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Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population
PURPOSE: Retinopathy of prematurity (ROP) is a disease that causes vision loss, vision impairment, and blindness, most frequently manifesting among preterm infants. ROPScore and CHOP ROP (Children’s Hospital of Philadelphia ROP) are similar scoring models to predict ROP using risk factors such as po...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890862/ https://www.ncbi.nlm.nih.gov/pubmed/33602298 http://dx.doi.org/10.1186/s13052-021-00991-z |
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author | Sun, Huiqing Dong, Yubin Liu, Yanxia Chen, Qingqin Wang, Yanxi Cheng, Bin Qin, Shaobo Meng, Liping Li, Shanxiu Zhang, Yanlun Zhang, Aiguo Yan, Weiling Dong, Yuhong Cheng, Shuyi Li, Mingchao Yu, Zengyuan |
author_facet | Sun, Huiqing Dong, Yubin Liu, Yanxia Chen, Qingqin Wang, Yanxi Cheng, Bin Qin, Shaobo Meng, Liping Li, Shanxiu Zhang, Yanlun Zhang, Aiguo Yan, Weiling Dong, Yuhong Cheng, Shuyi Li, Mingchao Yu, Zengyuan |
author_sort | Sun, Huiqing |
collection | PubMed |
description | PURPOSE: Retinopathy of prematurity (ROP) is a disease that causes vision loss, vision impairment, and blindness, most frequently manifesting among preterm infants. ROPScore and CHOP ROP (Children’s Hospital of Philadelphia ROP) are similar scoring models to predict ROP using risk factors such as postnatal weight gain, birth weight (BW), and gestation age (GA). The purpose of this study was to compare the accuracy and difference between using ROPScore and CHOP ROP for the early prediction of ROP. METHODS: A retrospective study was conducted from January 2009 to December 2019 in China. Patients eligible for enrollment included infants admitted to NICU at ≤32 weeks GA or those with ≤1500 g BW. The sensitivity and specificity of ROPScore and CHOP ROP were analyzed, as well as its suitability as an independent predictor of ROP. RESULTS: Severe ROP was found in 5.0% of preterm infants. The sensitivity and specificity of the ROPScore test at any stage of ROP was 55.8 and 77.8%, respectively. For severe ROP, the sensitivity and specificity was 50 and 87.0%, respectively. The area under the receiver operating characteristic curve for the ROPScore for predicting severe ROP was 0.76. This value was significantly higher than the values for birth weight (0.60), gestational age (0.73), and duration of ventilation (0.63), when each was category measured separately. For the CHOP ROP, it correctly predicted infants who developed type 1 ROP (sensitivity, 100%, specificity, 21.4%). CONCLUSIONS: The CHOP ROP model predicted infants who developed type 1 ROP at a sensitivity of 100% whereas ROPScore had a sensitivity of 55.8%. Therefore, the CHOP ROP model is more suitable for Chinese populations than the ROPScore test. CLINICAL REGISTRATION NUMBER AND STROBE GUIDELINES: This article was a retrospective cohort study and reported the results of the ROPScore and CHOP ROP algorithms. No results pertaining to interventions on human participants were reported. Thus, registration was not required and this study followed STROBE guidelines. |
format | Online Article Text |
id | pubmed-7890862 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78908622021-02-22 Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population Sun, Huiqing Dong, Yubin Liu, Yanxia Chen, Qingqin Wang, Yanxi Cheng, Bin Qin, Shaobo Meng, Liping Li, Shanxiu Zhang, Yanlun Zhang, Aiguo Yan, Weiling Dong, Yuhong Cheng, Shuyi Li, Mingchao Yu, Zengyuan Ital J Pediatr Research PURPOSE: Retinopathy of prematurity (ROP) is a disease that causes vision loss, vision impairment, and blindness, most frequently manifesting among preterm infants. ROPScore and CHOP ROP (Children’s Hospital of Philadelphia ROP) are similar scoring models to predict ROP using risk factors such as postnatal weight gain, birth weight (BW), and gestation age (GA). The purpose of this study was to compare the accuracy and difference between using ROPScore and CHOP ROP for the early prediction of ROP. METHODS: A retrospective study was conducted from January 2009 to December 2019 in China. Patients eligible for enrollment included infants admitted to NICU at ≤32 weeks GA or those with ≤1500 g BW. The sensitivity and specificity of ROPScore and CHOP ROP were analyzed, as well as its suitability as an independent predictor of ROP. RESULTS: Severe ROP was found in 5.0% of preterm infants. The sensitivity and specificity of the ROPScore test at any stage of ROP was 55.8 and 77.8%, respectively. For severe ROP, the sensitivity and specificity was 50 and 87.0%, respectively. The area under the receiver operating characteristic curve for the ROPScore for predicting severe ROP was 0.76. This value was significantly higher than the values for birth weight (0.60), gestational age (0.73), and duration of ventilation (0.63), when each was category measured separately. For the CHOP ROP, it correctly predicted infants who developed type 1 ROP (sensitivity, 100%, specificity, 21.4%). CONCLUSIONS: The CHOP ROP model predicted infants who developed type 1 ROP at a sensitivity of 100% whereas ROPScore had a sensitivity of 55.8%. Therefore, the CHOP ROP model is more suitable for Chinese populations than the ROPScore test. CLINICAL REGISTRATION NUMBER AND STROBE GUIDELINES: This article was a retrospective cohort study and reported the results of the ROPScore and CHOP ROP algorithms. No results pertaining to interventions on human participants were reported. Thus, registration was not required and this study followed STROBE guidelines. BioMed Central 2021-02-18 /pmc/articles/PMC7890862/ /pubmed/33602298 http://dx.doi.org/10.1186/s13052-021-00991-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sun, Huiqing Dong, Yubin Liu, Yanxia Chen, Qingqin Wang, Yanxi Cheng, Bin Qin, Shaobo Meng, Liping Li, Shanxiu Zhang, Yanlun Zhang, Aiguo Yan, Weiling Dong, Yuhong Cheng, Shuyi Li, Mingchao Yu, Zengyuan Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population |
title | Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population |
title_full | Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population |
title_fullStr | Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population |
title_full_unstemmed | Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population |
title_short | Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population |
title_sort | using ropscore and chop rop for early prediction of retinopathy of prematurity in a chinese population |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890862/ https://www.ncbi.nlm.nih.gov/pubmed/33602298 http://dx.doi.org/10.1186/s13052-021-00991-z |
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