Validation of three weight gain-based algorithms as a screening tool to detect retinopathy of prematurity: A multicenter study

Purpose: Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a...

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Published in	Indian journal of ophthalmology Vol. 71; no. 6; pp. 2555 - 2560
Main Authors	Raffa, Lina, Alamri, Aliaa, Alosaimi, Amal, Alessa, Sarah, Alharbi, Suzan, Ahmedhussain, Huda, Almarzouki, Hashem, AlQurashi, Mansour
Format	Journal Article
Language	English
Published	India Wolters Kluwer - Medknow 01.06.2023 Medknow Publications and Media Pvt. Ltd Medknow Publications & Media Pvt. Ltd Wolters Kluwer Medknow Publications
Edition	2
Subjects	Algorithms Analysis Birth Weight Care and treatment co-rop Developing countries Diagnosis Gestational Age Health aspects Humans Infant Infant, Newborn Infant, Premature Infants Infants (Premature) Medical screening Medical tests Methods Neonatal Screening Neonates Neonatology Newborn babies Original Original Article Premature babies preterm Retinopathy retinopathy of prematurity Retinopathy of Prematurity - diagnosis Retinopathy of Prematurity - epidemiology Retrolental fibroplasia Retrospective Studies Risk Factors ropscore Weight Gain winrop India Saudi Arabia Colorado Georgia preterm WINROP CO-ROP retinopathy of prematurity ROPScore
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ISSN	0301-4738 1998-3689 1998-3689
DOI	10.4103/ijo.IJO_2013_22

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Abstract	Purpose: Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a developing country. Methods: This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included. Results: One hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61. Conclusion: The sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP.
AbstractList	Purpose: Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a developing country. Methods: This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included. Results: One hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61. Conclusion: The sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP. Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a developing country. This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included. One hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61. The sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP. Purpose:Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms—WINROP, ROPScore, and CO-ROP—in detecting ROP in preterm infants in a developing country.Methods:This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included.Results:One hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61.Conclusion:The sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP. Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a developing country.PurposeScreening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a developing country.This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included.MethodsThis retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included.One hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61.ResultsOne hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61.The sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP.ConclusionThe sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP. Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms--WINROP, ROPScore, and CO-ROP--in detecting ROP in preterm infants in a developing country. This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included. One hundred twenty-three neonates (31.9) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100; ROPScore, 100; and CO-ROP, 92.3. The specificity was 28 for WINROP, 1.4 for ROPScore, and 19.3 for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61. The sensitivity was at 100 for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP. Purpose: Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms--WINROP, ROPScore, and CO-ROP--in detecting ROP in preterm infants in a developing country. Methods: This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included. Results: One hundred twenty-three neonates (31.9) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100; ROPScore, 100; and CO-ROP, 92.3. The specificity was 28 for WINROP, 1.4 for ROPScore, and 19.3 for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61. Conclusion: The sensitivity was at 100 for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP. Keywords: CO-ROP, preterm, retinopathy of prematurity, ROPScore, WINROP
Audience	Professional
Author	Alamri, Aliaa Ahmedhussain, Huda Almarzouki, Hashem Alosaimi, Amal Alessa, Sarah AlQurashi, Mansour Alharbi, Suzan Raffa, Lina
AuthorAffiliation	4 Department of Obstetrics and Gynecology, King Abdulaziz Medical City, National Guard Health Affairs, Jeddah, Saudi Arabia 6 College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia 8 King Abdullah International Medical Research Center, Jeddah, Saudi Arabia 7 Department of Ophthalmology, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Jeddah, Saudi Arabia 1 Department of Ophthalmology, King Abdulaziz University, Jeddah, Saudi Arabia 2 Department of Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia 5 Department of Ophthalmology, Jeddah Eye Hospital, Jeddah, Saudi Arabia 3 Department of Pediatrics, King Abdulaziz University Hospital, Jeddah, Saudi Arabia 9 Department of Pediatrics, Neonatology Division, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Western Region, Jeddah, Saudi Arabia
AuthorAffiliation_xml	– name: 1 Department of Ophthalmology, King Abdulaziz University, Jeddah, Saudi Arabia – name: 3 Department of Pediatrics, King Abdulaziz University Hospital, Jeddah, Saudi Arabia – name: 5 Department of Ophthalmology, Jeddah Eye Hospital, Jeddah, Saudi Arabia – name: 8 King Abdullah International Medical Research Center, Jeddah, Saudi Arabia – name: 2 Department of Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia – name: 4 Department of Obstetrics and Gynecology, King Abdulaziz Medical City, National Guard Health Affairs, Jeddah, Saudi Arabia – name: 7 Department of Ophthalmology, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Jeddah, Saudi Arabia – name: 9 Department of Pediatrics, Neonatology Division, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Western Region, Jeddah, Saudi Arabia – name: 6 College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia
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Cites_doi	10.1136/bjo.2007.126508 10.1007/s13312-021-2321-4 10.1001/archophthalmol.2010.255 10.1093/biomet/26.4.404 10.1016/j.jaapos.2016.08.008 10.1136/bjophthalmol-2012-301570 10.6061/clinics/2018/e377 10.1016/j.sjopt.2016.02.006 10.1159/000351297 10.4103/ijo.IJO_486_17 10.1542/peds.2018-3061 10.1542/peds.2008-2697 10.15537/smj.2020.6.25127 10.1016/S0140-6736(13)60178-6 10.4103/jcn.jcn_171_20 10.5935/0004-2749.20190093 10.5144/0256-4947.2020.87 10.4103/meajo.MEAJO_131_18 10.1016/j.jaapos.2017.03.009 10.4103/tjo.tjo_72_20 10.1016/j.jaapos.2015.10.017 10.1001/archophthalmol.2012.215 10.1001/archopht.123.7.991 10.1001/archopht.121.12.1684 10.1001/jamanetworkopen.2021.35879 10.1016/j.jaapos.2012.09.004 10.1111/aos.13117 10.1001/jamaophthalmol.2013.566
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Snippet	Purpose: Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study... Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to... Purpose: Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study... Purpose:Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study...
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SubjectTerms	Algorithms Analysis Birth Weight Care and treatment co-rop Developing countries Diagnosis Gestational Age Health aspects Humans Infant Infant, Newborn Infant, Premature Infants Infants (Premature) Medical screening Medical tests Methods Neonatal Screening Neonates Neonatology Newborn babies Original Original Article Premature babies preterm Retinopathy retinopathy of prematurity Retinopathy of Prematurity - diagnosis Retinopathy of Prematurity - epidemiology Retrolental fibroplasia Retrospective Studies Risk Factors ropscore Weight Gain winrop
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Title	Validation of three weight gain-based algorithms as a screening tool to detect retinopathy of prematurity: A multicenter study
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