Risk factors and prediction models for retinopathy of prematurity

Objectives: To develop a simple prediction model for the pre-screening of Retinopathy of Prematurity (ROP) among preterm babies. Methods: This was a prospective study. The test dataset (January 2007 until December 2010) was used to construct risk prediction models, and the validation dataset (January 2011 until March 2012) was used to validate the models developed from the test dataset. Two prediction models were produced using the test dataset based on logistic regression equations in which the development of ROP was used as the outcome. Results: The sensitivity and specificity for model 1 [gestational age (GA), birth weight (BW), intraventricular haemorrhage (IVH) and respiratory distress syndrome (RDS)] was 82 % and 81.7%, respectivelyfor model 2, (GA and BW) the sensitivity and specificity were 80.5% and 80.3%, respectively. Conclusion: Model 2 was preferable, as it only required two predictors (GA and BW). Our prediction model can be used for early detection of ROP to avoid poor outcomes