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WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants

PURPOSE: To determine the efficacy of the online monitoring tool, WINROP (https://winrop.com/) in detecting sight-threatening type 1 retinopathy of prematurity (ROP) in Indian preterm infants. METHODS: Birth weight, gestational age, and weekly weight measurements of seventy preterm infants (<32 w...

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Autores principales: Sanghi, Gaurav, Narang, Anil, Narula, Sunny, Dogra, Mangat R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778542/
https://www.ncbi.nlm.nih.gov/pubmed/29283134
http://dx.doi.org/10.4103/ijo.IJO_486_17
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author Sanghi, Gaurav
Narang, Anil
Narula, Sunny
Dogra, Mangat R
author_facet Sanghi, Gaurav
Narang, Anil
Narula, Sunny
Dogra, Mangat R
author_sort Sanghi, Gaurav
collection PubMed
description PURPOSE: To determine the efficacy of the online monitoring tool, WINROP (https://winrop.com/) in detecting sight-threatening type 1 retinopathy of prematurity (ROP) in Indian preterm infants. METHODS: Birth weight, gestational age, and weekly weight measurements of seventy preterm infants (<32 weeks gestation) born between June 2014 and August 2016 were entered into WINROP algorithm. Based on weekly weight gain, WINROP algorithm signaled an alarm to indicate that the infant is at risk for sight-threatening Type 1 ROP. ROP screening was done according to standard guidelines. The negative and positive predictive values were calculated using the sensitivity, specificity, and prevalence of ROP type 1 for the study group. 95% confidence interval (CI) was calculated. RESULTS: Of the seventy infants enrolled in the study, 31 (44.28%) developed Type 1 ROP. WINROP alarm was signaled in 74.28% (52/70) of all infants and 90.32% (28/31) of infants treated for Type 1 ROP. The specificity was 38.46% (15/39). The positive predictive value was 53.84% (95% CI: 39.59–67.53) and negative predictive value was 83.3% (95% CI: 57.73–95.59). CONCLUSION: This is the first study from India using a weight gain-based algorithm for prediction of ROP. Overall sensitivity of WINROP algorithm in detecting Type 1 ROP was 90.32%. The overall specificity was 38.46%. Population-specific tweaking of algorithm may improve the result and practical utility for ophthalmologists and neonatologists.
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spelling pubmed-57785422018-02-02 WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants Sanghi, Gaurav Narang, Anil Narula, Sunny Dogra, Mangat R Indian J Ophthalmol Original Article PURPOSE: To determine the efficacy of the online monitoring tool, WINROP (https://winrop.com/) in detecting sight-threatening type 1 retinopathy of prematurity (ROP) in Indian preterm infants. METHODS: Birth weight, gestational age, and weekly weight measurements of seventy preterm infants (<32 weeks gestation) born between June 2014 and August 2016 were entered into WINROP algorithm. Based on weekly weight gain, WINROP algorithm signaled an alarm to indicate that the infant is at risk for sight-threatening Type 1 ROP. ROP screening was done according to standard guidelines. The negative and positive predictive values were calculated using the sensitivity, specificity, and prevalence of ROP type 1 for the study group. 95% confidence interval (CI) was calculated. RESULTS: Of the seventy infants enrolled in the study, 31 (44.28%) developed Type 1 ROP. WINROP alarm was signaled in 74.28% (52/70) of all infants and 90.32% (28/31) of infants treated for Type 1 ROP. The specificity was 38.46% (15/39). The positive predictive value was 53.84% (95% CI: 39.59–67.53) and negative predictive value was 83.3% (95% CI: 57.73–95.59). CONCLUSION: This is the first study from India using a weight gain-based algorithm for prediction of ROP. Overall sensitivity of WINROP algorithm in detecting Type 1 ROP was 90.32%. The overall specificity was 38.46%. Population-specific tweaking of algorithm may improve the result and practical utility for ophthalmologists and neonatologists. Medknow Publications & Media Pvt Ltd 2018-01 /pmc/articles/PMC5778542/ /pubmed/29283134 http://dx.doi.org/10.4103/ijo.IJO_486_17 Text en Copyright: © 2017 Indian Journal of Ophthalmology http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Sanghi, Gaurav
Narang, Anil
Narula, Sunny
Dogra, Mangat R
WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants
title WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants
title_full WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants
title_fullStr WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants
title_full_unstemmed WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants
title_short WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants
title_sort winrop algorithm for prediction of sight threatening retinopathy of prematurity: initial experience in indian preterm infants
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778542/
https://www.ncbi.nlm.nih.gov/pubmed/29283134
http://dx.doi.org/10.4103/ijo.IJO_486_17
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