ArticleThe British journal of ophthalmology2022
Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity.
Article in The British journal of ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Validation of the DIGIROP 2.0 Models in predicting the risk of treatment-requiring retinopathy of prematurity in a Taiwanese cohort.Eye (London, England) · 2026Article
- Prediction of retinopathy of prematurity using machine learning models.Pediatric research · 2026Article
- External validation and updating of DIGIROP prediction models including parenteral nutrition for treatment-requiring retinopathy of prematurity in a Swedish national cohort.BMJ open ophthalmology · 2026Article
- Predicting the risk of treatment-requiring retinopathy of prematurity in preterm infants in Greece. External validation of DIGIROP prognostic models.Acta ophthalmologica · 2025Article
- Validation of DIGIROP- Birth and DIGIROP- Screen for the discovery of retinopathy of prematurity requiring treatment in preterm births in Saudi Arabia.Saudi medical journal · 2025Article
- ROP: 80 Years after Its Detection - Where Do We Stand and How Long Will We Continue to Laser?Neonatology · 2024Review
- Validation of DIGIROP models and decision support tool for prediction of treatment for retinopathy of prematurity on a contemporary Swedish cohort.The British journal of ophthalmology · 2023Article
- Early prediction of severe retinopathy of prematurity requiring laser treatment using physiological data.Pediatric research · 2023Article
- Comparison of Weight-Gain-Based Prediction Models for Retinopathy of Prematurity in an Australian Population.Journal of ophthalmology · 2023Article
- Latest Trends in Retinopathy of Prematurity: Research on Risk Factors, Diagnostic Methods and Therapies.International journal of general medicine · 2023Review
Corrections and comments
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Authors and funding
22 authors.
Funding
Abstract
BACKGROUND/
aimsPrematurely born infants undergo costly, stressful eye examinations to uncover the small fraction with retinopathy of prematurity (ROP) that needs treatment to prevent blindness. The aim was to develop a prediction tool (DIGIROP-Screen) with 100% sensitivity and high specificity to safely reduce screening of those infants not needing treatment. DIGIROP-Screen was compared with four other ROP models based on longitudinal weights.
methodsData, including infants born at 24-30 weeks of gestational age (GA), for DIGIROP-Screen development (DevGroup, N=6991) originate from the Swedish National Registry for ROP. Three international cohorts comprised the external validation groups (ValGroups, N=1241). Multivariable logistic regressions, over postnatal ages (PNAs) 6-14 weeks, were validated. Predictors were birth characteristics, status and age at first diagnosed ROP and essential interactions.
resultsROP treatment was required in 287 (4.1%)/6991 infants in DevGroup and 49 (3.9%)/1241 in ValGroups. To allow 100% sensitivity in DevGroup, specificity at birth was 53.1% and cumulatively 60.5% at PNA 8 weeks. Applying the same cut-offs in ValGroups, specificities were similar (46.3% and 53.5%). One infant with severe malformations in ValGroups was incorrectly classified as not needing screening. For all other infants, at PNA 6-14 weeks, sensitivity was 100%. In other published models, sensitivity ranged from 88.5% to 100% and specificity ranged from 9.6% to 45.2%.
conclusionsDIGIROP-Screen, a clinical decision support tool using readily available birth and ROP screening data for infants born GA 24-30 weeks, in the European and North American populations tested can safely identify infants not needing ROP screening. DIGIROP-Screen had equal or higher sensitivity and specificity compared with other models. DIGIROP-Screen should be tested in any new cohort for validation and if not validated it can be modified using the same statistical approaches applied to a specific clinical setting.
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