Assessment of Neonatal Care Standard by the Predictive Model for Retinopathy of Prematurity Based on Weight Gain

Abstract

Care of extremely premature infants is in constant need for evaluation and progress. WINROP, a predictive model based on weight gain, has been developed to reduce the number of stressful examinations for retinopathy for prematurity. Validation studies of WINROP emphasize the difference of applicability in neonatal units of various practice. The aim of the study was to assess the standard of neonatal care by WINROP. Data on extremely premature infants were collected from medical records and entered in WINROP. High-and low-risk WINROP distribution and retinopathy of prematurity outcomes were analyzed. Fifty-four infants, gestational age ≤28 weeks, were included in the study after exclusion of weight related comorbidities. High risk was noted in 74% (n=40) of infants with 24% (n=13) developing retinopathy of prematurity requiring treatment. In low alarm group, there were 3 cases with severe disease. In conclusion, WINROP is not just a provider of predictive information on the severity of retinopathy of prematurity. High-risk alarm indicates the need of adjustment of nutritional strategies. Infants without pathological growth morbidities who develop severe retinopathy of prematurity in low-risk group point to other risk factors for retinopathy of prematurity to be evaluated and changed in future practice.