ArticleBMC ophthalmology2021
Validation of the DIGIROP-birth model in a Chinese cohort.
Article in BMC ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 6 citations in OpenAlex.
- 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
- Construction of a prediction model for retinopathy of prematurity based on placenta-derived genes and clinical variables.Translational pediatrics · 2026Article
- Early Prediction Model for Retinopathy of Prematurity Using Placental and Neonatal Risk Factors.Investigative ophthalmology & visual science · 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
- Nomogram to predict severe retinopathy of prematurity in Southeast China.International journal of ophthalmology · 2024Article
- 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
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe aimed to validate the predictive performance of the DIGIROP-Birth model for identifying treatment-requiring retinopathy of prematurity (TR-ROP) in Chinese preterm infants to evaluate its generalizability across countries and races.
methodsWe retrospectively reviewed the medical records of preterm infants who were screened for retinopathy of prematurity (ROP) in a single Chinese hospital between June 2015 and August 2020. The predictive performance of the model for TR-ROP was assessed through the construction of a receiver-operating characteristic (ROC) curve and calculating the areas under the ROC curve (AUC), sensitivity, specificity, and positive and negative predictive values.
resultsFour hundred and forty-two infants (mean (SD) gestational age = 28.8 (1.3) weeks; mean (SD) birth weight = 1237.0 (236.9) g; 64.7% males) were included in the study. Analyses showed that the DIGIROP-Birth model demonstrated less satisfactory performance than previously reported in identifying infants with TR-ROP, with an area under the receiver-operating characteristic curve of 0.634 (95% confidence interval = 0.564-0.705). With a cutoff value of 0.0084, the DIGIROP-Birth model showed a sensitivity of 48/93 (51.6%), which increased to 89/93 (95.7%) after modification with the addition of postnatal risk factors. In infants with a gestational age < 28 weeks or birth weight < 1000 g, the DIGIROP-Birth model exhibited sensitivities of 36/39 (92.3%) and 20/23 (87.0%), respectively.
conclusionsAlthough the predictive performance was less satisfactory in China than in developed countries, modification of the DIGIROP-Birth model with postnatal risk factors shows promise in improving its efficacy for TR-ROP. The model may also be effective in infants with a younger gestational age or with an extremely low birth weight.
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