A model based on simple birth characteristics may provide a new, more efficient method for predicting the need for retinopathy of prematurity treatment in infants, according to researchers.
A model based on simple birth characteristics may provide a new, more efficient method for predicting the need for retinopathy of prematurity treatment in infants, according to researchers. It might also reduce screening frequency in infants at low risk.
Retinopathy of prematurity (ROP) is a sight-threatening disease common in infants with a gestational age (GA) of 31 weeks or less. It is a serious enough problem that the standard procedure in Swedish hospitals is to screen all infants with a GA of less than 31 weeks for ROP.
However, this approach is costly, since it requires repeated retinal eye examinations and each screening must be performed by a specially trained ophthalmologist. It is also often stressful for infants, and between 2008 and 2015, only a small number (5.7%) of those infants screened for ROP required treatment.
Ms Aldina Pivodic, MSc, a researcher at the University of Gothenburg in Sweden, and her colleagues wanted to see if they could avoid unnecessary screenings by using a predictive model for ROP risk based only on postnatal age, birth weight, sex, gestation age and important interactions. They conducted a study of 7,286 Swedish infants with a GA of 24 to 30 weeks, who were born between 2007 and 2017 and registered in the Swedish National Registry for Retinopathy of Prematurity. Their findings were published in JAMA Ophthalmology. The Researchers analysed the infants’ time-varying birth characteristics using Poisson regression to develop an individualised predictive model for ROP treatment, which they titled the DIGIROP-Birth prediction model.
They found that this model compared favourably to others currently in use, and had the benefit of being based purely on simple birth characteristics rather than complex longitudinal neonatal data, which is often inaccessible to ophthalmologists.