ArticleInternational journal of ophthalmology2021
Efficacy of the WINROP algorithm for retinopathy of prematurity screening in Southern China.
Article in International journal of ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Use of Postnatal Weight Gain Algorithms to Predict Severe or Type 1 Retinopathy of Prematurity: A Systematic Review and Meta-analysis.JAMA network open · 2021Pooled it
- Construction of a prediction model for retinopathy of prematurity based on placenta-derived genes and clinical variables.Translational pediatrics · 2026Article
- Prevalence of retinopathy of prematurity in African preterm infants and evaluation of the accuracy of the WINROP predictive algorithm: an observational clinical study.BMC ophthalmology · 2025Observational
- Validation of WINROP algorithm as screening tool of retinopathy of prematurity among Egyptian preterm neonates.Eye (London, England) · 2024Article
- Retinopathy of Prematurity-Targeting Hypoxic and Redox Signaling Pathways.Antioxidants (Basel, Switzerland) · 2024Review
- Changes of the peripapillary vascular parameters in premature infants without retinopathy of prematurity using U-net segmentation.International journal of ophthalmology · 2024Article
- Nomogram to predict severe retinopathy of prematurity in Southeast China.International journal of ophthalmology · 2024Article
- Haemoglobin Levels in Early Life among Infants with and without Retinopathy of Prematurity.International journal of environmental research and public health · 2021Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo evaluate the predicting efficacy of severe retinopathy of prematurity (ROP) by the WINROP algorithm (http://winrop.com) in Southern China.
methodsAll preterm infants with the gestational age (GA) less than 32wk were included. Their ROP screening results and serial postnatal body weight were analysed retrospectively. Weekly body weight was entered into and measured by the WINROP system. The outcomes were analysed, and the sensitivity, specificity, positive predictive value and negative predictive value (NPV) were calculated.
resultsTotally 432 infants with a median GA of 30.0 (24.0-31.9)wk, and a median birth weight (BW) of 1360 (540-2700) g were included. Among these 432 infants, 50 were diagnosed as type 1 ROP but only 28 were identified by the WINROP algorithm. The sensitivity was 56% (28/50) and the NPV was 92% (252/274). However, for infants with BW <1000 g or GA <28wk, the sensitivity was 93.8% (15/16) and 93.3% (14/15), respectively. Meanwhile, with several postnatal complications added as additional risk factors, the sensitivity was increased to 96% (48/50).
conclusionThe sensitivity of the WINROP algorithm from the Southern Chinese cohort is not as high as that reported in developed countries. This algorithm is effective for detecting severe ROP from extremely small or preterm infants. Modification of the algorithm with additional risk factors could improve the predictive value for infants with a GA>28wk in China.
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