The postnatal weight-gain algorithm WINROP early identifies sight threatening retinopathy of prematurity in a nation based cohort of extremely preterm infant

Abstract

Purpose: Evaluation of a postnatal weight-gain algorithm WINROP, identifying sight threatening retinopathy of prematurity (ROP) in a population based extremely preterm cohort.

Methods: This study enrolled all 707 live-born extremely preterm, gestational age (GA) <27 weeks infants, born 2004-2007 in Sweden, of which 407 infants met the criteria of WINROP analysis. WINROP analysis was performed retrospectively using weekly weight gain to estimate the preterm infant’s risk of developing ROP type 1 requiring treatment. GA, birth weight (BW) and weekly postnatal weight measurements were entered into WINROP. WINROP signals with an alarm to indicate if the preterm infant is at risk for ROP type 1.

Results: In this extremely preterm population WINROP correctly identified 95.7% (45/47) of the infants that required treatment for ROP type 1.Two infants with a complicated clinical course did not signal with an alarm but developed and received treatment for ROP type 1. The median time from alarm to treatment was 9 weeks (range, 4-20 weeks).

Conclusions: With a high sensitivity WINROP, an online surveillance system using weekly weight gain, early identifies extremely preterm infants at risk for ROP type 1 requiring treatment in a Swedish population based cohort. With WINROP as a supplement to traditional ROP screening programs, the infants without a WINROP alarm could have been spared 30% of their stressful eye examinations during their first fragile time of life.

Keywords: 706 retinopathy of prematurity