title: The pediatric sepsis biomarker risk model.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.forename: Hector R
authors.initials: HR
authors.lastname: Wong
authors.forename: Shelia
authors.initials: S
authors.lastname: Salisbury
authors.forename: Qiang
authors.initials: Q
authors.lastname: Xiao
authors.forename: Natalie Z
authors.initials: NZ
authors.lastname: Cvijanovich
authors.forename: Mark
authors.initials: M
authors.lastname: Hall
authors.forename: Geoffrey L
authors.initials: GL
authors.lastname: Allen
authors.forename: Neal J
authors.initials: NJ
authors.lastname: Thomas
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Freishtat
authors.forename: Nick
authors.initials: N
authors.lastname: Anas
authors.forename: Keith
authors.initials: K
authors.lastname: Meyer
authors.forename: Paul A
authors.initials: PA
authors.lastname: Checchia
authors.forename: Richard
authors.initials: R
authors.lastname: Lin
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Shanley
authors.forename: Michael T
authors.initials: MT
authors.lastname: Bigham
authors.forename: Anita
authors.initials: A
authors.lastname: Sen
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Nowak
authors.forename: Michael
authors.initials: M
authors.lastname: Quasney
authors.forename: Jared W
authors.initials: JW
authors.lastname: Henricksen
authors.forename: Arun
authors.initials: A
authors.lastname: Chopra
authors.forename: Sharon
authors.initials: S
authors.lastname: Banschbach
authors.forename: Eileen
authors.initials: E
authors.lastname: Beckman
authors.forename: Kelli
authors.initials: K
authors.lastname: Harmon
authors.forename: Patrick
authors.initials: P
authors.lastname: Lahni
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Lindsell
mesh_terms: D015415:Biomarkers / Q000097:blood; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D005260:Female; D006801:Humans; D007223:Infant; D015278:Intensive Care Units, Pediatric / Q000639:trends; D008297:Male; D008962:Models, Theoretical; D018570:Risk Assessment; D018805:Sepsis / Q000097:blood* / Q000175:diagnosis*
chemical_list: D015415:Biomarkers