Colorado retinopathy of prematurity model: a multi-institutional validation study

J AAPOS. 2016 Jun;20(3):220-5. doi: 10.1016/j.jaapos.2016.01.017. Epub 2016 May 7.


Purpose: The Colorado retinopathy of prematurity (ROP) prediction model (CO-ROP), developed using a cohort of infants from Colorado, calls for ROP examination of infants meeting all of the following criteria: gestational age of ≤30 weeks, birth weight of ≤1500 g, and a net weight gain of ≤650 g between birth and 4 weeks of age. The purpose of this study was to perform an external validation to assess the sensitivity and specificity of the CO-ROP model in a larger cohort of babies screened for ROP from four academic institutions in the United States.

Methods: The medical records of neonates screened for ROP according current national guidelines was conducted at 4 US academic centers were retrospectively reviewed. Sensitivity, specificity, and respective 95% confidence intervals in detecting ROP using CO-ROP were calculated for type 1, type 2, and any grade of ROP.

Results: A total of 858 cases were included. The CO-ROP algorithm had a sensitivity of 98.1% (95% CI, 93.3%-99.8%) for type 1 ROP, 95.6% (95% CI 78.0-99.9%) for type 2 ROP, and 95.0% (95% CI, 93.1-97.4%) for all grades of ROP. The CO-ROP model would have reduced the total number of infants screened by 23.9% compared to current 2013 screening guidelines.

Conclusions: CO-ROP demonstrated high sensitivity in predicting ROP and would have greatly reduced the number of infants needing examination.

Publication types

  • Multicenter Study
  • Validation Study

MeSH terms

  • Algorithms
  • Birth Weight
  • Cohort Studies
  • Colorado
  • Diagnostic Techniques, Ophthalmological*
  • Female
  • Gestational Age
  • Humans
  • Infant
  • Infant, Extremely Low Birth Weight
  • Infant, Newborn
  • Infant, Very Low Birth Weight
  • Male
  • Models, Statistical
  • Neonatal Screening / methods*
  • Retinopathy of Prematurity / diagnosis*
  • Retrospective Studies
  • Risk Factors
  • Sensitivity and Specificity
  • Weight Gain