Validation and Feasibility of the Postnatal Growth and Retinopathy of Prematurity Retinal Screening Criteria at a

Barbara Johnson1, Abhishek Makkar1, Rachel Sessler1

  • 1Department of Pediatrics, Neonatal Perinatal Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.

Insights

The G-ROP algorithm accurately predicts retinopathy of prematurity (ROP) in preterm infants, identifying all treatment-warranted cases. This approach can safely reduce screenings by 50% and hospital costs.

Area of Science:

  • Ophthalmology
  • Neonatology
  • Health Economics

Background:

  • Standardized screening for retinopathy of prematurity (ROP) in preterm infants often lacks sensitivity.
  • The Postnatal Growth and Retinopathy of Prematurity (G-ROP) algorithm shows promise for improved ROP prediction using weight gain.

Purpose of the Study:

  • To validate the G-ROP algorithm's sensitivity for ROP detection in infants born after 28 weeks' gestation in a US tertiary care setting.
  • To assess the potential cost savings from reduced ROP examinations using the G-ROP criteria.

Main Methods:

  • Retrospective analysis of retinal screening data from infants born >28 weeks' gestation (2014-2019).
  • Post-hoc application of G-ROP criteria to evaluate sensitivity and specificity for Type 1 and Type 2 ROP.
  • Estimation of cost savings based on billing codes and reduced examination frequency.

Main Results:

  • G-ROP criteria demonstrated 100% sensitivity for Type 1 ROP and 87.6% for Type 2 ROP.
  • Implementing G-ROP could reduce infant screenings by 50%, with a projected 49% cost saving.
  • All infants requiring treatment in the second tier were successfully identified.

Conclusions:

  • The G-ROP criteria are feasible for real-world application and can safely screen for ROP.
  • While all Type 1 ROP cases were detected, some Type 2 cases were missed.
  • Adoption of G-ROP guidelines offers significant potential for hospital cost savings and reduced unnecessary examinations.
Abstract

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