Purpose: The postnatal growth and retinopathy of prematurity (G-ROP) study has proposed a new model to increase the effectiveness of screening retinopathy of prematurity (ROP). The present study aimed to evaluate the effectiveness of the G-ROP model in a tertiary centre in Turkey.
Methods: The medical records of infants screened for ROP in our hospital between January 2018 and December 2022 were reviewed retrospectively. Babies with a documented ROP result and regular body weight measurements up to the 40th day of life were included in the study, and the G-ROP model was applied. The sensitivity of the G-ROP prediction model in detecting treated ROP, Type 1 ROP, Type 2 ROP, and low-grade ROP and the reduction in the number of babies to be screened by applying the model were calculated.
Results: The G-ROP model was applied to a total of 242 infants. While 194 babies were determined for screening, 22 of them were treated. The sensitivity to predict treated ROP was 100%, and the specificity was 21.8%. The model successfully predicted all cases of Type 1 ROP in the cohort, while the sensitivity was 90.9% for Type 2 ROP and 90.7% for low-grade ROP. The G-ROP model reduced the number of infants requiring screening by 19.8% in our study.
Conclusions: The G-ROP model was successfully validated in our cohort in detecting treated ROP and Type 1 ROP, reducing the number of infants requiring screening by approximately 1 in 5.
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Validation of postnatal growth and retinopathy of prematurity (G-ROP) screening guidelines in a tertiary care hospital of Pakistan: A report from low-middle income country.
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Department of Ophthalmology and Visual Sciences, The Aga Khan University Hospital, Karachi, Pakistan.
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Department of Ophthalmology, Faculty of Medicine, Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand.
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