Predictive algorithms for early detection of retinopathy of prematurity

Purpose To evaluate sensitivity, specificity and the safest cut‐offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). Methods A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks...

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Vydáno v:	Acta ophthalmologica (Oxford, England) Ročník 95; číslo 2; s. 158 - 164
Hlavní autoři:	Piermarocchi, Stefano, Bini, Silvia, Martini, Ferdinando, Berton, Marianna, Lavini, Anna, Gusson, Elena, Marchini, Giorgio, Padovani, Ezio Maria, Macor, Sara, Pignatto, Silvia, Lanzetta, Paolo, Cattarossi, Luigi, Baraldi, Eugenio, Lago, Paola
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England Wiley Subscription Services, Inc 01.03.2017
Témata:	Algorithms Babies CHOP ROP Early Diagnosis Female Gestational Age Humans Incidence Infant, Newborn Italy - epidemiology Male Neonatal Screening - methods Ophthalmology Ophthalmoscopy - methods Retina Retina - diagnostic imaging retinopathy of prematurity Retinopathy of Prematurity - diagnosis Retinopathy of Prematurity - epidemiology Retrospective Studies Risk Factors ROC Curve RORScore WINROP WINROP algorithms CHOP ROP retinopathy of prematurity RORScore
ISSN:	1755-375X, 1755-3768
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Abstract	Purpose To evaluate sensitivity, specificity and the safest cut‐offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). Methods A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks and/or birthweight (BW) ≤ 1500 g, and additional unstable cases, were included. No‐ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Results Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no‐ROP subjects (GA: 26.7 ± 2.2 and 30.2 ± 1.9, respectively, p < 0.0001; BW: 839.8 ± 287.0 and 1288.1 ± 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90–0.96, and 95% CI, 0.89–0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77–0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP, ROPScore and CHOP ROP, respectively. Conclusion ROPScore and CHOP ROP showed 100% sensitivity to identify sight‐threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies.
AbstractList	Purpose To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). Methods A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) less than or equal to 30 weeks and/or birthweight (BW) less than or equal to 1500 g, and additional unstable cases, were included. No-ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Results Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no-ROP subjects (GA: 26.7 plus or minus 2.2 and 30.2 plus or minus 1.9, respectively, p < 0.0001; BW: 839.8 plus or minus 287.0 and 1288.1 plus or minus 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90-0.96, and 95% CI, 0.89-0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77-0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP, ROPScore and CHOP ROP, respectively. Conclusion ROPScore and CHOP ROP showed 100% sensitivity to identify sight-threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies. Purpose To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP,ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). Methods A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks and/or birthweight (BW) ≤ 1500 g, and additional unstable cases, were included. No-ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA,BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Results Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no-ROP subjects (GA: 26.7 ± 2.2 and 30.2 ± 1.9, respectively, p < 0.0001; BW: 839.8 ± 287.0 and 1288.1 ± 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90-0.96, and 95% CI, 0.89-0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77-0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP,ROPScore and CHOP ROP, respectively. Conclusion ROPScore and CHOP ROP showed 100% sensitivity to identify sight-threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies. PURPOSETo evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP).METHODSA retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks and/or birthweight (BW) ≤ 1500 g, and additional unstable cases, were included. No-ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies).RESULTSRetinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no-ROP subjects (GA: 26.7 ± 2.2 and 30.2 ± 1.9, respectively, p < 0.0001; BW: 839.8 ± 287.0 and 1288.1 ± 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90-0.96, and 95% CI, 0.89-0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77-0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP, ROPScore and CHOP ROP, respectively.CONCLUSIONROPScore and CHOP ROP showed 100% sensitivity to identify sight-threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies. Purpose To evaluate sensitivity, specificity and the safest cut‐offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). Methods A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks and/or birthweight (BW) ≤ 1500 g, and additional unstable cases, were included. No‐ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Results Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no‐ROP subjects (GA: 26.7 ± 2.2 and 30.2 ± 1.9, respectively, p < 0.0001; BW: 839.8 ± 287.0 and 1288.1 ± 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90–0.96, and 95% CI, 0.89–0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77–0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP, ROPScore and CHOP ROP, respectively. Conclusion ROPScore and CHOP ROP showed 100% sensitivity to identify sight‐threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies. To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks and/or birthweight (BW) ≤ 1500 g, and additional unstable cases, were included. No-ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no-ROP subjects (GA: 26.7 ± 2.2 and 30.2 ± 1.9, respectively, p < 0.0001; BW: 839.8 ± 287.0 and 1288.1 ± 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90-0.96, and 95% CI, 0.89-0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77-0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP, ROPScore and CHOP ROP, respectively. ROPScore and CHOP ROP showed 100% sensitivity to identify sight-threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies.
Author	Lavini, Anna Pignatto, Silvia Lago, Paola Marchini, Giorgio Baraldi, Eugenio Gusson, Elena Lanzetta, Paolo Padovani, Ezio Maria Martini, Ferdinando Piermarocchi, Stefano Bini, Silvia Berton, Marianna Macor, Sara Cattarossi, Luigi
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Copyright	2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd 2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd. Copyright © 2017 Acta Ophthalmologica Scandinavica Foundation
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Keywords	WINROP algorithms CHOP ROP retinopathy of prematurity RORScore
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Snippet	Purpose To evaluate sensitivity, specificity and the safest cut‐offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of... To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity... Purpose To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP,ROPScore and CHOP ROP) for retinopathy of... PURPOSETo evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of... Purpose To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of...
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SubjectTerms	Algorithms Babies CHOP ROP Early Diagnosis Female Gestational Age Humans Incidence Infant, Newborn Italy - epidemiology Male Neonatal Screening - methods Ophthalmology Ophthalmoscopy - methods Retina Retina - diagnostic imaging retinopathy of prematurity Retinopathy of Prematurity - diagnosis Retinopathy of Prematurity - epidemiology Retrospective Studies Risk Factors ROC Curve RORScore WINROP
Title	Predictive algorithms for early detection of retinopathy of prematurity
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