Predicting Mortality or Intestinal Failure in Infants with Surgical Necrotizing Enterocolitis

Darshna Bhatt*, Curtis Travers, Ravi M. Patel, Julia Shinnick, Kelly Arps, Sarah Keene, Mehul V. Raval

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Objective To compare existing outcome prediction models and create a novel model to predict death or intestinal failure (IF) in infants with surgical necrotizing enterocolitis (NEC). Study design A retrospective, observational cohort study conducted in a 2-campus health system in Atlanta, Georgia, from September 2009 to May 2015. Participants included all infants ≤37 weeks of gestation with surgical NEC. Logistic regression was used to model the probability of death or IF, as a composite outcome, using preoperative variables defined by specifications from 3 existing prediction models: American College of Surgeons National Surgical Quality Improvement Program Pediatric, Score for Neonatal Acute Physiology Perinatal Extension, and Vermont Oxford Risk Adjustment Tool. A novel preoperative hybrid prediction model was also derived and validated against a patient cohort from a separate campus. Results Among 147 patients with surgical NEC, discrimination in predicting death or IF was greatest with American College of Surgeons National Surgical Quality Improvement Program Pediatric (area under the receiver operating characteristic curve [AUC], 0.84; 95% CI, 0.77-0.91) when compared with the Score for Neonatal Acute Physiology Perinatal Extension II (AUC, 0.60; 95% CI, 0.48-0.72) and Vermont Oxford Risk Adjustment Tool (AUC, 0.74; 95% CI, 0.65-0.83). A hybrid model was developed using 4 preoperative variables: the 1-minute Apgar score, inotrope use, mean blood pressure, and sepsis. The hybrid model AUC was 0.85 (95% CI, 0.78-0.92) in the derivation cohort and 0.77 (95% CI, 0.66-0.86) in the validation cohort. Conclusions Preoperative prediction of death or IF among infants with surgical NEC is possible using existing prediction tools and, to a greater extent, using a newly proposed 4-variable hybrid model.

Original languageEnglish (US)
Pages (from-to)22-27.e3
JournalJournal of Pediatrics
Volume191
DOIs
StatePublished - Dec 2017

Keywords

  • AUC, Area Under the Receiver Operating Curve
  • Infection
  • NSQIP-P, The American College of Surgeons’ National Surgical Quality Improvement Program - Pediatric
  • Neonatal
  • SNAPPE-II, Score for Neonatal Acute Physiology Perinatal Extension* Version II
  • Vermont Oxford Network Risk Adjusted Model

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health

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