July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
The Colorado Retinopathy of Prematurity Algorithm in a High Risk Population
Author Affiliations & Notes
  • Sneha Padidam
    Ophthalmology, Kresge Eye Institute/Wayne State University, Detroit, Michigan, United States
  • Marie Burke
    Ophthalmology, Kresge Eye Institute/Wayne State University, Detroit, Michigan, United States
  • Kim Le
    Ophthalmology, Henry Ford Hospital, Detroit, Michigan, United States
  • Jennifer Cao
    Ophthalmology, UT Southwestern, Dallas , Texas, United States
  • Xihui Lin
    Ophthalmology, Kresge Eye Institute/Wayne State University, Detroit, Michigan, United States
  • Footnotes
    Commercial Relationships   Sneha Padidam, None; Marie Burke, None; Kim Le, None; Jennifer Cao, None; Xihui Lin, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 2787. doi:
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      Sneha Padidam, Marie Burke, Kim Le, Jennifer Cao, Xihui Lin; The Colorado Retinopathy of Prematurity Algorithm in a High Risk Population. Invest. Ophthalmol. Vis. Sci. 2018;59(9):2787.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Current screening guidelines for retinopathy of prematurity (ROP) recommend screening premature infants with birth weight less than 1500 grams, gestational age less than 30 weeks or an unstable clinical course with a high risk of ROP. This screening practice has a high sensitivity but less than 10% of screened infants require treatment. The Colorado ROP model (CO-ROP) aims to minimize the amount of unnecessary examinations; however, a 2016 study found a 92.7% sensitivity and only identified 27 out of 29 infants with type I ROP. The purpose of this study is to validate the CO-ROP algorithm in an underserved high risk population.

Methods : This is a retrospective cohort study of all neonates screened for retinopathy of prematurity using national screening guidelines at an inner city Detroit hospital from 2014 to 2016. Data collection included gestational age, birth weight, weight at 1 month of age (defined as 28 days of life), presence or absence of sepsis, ROP severity and, if applicable, treatment received. ROP was graded using the International Classification of ROP criteria. The CO-ROP algorithm was applied to patients: age ≤ 30 weeks, birth weight ≤ 1500 grams and net weight gain ≤ 650 grams in the first 28 days. The CO-ROP model was evaluated by calculating sensitivities and specificities for detection of Type I and overall ROP.

Results : The overall incidence of retinopathy of prematurity was 58.0%, and, of these patients, 58.3% required laser ablation. The CO-ROP algorithm decreased screening load by 22.6%. The CO-ROP algorithm had a sensitivity of 94.4% in detecting any ROP and 100.0% sensitivity in detecting Type 1 and Type 2 ROP. No patients with treatment-requiring ROP were missed by the CO-ROP algorithm.

Conclusions : In a cohort with a high prevalence of treatment-requiring retinopathy of prematurity, the CO-ROP screening algorithm was able to significantly reduce the number of infants screened for ROP and did not miss any patients with severe ROP. The 100% sensitivity observed in our study re-affirmed CO-ROP as a valid screening algorithm even in a high-risk population.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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