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

Jennifer H. Cao, Brandie D. Wagner, Ashlee Cerda, Emily A. McCourt, Alan Palestine, Robert W. Enzenauer, Rebecca S. Braverman, Ryan K. Wong, Irena Tsui, Charlotte Gore, Shira L. Robbins, Michael A. Puente, Levi Kauffman, Lingkun Kong, David G. Morrison, Anne M. Lynch

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)220-225
Number of pages6
JournalJournal of AAPOS
Volume20
Issue number3
DOIs
StatePublished - Jun 1 2016

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Retinopathy of Prematurity
Validation Studies
Carbon Monoxide
Guidelines
Sensitivity and Specificity

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Ophthalmology

Cite this

Cao, J. H., Wagner, B. D., Cerda, A., McCourt, E. A., Palestine, A., Enzenauer, R. W., ... Lynch, A. M. (2016). Colorado retinopathy of prematurity model: A multi-institutional validation study. Journal of AAPOS, 20(3), 220-225. https://doi.org/10.1016/j.jaapos.2016.01.017

Colorado retinopathy of prematurity model : A multi-institutional validation study. / Cao, Jennifer H.; Wagner, Brandie D.; Cerda, Ashlee; McCourt, Emily A.; Palestine, Alan; Enzenauer, Robert W.; Braverman, Rebecca S.; Wong, Ryan K.; Tsui, Irena; Gore, Charlotte; Robbins, Shira L.; Puente, Michael A.; Kauffman, Levi; Kong, Lingkun; Morrison, David G.; Lynch, Anne M.

In: Journal of AAPOS, Vol. 20, No. 3, 01.06.2016, p. 220-225.

Research output: Contribution to journalArticle

Cao, JH, Wagner, BD, Cerda, A, McCourt, EA, Palestine, A, Enzenauer, RW, Braverman, RS, Wong, RK, Tsui, I, Gore, C, Robbins, SL, Puente, MA, Kauffman, L, Kong, L, Morrison, DG & Lynch, AM 2016, 'Colorado retinopathy of prematurity model: A multi-institutional validation study', Journal of AAPOS, vol. 20, no. 3, pp. 220-225. https://doi.org/10.1016/j.jaapos.2016.01.017
Cao JH, Wagner BD, Cerda A, McCourt EA, Palestine A, Enzenauer RW et al. Colorado retinopathy of prematurity model: A multi-institutional validation study. Journal of AAPOS. 2016 Jun 1;20(3):220-225. https://doi.org/10.1016/j.jaapos.2016.01.017
Cao, Jennifer H. ; Wagner, Brandie D. ; Cerda, Ashlee ; McCourt, Emily A. ; Palestine, Alan ; Enzenauer, Robert W. ; Braverman, Rebecca S. ; Wong, Ryan K. ; Tsui, Irena ; Gore, Charlotte ; Robbins, Shira L. ; Puente, Michael A. ; Kauffman, Levi ; Kong, Lingkun ; Morrison, David G. ; Lynch, Anne M. / Colorado retinopathy of prematurity model : A multi-institutional validation study. In: Journal of AAPOS. 2016 ; Vol. 20, No. 3. pp. 220-225.
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abstract = "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.",
author = "Cao, {Jennifer H.} and Wagner, {Brandie D.} and Ashlee Cerda and McCourt, {Emily A.} and Alan Palestine and Enzenauer, {Robert W.} and Braverman, {Rebecca S.} and Wong, {Ryan K.} and Irena Tsui and Charlotte Gore and Robbins, {Shira L.} and Puente, {Michael A.} and Levi Kauffman and Lingkun Kong and Morrison, {David G.} and Lynch, {Anne M.}",
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AU - Cao, Jennifer H.

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AU - Cerda, Ashlee

AU - McCourt, Emily A.

AU - Palestine, Alan

AU - Enzenauer, Robert W.

AU - Braverman, Rebecca S.

AU - Wong, Ryan K.

AU - Tsui, Irena

AU - Gore, Charlotte

AU - Robbins, Shira L.

AU - Puente, Michael A.

AU - Kauffman, Levi

AU - Kong, Lingkun

AU - Morrison, David G.

AU - Lynch, Anne M.

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N2 - 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.

AB - 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.

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