title: Biomarker Enhanced Risk Prediction for Adverse Outcomes in Critically Ill Patients Receiving RRT.
abstract: OBJECTIVE
  Higher plasma concentrations of inflammatory and apoptosis markers in critically ill patients receiving RRT are associated with RRT dependence and death. This study objective was to examine whether plasma inflammatory (IL-6, -8, -10, and -18; macrophage migration inhibitory factor) and apoptosis (death receptor-5, tumor necrosis factor receptor I and II) biomarkers augment risk prediction of renal recovery and mortality compared with clinical models.
  
  
  METHODS
  The Biologic Markers of Recovery for the Kidney study (n=817) was a prospective, nested, observational cohort study conducted as an ancillary to the Veterans Affairs/National Institutes of Health Acute renal failure Trial Network study, a randomized trial of intensive versus less intensive RRT in critically ill patients with AKI conducted between November 2003 and July 2007 at 27 Veterans Affairs- and university-affiliated centers. Primary outcomes of interest were renal recovery and mortality at day 60.
  
  
  RESULTS
  A parsimonious clinical model consisting of only four variables (age, mean arterial pressure, mechanical ventilation, and bilirubin) predicted renal recovery (area under the receiver-operating characteristic curve [AUROC], 0.73; 95% confidence interval [95% CI], 0.68 to 0.78) and mortality (AUROC, 0.74; 95% CI, 0.69 to 0.78). By contrast, individual biomarkers were only modestly predictive of renal recovery (AUROC range, 0.55-0.63) and mortality (AUROC range, 0.54-0.68). Adding plasma IL-8 to a parsimonious model augmented prediction of recovery (AUROC, 0.76; 95% CI, 0.71 to 0.81; P=0.04) and mortality (AUROC, 0.78; 95% CI, 0.73 to 0.82; P<0.01) compared with the clinical model alone.
  
  
  CONCLUSIONS
  This study suggests that a simple four-variable clinical model with plasma IL-8 had predictive value for renal recovery and mortality. These findings require external validation but could easily be used by clinicians.
authors.affiliation: The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania; The CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania;
authors.forename: Francis
authors.initials: F
authors.lastname: Pike
authors.affiliation: The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania; The CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania;
authors.forename: Raghavan
authors.initials: R
authors.lastname: Murugan
authors.affiliation: The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania; The CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania;
authors.forename: Christopher
authors.initials: C
authors.lastname: Keener
authors.affiliation: The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania; Renal Section, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania;
authors.forename: Paul M
authors.initials: PM
authors.lastname: Palevsky
authors.affiliation: Division of Renal Diseases, Washington University, St. Louis, Missouri;
authors.forename: Anitha
authors.initials: A
authors.lastname: Vijayan
authors.affiliation: The CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Division of Nephrology, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico; and.
authors.forename: Mark
authors.initials: M
authors.lastname: Unruh
authors.affiliation: Division of Renal Diseases and Hypertension, University of Texas Medical School at Houston, Houston, Texas.
authors.forename: Kevin
authors.initials: K
authors.lastname: Finkel
authors.affiliation: The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania; The CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania;
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Wen
authors.affiliation: The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania; The CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; kellumja@ccm.upmc.edu.
authors.forename: John A
authors.initials: JA
authors.lastname: Kellum
mesh_terms: D000367:Age Factors; D051017:Apoptosis Regulatory Proteins / Q000097:blood*; D019540:Area Under Curve; D062186:Arterial Pressure; D001663:Bilirubin / Q000097:blood; D015415:Biomarkers / Q000097:blood; D016638:Critical Illness; D006801:Humans; D018836:Inflammation Mediators / Q000097:blood*; D016209:Interleukin-8 / Q000097:blood; D007668:Kidney / Q000503:physiopathology; D007674:Kidney Diseases / Q000097:blood* / Q000175:diagnosis / Q000401:mortality / Q000503:physiopathology / Q000628:therapy*; D008954:Models, Biological; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D020127:Recovery of Function; D017582:Renal Replacement Therapy / Q000009:adverse effects / Q000401:mortality; D012121:Respiration, Artificial; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States; D014493:United States Department of Veterans Affairs
chemical_list: D051017:Apoptosis Regulatory Proteins; D015415:Biomarkers; C508606:CXCL8 protein, human; D018836:Inflammation Mediators; D016209:Interleukin-8; D001663:Bilirubin
keywords: apoptosis; dialysis; mortality