Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment

Jimmy S Chen1, Jamie E Anderson1, Aaron S Coyner1

  • 1Department of Ophthalmology, Oregon Health and Science University, Portland, Oregon.

Ophthalmology Science
|October 24, 2022
PubMed

Insights

Early oxygen exposure in premature infants is a risk factor for retinopathy of prematurity (ROP). Electronic health record data can predict treatment-requiring ROP (TR-ROP) and aggressive ROP (A-ROP).

Area of Science:

  • Neonatal ophthalmology
  • Neonatal intensive care
  • Medical informatics

Background:

  • Retinopathy of prematurity (ROP) is a leading cause of childhood blindness.
  • While oxygen monitoring has reduced ROP incidence, its role as a risk factor for severe forms like treatment-requiring ROP (TR-ROP) and aggressive ROP (A-ROP) remains unclear.
  • Premature infants require careful oxygen management to prevent ROP.

Purpose of the Study:

  • To evaluate early oxygen exposure as a predictive variable for developing TR-ROP and A-ROP.
  • To utilize electronic health record (EHR) data for this proof-of-concept study.
  • To assess the predictive value of oxygen exposure in infants at risk for ROP.

Main Methods:

  • Retrospective cohort study of 244 infants screened for ROP.
  • Extraction of oxygen saturation and fraction of inspired oxygen (FiO2) data from EHRs up to 31 weeks postmenstrual age (PMA).
  • Random forest models trained with gestational age (GA) and cumulative minimum FiO2 at 30 weeks PMA to predict TR-ROP; ROC analysis for A-ROP.

Main Results:

  • Random forest models using GA and cumulative minimum FiO2 showed high predictive performance for TR-ROP (AUC = 0.93 ± 0.06).
  • Models using GA alone were not significantly different (AUC = 0.92 ± 0.06).
  • Oxygen exposure alone demonstrated predictive capability (AUC = 0.80 ± 0.09), and A-ROP prediction yielded an AUC of 0.92.

Conclusions:

  • Early oxygen exposure, extractable from EHR data, is a quantifiable risk factor for TR-ROP and A-ROP.
  • EHR data can be leveraged to build risk models for diseases like ROP.
  • This approach aids in understanding complex relationships between oxygen exposure and prematurity sequelae.
Abstract