Literature DB >> 33602298

Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population.

Huiqing Sun1, Yubin Dong2, Yanxia Liu3, Qingqin Chen4, Yanxi Wang5, Bin Cheng6, Shaobo Qin7, Liping Meng8, Shanxiu Li9, Yanlun Zhang10, Aiguo Zhang11, Weiling Yan12, Yuhong Dong13, Shuyi Cheng14, Mingchao Li15, Zengyuan Yu15.   

Abstract

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.

Entities:  

Keywords:  Preterm infant; Retinopathy of prematurity; Score

Year:  2021        PMID: 33602298      PMCID: PMC7890862          DOI: 10.1186/s13052-021-00991-z

Source DB:  PubMed          Journal:  Ital J Pediatr        ISSN: 1720-8424            Impact factor:   2.638


  30 in total

Review 1.  Retinopathy of prematurity: an epidemic in the making.

Authors:  Graham E Quinn; Clare Gilbert; Brian A Darlow; Andrea Zin
Journal:  Chin Med J (Engl)       Date:  2010-10       Impact factor: 2.628

Review 2.  The International Classification of Retinopathy of Prematurity revisited.

Authors: 
Journal:  Arch Ophthalmol       Date:  2005-07

3.  Validation of the Children's Hospital of Philadelphia Retinopathy of Prematurity (CHOP ROP) Model.

Authors:  Gil Binenbaum; Gui-Shuang Ying; Lauren A Tomlinson
Journal:  JAMA Ophthalmol       Date:  2017-08-01       Impact factor: 7.389

4.  Incidence and early course of retinopathy of prematurity. The Cryotherapy for Retinopathy of Prematurity Cooperative Group.

Authors:  E A Palmer; J T Flynn; R J Hardy; D L Phelps; C L Phillips; D B Schaffer; B Tung
Journal:  Ophthalmology       Date:  1991-11       Impact factor: 12.079

5.  Longitudinal postnatal weight measurements for the prediction of retinopathy of prematurity.

Authors:  Carolyn Wu; Deborah K Vanderveen; Ann Hellström; Chatarina Löfqvist; Lois E H Smith
Journal:  Arch Ophthalmol       Date:  2010-04

6.  An international classification of retinopathy of prematurity. II. The classification of retinal detachment. The International Committee for the Classification of the Late Stages of Retinopathy of Prematurity.

Authors: 
Journal:  Arch Ophthalmol       Date:  1987-07

7.  The use of the WINROP screening algorithm for the prediction of retinopathy of prematurity in a Chinese population.

Authors:  Huiqing Sun; Wengqing Kang; Xiuyong Cheng; Chao Chen; Hong Xiong; Jing Guo; Chongchen Zhou; Yinghui Zhang; Ann Hellström; Chatarina Löfqvist; Changlian Zhu
Journal:  Neonatology       Date:  2013-07-24       Impact factor: 4.035

8.  Natural history of retinopathy of prematurity in infants born before 27 weeks' gestation in Sweden.

Authors:  Dordi Austeng; Karin B M Källen; Ann Hellström; Kristina Tornqvist; Gerd E Holmström
Journal:  Arch Ophthalmol       Date:  2010-10

9.  The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model.

Authors:  Gil Binenbaum; Gui-Shuang Ying; Graham E Quinn; Jiayan Huang; Stephan Dreiseitl; Jules Antigua; Negar Foroughi; Soraya Abbasi
Journal:  Arch Ophthalmol       Date:  2012-12

10.  Serum levels of IGF1 are a useful predictor of retinopathy of prematurity.

Authors:  A Pérez-Muñuzuri; J R Fernández-Lorenzo; M L Couce-Pico; M J Blanco-Teijeiro; J M Fraga-Bermúdez
Journal:  Acta Paediatr       Date:  2010-01-18       Impact factor: 2.299

View more
  1 in total

1.  The Use of Postnatal Weight Gain Algorithms to Predict Severe or Type 1 Retinopathy of Prematurity: A Systematic Review and Meta-analysis.

Authors:  Sam Athikarisamy; Saumil Desai; Sanjay Patole; Shripada Rao; Karen Simmer; Geoffrey C Lam
Journal:  JAMA Netw Open       Date:  2021-11-01
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.