William
authors.initials: W
authors.lastname: Mullen
authors.affiliation: Institute of Cardiovascular and Medical Sciences, Glasgow, UK.
authors.forename: Holger
authors.initials: H
authors.lastname: Husi
authors.affiliation: Institute of Cardiovascular and Medical Sciences, Glasgow, UK.
authors.forename: Angelique
authors.initials: A
authors.lastname: Stalmach
authors.affiliation: Department of Medicine and Nephrology, Rotes Kreuz Krankenhaus, Bremen, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Herget-Rosenthal
authors.affiliation: Department of Anaesthesiology, Intensive Care and Pain Medicine, Saarland University Medical Centre, Homburg-Saar, Germany.
authors.forename: Heiner V
authors.initials: HV
authors.lastname: Groesdonk
authors.affiliation: Mosaiques Diagnostics GmbH, Hannover, Germany.|Institute of Cardiovascular and Medical Sciences, Glasgow, UK.
authors.forename: Harald
authors.initials: H
authors.lastname: Mischak
authors.affiliation: Department of Internal Medicine, Nephrology and Hypertension, Saarland University Medical Centre, Homburg-Saar, Germany.|Department of Internal Medicine, Hochtaunus-Kliniken, Usingen, Germany.
authors.forename: Matthias
authors.initials: M
authors.lastname: Klingele
mesh_terms: D058186:Acute Kidney Injury / Q000175:diagnosis* / Q000401:mortality; D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000652:urine; D006348:Cardiac Surgical Procedures / Q000401:mortality; D016022:Case-Control Studies; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010455:Peptides / Q000652:urine; D011237:Predictive Value of Tests; D011446:Prospective Studies; D040901:Proteomics / Q000379:methods
chemical_list: D015415:Biomarkers; D010455:Peptides
keywords: Acute kidney injury; Cardiac surgery; Prediction; Test validation; Urinary peptide pattern