Literature DB >> 27991614

Evaluation of the WinROP system for identifying retinopathy of prematurity in Czech preterm infants.

Juraj Timkovic1,2,3, Martina Pokryvkova4, Katerina Janurova5, Denisa Barinova4, Renata Polackova3,4, Petr Masek1,3.   

Abstract

AIMS: Retinopathy of Prematurity (ROP) is a potentially serious condition that can afflict preterm infants. Timely and correct identification of individuals at risk of developing a serious form of ROP is therefore of paramount importance. WinROP is an online system for predicting ROP based on birth weight and weight increments. However, the results vary significantly for various populations. It has not been evaluated in the Czech population. This study evaluates the test characteristics (specificity, sensitivity, positive and negative predictive values) of the WinROP system in Czech preterm infants.
METHODS: Data on 445 prematurely born infants included in the ROP screening program at the University Hospital Ostrava, Czech Republic, were retrospectively entered into the WinROP system and the outcomes of the WinROP and regular screening were compared.
RESULTS: All 24 infants who developed high-risk (Type 1 or Type 2) ROP were correctly identified by the system. The sensitivity and negative predictive values for this group were 100%. However, the specificity and positive predictive values were substantially lower, resulting in a large number of false positives. Extending the analysis to low risk ROP, the system did not provide such reliable results.
CONCLUSIONS: The system is a valuable tool for identifying infants who are not likely to develop high-risk ROP and this could help to substantially reduce the number of preterm infants in need of regular ROP screening. It is not suitable for predicting the development of less serious forms of ROP which is however in accordance with the declared aims of the WinROP system.

Entities:  

Keywords:  ROP prediction; WinROP system; early diagnosis of ROP; retinopathy of prematurity

Mesh:

Year:  2016        PMID: 27991614     DOI: 10.5507/bp.2016.061

Source DB:  PubMed          Journal:  Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub        ISSN: 1213-8118            Impact factor:   1.245


  4 in total

1.  Prediction of severe retinopathy of prematurity using the weight gain, insulin-like growth factor 1, and neonatal retinopathy of prematurity algorithm in a Japanese population of preterm infants.

Authors:  Kaori Ueda; Akiko Miki; Shunichiro Nakai; Suiho Yanagisawa; Koji Nomura; Makoto Nakamura
Journal:  Jpn J Ophthalmol       Date:  2020-01-03       Impact factor: 2.447

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

Authors:  Huiqing Sun; Yubin Dong; Yanxia Liu; Qingqin Chen; Yanxi Wang; Bin Cheng; Shaobo Qin; Liping Meng; Shanxiu Li; Yanlun Zhang; Aiguo Zhang; Weiling Yan; Yuhong Dong; Shuyi Cheng; Mingchao Li; Zengyuan Yu
Journal:  Ital J Pediatr       Date:  2021-02-18       Impact factor: 2.638

3.  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

4.  Diagnostic Accuracy of WINROP, CHOP-ROP and ROPScore in Detecting Type 1 Retinopathy of Prematurity.

Authors:  Deena Thomas; Shamnad Madathil; Anu Thukral; M Jeeva Sankar; Parijat Chandra; Ramesh Agarwal; Ashok Deorari
Journal:  Indian Pediatr       Date:  2021-05-20       Impact factor: 1.411

  4 in total

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