June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
ROPScore screening tool validation in a 3rd level hospital in Argentina
Author Affiliations & Notes
  • Evangelina Esposito
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Erna Knoll
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
    Ophthalmology, Hospital Maternoneonatal Ramon Carrillo, Cordoba, Cordoba, Argentina
  • Carla Guantay
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Alejandro Gonzalez-Castellanos
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Alejandra Miranda
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Maria Fernanda Barros Centeno
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Christina Mastromonaco
    Henry C Witelson Ocular Pathology Laboratory, McGill University, Quebec, Canada
  • Priscila M Viotto
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Roxana Di Fede
    Ophthalmology, Hospital Maternoneonatal Ramon Carrillo, Cordoba, Cordoba, Argentina
  • German Parisi
    PABEX, Argentina
  • Martha Gomez Flores
    Ophthalmology, Hospital Maternoneonatal Ramon Carrillo, Cordoba, Cordoba, Argentina
  • Julio A Urrets-Zavalia
    Ophthalmology, Clinica Universitaria Reina Fabiola, Universidad Catolica de Cordoba, Cordoba, Cordoba, Argentina
  • Footnotes
    Commercial Relationships   Evangelina Esposito, None; Erna Knoll, None; Carla Guantay, None; Alejandro Gonzalez-Castellanos, None; Alejandra Miranda, None; Maria Barros Centeno, None; Christina Mastromonaco, None; Priscila Viotto, None; Roxana Di Fede, None; German Parisi, PABEX Corp (I); Martha Gomez Flores, None; Julio Urrets-Zavalia, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 2177. doi:
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      Evangelina Esposito, Erna Knoll, Carla Guantay, Alejandro Gonzalez-Castellanos, Alejandra Miranda, Maria Fernanda Barros Centeno, Christina Mastromonaco, Priscila M Viotto, Roxana Di Fede, German Parisi, Martha Gomez Flores, Julio A Urrets-Zavalia; ROPScore screening tool validation in a 3rd level hospital in Argentina. Invest. Ophthalmol. Vis. Sci. 2020;61(7):2177.

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

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Abstract

Purpose : Retinopathy of prematurity (ROP) is a developmental alteration that affects normal retinal vascularization and may lead to complete bilateral blindness. ROP screening takes resources and time, and should be wide enough to avoid missed cases. Therefore, it is important to define a strategy to safely diminish the number of screened babies. ROPScore is a mathematical tool that predicts severe ROP using clinical parameters at the 6th week of life. Our aim is to evaluate if ROPScore can be useful to predict severe ROP in a population of premature babies in Argentina.

Methods : Data from the clinical records of all premature babies examined between 2012 and 2018 in the ophthalmology department of a public third level hospital in Cordoba, Argentina, were obtained. ROPScore screening was applied using a Microsoft Excel spreadsheet. The sensitivity, specificity, positive and negative predictive values of the algorithm was analyzed. Agreement between ROPScore calculations and ROPScore calculator app was assesed.

Results : Between 2012 and 2018, a total of 2894 preterm infants were examined. 411 children met the inclusion criteria, of whom 34% (n 139) presented some form of ROP and 6% (n 25) developed severe forms that required treatment. The sensitivity of the algorithm for any ROP and severe ROP was 100%. The PPV and NPV were 35.64% and 100%, respectively, for any ROP and 9.88% and 100% for severe ROP.

Conclusions : The ROPScore algorithm could identify severe cases after validation for each population, reducing the number of screened babies by 38% in babies ≤1500 gr or ≤32 weeks of gestational age.

This is a 2020 ARVO Annual Meeting abstract.

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