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The pediatric sepsis biomarker risk model

Hector R Wong12*, Shelia Salisbury2, Qiang Xiao3, Natalie Z Cvijanovich4, Mark Hall5, Geoffrey L Allen6, Neal J Thomas7, Robert J Freishtat8, Nick Anas9, Keith Meyer10, Paul A Checchia11, Richard Lin12, Thomas P Shanley13, Michael T Bigham14, Anita Sen15, Jeffrey Nowak16, Michael Quasney17, Jared W Henricksen18, Arun Chopra19, Sharon Banschbach1, Eileen Beckman1, Kelli Harmon1, Patrick Lahni1 and Christopher J Lindsell20

Author Affiliations

1 Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, OH, USA

2 Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

3 The EMD Millipore Corporation, St Charles, MO, USA

4 Children's Hospital and Research Center Oakland, Oakland, CA, USA

5 Nationwide Children's Hospital, Columbus, OH, USA

6 Children's Mercy Hospital, Kansas City, MO, USA

7 Penn State Hershey Children's Hospital, Hershey, PA, USA

8 Children's National Medical Center, Washington, DC, USA

9 Children's Hospital of Orange County, Orange, CA, USA

10 Miami Children's Hospital, Miami, FL, USA

11 Texas Children's Hospital, Houston, TX, USA

12 The Children's Hospital of Philadelphia, Philadelphia, PA, USA

13 CS Mott Children's Hospital at the University of Michigan, Ann Arbor, MI, USA

14 Akron Children's Hospital, Akron, OH, USA

15 Morgan Stanley Children's Hospital, Columbia University Medical Center, New York, NY, USA

16 Children's Hospital and Clinics of Minnesota, Minneapolis, MN, USA

17 Children's Hospital of Wisconsin, Milwaukee, WI, USA

18 Primary Children's Medical Center, Salt Lake City, UT, USA

19 St Christopher's Hospital for Children, Philadelphia, PA, USA

20 Department of Emergency Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA

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Critical Care 2012, 16:R174  doi:10.1186/cc11652

Published: 1 October 2012



The intrinsic heterogeneity of clinical septic shock is a major challenge. For clinical trials, individual patient management, and quality improvement efforts, it is unclear which patients are least likely to survive and thus benefit from alternative treatment approaches. A robust risk stratification tool would greatly aid decision-making. The objective of our study was to derive and test a multi-biomarker-based risk model to predict outcome in pediatric septic shock.


Twelve candidate serum protein stratification biomarkers were identified from previous genome-wide expression profiling. To derive the risk stratification tool, biomarkers were measured in serum samples from 220 unselected children with septic shock, obtained during the first 24 hours of admission to the intensive care unit. Classification and Regression Tree (CART) analysis was used to generate a decision tree to predict 28-day all-cause mortality based on both biomarkers and clinical variables. The derived tree was subsequently tested in an independent cohort of 135 children with septic shock.


The derived decision tree included five biomarkers. In the derivation cohort, sensitivity for mortality was 91% (95% CI 70 - 98), specificity was 86% (80 - 90), positive predictive value was 43% (29 - 58), and negative predictive value was 99% (95 - 100). When applied to the test cohort, sensitivity was 89% (64 - 98) and specificity was 64% (55 - 73). In an updated model including all 355 subjects in the combined derivation and test cohorts, sensitivity for mortality was 93% (79 - 98), specificity was 74% (69 - 79), positive predictive value was 32% (24 - 41), and negative predictive value was 99% (96 - 100). False positive subjects in the updated model had greater illness severity compared to the true negative subjects, as measured by persistence of organ failure, length of stay, and intensive care unit free days.


The pediatric sepsis biomarker risk model (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl) reliably identifies children at risk of death and greater illness severity from pediatric septic shock. PERSEVERE has the potential to substantially enhance clinical decision making, to adjust for risk in clinical trials, and to serve as a septic shock-specific quality metric.