Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity

Detalhes bibliográficos
Autor(a) principal: Figueiredo, Ricardo
Data de Publicação: 2020
Outros Autores: Sarmento, Tiago Morais, Garrido, João, Nunes Marques, M. Inês, Almeida, Teresa, Carrasquinho, Sara
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.48560/rspo.18704
Resumo: Introduction and purpose: ROPScore is a scoring system that was proposed to predict severe retinopathy of prematurity (ROP) using easily obtainable parameters as predictive variables. The aim of this study is to assess the accuracy of the ROPScore algorithm as a predictor of ROP by the second week of life. Materials and Methods: Retrospective cohort study of 239 preterm infants with a gestational age (GA) ≤ 32 weeks and/or birthweight (BW) ≤ 1500 g. No ROP, any stage of ROP and severe ROP requiring treatment were categorized. ROPScore was calculated in the second week of life using the following parameters: GA, BW, weight by the second week of life, use of oxygen in mechanical ventilation and use of blood transfusions. Sensitivity, specificity and positive (PPV) and negative (NPV) predictive values were calculated. The best cut-offs of the algorithm were calculated and, whenever possible, a sensitivity of 100% was chosen. Results: Mean BW was 1241.6 ± 310.0g and mean GA was 29.8 ± 3.4 weeks. Of the 239 infants, ROP was identified in 101 (42.3%) and 12 (11.9%) had severe ROP requiring treatment. Mean ROPScore was 15.39 ± 1.94 in the any stage of ROP cohort and 17.52 ± 1.80 in the severe ROP cohort. The sensitivity of the algorithm was 96.0% and 100% for any stage of ROP and severe ROP, respectively. NPV was 92.3% and 100% for any stage of ROP and severe ROP, respectively. Conclusion: ROPScore is a simple public domain algorithm that can be applied as early as by the second week of life. It may be used as a reliable screening tool for ROP and optimize examination timings, but further validation is required. 
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spelling Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurityArtigos OriginaisIntroduction and purpose: ROPScore is a scoring system that was proposed to predict severe retinopathy of prematurity (ROP) using easily obtainable parameters as predictive variables. The aim of this study is to assess the accuracy of the ROPScore algorithm as a predictor of ROP by the second week of life. Materials and Methods: Retrospective cohort study of 239 preterm infants with a gestational age (GA) ≤ 32 weeks and/or birthweight (BW) ≤ 1500 g. No ROP, any stage of ROP and severe ROP requiring treatment were categorized. ROPScore was calculated in the second week of life using the following parameters: GA, BW, weight by the second week of life, use of oxygen in mechanical ventilation and use of blood transfusions. Sensitivity, specificity and positive (PPV) and negative (NPV) predictive values were calculated. The best cut-offs of the algorithm were calculated and, whenever possible, a sensitivity of 100% was chosen. Results: Mean BW was 1241.6 ± 310.0g and mean GA was 29.8 ± 3.4 weeks. Of the 239 infants, ROP was identified in 101 (42.3%) and 12 (11.9%) had severe ROP requiring treatment. Mean ROPScore was 15.39 ± 1.94 in the any stage of ROP cohort and 17.52 ± 1.80 in the severe ROP cohort. The sensitivity of the algorithm was 96.0% and 100% for any stage of ROP and severe ROP, respectively. NPV was 92.3% and 100% for any stage of ROP and severe ROP, respectively. Conclusion: ROPScore is a simple public domain algorithm that can be applied as early as by the second week of life. It may be used as a reliable screening tool for ROP and optimize examination timings, but further validation is required. Ajnet2020-10-21T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://doi.org/10.48560/rspo.18704por1646-69501646-6950Figueiredo, RicardoSarmento, Tiago MoraisGarrido, JoãoNunes Marques, M. InêsAlmeida, TeresaCarrasquinho, Sarainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-09-22T17:06:09Zoai:ojs.revistas.rcaap.pt:article/18704Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:01:43.480615Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
title Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
spellingShingle Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
Figueiredo, Ricardo
Artigos Originais
title_short Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
title_full Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
title_fullStr Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
title_full_unstemmed Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
title_sort Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity
author Figueiredo, Ricardo
author_facet Figueiredo, Ricardo
Sarmento, Tiago Morais
Garrido, João
Nunes Marques, M. Inês
Almeida, Teresa
Carrasquinho, Sara
author_role author
author2 Sarmento, Tiago Morais
Garrido, João
Nunes Marques, M. Inês
Almeida, Teresa
Carrasquinho, Sara
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Figueiredo, Ricardo
Sarmento, Tiago Morais
Garrido, João
Nunes Marques, M. Inês
Almeida, Teresa
Carrasquinho, Sara
dc.subject.por.fl_str_mv Artigos Originais
topic Artigos Originais
description Introduction and purpose: ROPScore is a scoring system that was proposed to predict severe retinopathy of prematurity (ROP) using easily obtainable parameters as predictive variables. The aim of this study is to assess the accuracy of the ROPScore algorithm as a predictor of ROP by the second week of life. Materials and Methods: Retrospective cohort study of 239 preterm infants with a gestational age (GA) ≤ 32 weeks and/or birthweight (BW) ≤ 1500 g. No ROP, any stage of ROP and severe ROP requiring treatment were categorized. ROPScore was calculated in the second week of life using the following parameters: GA, BW, weight by the second week of life, use of oxygen in mechanical ventilation and use of blood transfusions. Sensitivity, specificity and positive (PPV) and negative (NPV) predictive values were calculated. The best cut-offs of the algorithm were calculated and, whenever possible, a sensitivity of 100% was chosen. Results: Mean BW was 1241.6 ± 310.0g and mean GA was 29.8 ± 3.4 weeks. Of the 239 infants, ROP was identified in 101 (42.3%) and 12 (11.9%) had severe ROP requiring treatment. Mean ROPScore was 15.39 ± 1.94 in the any stage of ROP cohort and 17.52 ± 1.80 in the severe ROP cohort. The sensitivity of the algorithm was 96.0% and 100% for any stage of ROP and severe ROP, respectively. NPV was 92.3% and 100% for any stage of ROP and severe ROP, respectively. Conclusion: ROPScore is a simple public domain algorithm that can be applied as early as by the second week of life. It may be used as a reliable screening tool for ROP and optimize examination timings, but further validation is required. 
publishDate 2020
dc.date.none.fl_str_mv 2020-10-21T00:00:00Z
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