Implementation of a clinical prediction model using daily postnatal weight gain, birth weight, and gestational age to risk stratify ROP

Kortany McCauley, Anupama Chundu, Helen Song, Robin High, Donny Suh

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Purpose: To develop a simple prognostic model using postnatal weight gain, birth weight, and gestational age to identify infants at risk for developing severe retinopathy of prematurity (ROP). Methods: Medical records from two tertiary referral centers with the diagnosis code “Retinopathy of Prematurity” were evaluated. Those with a birth weight of 1,500 g or less, gestational age of 30 weeks or younger, and unstable clinical courses were included. Multivariate regression analysis was applied to transform three independent variables into a growth rate algorithm. Results: Seventeen of 191 neonates had severe ROP. Weight gain of at least 23 g/d was determined as a protective cut-off value against development of severe ROP. This value maintained 100% sensitivity with 62% specificity to ensure all neonates who require treatment would be captured. Overall, the Omaha (OMA)-ROP model calculated a 58% reduction in eye examinations within the cohort. Conclusions: Inclusion of postnatal growth rate in risk stratification will minimize the number of eye examinations performed without increasing adverse visual outcomes. The OMA-ROP model predicts neonates who gain less than 23 g/d are at higher risk for developing severe ROP. Although promising, larger cohort studies may be necessary to validate and implement new screening practices among preterm infants.

Original languageEnglish (US)
Pages (from-to)326-334
Number of pages9
JournalJournal of pediatric ophthalmology and strabismus
Volume55
Issue number5
DOIs
StatePublished - Sep 1 2018

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Ophthalmology

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