• Hector R Wong, Natalie Z Cvijanovich, Nick Anas, Geoffrey L Allen, Neal J Thomas, Michael T Bigham, Scott L Weiss, Julie Fitzgerald, Paul A Checchia, Keith Meyer, Thomas P Shanley, Michael Quasney, Mark Hall, Rainer Gedeit, Robert J Freishtat, Jeffrey Nowak, Shekhar S Raj, Shira Gertz, Emily Dawson, Kelli Howard, Kelli Harmon, Patrick Lahni, Erin Frank, Kimberly W Hart, and Christopher J Lindsell.
• 1Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, OH. 2Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH. 3Division of Critical Care Medicine, UCSF Benioff Children's Hospital Oakland, Oakland, CA. 4Division of Critical Care Medicine, Children's Hospital of Orange County, Orange, CA. 5Division of Critical Care Medicine, Children's Mercy Hospital, Kansas City, MO. 6Division of Critical Care Medicine, Penn State Hershey Children's Hospital, Hershey, PA. 7Division of Critical Care Medicine, Akron Children's Hospital, Akron, OH. 8Division of Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA. 9Division of Critical Care Medicine, Texas Children's Hospital, Houston, TX. 10Division of Critical Care Medicine, Miami Children's Hospital, Miami, FL. 11Division of Critical Care Medicine, CS Mott Children's Hospital at the University of Michigan, Ann Arbor, MI. 12Division of Critical Care Medicine, Nationwide Children's Hospital, Columbus, OH. 13Division of Critical Care Medicine, Children's Hospital of Wisconsin, Milwaukee, WI. 14Division of Critical Care Medicine, Children's National Medical Center, Washington, DC. 15Division of Critical Care Medicine, Children's Hospital and Clinics of Minnesota, Minneapolis, MN. 16Division of Critical Care Medicine, Riley Hospital for Children, Indianapolis, IN. 17Division of Critical Care Medicine, Hackensack University Medical Center, Joseph M. Sanzari Children's Hospital, Hackensack, NJ. 18Division of Critical Care Medicine, The University of Chicago Comer Children's Hospital, Chicago, IL. 19Department of Emergency Medicine, University of Cincinnati College of Medicine, Cincinnati, OH.
• Crit. Care Med. 2015 Aug 1;43(8):1646-53.

ObjectiveThe development of acute kidney injury in patients with sepsis is associated with worse outcomes. Identifying those at risk for septic acute kidney injury could help to inform clinical decision making. We derived and tested a multibiomarker-based model to estimate the risk of septic acute kidney injury in children with septic shock.DesignCandidate serum protein septic acute kidney injury biomarkers were identified from previous transcriptomic studies. Model derivation involved measuring these biomarkers in serum samples from 241 subjects with septic shock obtained during the first 24 hours of admission and then using a Classification and Regression Tree approach to estimate the probability of septic acute kidney injury 3 days after the onset of septic shock, defined as at least two-fold increase from baseline serum creatinine. The model was then tested in a separate cohort of 200 subjects.SettingMultiple PICUs in the United States.InterventionsNone other than standard care.Measurements And Main ResultsThe decision tree included a first-level decision node based on day 1 septic acute kidney injury status and five subsequent biomarker-based decision nodes. The area under the curve for the tree was 0.95 (CI95, 0.91-0.99), with a sensitivity of 93% and a specificity of 88%. The tree was superior to day 1 septic acute kidney injury status alone for estimating day 3 septic acute kidney injury risk. In the test cohort, the tree had an area under the curve of 0.83 (0.72-0.95), with a sensitivity of 85% and a specificity of 77% and was also superior to day 1 septic acute kidney injury status alone for estimating day 3 septic acute kidney injury risk.ConclusionsWe have derived and tested a model to estimate the risk of septic acute kidney injury on day 3 of septic shock using a novel panel of biomarkers. The model had very good performance in a test cohort and has test characteristics supporting clinical utility and further prospective evaluation.

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