title: Discrimination of GutCheck(NEC): a clinical risk index for necrotizing enterocolitis.
abstract: OBJECTIVE
  Better measures are needed to identify infants at risk for developing necrotizing enterocolitis (NEC) and facilitate communication about risk across transitions. Although NEC is multi-factorial, quantification of composite risk for NEC in an individual infant is not clearly defined. The objective of this study was to describe the derivation, validation and calibration testing of a novel clinical NEC risk index, GutCheck(NEC). Individual risk factors were weighted to assess composite odds of developing NEC. GutCheck(NEC) is designed to improve communication about NEC risk and coordination of care among clinicians across an infant's clinical course.
  
  
  METHODS
  On the basis of a synthesis of research evidence about NEC risk and an e-Delphi study including 35 neonatal experts, we identified NEC risk factors believed by the experts to be most relevant for a NEC risk index, then applied a logistic model building process to derive and validate GutCheck(NEC). De-identified data from the Pediatrix BabySteps Clinical Data Warehouse (discharge date 2007 to 2011) were split into three samples for derivation, validation and calibration. By comparing infants with medical NEC, surgical NEC and those who died to infants without NEC, we derived the logistic model using the un-matched derivation set. Discrimination was then tested in a case-control matched validation set and an un-matched calibration set using receiver operating characteristic curves.
  
  
  RESULTS
  Sampled from a cohort of 58 820 infants, the randomly selected derivation set (n=35 013) revealed nine independent risk factors (gestational age, history of packed red blood cell transfusion, unit NEC rate, late-onset sepsis, multiple infections, hypotension treated with inotropic medications, Black or Hispanic race, outborn status and metabolic acidosis) and two risk reducers (human milk feeding on both days 7 and 14 of life, and probiotics). Unit NEC rate carried the most weight in the summed score. Validation using a 2:1 matched case-control sample (n=360) demonstrated fair to good discrimination. In the calibration set (n=23 447), GutCheck(NEC) scores (range 0 to 58) discriminated those infants who developed surgical NEC (area under the curve (AUC)=0.84, 95% confidence interval (CI) 0.82 to 0.84) and NEC leading to death (AUC=0.83, 95% CI 0.81 to 0.85), more accurately than medical NEC (AUC= 0.72, 95% CI 0.70 to 0.74).
  
  
  CONCLUSIONS
  GutCheck(NEC) represents weighted composite risk for NEC and discriminated infants who developed NEC from those who did not with very good accuracy. We speculate that targeting modifiable NEC risk factors could reduce national NEC prevalence.
authors.affiliation: The University of Arizona College of Nursing, Tucson, AZ, USA.
authors.forename: S M
authors.initials: SM
authors.lastname: Gephart
authors.affiliation: The Center for Research, Education and Quality, Pediatrix Medical Group, Sunrise, FL, USA.
authors.forename: A R
authors.initials: AR
authors.lastname: Spitzer
authors.affiliation: The University of Arizona College of Nursing, Tucson, AZ, USA.
authors.forename: J A
authors.initials: JA
authors.lastname: Effken
authors.affiliation: The Center for Research, Education and Quality, Pediatrix Medical Group, Sunrise, FL, USA.
authors.forename: E
authors.initials: E
authors.lastname: Dodd
authors.affiliation: Steele Children's Research Center, The University of Arizona, Tucson, AZ, USA.
authors.forename: M
authors.initials: M
authors.lastname: Halpern
authors.affiliation: 1] Connecticut Children's Medical Center, Hartford, CT, USA [2] The University of Connecticut School of Nursing, Hartford, CT, USA.
authors.forename: J M
authors.initials: JM
authors.lastname: McGrath
mesh_terms: D016022:Case-Control Studies; D003937:Diagnosis, Differential; D020345:Enterocolitis, Necrotizing / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature; D016015:Logistic Models; D008297:Male; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors